Healthcare Cost and Utilization Project (HCUP) Fast Stats

State-level statistics on inpatient stays are drawn from the HCUP State Inpatient Databases (SID) and quarterly data if available. Counts are summarized by discharge quarter. Information based on quarterly data should be considered preliminary. Quarterly data will be replaced by the State’s complete annual SID for the year when it is available. Additionally, it is possible for a State’s annual SID to be updated. As a result of either the replacement of quarterly data with annual SID or the update of an annual SID, previously released statistics for a given State may change. This analysis is limited to patients treated in community, nonrehabilitation hospitals in the State. Discharge counts for inpatient stays exclude transfers out to another acute care hospital.

We adjust the discharge counts for community, nonrehabilitation hospitals that are not included in the SID or quarterly data. Across all States, the SID are missing about 7 percent of community hospitals and about 1.5 percent of discharges. Weighting for missing hospitals uses the following information from the American Hospital Association (AHA) Annual Survey of Hospitals to define strata within the State:

•  Ownership: government, private nonprofit, and private investor-owned
•  Size of the hospital based on the number of beds: small, medium, and large categories defined within region
•  Location combined with teaching status: rural, urban nonteaching, urban teaching

If a stratum is missing one or more hospitals in the State data, then we set the discharge weight to the total number of discharges reported in the AHA divided by the total number of discharges in the State data. If all hospitals in a stratum are represented in the State data, then we set the discharge weight to 1. We also adjust the discharge weights for hospitals that have missing discharge quarters of data, provided there is no indication in the AHA Annual Survey that the facility had closed.

Discharge weights are specific to the data year for SID through 2012 (e.g., discharge weights for the 2012 SID use 2012 AHA data). Weighting for HCUP data starting in 2013 is based on AHA data from the prior year because current information is often unavailable (e.g., discharge weights for the 2014 SID use 2013 AHA data).

Counts are rounded to the nearest 50 discharges with any counts less than 26 suppressed for confidentiality. This will cause a discontinuity in the trend lines displayed in the figures.

The unit of analysis is the hospital discharge (i.e., the hospital inpatient stay) or an emergency department (ED) visit, not a person or patient. This means that a person who is admitted to the hospital or visits the ED multiple times in one year is counted each time as a separate discharge from the hospital or a separate visit in the ED.

For Fast Stats, all stays and visits are counted one time only, regardless of the number of relevant diagnosis or procedure codes that appear on the record. For instance, when identifying injury-related inpatient stays and ED visits, a record may include more than one of the injury-specific codes; in such a case, the record is only included once in the injury counts.

On October 1, 2015, the United States transitioned from ICD-9-CM¹ to ICD-10-CM/PCS². The graphics demarcate this transition with statistics reported using ICD-9-CM coding identified as “ICD-9-CM” on the graphs and statistics reported using ICD-10-CM/PCS coding identified as “ICD-10-CM/PCS” on the graphs. The 2015 rates of stays per 100,000 population and average statistics for hospitalization type are based on the first three quarters of data with ICD-9-CM codes only (January 1, 2015 to September 30, 2015). The number of inpatient stays by hospitalization type in 2015 is not reported because the statistics are not based on full year data. Statistics for all other characteristics include data for the full 2015 calendar year since these statistics are non-clinical, and therefore not impacted by the transition to ICD-10-CM/PCS.

Notable increases or decreases may be observed in the statistics across the ICD-9-CM to ICD-10-CM/PCS transition that are more reflective of definitional changes rather than changes in hospital utilization. Compared with the ICD-9-CM time period, some definitions of hospitalization type for ICD-10-CM/PCS may be more narrowly or more broadly defined. More information on the impact of ICD-10-CM/PCS is available on the HCUP User Support (HCUP-US) web page for ICD-10-CM/PCS Resources.

¹International Classification of Diseases, Ninth Revision, Clinical Modification
² International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System

The “expected payer” data element in HCUP databases provides information on the type of payer that the hospital expects to be the source of payment for the hospital bill. Trends in discharge counts are provided by the following expected primary payers and limited to specific age ranges as indicated:

• Medicare patients aged 65 years and older
• Medicaid patients aged 19 to 64 years with the exception that information on maternal discharges is limited to those aged 19 to 45 years
• Privately insured patients aged 19 to 64 years with the exception that information on maternal discharges is limited to those aged 19 to 45 years
• Self-pay/No charge patients aged 19 to 64 years with the exception that information on maternal discharges is limited to those aged 19 to 45 years

Patients identified as self-pay/no charge have an expected primary payer of self-pay, no charge, charity, or no expected payment. The self-pay/no charge category may also include patients with an expected payer of Indian Health Services, county indigent, migrant health programs, Ryan White Act, Hill-Burton Free Care, or other Federal, State, and local programs for the indigent when those programs are identifiable in the Partner-provided coding of expected payer. This reclassification of patients is only possible for some States. More information on identifying programs reported in HCUP data that may cover the self-pay/no charge category is available in HCUP Methods Series Reports by Topic “User Guide – An Examination of Expected Payer Coding in HCUP Databases” (multiple documents; updated annually).

Discharges with the following expected primary payers and age groups are not reported: Medicare, age 19-64; Medicaid, age 65+; private insurance, age 65+; self-pay/no charge, age 65+; other Federal, State, and local programs, age 19+; missing, age 19+; or invalid, age 19+. In 2022, across all States, these excluded discharges represented from 11 to 28 percent of all discharges for age 19+.

The total reflecting the number of discharges across all expected payers and age groups (including those groups not presented in the graphs) is provided in the underlying data tables (“Show Underlying Data Tables”) and in the Excel data download file (“Show Data Export Options”) for all adult hospitalizations and each separate hospitalization type. This statistic was added to Fast Stats in December 2019. It was calculated using the currently available SID for data years 2003 and forward. If the SID initially used for Fast Stats has been updated, then the total counts could be based on different versions of the SID than the counts shown for Medicare, Medicaid, private insurance, and self-pay/no charge.

For comparison against the total described above for all expected payers and age groups, the Excel download file also provides the sum of the displayed expected payers and age groups (i.e., the sum of the rounded weighted quarterly expected payer counts of discharges across the expected payers and age groups that are displayed in the graphs).

It should be noted that in certain data years and for certain States, data anomalies are identified that may impact the observed trends in inpatients stays by expected primary payer:

• In the Nebraska SID prior to 2016, some Medicaid managed care patients may have been categorized in the data under private insurance instead of Medicaid because the Medicaid program was managed by a commercial insurance company. Beginning with data year 2016, there are large increases in the number of Medicaid records and proportionate decreases in records categorized as private insurance because the Nebraska Partner organization improved the process for the identification of patients covered by Medicaid managed care programs managed by commercial insurance companies.
• In the Texas 2004-2011 SID data, some Medicare records were incorrectly mapped to private insurance. Thus, the counts for Medicare are slightly underreported and the counts for private insurance are slightly overreported. This impacts roughly 1.5-3.5 percent of SID records between 2004-2011.

Each discharge is assigned to a single hospitalization type hierarchically, based on the following order: maternal, mental health/substance use, injury, surgical, and medical. All discharges are categorized in one of the five mutually exclusive hospitalization types based on the principal diagnosis for the hospital stay.

The definitions for the maternal, mental health/substance use, and injury hospitalization types have changed over time; they are identified differently under ICD-9-CM and ICD-10-CM:

• Beginning with quarter 4 of 2015 (2015 Q4): Major Diagnostic Category (MDC) or Clinical Classifications Software Refined (CCSR) for ICD-10-CM default categorization scheme for the principal diagnosis
• Through quarter 3 of 2015 (2015 Q3): A principal diagnosis based on either ranges of ICD-9-CM codes or the Clinical Classifications Software (CCS) for ICD-9-CM

The definitions for the surgical and medical hospitalization types remain the same under both the ICD-9-CM and ICD-10-CM coding systems. They are defined based on the Diagnosis-Related Group (DRG).

It should be noted that beginning in December 2020, statistics by hospitalization type using the ICD-10-CM coding system (since quarter 4 of 2015) have been updated to reflect new definitions provided below for each of the five hospitalization types. Thus, there is a one-time change in previously released statistics beginning quarter 4 of 2015 through as late as quarter 1 of 2019, depending on the availability of a State’s data when the statistics were last updated prior to December 2020. Many of the current and previously released statistics are similar, but statistics for some hospitalization types have changed substantially, specifically for mental health/substance use. The new definition of mental health/substance use is based on major diagnostic category (MDC). As a result, there are specific ICD-10-CM diagnosis codes that are no longer included. For example, discharges with a principal diagnosis code indicating alcoholic cirrhosis of the liver, Alzheimer’s disease, and poisoning by narcotics and psychodysleptics are no longer assigned to the hospitalization type for mental health/substance use. Additional information on the amount of change between current and previously released statistics for each hospitalization type by age group and expected payer is provided in the “ICD-10-CM Definition Changes” worksheet of the Excel download file.

Maternal discharges are defined using the following Clinical Classifications Software (CCS) for ICD-9-CM categories for data years 2015 and earlier or Major Diagnostic Category (MDC) beginning with data year 2016. MDC was assigned without using “present on admission” information on the record because not all HCUP data sources provide present on admission indicators.

• Beginning with Data Year 2016: MDC 14, Pregnancy, Childbirth and the Puerperium
• For Data Years 1994-2015: CCS 176-196

For data years 2015 and earlier, the CCS-based definition of maternal may result in slightly different counts of discharges when compared with other ways of classifying diagnosis codes. For example, compared with using MDC from 2015 and earlier, the CCS approach assigns 0.9 percent fewer cases to “maternal” because a maternal discharge is classified into a mental health CCS or a substance use CCS when the diagnosis code includes a mental health or substance abuse condition along with a maternal condition (e.g., drug dependence in pregnancy).

The definition for adult discharges related to mental health/substance use has changed over time:

• Beginning 2015 Q4: MDC 19, Mental Diseases and Disorders, or 20, Alcohol/Drug Use or Induced Mental Disorders
• For 2007-2015 Q3: Principal diagnosis CCS 650-663, 670
• For 2003-2006: Principal diagnosis CCS 65-75
• For National Inpatient NIS Data Years 1994-2006: CCS 65-75

MDCs were assigned without using “present on admission” information on the record because not all HCUP data sources provide present on admission indicators.

Beginning with the 2017 data year, the Iowa SID includes records for behavioral health patients treated in chemical dependency or psychiatric care units. Prior to 2017 data, these records were prohibited from release, and therefore not reported in Fast Stats.

Injury discharges are identified by either: a) a principal diagnosis based on ranges of ICD-9-CM codes for data years 2015 and earlier, or b) a combination of the Clinical Classifications Software Refined (CCSR) for ICD-10-CM default categorization scheme for the principal diagnosis and individual ICD-10-CM diagnosis codes, for data years 2016 and later.

The definition for adult discharges related to injury has changed over time:

•  Beginning with Data Year 2016: CCSR INJ001-INJ027, INJ032 and ICD-10-CM diagnosis codes in the T84 series (used only for discharges from 1/1/2016-9/30/2016)
•  Beginning 2015 Q4: Default for principal diagnosis CCSR INJ001-INJ027, INJ032
•  Through 2015 Q3: Principal ICD-9-CM diagnosis codes 800-909.2, 909.4, 909.9, 910-994.9, 995.50-995.59, 995.80-995.85

The above definition of injury through 2015 Q3 includes five ICD-9-CM diagnosis codes (965.00, 965.01, 965.02, 965.09, and 980.0) that are also included under two CCS diagnosis categories (660 and 661) used for the definition of the mental health/substance use hospitalization type for ICD-9-CM. Because of the hierarchical ordering used to assign discharges to hospitalization type, discharges with one of these five principal ICD-9-CM diagnosis codes are assigned to the mental health/substance use hospitalization type and not the injury hospitalization type.

Excluded Codes

It should be noted that ICD-9-CM and ICD-10-CM diagnosis codes related to complications of surgical or medical care, or adverse events or anaphylactic shock resulting from medication, anesthesia, or food are not used in the definition of the injury hospitalization type.

Surgical discharges are identified by a surgical diagnosis-related group (DRG). The DRG grouper first assigns the discharge to a MDC based on the principal diagnosis. For each MDC, there is a list of procedure codes that qualify as operating room procedures. If the discharge involves an operating room procedure, it is assigned to one of the surgical DRGs within the MDC category; otherwise it is assigned to a medical DRG.

Medical discharges are identified by a medical DRG. The DRG grouper first assigns the discharge to an MDC based on the principal diagnosis. For each MDC there is a list of procedure codes that qualify as operating room procedures. If the discharge involves an operating room procedure, it is assigned to one of the surgical DRGs within the MDC category; otherwise it is assigned to a medical DRG. If the DRG indicates the information on the record is ungroupable (i.e., not identifiable as medical or surgical), then the discharge is assumed to be medical. This rarely occurs (less than 0.1 percent of total discharges).

Trends in the number of adult inpatient stays for specific medical conditions are not currently being reported in HCUP Fast Stats. Three conditions, defined based on principal diagnosis, previously were included in HCUP Fast Stats: asthma, congestive heart failure (CHF), and diabetes. Reporting of CHF in HCUP Fast Stats was discontinued as of November 2017 because a change in the ICD-10-CM coding guidelines effective October 1, 2016 caused a discontinuity in the trend. Reporting of asthma and diabetes in HCUP Fast Stats was discontinued as of December 2019 because the framework for the inpatient data is focused around presenting payer trends for the five high-level hospitalization types. The specific medical conditions have been removed from the active query tool, but historical data previously released in HCUP Fast Stats for CHF (with data reported through 2016 Q3 for some States) and for asthma and diabetes (with data reported through 2018 Q2 for some States) is offered in the Excel download file, which can be downloaded by expanding “Show Data Export Options.”

The State-specific Medicaid expansion information quoted on this site is compiled from the Kaiser Family Foundation (kff.org):³

• Kaiser Family Foundation “Status of State Action on the Medicaid Expansion Decision”
• Kaiser Family Foundation “States Getting a Jump Start on Health Reform’s Medicaid Expansion”

When these sources indicate a definitive implementation date for expansion, and HCUP data are available for the time period covered by the expansion, the graphs show a vertical dotted line marking the initial Medicaid expansion date.

³ The U.S. Department of Health and Human Services (HHS) is offering these links for informational purposes only, and this fact should not be construed as an endorsement of the host organization’s programs or activities.

• Statistics on the number of eligible individuals who enrolled in marketplace plans are available at the State-level from the Office of The Assistant Secretary for Planning and Evaluation (ASPE) in periodic Enrollment Reports posted on their website under Enrollment Reports.
• Information on Medicaid and CHIP enrollment is available at the State level from the Centers for Medicare & Medicaid Services (CMS) in monthly reports posted on the Medicaid website under Medicaid and CHIP Enrollment Data.
• Information on the income-based eligibility levels required by the Affordable Care Act and effective as of April 1, 2016 is available at the State level from CMS on the Medicaid website under Medicaid and CHIP Eligibility Levels.
• Yearly information on the percent of adults aged 19 to 64 years who were uninsured is available from the Kaiser Family Foundation (KFF) website under State Health Facts.

State-level statistics on emergency department (ED) visits are drawn from the HCUP State Emergency Department Databases (SEDD) and State Inpatient Databases (SID) and quarterly data if available. The SEDD capture information on ED visits that do not result in an admission (i.e., the data include treat-and-release visits and transfers to another hospital). The SID contain information on patients initially seen in the ED and then admitted to the same hospital. Records for ED admissions are selected from the SID using the HCUP data element HCUP_ED. A value of HCUP_ED that is greater than 0 indicates that the patient received ED services.

Counts are summarized by discharge quarter. Information based on quarterly data should be considered preliminary. Quarterly data will be replaced by the State’s complete annual SID/SEDD for the year when it is available. Additionally, it is possible for a State’s annual SID/SEDD to be updated. As a result of either the replacement of quarterly data with annual SID/SEDD or the update of an annual SID/SEDD, previously released statistics for a given State may change.

This analysis is limited to patients treated in hospital-owned EDs of community hospitals in the State. ED visits for patients transferred out to another acute care hospital are excluded.

We adjust the ED visit counts for hospital-owned EDs in community hospitals that are missing from the SEDD and missing from the SID. Across all States, the SID are missing about 7 percent of community hospitals (about 1.5 percent of discharges), and the SEDD are missing about 5 percent of EDs (about 2 percent of ED visits). Data from the following data sources are used to weight for missing information: the American Hospital Association (AHA) Survey of Hospitals and the Trauma Information Exchange Program (TIEP) database, a national inventory of trauma centers in the United States collected by the American Trauma Society. Weighting for missing EDs uses the following information to define strata within the State:

• Ownership: government, private nonprofit, and private investor-owned (AHA)
• Location: large metropolitan, small metropolitan, micropolitan, and rural (AHA)
• Teaching status: nonteaching and teaching (AHA)
• Trauma center designation: levels I, II, and III (TIEP)

If a stratum is missing one or more EDs in the State data, then we set the weight to the total number of ED visits reported in the AHA divided by the total number of ED visits in the State data. If all EDs in a stratum are represented in the State data, then we set the discharge weight to 1. We also adjust the discharge weights for EDs that have missing quarters of data, provided there is no indication in the AHA Annual Survey that the facility had closed.

Discharge weights are specific to the data year for ED visits through 2013 (e.g., discharge weights for the 2013 ED visits use 2013 AHA data). Weighting of HCUP data for ED visits starting in 2014 is based on AHA data from the prior year because current information is often unavailable (e.g., discharge weights for the 2014 ED visits use 2013 AHA data).

Counts are rounded to the nearest 50 ED visits with any counts less than 26 suppressed for confidentiality. This will cause a discontinuity in the trend lines displayed in the figures.

The unit of analysis is the hospital discharge (i.e., the hospital inpatient stay) or an emergency department (ED) visit, not a person or patient. This means that a person who is admitted to the hospital or visits the ED multiple times in one year is counted each time as a separate discharge from the hospital or a separate visit in the ED.

For Fast Stats, all stays and visits are counted one time only, regardless of the number of relevant diagnosis or procedure codes that appear on the record. For instance, when identifying injury-related inpatient stays and ED visits, a record may include more than one of the injury-specific codes; in such a case, the record is only included once in the injury counts.

On October 1, 2015, the United States transitioned from ICD-9-CM¹ to ICD-10-CM/PCS². The 2015 data in HCUP Fast Stats include three quarters of information based on ICD-9-CM coding, whereas the fourth quarter is based on ICD-10-CM/PCS coding. Users may observe discontinuity in trends analyses that span the October 1, 2015 transition date.

Notable increases or decreases may be observed in the statistics across the ICD-9-CM to ICD-10-CM/PCS transition that are more reflective of definitional changes rather than changes in ED utilization. Compared with the ICD-9-CM time period, some definitions of ED visit type for ICD-10-CM/PCS may be more narrowly or more broadly defined. More information on the impact of ICD-10-CM/PCS is available on the HCUP User Support (HCUP-US) web page for ICD-10-CM/PCS Resources.
¹ International Classification of Diseases, Ninth Revision, Clinical Modification
² International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System

The “expected payer” data element in HCUP databases provides information on the type of payer that the hospital expects to be the source of payment for the hospital bill. Trends in ED visit counts are provided by the following expected primary payers and limited to specific age ranges as indicated:

• Medicare patients aged 65 years and older
• Medicaid patients aged 0 to 18 years for pediatrics and 19 to 64 years for adults
• Privately insured patients aged 0 to 18 years for pediatrics and 19 to 64 years for adults
• Self-pay/No charge patients aged 0 to 18 years for pediatrics and 19 to 64 years for adults

Patients identified as self-pay/no charge have an expected primary payer of self-pay, no charge, charity, or no expected payment. The self-pay/no charge category may also include patients with an expected payer of Indian Health Services, county indigent, migrant health programs, Ryan White Act, Hill-Burton Free Care, or other Federal, State, and local programs for the indigent when those programs are identifiable in the Partner-provided coding of expected payer. This reclassification of patients is only possible for some States. More information on identifying programs reported in HCUP data that may cover the self-pay/no charge category is available in HCUP Methods Series Reports by Topic “User Guide – An Examination of Expected Payer Coding in HCUP Databases” (multiple documents; updated annually).

ED visits with the following expected primary payers and age groups are not reported: Medicare, age 0-64; Medicaid, age 65+; private insurance, age 65+; self-pay/no charge, age 65+; other Federal, state, and local programs (age 0+); missing (age 0+); or invalid (age 0+). In 2022, across all States, these excluded ED visits represented from 10 to 25 percent of all ED visits for age 0+.

The total number of ED visits across all expected payers and age groups, including those not shown, are provided in the underlying data tables (“Show Underlying Data Tables”) and in the Excel data download file (“Show Data Export Options”) for all ED visit types and each separate ED condition. This statistic was added to Fast Stats in December 2019. It was calculated using the currently available SID and SEDD for data years 2006 and forward. If the SID and/or SEDD initially used for Fast Stats has been updated, then the total counts could be based on different versions of the SID and/or SEDD than the counts shown for Medicare, Medicaid, private insurance, and self-pay/no charge.

For comparison against the total described above for all expected payers and age groups, the Excel download file also provides the sum of the displayed expected payers and age groups (i.e., the sum of the rounded weighted quarterly expected payer counts of ED visits across the expected payers and age groups that are displayed in the graphs).

It should be noted that in certain data years and for certain States, data anomalies are identified that may impact the observed trends in ED visits by expected primary payer:

• In the Nebraska SID and SEDD prior to 2016, some Medicaid managed care patients may have been categorized in the data under private insurance instead of Medicaid because the Medicaid program was managed by a commercial insurance company. Beginning with data year 2016, there are large increases in the number of Medicaid records and proportionate decreases in records categorized as private insurance because the Nebraska Partner organization improved the process for the identification of patients covered by Medicaid managed care programs managed by commercial insurance companies.
• In the New York SEDD, the coding of expected primary payer prior to 2011 did not distinguish between patients covered by commercial managed care plans and patients covered by Medicaid managed care plans. Because of this ambiguity in the payer coding, ED visits for patients with Medicaid managed care plans are reported under private insurance in this section of Fast Stats. Starting in 2011, the expected payer coding in New York data separately identifies Medicaid managed care patients and therefore ED visits for these patients are reported under Medicaid.
• In the Vermont 2015 SEDD, increases in Medicaid should be considered an anomaly. Vermont briefly modified their billing process in late 2014, which led to increases in records with a primary expected payer value of Medicaid. In 2016 data, the coding of Medicaid returns to a normal level that is consistent with historical data.

Emergency department visits are reported as Pediatric for patients aged 0 to 18 years and as Adult for patients aged 19 years and older.

Each ED visit is assigned to one of the following ED visit types: abdominal pain, asthma (age 0-18 only), back or neck pain (age 19+ only), dental (age 19+ only), ear infection (age 0-18 only), headache, injury, mental/health substance use (age 19+ only), and skin infections.

The definition for ED visit type has changed over time. ED visit type is identified differently under ICD-9-CM and ICD-10-CM:

• Beginning with quarter 4 of 2015 (2015 Q4): Clinical Classifications Software Refined (CCSR) for ICD-10-CM default categorization scheme for the principal or first-listed diagnosis
• Through quarter 3 of 2015 (2015 Q3): A principal or first-listed diagnosis based on either ranges of ICD-9-CM codes or the Clinical Classifications Software (CCS) for ICD-9-CM

It should be noted that beginning in December 2020, statistics by ED visit type using the ICD-10-CM coding system since quarter 4 of 2015 have been updated to reflect new definitions for each ED visit type. Thus, there is a one-time change in previously released statistics beginning quarter 4 of 2015 through as late as quarter 4 of 2018, depending on the availability of a State’s data when the statistics were last updated prior to December 2020. Many of the current and previously released statistics are similar, but statistics for some ED visit types have changed substantially, specifically for abdominal pain and dental pain. Additional information on the amount of change between current and previously released statistics for each ED visit type by age group and expected payer is provided in the “ICD-10-CM Definition Changes” worksheet of the Excel download file.

The definition for emergency department visits with a principal or first-listed diagnosis of abdominal pain has changed over time:

• Beginning 2015 Q4: Default CCSR SYM006, Abdominal pain and other digestive/abdomen signs and symptoms
• Through 2015 Q3: CCS 251, Abdominal pain

The definition for emergency department visits with a principal or first-listed diagnosis of asthma has changed over time:

• Beginning 2015 Q4: Default CCSR RSP009, Asthma
• Through 2015 Q3: CCS 128, Asthma

The definition for emergency department visits with a principal or first-listed diagnosis of back or neck pain has changed over time:

• Beginning 2015 Q4: Default CCSR MUS011, Spondylopathies/spondyloarthropathy (including infective) or MUS038, Low back pain
• Through 2015 Q3: CCS 205, Spondylosis; intervertebral disc disorders; other back problems

The definition for emergency department visits with a principal or first-listed diagnosis of dental has changed over time:

• Beginning 2015 Q4: Default CCSR DIG002, Disorders of teeth and gingiva
• Through 2015 Q3: ICD-9-CM diagnosis codes 520.0 to 523.9

The definition for emergency department visits with a principal or first-listed diagnosis of ear infection has changed over time:

• Beginning 2015 Q4: Default CCSR EAR001, Otitis media
• Through 2015 Q3: ICD-9-CM diagnosis codes 382.00-382.02, 382.1-382.4, and 382.9

The definition for emergency department visits with a principal or first-listed diagnosis of headache has changed over time:

• Beginning 2015 Q4: Default CCSR NVS010, Headache, including migraine
• Through 2015 Q3: CCS 84, Headache, including migraine

The definition for emergency department visits with a principal or first-listed diagnosis of injury has changed over time:

• Beginning 2015 Q4: Default CCSR INJ001-INJ027, INJ032
• Through 2015 Q3: ICD-9-CM diagnosis codes 800-909.2, 909.4, 909.9, 910-994.9, 995.50-995.59, 995.80-995.85

The above definition of injury through 2015 Q3 includes five diagnosis codes (965.00, 965.01, 965.02, 965.09, and 980.0) that also are included under two CCS diagnosis categories (660 and 661) used for the definition of the mental health/substance use ED visit type for adults, age 19+. As a result, an ED visit for adults with one of these five diagnosis codes is assigned only to the mental health/substance use ED visit type.

Excluded Codes

It should be noted that ICD-9-CM and ICD-10-CM diagnosis codes related to complications of surgical or medical care, or adverse events or anaphylactic shock resulting from medication, anesthesia, or food are not used in the definition of the injury ED visit type.

The definition for adult discharges related to mental health/substance use has changed over time:

• Beginning 2015 Q4: MDC 19, Mental Diseases and Disorders, or 20, Alcohol/Drug Use or Induced Mental Disorders
• For 2007-2015 Q3: Principal diagnosis CCS 650-663, 670
• For 2003-2006: Principal diagnosis CCS 65-75
• For National Inpatient NIS Data Years 1994-2006: CCS 65-75

MDCs were assigned without using “present on admission” information on the record because not all HCUP data sources provide present on admission indicators.

Beginning with the 2017 data year, the Iowa SID includes records for behavioral health patients treated in chemical dependency or psychiatric care units. Prior to 2017 data, these records were prohibited from release, and therefore not reported in Fast Stats.

The definition for emergency department visits with a principal or first-listed diagnosis of skin infection has changed over time:

• Beginning 2015 Q4: Default CCSR SKN001, Skin and subcutaneous tissue infections
• Through 2015 Q3: CCS 197, Skin and subcutaneous tissue infections

Reporting of stomach flu in this section of Fast Stats was discontinued in December 2020. At that time, changes were made to the ICD-10-CM definitions for each ED visit type. One specific ICD-10-CM diagnosis code, R19.7 (Diarrhea, unspecified), which was previously included in the definition for stomach flu and responsible for the majority of ED visits with this first-listed diagnosis, is now included in the definition for abdominal pain. As a result, trends in pediatric ED visits for stomach flu significantly declined. Stomach flu has been removed from the active query tool, but historical data previously released in HCUP Fast Stats for this ED visit type (with data reported through 2018 Q4 for some States) is offered in the Excel download file, which can be downloaded by expanding “Show Data Export Options.”

• Statistics on the number of eligible individuals who enrolled in marketplace plans are available at the State-level from the Office of The Assistant Secretary for Planning and Evaluation (ASPE) in periodic Enrollment Reports posted on their website under Enrollment Reports.
• Information on Medicaid and CHIP enrollment is available at the State level from the Centers for Medicare & Medicaid Services (CMS) in monthly reports posted on the Medicaid website under Medicaid and CHIP Enrollment Data.
• Information on the income-based eligibility levels required by the Affordable Care Act and effective as of April 1, 2016 is available at the State level from CMS on the Medicaid website under Medicaid and CHIP Eligibility Levels.
• Yearly information on the percent of adults aged 19 to 64 years who were uninsured is available from the Kaiser Family Foundation (KFF) website under State Health Facts.

The State-specific Medicaid expansion information quoted on this site is compiled from the Kaiser Family Foundation (kff.org):³

• Kaiser Family Foundation “Status of State Action on the Medicaid Expansion Decision”
• Kaiser Family Foundation “States Getting a Jump Start on Health Reform’s Medicaid Expansion”

When these sources indicate a definitive implementation date for expansion, and HCUP data are available for the time period covered by the expansion, the graphs show a vertical dotted line marking the initial Medicaid expansion date.

³ The U.S. Department of Health and Human Services (HHS) is offering these links for informational purposes only, and this fact should not be construed as an endorsement of the host organization’s programs or activities.

The national estimates are drawn from the HCUP National (Nationwide) Inpatient Sample (NIS). The NIS is based on data from community hospitals, which are defined as short-term, non-Federal, general, and other hospitals, excluding hospital units of other institutions (e.g., prisons). The NIS includes obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are community hospitals that are also long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals. Beginning in 2012, long-term acute care hospitals (LTACs) are also excluded from the sampling frame. However, if a patient received long-term care, rehabilitation, or treatment for psychiatric or chemical dependency conditions in a community hospital, the discharge record for that stay will be included in the NIS.

The NIS is sampled from the HCUP State Inpatient Databases (SID). Beginning with the 2012 data year, the NIS is a 20 percent sample of discharges from all community hospitals that participate in the corresponding data year. For data years 1988 through 2011, the NIS was a 20 percent sample of community hospitals and included all discharges within sampled hospitals. The national estimates were developed using the NIS Trend Weight Files for consistent estimates across all data years (e.g., LTACs were removed from analysis using trend weights).

The unit of analysis is the hospital discharge (i.e., the hospital inpatient stay) or an emergency department (ED) visit, not a person or patient. This means that a person who is admitted to the hospital or visits the ED multiple times in one year is counted each time as a separate discharge from the hospital or a separate visit in the ED.

For Fast Stats, all stays and visits are counted one time only, regardless of the number of relevant diagnosis or procedure codes that appear on the record. For instance, when identifying injury-related inpatient stays and ED visits, a record may include more than one of the injury-specific codes; in such a case, the record is only included once in the injury counts.

On October 1, 2015, the United States transitioned from ICD-9-CM¹ to ICD-10-CM/PCS². The graphics demarcate this transition with statistics reported using ICD-9-CM coding identified as “ICD-9-CM” on the graphs and statistics reported using ICD-10-CM/PCS coding identified as “ICD-10-CM/PCS” on the graphs. The 2015 rates of stays per 100,000 population and average statistics for hospitalization type are based on the first three quarters of data with ICD-9-CM codes only (January 1, 2015 to September 30, 2015). The number of inpatient stays by hospitalization type in 2015 is not reported because the statistics are not based on full year data. Statistics for all other characteristics include data for the full 2015 calendar year since these statistics are non-clinical, and therefore not impacted by the transition to ICD-10-CM/PCS.

Notable increases or decreases may be observed in the statistics across the ICD-9-CM to ICD-10-CM/PCS transition that are more reflective of definitional changes rather than changes in hospital utilization. Compared with the ICD-9-CM time period, some definitions of hospitalization type for ICD-10-CM/PCS may be more narrowly or more broadly defined. More information on the impact of ICD-10-CM/PCS is available on the HCUP User Support (HCUP-US) web page for ICD-10-CM/PCS Resources.

¹ International Classification of Diseases, Ninth Revision, Clinical Modification
² International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System

Population-based rates are presented for inpatient stay trends overall and by age, sex, community-level income, and hospitalization type. Rates are not reported by expected payer because currently there is no data source for national population insurance estimates that align with HCUP’s definition of expected primary payer. The rate of stays includes the HCUP number of stays in the numerator and the U.S. resident population in the denominator (with a multiplier of 100,000). For age, sex, and community-level income, the denominator is consistently defined with the numerator (i.e., rates for females use HCUP counts and population counts specific to females). For hospitalization type, the denominator represents the total U.S. resident population. Population data are obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. Rates are only reported from 2002 forward because the population denominators for age, sex, and community-level income were unavailable prior to 2002.

The NIS includes information on total hospital charges for an inpatient stay. Charges represent the amount a hospital billed for the entire hospital stay, excluding professional (physician) fees. Total hospital charges are converted to costs using HCUP Cost-to-Charge Ratios (CCRs) based on hospital accounting reports from the Centers for Medicare & Medicaid Services (CMS). Costs reflect the actual expenses incurred in the production of hospital services, such as wages, supplies, and utility costs. For each hospital in the NIS, a hospital-wide cost-to-charge ratio is used. The average cost per stay is calculated using discharges with nonmissing total costs. Costs are not imputed if total charges are not reported on the discharge record. Costs are only reported from 2000 forward because HCUP Cost-to-Charge Ratios are unavailable prior to 2000.

The actual average cost per stay is inflation adjusted using price indexes for the Gross Domestic Product (GDP) from the U.S. Department of Commerce Bureau of Economic Analysis (BEA). We used the BEA Interactive Data query tool to request National Data, GDP & Personal Income, Section 1 Domestic Product and Income, Table 1.1.4. Price Indexes for Gross Domestic Product. Price indexes for data years 1994-2014 were obtained on June 23, 2015. Price indexes for subsequent data years were obtained at later dates to coincide with Fast Stats updates. The adjustment used 2010 as the index base so that updates to the trends could retain a consistent base.

The length of stay (LOS) is the number of days that the patient stayed in the hospital. It is calculated by subtracting the admission date from the discharge date. Same-day stays are therefore coded with a length of stay of 0. The average LOS is calculated using discharges with nonmissing LOS.

In-hospital mortality is determined by the discharge disposition of the patient from the hospital. The numerator of the mortality rate is the number of patients within a reporting category (e.g., within a specific diagnosis category) who died in the hospital. The denominator is based on the total number of discharges in the reporting category. Discharges missing discharge disposition are excluded from the numerator and denominator of the in-hospital mortality rate.

National Inpatient Stays:
Age refers to the age of the patient at admission. Discharges missing age are excluded from results reported by age.

National Emergency Department Visits:
Age refers to the age of the patient at admission to the ED. ED visits missing age are excluded from results reported by age.

Opioids Hospital Use:
Age refers to the age of the patient at admission. Discharges or visits missing age are excluded from results reported by age.

It should be noted that beginning with the transition to the ICD-10-CM/PCS coding system on October 1, 2015, a noticeable increase in opioid-related inpatient stays was observed for adults aged 65 years and older in most States. Additional information regarding this pattern is available on the HCUP-US web page for ICD-10-CM/PCS Resources in the report Preliminary Case Study: Exploring How Opioid-Related Diagnosis Codes Translate from ICD-9-CM to ICD-10-CM.

Hurricane Impact:
Age refers to the age (in years) of the patient at admission. Discharges or visits missing age are excluded from results reported by age. Age is grouped into three categories: 0-17 years, 18-64 years, and 65+ years. Less than 0.05 percent of records are missing information on age.

All nonmale, nonfemale responses are set to missing.
Discharges for inpatient stays and ED visits from emergency department visits with missing values for sex are excluded from results reported by sex.

The “expected payer” data element in HCUP databases provides information on the type of payer that the hospital expects to be the source of payment for the hospital bill. Information is reported by the following expected primary payers: Medicare, Medicaid, private insurance, and self-pay/no charge. Patients identified as self-pay/no charge have an expected primary payer of self-pay, no charge, charity, or no expected payment. More information on expected payer coding in HCUP data is available in HCUP Methods Series Reports by Topic “User Guide – An Examination of Expected Payer Coding in HCUP Databases” (multiple documents; updated annually). Discharges missing expected payer are excluded from results reported by expected payer.

Discharges with the following expected primary payers are not reported by expected payers: other Federal, State, and local programs; missing; or invalid. These excluded discharges represent approximately 3 percent of all annual discharges.

The total reflecting the number of discharges across all expected payers (including those groups not presented in the graphs) is provided in the underlying data tables (“Show Underlying Data Tables”) by expected payer. These totals are the same as the counts obtained for the all inpatient stays characteristic selection.

For comparison against the total described above for all expected payers, the Excel download file also provides the sum of the displayed expected payers (i.e., the sum of the expected payer counts of discharges across the expected payers that are displayed in the graphs).

Community-level income is based on the median household income of the patient’s ZIP Code of residence. Quartiles are defined so that the total U.S. population is evenly distributed across four groups. Over time, the data element in the NIS for community-level income has changed definitions. The cut-offs for the quartile designation are determined annually using ZIP Code demographic data obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. The value ranges for the national income quartiles vary by year. Income quartile is missing if the patient is homeless or foreign. Records missing the income quartile are excluded from results reported by community-level income.

For Inpatient data, information by community-level income is only reported from 2002 forward because of inconsistent definitions over time in the income-related data elements in the NIS.

Each discharge is assigned to a single hospitalization type hierarchically, based on the following order: maternal, mental health/substance use, injury, surgical, and medical. All discharges are categorized in one of the five mutually exclusive hospitalization types based on the principal diagnosis for the hospital stay.

The definitions for the maternal, mental health/substance use, and injury hospitalization types have changed over time; they are identified differently under ICD-9-CM and ICD-10-CM:

• Beginning with quarter 4 of 2015 (2015 Q4): Major Diagnostic Category (MDC) or Clinical Classifications Software Refined (CCSR) for ICD-10-CM default categorization scheme for the principal diagnosis
• Through quarter 3 of 2015 (2015 Q3): A principal diagnosis based on either ranges of ICD-9-CM codes or the Clinical Classifications Software (CCS) for ICD-9-CM

The definitions for the surgical and medical hospitalization types remain the same under both the ICD-9-CM and ICD-10-CM coding systems. They are defined based on the Diagnosis-Related Group (DRG).

It should be noted that beginning in December 2020, statistics by hospitalization type using the ICD-10-CM coding system (since quarter 4 of 2015) have been updated to reflect new definitions provided below for each of the five hospitalization types. Thus, there is a one-time change in previously released statistics beginning quarter 4 of 2015 through as late as quarter 1 of 2019, depending on the availability of a State’s data when the statistics were last updated prior to December 2020. Many of the current and previously released statistics are similar, but statistics for some hospitalization types have changed substantially, specifically for mental health/substance use. The new definition of mental health/substance use is based on major diagnostic category (MDC). As a result, there are specific ICD-10-CM diagnosis codes that are no longer included. For example, discharges with a principal diagnosis code indicating alcoholic cirrhosis of the liver, Alzheimer’s disease, and poisoning by narcotics and psychodysleptics are no longer assigned to the hospitalization type for mental health/substance use. Additional information on the amount of change between current and previously released statistics for each hospitalization type by age group and expected payer is provided in the “ICD-10-CM Definition Changes” worksheet of the Excel download file.

Maternal discharges are defined using the following Clinical Classifications Software (CCS) for ICD-9-CM categories for data years 2015 and earlier or Major Diagnostic Category (MDC) beginning with data year 2016. MDC was assigned without using “present on admission” information on the record because not all HCUP data sources provide present on admission indicators.

• Beginning with Data Year 2016: MDC 14, Pregnancy, Childbirth and the Puerperium
• For Data Years 1994-2015: CCS 176-196

For data years 2015 and earlier, the CCS-based definition of maternal may result in slightly different counts of discharges when compared with other ways of classifying diagnosis codes. For example, compared with using MDC from 2015 and earlier, the CCS approach assigns 0.9 percent fewer cases to “maternal” because a maternal discharge is classified into a mental health CCS or a substance use CCS when the diagnosis code includes a mental health or substance abuse condition along with a maternal condition (e.g., drug dependence in pregnancy).

Neonatal discharges are defined using the following Clinical Classifications Software (CCS) for ICD-9-CM categories for data years 2015 and earlier or Major Diagnostic Category (MDC) beginning with data year 2016. MDC was assigned without using “present on admission” information on the record because not all HCUP data sources provide present on admission indicators.

• Beginning with Data Year 2016: MDC 15, Newborns and Other Neonates with Conditions Originating in the Perinatal Period
• For Data Years 1994-2015: CCS 218-224

For data years 2015 and earlier, the CCS-based definition of neonatal may result in slightly different counts of discharges when compared with other ways of classifying diagnosis codes. For example, compared with using MDC from 2015 and earlier, the CCS approach assigns 0.1 percent fewer cases to “neonatal” because a neonatal discharge is classified into a substance use CCS when the diagnosis code refers to a drug effect on the fetus or neonatal drug withdrawal.

The definition for adult discharges related to mental health/substance use has changed over time:

• Beginning 2015 Q4: MDC 19, Mental Diseases and Disorders, or 20, Alcohol/Drug Use or Induced Mental Disorders
• For 2007-2015 Q3: Principal diagnosis CCS 650-663, 670
• For 2003-2006: Principal diagnosis CCS 65-75
• For National Inpatient NIS Data Years 1994-2006: CCS 65-75

MDCs were assigned without using “present on admission” information on the record because not all HCUP data sources provide present on admission indicators.

Beginning with the 2017 data year, the Iowa SID includes records for behavioral health patients treated in chemical dependency or psychiatric care units. Prior to 2017 data, these records were prohibited from release, and therefore not reported in Fast Stats.

Injury discharges are identified by either: a) a principal diagnosis based on ranges of ICD-9-CM codes for data years 2015 and earlier, or b) a combination of the Clinical Classifications Software Refined (CCSR) for ICD-10-CM default categorization scheme for the principal diagnosis and individual ICD-10-CM diagnosis codes, for data years 2016 and later.

The definition for adult discharges related to injury has changed over time:

•  Beginning with Data Year 2016: CCSR INJ001-INJ027, INJ032 and ICD-10-CM diagnosis codes in the T84 series (used only for discharges from 1/1/2016-9/30/2016)
•  Beginning 2015 Q4: Default for principal diagnosis CCSR INJ001-INJ027, INJ032
•  Through 2015 Q3: Principal ICD-9-CM diagnosis codes 800-909.2, 909.4, 909.9, 910-994.9, 995.50-995.59, 995.80-995.85

The above definition of injury through 2015 Q3 includes five ICD-9-CM diagnosis codes (965.00, 965.01, 965.02, 965.09, and 980.0) that are also included under two CCS diagnosis categories (660 and 661) used for the definition of the mental health/substance use hospitalization type for ICD-9-CM. Because of the hierarchical ordering used to assign discharges to hospitalization type, discharges with one of these five principal ICD-9-CM diagnosis codes are assigned to the mental health/substance use hospitalization type and not the injury hospitalization type.

Excluded Codes

It should be noted that ICD-9-CM and ICD-10-CM diagnosis codes related to complications of surgical or medical care, or adverse events or anaphylactic shock resulting from medication, anesthesia, or food are not used in the definition of the injury hospitalization type.

Surgical discharges are identified by a surgical diagnosis-related group (DRG). The DRG grouper first assigns the discharge to a MDC based on the principal diagnosis. For each MDC, there is a list of procedure codes that qualify as operating room procedures. If the discharge involves an operating room procedure, it is assigned to one of the surgical DRGs within the MDC category; otherwise it is assigned to a medical DRG.

All other discharges that are not identified as maternal, neonatal, mental health/substance use, injury, or surgical are identified as medical discharge.  If the DRG indicates the information on the record is ungroupable (i.e., not identifiable as medical or surgical), then the discharge is assumed to be medical. This rarely occurs (less than 0.1 percent of total discharges).

The national estimates are drawn from the HCUP Nationwide Emergency Department Sample (NEDS). The NEDS is the largest all-payer emergency department (ED) database in the United States, yielding national estimates of hospital-owned ED visits. Hospital-owned EDs are limited to community hospitals, which are defined as short-term, non-Federal, general, and other hospitals, excluding hospital units of other institutions (e.g., prisons). The NEDS includes specialty, pediatric, public, and academic medical hospitals. Excluded are long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals.

The NEDS is sampled from the HCUP State Emergency Department Databases (SEDD), which capture information on ED encounters that do not result in an admission (i.e., treat-and-release visits and transfers to other hospitals), and the HCUP State Inpatient Databases (SID), which contain information on patients initially seen in the ED and then admitted to the same hospital. The NEDS approximates a 20 percent stratified sample of U.S. hospital-owned EDs. The NEDS is stratified on the following hospital characteristics: U.S. Census region, trauma center designation, urban-rural location of the hospital, ownership, and teaching status. The NEDS is currently available for data years 2006-2019. Since the initial release of the NEDS, State participation has grown from 24 States in 2006 to 40 States and the District of Columbia in 2019.

The unit of analysis is the hospital discharge (i.e., the hospital inpatient stay) or an emergency department (ED) visit, not a person or patient. This means that a person who is admitted to the hospital or visits the ED multiple times in one year is counted each time as a separate discharge from the hospital or a separate visit in the ED.

For Fast Stats, all stays and visits are counted one time only, regardless of the number of relevant diagnosis or procedure codes that appear on the record. For instance, when identifying injury-related inpatient stays and ED visits, a record may include more than one of the injury-specific codes; in such a case, the record is only included once in the injury counts.

On October 1, 2015, the United States transitioned from ICD-9-CM¹ to ICD-10-CM/PCS². The 2015 data in HCUP Fast Stats include three quarters of information based on ICD-9-CM coding, whereas the fourth quarter is based on ICD-10-CM/PCS coding. Users may observe discontinuity in trends analyses that span the October 1, 2015 transition date.

Notable increases or decreases may be observed in the statistics across the ICD-9-CM to ICD-10-CM/PCS transition that are more reflective of definitional changes rather than changes in ED utilization. Compared with the ICD-9-CM time period, some definitions of ED visit type for ICD-10-CM/PCS may be more narrowly or more broadly defined. More information on the impact of ICD-10-CM/PCS is available on the HCUP User Support (HCUP-US) web page for ICD-10-CM/PCS Resources.
¹ International Classification of Diseases, Ninth Revision, Clinical Modification
² International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System

Population-based rates are presented for ED visit trends overall and by age, sex, community-level income, and patient location. Population-based rates are not reported by expected payer because currently there is no data source of national population insurance estimates that aligns with HCUP’s definition of expected primary payer. The rate of ED visits includes the HCUP number of ED visits in the numerator and the U.S. resident population in the denominator (with a multiplier of 100,000). For all characteristics, the denominator is consistently defined with the numerator (i.e., rates for females use HCUP counts and population counts specific to females). Population data are obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas.

National Inpatient Stays:
Age refers to the age of the patient at admission. Discharges missing age are excluded from results reported by age.

National Emergency Department Visits:
Age refers to the age of the patient at admission to the ED. ED visits missing age are excluded from results reported by age.

Opioids Hospital Use:
Age refers to the age of the patient at admission. Discharges or visits missing age are excluded from results reported by age.

It should be noted that beginning with the transition to the ICD-10-CM/PCS coding system on October 1, 2015, a noticeable increase in opioid-related inpatient stays was observed for adults aged 65 years and older in most States. Additional information regarding this pattern is available on the HCUP-US web page for ICD-10-CM/PCS Resources in the report Preliminary Case Study: Exploring How Opioid-Related Diagnosis Codes Translate from ICD-9-CM to ICD-10-CM.

Hurricane Impact:
Age refers to the age (in years) of the patient at admission. Discharges or visits missing age are excluded from results reported by age. Age is grouped into three categories: 0-17 years, 18-64 years, and 65+ years. Less than 0.05 percent of records are missing information on age.

All nonmale, nonfemale responses are set to missing.
Discharges for inpatient stays and ED visits from emergency department visits with missing values for sex are excluded from results reported by sex.

The “expected payer” data element in HCUP databases provides information on the type of payer that is expected to be the source of payment for the ED bill. Information is reported by the following expected primary payers: Medicare, Medicaid, private insurance, and self-pay/no charge. Patients identified as self-pay/no charge have an expected primary payer of self-pay, no charge, charity, or no expected payment. More information on expected payer coding in HCUP data is available in HCUP Methods Series Reports by Topic “User Guide – An Examination of Expected Payer Coding in HCUP Databases” (multiple documents; updated annually). ED visits missing expected payer are excluded from results reported by expected payer.

ED visits with the following expected primary payers are not reported by expected payer: other Federal, State, and local programs; missing; or invalid. These excluded ED visits represent approximately 4 percent of all annual ED visits.

The total reflecting the number of ED visits across all expected payers (including those groups not presented in the graphs) is provided in the underlying data tables (“Show Underlying Data Tables”) by expected payer by ED visit type. These totals are the same as the counts obtained for the overall characteristic selection for the respective ED visit type.

For comparison against the total described above for all expected payers, the Excel download file also provides the sum of the displayed expected payers (i.e., the sum of the expected payer counts of ED visits across the expected payers that are displayed in the graphs).

Community-level income is based on the median household income of the patient’s ZIP Code of residence. Quartiles are defined so that the total U.S. population is evenly distributed across four groups. Over time, the data element in the NIS for community-level income has changed definitions. The cut-offs for the quartile designation are determined annually using ZIP Code demographic data obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. The value ranges for the national income quartiles vary by year. Income quartile is missing if the patient is homeless or foreign. Records missing the income quartile are excluded from results reported by community-level income.

For Inpatient data, information by community-level income is only reported from 2002 forward because of inconsistent definitions over time in the income-related data elements in the NIS.

Patient location is based on the six-category, county-level scheme developed by the National Center for Health Statistics (NCHS) to study the relationship between urbanization and health:

• Large central metropolitan: Counties in metropolitan statistical areas (MSAs) of 1 million or more population that contain the entire population of the largest principal city of the MSA, have their entire population contained in the largest principal city of the MSA, or contain at least 250,000 inhabitants of any principal city of the MSA
• Large fringe metropolitan (suburbs): Counties in MSAs of 1 million or more population that did not qualify as large central metropolitan counties
• Medium metropolitan: Counties in MSAs of populations of 250,000 to 999,999
• Small metropolitan: Counties in MSAs of population less than 250,000
• Micropolitan: Counties in micropolitan statistical areas
• Noncore: Nonmetropolitan counties that did not qualify as micropolitan

The micropolitan and noncore categories are combined into a single category (“Rural”) in order to preserve results when cell sizes are too small. For rates prior to 2014, the NCHS classification is based on population density from the 2000 Census. Starting in 2014, the NCHS classification is based on population density from the 2010 Census. Newborn hospitalizations missing patient location are excluded from results reported by patient location.
Patient location categories may include out-of-state patients because the classification is based on patient residence county but reported by the State for the hospital. Additional information on the patient location classification system is available at NCHS Urban-Rural Classification Scheme for Counties.

The national estimates are drawn from the HCUP National (Nationwide) Inpatient Sample (NIS). The NIS is based on data from community hospitals, which are defined as short-term, non-Federal, general, and other hospitals, excluding hospital units of other institutions (e.g., prisons). The NIS includes obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are community hospitals that are also long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals. Beginning in 2012, long-term acute care hospitals (LTACs) are also excluded from the sampling frame. However, if a patient received long-term care, rehabilitation, or treatment for psychiatric or chemical dependency conditions in a community hospital, the discharge record for that stay will be included in the NIS.

The NIS is sampled from the HCUP State Inpatient Databases (SID). Beginning with the 2012 data year, the NIS is a 20 percent sample of discharges from all community hospitals that participate in the corresponding data year. For data years 1988 through 2011, the NIS was a 20 percent sample of community hospitals and included all discharges within sampled hospitals. The national estimates were developed using the NIS Trend Weight Files for consistent estimates across all data years (e.g., LTACs were removed from analysis using trend weights).

The unit of analysis is the hospital discharge (i.e., the hospital inpatient stay) or an emergency department (ED) visit, not a person or patient. This means that a person who is admitted to the hospital or visits the ED multiple times in one year is counted each time as a separate discharge from the hospital or a separate visit in the ED.

For Fast Stats, all stays and visits are counted one time only, regardless of the number of relevant diagnosis or procedure codes that appear on the record. For instance, when identifying injury-related inpatient stays and ED visits, a record may include more than one of the injury-specific codes; in such a case, the record is only included once in the injury counts.

Beginning with data year 2020, COVID-19-related hospitalizations may be identified by any-listed ICD-10-CM diagnosis code of “U071” (2019 novel coronavirus disease) on the discharge record. Per coding guidelines, the use of diagnosis code “U071” is based on documentation by the provider or documentation of a positive COVID-19 test result.  The ICD-10-CM diagnosis code for COVID-19 was implemented beginning April 1, 2020.  There may be other ICD-10-CM codes that reflect conditions related to COVID-19 stays.

On October 1, 2015, the United States transitioned from ICD-9-CM¹ to ICD-10-CM/PCS². The 2015 rates of stays per 100,000 population are based on the first three quarters of data with ICD-9-CM codes only (January 1, 2015 to September 30, 2015). The number of inpatient stays by diagnosis in 2015 is not reported because the statistics are not based on full year data. More information on the impact of ICD-10-CM/PCS is available on the HCUP User Support (HCUP-US) web page for ICD-10-CM/PCS Resources.

¹ International Classification of Diseases, Ninth Revision, Clinical Modification
² International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System

A change in the ICD-10-CM coding guidelines on which diagnosis to code as the principal diagnosis has caused a discontinuity in the ranking of inpatient stays related to chronic obstructive pulmonary disease (COPD) and pneumonia. Effective October 1, 2016 precedence was given to the COPD diagnosis. A subsequent revision effective October 1, 2017 bases precedence on the discretion of a clinical coder.

The principal diagnosis is that condition established after study to be chiefly responsible for the patient’s admission to the hospital. Diagnoses in the NIS are reported using ICD-9-CM codes through September 30, 2015 and ICD-10-CM codes beginning October 1, 2015. There are approximately 14,000 ICD-9-CM diagnosis codes and over 70,000 ICD-10-CM diagnosis codes.

The principal diagnosis is defined using the Clinical Classifications Software (CCS) for ICD-9-CM for data years 2015 and earlier, and the Clinical Classifications Software Refined (CCSR) for ICD-10-CM default categorization scheme for the principal diagnosis beginning with data year 2016. Results are reported by the CCS or CCSR category and list the top 10 most common principal diagnoses for each data year. The top 10 ranking is based on the weighted number of stays. Because of the transition from ICD-9-CM to ICD-10-CM/PCS on October 1, 2015, the total number of inpatient stays in 2015 is not reported. The 2015 rate of stays per 100,000 population is based on the first three quarters of 2015 data (Q1-3) only.

Results can be displayed with maternal and neonatal stays included or excluded from the ranking. This option is provided because maternal and neonatal discharges account for nearly a fourth of all hospital discharges in a year and the majority are low complexity, low cost stays. Maternal and neonatal stays are defined differently across data years. For data years 2015 and earlier, the principal diagnosis CCS 176 through 196 are used for maternal and CCS 218 through 224 are used for neonatal. Beginning with data year 2016, Major Diagnostic Category (MDC) 14 (Pregnancy, Childbirth, and the Puerperium) and MDC 15 (Newborns and Other Neonates with Conditions Originating in the Perinatal Period) are used.

Population-based rates are presented for inpatient stay trends overall and by age, sex, community-level income, and hospitalization type. Rates are not reported by expected payer because currently there is no data source for national population insurance estimates that align with HCUP’s definition of expected primary payer. The rate of stays includes the HCUP number of stays in the numerator and the U.S. resident population in the denominator (with a multiplier of 100,000). For age, sex, and community-level income, the denominator is consistently defined with the numerator (i.e., rates for females use HCUP counts and population counts specific to females). For hospitalization type, the denominator represents the total U.S. resident population. Population data are obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. Rates are only reported from 2002 forward because the population denominators for age, sex, and community-level income were unavailable prior to 2002.

National Inpatient Stays:
Age refers to the age of the patient at admission. Discharges missing age are excluded from results reported by age.

National Emergency Department Visits:
Age refers to the age of the patient at admission to the ED. ED visits missing age are excluded from results reported by age.

Opioids Hospital Use:
Age refers to the age of the patient at admission. Discharges or visits missing age are excluded from results reported by age.

It should be noted that beginning with the transition to the ICD-10-CM/PCS coding system on October 1, 2015, a noticeable increase in opioid-related inpatient stays was observed for adults aged 65 years and older in most States. Additional information regarding this pattern is available on the HCUP-US web page for ICD-10-CM/PCS Resources in the report Preliminary Case Study: Exploring How Opioid-Related Diagnosis Codes Translate from ICD-9-CM to ICD-10-CM.

Hurricane Impact:
Age refers to the age (in years) of the patient at admission. Discharges or visits missing age are excluded from results reported by age. Age is grouped into three categories: 0-17 years, 18-64 years, and 65+ years. Less than 0.05 percent of records are missing information on age.

All nonmale, nonfemale responses are set to missing.
Discharges for inpatient stays and ED visits from emergency department visits with missing values for sex are excluded from results reported by sex.

The “expected payer” data element in HCUP databases provides information on the type of payer that the hospital expects to be the source of payment for the hospital bill. Information is reported by the following expected primary payers: Medicare, Medicaid, private insurance, and self-pay/no charge. Patients identified as self-pay/no charge have an expected primary payer of self-pay, no charge, charity, or no expected payment. More information on expected payer coding in HCUP data is available in HCUP Methods Series Reports by Topic “User Guide – An Examination of Expected Payer Coding in HCUP Databases” (multiple documents; updated annually). Discharges missing expected payer are excluded from results reported by expected payer.

Discharges with the following expected primary payers are not reported by expected payer: other Federal, State, and local programs; missing; or invalid.

Community-level income is based on the median household income of the patient’s ZIP Code of residence. Quartiles are defined so that the total U.S. population is evenly distributed across four groups. Over time, the data element in the NIS for community-level income has changed definitions. The cut-offs for the quartile designation are determined annually using ZIP Code demographic data obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. The value ranges for the national income quartiles vary by year. Income quartile is missing if the patient is homeless or foreign. Records missing the income quartile are excluded from results reported by community-level income.

For Inpatient data, information by community-level income is only reported from 2002 forward because of inconsistent definitions over time in the income-related data elements in the NIS.

The national estimates are drawn from the HCUP National (Nationwide) Inpatient Sample (NIS). The NIS is based on data from community hospitals, which are defined as short-term, non-Federal, general, and other hospitals, excluding hospital units of other institutions (e.g., prisons). The NIS includes obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are community hospitals that are also long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals. Beginning in 2012, long-term acute care hospitals (LTACs) are also excluded from the sampling frame. However, if a patient received long-term care, rehabilitation, or treatment for psychiatric or chemical dependency conditions in a community hospital, the discharge record for that stay will be included in the NIS.

The NIS is sampled from the HCUP State Inpatient Databases (SID). Beginning with the 2012 data year, the NIS is a 20 percent sample of discharges from all community hospitals that participate in the corresponding data year. For data years 1988 through 2011, the NIS was a 20 percent sample of community hospitals and included all discharges within sampled hospitals. The national estimates were developed using the NIS Trend Weight Files for consistent estimates across all data years (e.g., LTACs were removed from analysis using trend weights).

The unit of analysis is the hospital discharge (i.e., the hospital inpatient stay) or an emergency department (ED) visit, not a person or patient. This means that a person who is admitted to the hospital or visits the ED multiple times in one year is counted each time as a separate discharge from the hospital or a separate visit in the ED.

For Fast Stats, all stays and visits are counted one time only, regardless of the number of relevant diagnosis or procedure codes that appear on the record. For instance, when identifying injury-related inpatient stays and ED visits, a record may include more than one of the injury-specific codes; in such a case, the record is only included once in the injury counts.

On October 1, 2015, the United States transitioned from ICD-9-CM¹ to ICD-10-CM/PCS². The 2015 rates of stays per 100,000 population are based on the first three quarters of data with ICD-9-CM codes only (January 1, 2015 to September 30, 2015). The number of inpatient stays by diagnosis in 2015 is not reported because the statistics are not based on full year data. More information on the impact of ICD-10-CM/PCS is available on the HCUP User Support (HCUP-US) web page for ICD-10-CM/PCS Resources.

¹ International Classification of Diseases, Ninth Revision, Clinical Modification
² International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System

Operating room (OR) procedures are identified using the Procedure Classes for ICD-9-CM for data years 2015 and earlier and the Procedure Classes Refined for ICD-10-PCS beginning data year 2016. The Procedure Classes tools identify procedures as diagnostic or therapeutic and whether they would be expected to be performed in an operating room. OR procedures are identified using all-listed procedures (principal and secondary) that are available on the discharge record.

The definition of an OR procedure varies over time. With the Procedure Classes for ICD-9-CM, procedure codes are considered to be valid OR procedures based on the definition of a major surgery in the Medicare Severity Diagnosis Related Group (MS-DRG) grouper. The MS-DRG classification scheme relied on physician panels that classified ICD-9-CM procedure codes according to whether the procedure would be performed in a hospital OR in most hospitals. Beginning with the Procedure Classes Refined for ICD-10-PCS v2021.2, ICD-10-PCS procedure codes are determined to be valid OR procedures based on the AHRQ Quality Indicator (QI) software. Changes to either the definition of an OR procedure or the coding system may affect how some procedures are ranked. For example, circumcision is no longer reported as a most common OR procedure beginning data year 2016.

Results are reported using the Clinical Classifications Software (CCS) for ICD-9-CM for data years 2015 and earlier, and the Clinical Classifications Software Refined (CCSR) for ICD-10-PCS procedure codes beginning with data year 2016. Results are reported by the CCS or CCSR category and list the top 10 most common operations for each data year. Counts for procedures are de-duplicated within a discharge record: if a particular CCS or CCSR procedure occurs multiple times during the same hospital stay, it is counted only once. Because there can be multiple procedures reported on a single hospital stay, one discharge record may contribute to the count for more than one operating room procedure. The top 10 ranking is based on the weighted number of stays. Because of the transition from ICD-9-CM to ICD-10-CM/PCS on October 1, 2015, the total number of inpatient stays in 2015 is not reported. The 2015 rate of stays per 100,000 population is based on the first three quarters of 2015 data (Q1-3) only.

Results can be displayed with maternal and neonatal stays included or excluded from the ranking. This option is provided because maternal and neonatal discharges account for nearly a fourth of all hospital discharges in a year and the majority are low complexity, low cost stays. Maternal and neonatal stays are defined differently across data years. For data years 2015 and earlier, the principal diagnosis CCS 176 through 196 are used for maternal and CCS 218 through 224 are used for neonatal. Beginning with data year 2016, Major Diagnostic Category (MDC) 14 (Pregnancy, Childbirth, and the Puerperium) and MDC 15 (Newborns and Other Neonates with Conditions Originating in the Perinatal Period) are used.

Population-based rates are presented for inpatient stay trends overall and by age, sex, community-level income, and hospitalization type. Rates are not reported by expected payer because currently there is no data source for national population insurance estimates that align with HCUP’s definition of expected primary payer. The rate of stays includes the HCUP number of stays in the numerator and the U.S. resident population in the denominator (with a multiplier of 100,000). For age, sex, and community-level income, the denominator is consistently defined with the numerator (i.e., rates for females use HCUP counts and population counts specific to females). For hospitalization type, the denominator represents the total U.S. resident population. Population data are obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. Rates are only reported from 2002 forward because the population denominators for age, sex, and community-level income were unavailable prior to 2002.

National Inpatient Stays:
Age refers to the age of the patient at admission. Discharges missing age are excluded from results reported by age.

National Emergency Department Visits:
Age refers to the age of the patient at admission to the ED. ED visits missing age are excluded from results reported by age.

Opioids Hospital Use:
Age refers to the age of the patient at admission. Discharges or visits missing age are excluded from results reported by age.

It should be noted that beginning with the transition to the ICD-10-CM/PCS coding system on October 1, 2015, a noticeable increase in opioid-related inpatient stays was observed for adults aged 65 years and older in most States. Additional information regarding this pattern is available on the HCUP-US web page for ICD-10-CM/PCS Resources in the report Preliminary Case Study: Exploring How Opioid-Related Diagnosis Codes Translate from ICD-9-CM to ICD-10-CM.

Hurricane Impact:
Age refers to the age (in years) of the patient at admission. Discharges or visits missing age are excluded from results reported by age. Age is grouped into three categories: 0-17 years, 18-64 years, and 65+ years. Less than 0.05 percent of records are missing information on age.

All nonmale, nonfemale responses are set to missing.
Discharges for inpatient stays and ED visits from emergency department visits with missing values for sex are excluded from results reported by sex.

The “expected payer” data element in HCUP databases provides information on the type of payer that the hospital expects to be the source of payment for the hospital bill. Information is reported by the following expected primary payers: Medicare, Medicaid, private insurance, and self-pay/no charge. Patients identified as self-pay/no charge have an expected primary payer of self-pay, no charge, charity, or no expected payment. More information on expected payer coding in HCUP data is available in HCUP Methods Series Reports by Topic “User Guide – An Examination of Expected Payer Coding in HCUP Databases” (multiple documents; updated annually). Discharges missing expected payer are excluded from results reported by expected payer.

Discharges with the following expected primary payers are not reported by expected payer: other Federal, State, and local programs; missing; or invalid.

Community-level income is based on the median household income of the patient’s ZIP Code of residence. Quartiles are defined so that the total U.S. population is evenly distributed across four groups. Over time, the data element in the NIS for community-level income has changed definitions. The cut-offs for the quartile designation are determined annually using ZIP Code demographic data obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. The value ranges for the national income quartiles vary by year. Income quartile is missing if the patient is homeless or foreign. Records missing the income quartile are excluded from results reported by community-level income.

For Inpatient data, information by community-level income is only reported from 2002 forward because of inconsistent definitions over time in the income-related data elements in the NIS.

Inpatient stays and emergency department (ED) visits involving opioid-related hospital use are identified by any diagnosis (all-listed) in the following ranges of ICD-10-CM¹ and ICD-9-CM² codes:

ICD-10-CM Codes Starting October 1, 2015

• F11 series: Opioid-related disorders
  • All codes are included except F11.11, F11.21, and F11.91
• T40 series: Poisoning by, adverse effect of, and underdosing of narcotics
  • The following codes are included – encompassing accidental (unintentional) poisoning, intentional self-harm, assault, undetermined, and adverse effect (except heroin) – with a seventh digit indicating initial, subsequent encounter, or sequela
    • 0X1, 0X2, 0X3, 0X4, 0X5: Opium
    • 1X1, 1X2, 1X3, 1X4: Heroin
    • 2X1, 2X2, 2X3, 2X4, 2X5: Other opioids
    • 3X1, 3X2, 3X3, 3X4, 3X5: Methadone
    • 4X1, 4X2, 4X3, 4X4, 4X5: Other synthetic narcotics (through 2020 Q3)
    • 411, 412, 413, 414, 415: Fentanyl or fentanyl analogs (beginning 2020 Q4)
    • 421, 422, 423, 424, 425: Tramadol (beginning 2020 Q4)
    • 491, 492, 493, 494, 495: Other synthetic narcotics (beginning 2020 Q4)
    • 601, 602, 603, 604, 605: Unspecified narcotics
    • 691, 692, 693, 694, 695: Other narcotics
  • Codes with a sixth digit of “6”, indicating underdosing, are excluded

We observed some differences in the reporting of opioid-related inpatient stays and ED visits identified using ICD-10-CM codes. These differences are explored within the Case Study: Exploring How Opioid-Related Diagnosis Codes Translate from ICD-9-CM to ICD-10-CM, which is found under “Doing Analysis with ICD-10 Data” on the ICD-10-CM/PCS Resources web page of HCUP-US.

ICD-9-CM Codes Prior to October 1, 2015

• 304.00-304.02: Opioid type dependence (unspecified; continuous; episodic)
• 304.70-304.72: Combinations of opioid type drug with any other drug dependence (unspecified; continuous; episodic)
• 305.50-305.52: Opioid abuse (unspecified; continuous; episodic)
• 965.00-965.02; 965.09: Poisoning by opium (alkaloids), unspecified; heroin; methadone; other opiates and related narcotics
• 970.1: Poisoning by opiate antagonists
• E850.0-E850.2: Accidental poisoning by heroin; methadone; other opiates and related narcotics
• E935.0-E935.2: Heroin, methadone, other opiates and related narcotics causing adverse effects in therapeutic use
• E940.1: Opiate antagonists causing adverse effects in therapeutic use

These codes include opioid-related use stemming from illicit opioids such as heroin, illegal use of prescription opioids, and the use of opioids as prescribed. Each type of opioid use is important for understanding and addressing the opioid epidemic in the United States.³ While there may be interest in examining how much each type of opioid use contributes to the overall opioid problem, many of the opioid-related codes under the ICD-9-CM clinical coding system do not allow heroin-related cases to be explicitly identified (e.g., in the 304.0x series, heroin is not distinguished from other opioids). In addition, the codes do not distinguish between illegal use of prescription drugs and their use as prescribed.

Excluded Codes

It should be noted that ICD-10-CM and ICD-9-CM diagnosis codes related to opioid dependence or abuse “in remission” are not used to identify opioid-related hospital use because remission does not indicate active use of opioids. Codes indicating neonatal abstinence syndrome (NAS) are also not included. HCUP Fast Stats provides a separate topic, Neonatal Abstinence Syndrome (NAS) Among Newborn Hospitalizations, for users interested in trends for NAS.

State-Specific Differences

It should be noted that for certain States, data differences or restrictions may impact the presented trends.

• In the Iowa State Databases prior to data year 2017, records for behavioral health patients treated in chemical dependency or psychiatric care units were prohibited from release, and therefore not reported within the definition of opioid-related hospital use. Beginning with the 2017 data year those records are included.
• In the Georgia State databases, diagnoses indicating medical misadventures and adverse reactions, which include diagnosis codes specific to the adverse effects of opioids, are not available because of an HCUP Partner restriction. For this reason, rates and counts are under-estimated for Georgia data.

1 International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System

2 International Classification of Diseases, Ninth Revision, Clinical Modification

3 Compton WM, Jones CM, Baldwin GT. Relationship between nonmedical prescription-opioid use and heroin use. The New England Journal of Medicine. 2016; 374:154-63.

State-level statistics on inpatient stays are drawn from the HCUP State Inpatient Databases (SID) and quarterly data if available. Information based on quarterly data should be considered preliminary. Quarterly data will be replaced by the State’s complete annual SID for the year when it is available. Additionally, it is possible for a State’s annual SID to be updated. As a result of either the replacement of quarterly data with annual SID or the update of an annual SID, previously reported statistics for a given State may change. The SID are limited to patients treated in community hospitals in the State. Community hospitals are defined as short-term, non-Federal, general, and other hospitals, excluding hospital units of other institutions (e.g., prisons). Included among community hospitals are obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are community hospitals that are also long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals.

We adjust the discharge counts for hospitals that were not included in the SID or quarterly data. Across all States, the SID are missing about 7 percent of community hospitals and about 1.5 percent of discharges. Weighting for missing hospitals uses the following information from the American Hospital Association (AHA) Annual Survey of Hospitals to define strata within the State:

• Ownership: government, private nonprofit, and private investor-owned
• Size of the hospital based on the number of beds: small, medium, and large categories defined within region
• Location combined with teaching status: rural, urban nonteaching, urban teaching

If a stratum is missing one or more hospitals in the State data, then we set the discharge weight to the total number of discharges reported in the AHA divided by the total number of discharges in the State data. If all hospitals in a stratum are represented in the State data, then we set the discharge weight to 1. We also adjust the discharge weights for hospitals that have missing discharge quarters of data, provided there is no indication in the AHA Annual Survey that the facility had closed.

Discharge weights are specific to the data year for SID through 2013 (e.g., discharge weights for the 2013 SID use 2013 AHA data). Weighting for HCUP data starting in 2014 is based on AHA data from the prior year because current information is often unavailable (e.g., discharge weights for the 2014 SID use 2013 AHA data).

National statistics on inpatient stays are drawn from the HCUP National (Nationwide) Inpatient Sample (NIS). The NIS is sampled from the HCUP State Inpatient Databases (SID). Beginning with the 2012 data year, the NIS is a 20 percent sample of discharges from community hospitals, excluding rehabilitation and long-term acute care (LTAC) hospitals that participate in HCUP in the corresponding data year. For data years 1988 through 2011, the NIS was a 20 percent sample of community, nonrehabilitation hospitals and included all discharges from sampled hospitals. The national estimates on inpatient stays were developed using the NIS Trend Weight Files for consistent estimates across all data years (e.g., LTACs were removed from earlier data years using trend weights).

Emergency department (ED) visits are defined as ED encounters that do not result in a hospital admission to the same hospital (i.e., treat-and-release ED visits).

State-level statistics on ED treat-and-release visits are drawn from the HCUP State Emergency Department Databases (SEDD) and quarterly data if available. Information based on quarterly data should be considered preliminary. Quarterly data will be replaced by the State’s complete annual SEDD for the year when it is available. Additionally, it is possible for a State’s annual SEDD to be updated. As a result of either the replacement of quarterly data with annual SEDD or the update of an annual SEDD, previously reported statistics for a given State may change. The SEDD are limited to patients treated in community hospital-owned EDs in the State.

We adjust the ED visit counts for hospital-owned EDs that are missing from the SEDD. Across all States, the SEDD are missing about 5 percent of EDs and about 2 percent of ED visits. Data from the following data sources are used to weight for missing information: the American Hospital Association (AHA) Survey of Hospitals and the Trauma Information Exchange Program (TIEP) database, a national inventory of trauma centers in the United States collected by the American Trauma Society. Weighting for missing EDs uses the following information to define strata within the State:

• Ownership: government, private nonprofit, and private investor-owned (AHA)
• Location: large metropolitan, small metropolitan, micropolitan, and rural (AHA)
• Teaching status: nonteaching and teaching (AHA)
• Trauma center designation: levels I, II, and III (TIEP)

If a stratum is missing one or more EDs in the State data, then we set the weight to the total number of ED visits reported in the AHA divided by the total number of ED visits in the State data. If all EDs in a stratum are represented in the State data, then we set the discharge weight to 1. We also adjust the discharge weights for EDs that have missing quarters of data, provided there is no indication in the AHA Annual Survey that the facility had closed.

Discharge weights are specific to the data year for ED visits through 2013 (e.g., discharge weights for the 2013 ED visits use 2013 AHA data). Weighting of HCUP data for ED visits starting in 2014 is based on AHA data from the prior year because current information is often unavailable (e.g., discharge weights for the 2014 ED visits use 2013 AHA data).

National statistics on ED treat-and-release visits are drawn from the HCUP Nationwide Emergency Department Sample (NEDS). Treat-and-release records were selected from the NEDS using the HCUP data element HCUPFILE, which identifies the source of the ED record: the HCUP State Emergency Department Databases (SEDD) or the HCUP State Inpatient Databases (SID). All records where HCUPFILE was equal to SEDD are included in this analysis, that is, inpatient admissions from the ED were excluded since these cases are represented in the NIS.

The unit of analysis is the hospital discharge (i.e., the hospital inpatient stay) or an emergency department (ED) visit, not a person or patient. This means that a person who is admitted to the hospital or visits the ED multiple times in one year is counted each time as a separate discharge from the hospital or a separate visit in the ED.

For Fast Stats, all stays and visits are counted one time only, regardless of the number of relevant diagnosis or procedure codes that appear on the record. For instance, when identifying injury-related inpatient stays and ED visits, a record may include more than one of the injury-specific codes; in such a case, the record is only included once in the injury counts.

On October 1, 2015, the United States transitioned from ICD-9-CM to ICD-10-CM/PCS. The graphs demarcate this transition with statistics reported using ICD-9-CM coding identified as “ICD-9-CM” on the graphs and statistics reported using ICD-10-CM coding identified as “ICD-10-CM” on the graphs. The 2015 statistics include three quarters of data based on ICD-9-CM coding, whereas the fourth quarter is based on ICD-10-CM/PCS coding. Users may observe discontinuity in trends analyses that span the October 1, 2015 transition date. More information on the impact of ICD-10-CM/PCS is available on the HCUP User Support (HCUP-US) web page for ICD-10-CM/PCS Resources.

Population-based rates are presented for trends of opioid-related inpatient stays and ED visits reported overall and by age, sex, community-level income, and patient location. For expected payer, trends in opioid-related hospital use are presented as discharge/visit counts. Currently, there is no data source for national population insurance estimates that align with HCUP’s definition of expected primary payer. More information is available in HCUP Methods Series Reports by Topic “Population Denominator Data for Use with the HCUP Databases” (multiple documents; updated annually).

Discharge/visit counts for expected payer and numerator counts for age, sex, community-level income, and patient location are summarized by discharge quarter. For records where the discharge quarter is missing, the value is imputed based on the average quarterly discharge distribution in the United States between 2005 and 2014, as follows:

• Inpatient – quarter 1: 23 percent; quarter 2: 25 percent; quarter 3: 27 percent; quarter 4: 25 percent
• ED – quarter 1: 24 percent; quarter 2: 25 percent; quarter 3: 26 percent; quarter 4: 25 percent

For age, sex, community-level income, and patient location, denominator counts are consistently defined with the numerator (i.e., rates for females use HCUP counts and population counts specific to females). Population data are obtained from the Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas.

The rate of inpatient stays or rate of ED visits includes the HCUP number of stays or ED visits in the numerator and the U.S. resident population in the denominator (with a multiplier of 100,000).

Annualized quarterly rates are calculated as the quarterly count of inpatient stays or ED visits divided by one-fourth the annual population, times 100,000. Rates are suppressed for confidentiality when numerator counts are less than or equal to 25.

Information based on quarterly data from less than a full year should be considered preliminary. Quarterly data will be replaced by quarterly counts from the State’s complete annual State Inpatient Database (SID) or State Emergency Department Database (SEDD) for the year, when it is available.

The number of years of data reported for each individual State and the United States depends on the availability of the corresponding HCUP database. For example, the HCUP nationwide databases for the most recent data year can only be created after all of the necessary State databases are available. State-level data are included in Fast Stats when they become available. It is possible for a State’s annual SID or SEDD to be updated. As a result, previously reported statistics for a given State may change.

The discharge/visit counts and numerator counts are available in the exported data file, which can be downloaded by expanding “Show Data Export Options.” Counts are rounded to the nearest 50 discharges or visits, with any counts less than or equal to 25 suppressed for confidentiality. The exported data file also includes rates calculated on an annual rather than quarterly basis for trends of opioid-related inpatient stays and ED visits reported overall and by age, sex, community-level income, and patient location.

National Inpatient Stays:
Age refers to the age of the patient at admission. Discharges missing age are excluded from results reported by age.

National Emergency Department Visits:
Age refers to the age of the patient at admission to the ED. ED visits missing age are excluded from results reported by age.

Opioids Hospital Use:
Age refers to the age of the patient at admission. Discharges or visits missing age are excluded from results reported by age.

It should be noted that beginning with the transition to the ICD-10-CM/PCS coding system on October 1, 2015, a noticeable increase in opioid-related inpatient stays was observed for adults aged 65 years and older in most States. Additional information regarding this pattern is available on the HCUP-US web page for ICD-10-CM/PCS Resources in the report Preliminary Case Study: Exploring How Opioid-Related Diagnosis Codes Translate from ICD-9-CM to ICD-10-CM.

Hurricane Impact:
Age refers to the age (in years) of the patient at admission. Discharges or visits missing age are excluded from results reported by age. Age is grouped into three categories: 0-17 years, 18-64 years, and 65+ years. Less than 0.05 percent of records are missing information on age.

All nonmale, nonfemale responses are set to missing.
Discharges for inpatient stays and ED visits from emergency department visits with missing values for sex are excluded from results reported by sex.

Community-level income is based on the median household income of the patient’s ZIP Code of residence. Quartiles are defined so that the total U.S. population is evenly distributed across four groups. Over time, the data element in the NIS for community-level income has changed definitions. The cut-offs for the quartile designation are determined annually using ZIP Code demographic data obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. The value ranges for the national income quartiles vary by year. Income quartile is missing if the patient is homeless or foreign. Records missing the income quartile are excluded from results reported by community-level income.

For Inpatient data, information by community-level income is only reported from 2002 forward because of inconsistent definitions over time in the income-related data elements in the NIS.

Patient location is based on the six-category, county-level scheme developed by the National Center for Health Statistics (NCHS) to study the relationship between urbanization and health:

• Large central metropolitan: Counties in metropolitan statistical areas (MSAs) of 1 million or more population that contain the entire population of the largest principal city of the MSA, have their entire population contained in the largest principal city of the MSA, or contain at least 250,000 inhabitants of any principal city of the MSA
• Large fringe metropolitan (suburbs): Counties in MSAs of 1 million or more population that did not qualify as large central metropolitan counties
• Medium metropolitan: Counties in MSAs of populations of 250,000 to 999,999
• Small metropolitan: Counties in MSAs of population less than 250,000
• Micropolitan: Counties in micropolitan statistical areas
• Noncore: Nonmetropolitan counties that did not qualify as micropolitan

The micropolitan and noncore categories are combined into a single category (“Rural”) in order to preserve results when cell sizes are too small. For rates prior to 2014, the NCHS classification is based on population density from the 2000 Census. Starting in 2014, the NCHS classification is based on population density from the 2010 Census. Newborn hospitalizations missing patient location are excluded from results reported by patient location.
Patient location categories may include out-of-state patients because the classification is based on patient residence county but reported by the State for the hospital. Additional information on the patient location classification system is available at NCHS Urban-Rural Classification Scheme for Counties.

The “expected payer” data element in HCUP databases provides information on the type of payer that the hospital expects to be the source of payment for the hospital bill. Trends in inpatient and ED visit counts are provided by the following expected primary payers: Medicare, Medicaid, private insurance, and self-pay/no charge.

Patients identified as self-pay/no charge have an expected primary payer of self-pay, no charge, charity, or no expected payment. The self-pay/no charge category may also include patients with an expected payer of Indian Health Services, county indigent, migrant health programs, Ryan White Act, Hill-Burton Free Care, or other Federal, State, and local programs for the indigent when those programs are identifiable in the Partner-provided coding of expected payer. This reclassification of patients is only possible for some States and not for national estimates. More information on identifying programs reported in HCUP data that may cover the uninsured is available in HCUP Methods Series Reports by Topic “User Guide – An Examination of Expected Payer Coding in HCUP Databases” (multiple documents; updated annually).

Discharges/visits with the following expected primary payers are not reported by expected payer: other Federal, State, and local programs; missing; or invalid. In 2019, across all states, these excluded discharges/visits represented 3.1 percent (range of 0.3 to 14.3 percent) of all discharges and 3.5 percent (range of 0.4 to 16 percent) of all ED visits.

The total reflecting the number of discharges or ED visits across all expected payers (including those groups not presented in the graphs) is provided in the underlying data tables (“Show Underlying Data Tables”) and in the Excel data download file (“Show Data Export Options”). This statistic was added to Fast Stats in April 2020. It was calculated using the currently available SID and SEDD for data years 2005 and forward. If the SID/SEDD initially used for Fast Stats has been updated, then the total counts could be based on different versions of the SID/SEDD than the counts shown for Medicare, Medicaid, private insurance, and self-pay/no charge.

For comparison against the total described above for all expected payers, the Excel download file also provides the sum of the displayed expected payers (i.e., the sum of the rounded weighted quarterly expected payer counts of discharges/visits across the expected payers that are displayed in the graphs).

It should be noted that in certain data years and for certain States, data anomalies are identified that may impact the observed trends in inpatient stays and ED visits by expected primary payer:

• In the New York SEDD prior to 2011, the coding of expected primary payer did not distinguish between patients covered by commercial managed care plans and patients covered by Medicaid managed care plans. Because of this ambiguity in the payer coding, ED visits for patients with Medicaid managed care plans are reported under private insurance. Starting in 2011, the expected payer coding in New York data separately identifies Medicaid managed care patients and therefore ED visits for these patients are reported under Medicaid.
• In the Texas 2004-2011 SID, some Medicare records were incorrectly mapped to private insurance. Thus, the counts for Medicare are slightly underreported and the counts for private insurance are slightly overreported. This impacts roughly 1.5-3.5 percent of SID records between 2004-2011.
• In the Nebraska SID and SEDD prior to 2016, some Medicaid managed care patients may have been categorized in the data under private insurance instead of Medicaid because the Medicaid program was managed by a commercial insurance company. Beginning with data year 2016, there are large increases in the number of Medicaid records and proportionate decreases in records categorized as private insurance because the Nebraska Partner organization improved the process for the identification of patients covered by Medicaid managed care programs managed by commercial insurance companies.
• In the Vermont 2015 SID and SEDD, increases in Medicaid should be considered an anomaly. Vermont briefly modified their billing process in late 2014, which led to increases in records with a primary expected payer value of Medicaid. In 2016 data, the coding of Medicaid returns to a normal level that is consistent with historical data.

The opioid-related hospital use map provides annual rates of opioid-related inpatient stays or ED visits per 100,000 population. States are color-coded to identify each State’s opioid-related inpatient or ED rate relative to the distribution across all States providing data in 2016. States are classified into one of five groups based on the distribution of rates in 2016: lowest 20 percent, 2nd lowest 20 percent, middle 20 percent, 2nd highest 20 percent, highest 20 percent. The five groups are defined separately for opioid-related inpatient and ED rates. States in grey do not have data available; this may include States that are not currently HCUP Partners, do not provide the specific data type (e.g., ED) to HCUP, are not participating in Fast Stats, or participate but have not provided data for the year displayed. (Note: prior to the September 2021 update to this topic, the quintiles were based on a distribution of States that provided 2015 data.)

Newborn hospitalizations involving neonatal abstinence syndrome (NAS) require that the discharge record includes both of the following:

• A diagnosis of NAS
• A diagnosis of in-hospital birth or a birth before admission to the hospital, either in this case resulting in a newborn hospitalization. Eligible cases only exist on the initial hospitalization related to the birth and not subsequent hospital admissions during the neonatal period.

The coding for NAS and birth is identified by any diagnosis (all-listed) in the following ranges of ICD-10-CM¹ and ICD-9-CM² codes:

ICD-10-CM Codes Starting October 1, 2015

To identify NAS under ICD-10-CM, the birth record must include any diagnosis of:

• P96.1: Neonatal withdrawal symptoms from maternal use of drugs of addiction

Note that a diagnosis of P04.14 (Newborn affected by maternal use of opiates), which was a valid ICD-10-CM code as of October 1, 2018, was initially included in the definition of NAS when statistics were previously updated to include 2018 data for some States.  However, this code has since been dropped because it does not necessarily reflect the definition of NAS (newborns exhibiting withdrawal symptoms as a result of prenatal opioid exposure), and 2018 statistics have been updated accordingly.

Birth records under ICD-10-CM are identified by any diagnosis of:

• Z38 Series: Liveborn infants according to place of birth and type of delivery

ICD-9-CM Codes Prior to October 1, 2015

To identify NAS under ICD-9-CM, the birth record must include any diagnosis of:

• 779.5: Drug withdrawal syndrome in newborn

Birth records under ICD-9-CM are identified by any diagnosis of:

• V30-V39 Series: Liveborn infants according to type of birth
  • Ending in 00 or 01: Indication of birth inside hospital
  • Ending in 1: Indication of birth before admission to hospital.

Excluded Codes

It should be noted that under ICD-9-CM, the identification of NAS must not include an indication of a possible iatrogenic case, which is defined by ICD-9-CM diagnosis codes of 765.00-765.05, 770.7, 772.10-772.14, 777.50-777.53, 777.6, and 779.7. Similar exclusions are not necessary under ICD-10-CM because iatrogenic cases would be reported under a different ICD-10-CM diagnosis code (P96.2: Withdrawal symptoms from therapeutic use of drugs in newborn), which is not included in the ICD-10-CM definition of NAS.

Records under ICD-9-CM that indicate a birth outside a hospital with the infant not being hospitalized are not included.

Specific to Missouri, the Missouri Hospital Association (MHA) published a policy brief in 2018 (http://www.mhanet.com/mhaimages/advocacy/PolicyBrief_Preventing_NAS_0618.pdf) that focuses on the prevalence of NAS in the state. This report defines rates of NAS using the ICD-10-CM diagnosis code P96.2 (withdrawal symptoms from therapeutic use of drugs in newborn) in addition to the code P96.1 (neonatal withdrawal symptoms from maternal use of drugs of addiction) that is used to identify NAS hospitalizations in HCUP Fast Stats. As a result, the NAS rates reported in Fast Stats for Missouri may be lower than NAS rates reported by MHA.

¹ International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System
² International Classification of Diseases, Ninth Revision, Clinical Modification

State-level statistics on newborn hospitalizations are drawn from the HCUP State Inpatient Databases (SID). The SID are limited to patients treated in community hospitals in the State. Community hospitals are defined as short-term, non-Federal, general, and other hospitals, excluding hospital units of other institutions (e.g., prisons). Included among community hospitals are obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are community hospitals that are also long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals.

State-level statistics are based on the hospital State and not the patient resident State. This means that State-level statistics include all newborn hospitalizations in the State’s community hospitals—newborn hospitalizations among in-State residents and newborn hospitalizations by residents of other States. State-level statistics do not include newborn hospitalizations by in-State residents that occurred at hospitals in other States. Thus, the statistics reported here may differ from other NAS-related statistics that are based on the State of the patient’s residence.

We adjust the discharge counts for hospitals that were not included in the SID or quarterly data. Across all States, the SID are missing about 7 percent of community hospitals and about 1.5 percent of discharges. Weighting for missing hospitals uses the following information from the American Hospital Association (AHA) Annual Survey of Hospitals to define strata within the State:

• Ownership: government, private nonprofit, and private investor-owned
• Size of the hospital based on the number of beds: small, medium, and large categories defined within region
• Location combined with teaching status: rural, urban nonteaching, urban teaching

If a stratum is missing one or more hospitals in the State data, then we set the discharge weight to the total number of discharges reported in the AHA divided by the total number of discharges in the State data. If all hospitals in a stratum are represented in the State data, then we set the discharge weight to 1. We also adjust the discharge weights for hospitals that have missing discharge quarters of data, provided there is no indication in the AHA Annual Survey that the facility had closed.

Discharge weights are specific to the data year for SID through 2017 (e.g., discharge weights for the 2017 SID use 2017 AHA data). Weighting for HCUP data starting in 2018 is based on AHA data from the prior year because current information is often unavailable (e.g., discharge weights for the 2018 SID use 2017 AHA data).

National statistics on newborn hospitalizations are drawn from the HCUP National (Nationwide) Inpatient Sample (NIS). The NIS is sampled from the HCUP State Inpatient Databases (SID). Beginning with the 2012 data year, the NIS is a 20 percent sample of discharges from community hospitals, excluding rehabilitation and long-term acute care (LTAC) hospitals that participate in the corresponding data year. For data years 1988 through 2011, the NIS was a 20 percent sample of community, nonrehabilitation hospitals and included all discharges from sampled hospitals. The national estimates on newborn hospitalizations were developed using the NIS Trend Weight Files for consistent estimates across all data years (e.g., LTACs were removed from earlier data years using trend weights).

The number of years of data reported for each individual State and the United States depends on the availability of the corresponding HCUP database. For example, the HCUP nationwide databases for the most recent data year can only be created after all of the necessary State databases are available. State-level data are included in Fast Stats when they become available. It is possible for a State’s annual SID to be updated. As a result, previously reported statistics for a given State may change.

Counts in this section of Fast Stats are un-rounded with any counts less than or equal to 10 suppressed for confidentiality. This will cause a discontinuity in the trend lines displayed in the figures.

Specific to Colorado, the number of newborn hospitalizations for babies born to mothers covered by Medicaid may be an undercount because of sporadic reporting of the normal newborn births with the mother’s delivery record, instead of a separate newborn hospitalization. This results in NAS rates, particularly for Medicaid, being somewhat higher.

The unit of analysis is the newborn hospitalization (i.e., birth inside hospital or prior to hospital admission), not a person or patient.

On October 1, 2015, the United States transitioned the reporting of diagnosis codes from ICD-9-CM1 to ICD-10-CM2. The graphs demarcate this transition with statistics reported using ICD-9-CM coding identified as “ICD-9-CM” on the graphs and statistics reported using ICD-10-CM coding identified as “ICD-10-CM” on the graphs. The 2015 rates of NAS per 1,000 newborn hospitalizations and statistics for costs and length of stay in this section of HCUP Fast Stats are based on three quarters of data with ICD-9-CM codes only (January 1, 2015 to September 30, 2015). The number of NAS newborn hospitalizations in 2015 is not reported because the statistics are not based on full year data. Users may observe discontinuity in trends between NAS records defined by ICD-9-CM coding (ending in 2015) and ICD-10-CM coding (starting in 2016). More information on the impact of ICD-10-CM/PCS is available on the HCUP User Support (HCUP-US) web page for ICD-10-CM/PCS Resources.

Rates per 1,000 newborn hospitalizations are presented overall and by sex, expected payer, community-level income, and patient location. The rate includes the HCUP number of NAS-related newborn hospitalizations in the numerator and the total number of newborn hospitalizations in the denominator (with a multiplier of 1,000). The denominator is consistently defined with the numerator (e.g., rates for females use NAS and newborn hospitalization counts specific to females).

Rates are suppressed for confidentiality when the denominator is less than or equal to 25.

Costs are calculated using Cost-to-Charge Ratios (CCR), which are specific to each hospital as opposed to individual types of care. The cost per stay is presented as a median value rounded to the nearest hundred. The median cost is not an average but rather represents the cost that occurs at the midpoint of the ordered distribution of all observed costs. The cost per stay is presented for NAS newborn hospitalizations overall compared with that of other newborn hospitalizations that do not include a diagnosis of NAS.

The SID and NIS include information on total hospital charges for a newborn hospitalization. Charges represent the amount a hospital billed for the entire hospital stay, excluding professional (physician) fees. Total hospital charges are converted to costs using HCUP Cost-to-Charge Ratios (CCRs) based on hospital accounting reports from the Centers for Medicare & Medicaid Services (CMS). Costs reflect the actual expenses incurred in the production of hospital services, such as wages, supplies, and utility costs. For each hospital in the NIS, a hospital-wide cost-to-charge ratio is used. The median cost per stay is calculated using newborn hospitalizations with nonmissing total costs. Costs are not imputed if total charges are not reported on the discharge record. Costs for the most recent data year will not be presented if the HCUP CCRs for that data year are not yet available.

Cost per stay statistics may not be reported for the most recent data year, depending on the availability of the HCUP CCR files. The cost per stay is suppressed when the numerator is less than or equal to 10.

The inflation-adjusted cost per stay is presented as a median value rounded to the nearest hundred. The median inflation-adjusted cost is not an average but rather represents the cost that occurs at the midpoint of the ordered distribution of all observed costs. The inflation-adjusted cost per stay is presented for NAS newborn hospitalizations overall compared with that of other newborn hospitalizations that do not include a diagnosis of NAS.

The median cost per stay is inflation adjusted using price indexes for the Gross Domestic Product (GDP) from the U.S. Department of Commerce Bureau of Economic Analysis (BEA). We used the BEA Interactive Data query tool to request National Data, GDP & Personal Income, Section 1 Domestic Product and Income, Table 1.1.4. Price Indexes for Gross Domestic Product. Price indexes for data years 2008-2014 were obtained on June 23, 2015. Price indexes for subsequent data years were obtained at later dates to coincide with updates to this section of Fast Stats. The adjustment used 2010 as the index base so that updates to the trends could retain a consistent base.

Inflation-adjusted cost per stay statistics may not be reported for the most recent data year, depending on the availability of the HCUP CCR files. The inflation-adjusted cost per stay is suppressed when the numerator is less than or equal to 10.

The length of stay (LOS) is presented as a median value. The median LOS is not an average but rather represents the LOS that occurs at the midpoint of the ordered distribution of all observed LOS values. The LOS is presented for NAS newborn hospitalizations overall compared with that of other newborn hospitalizations that do not include a diagnosis of NAS.

LOS is the number of days that the patient stayed in the hospital. It is calculated by subtracting the admission date from the discharge date. Same-day stays are therefore coded with a length of stay of 0. The median LOS is calculated using newborn hospitalizations with nonmissing LOS.

LOS is suppressed when the numerator is less than or equal to 10.

All nonmale, nonfemale responses are set to missing.
Discharges for inpatient stays and ED visits from emergency department visits with missing values for sex are excluded from results reported by sex.

The “expected payer” data element in HCUP databases provides information on the type of payer that the hospital expects to be the source of payment for the hospital bill. Trends in NAS among newborn hospitalizations by expected payer are presented by the following categories: Medicaid, private insurance, and self-pay/no charge. Information by Medicare, other, missing, or invalid are not included in the reporting by expected payer. The distribution of cases in the excluded payer categories is provided below. Please note that all other reporting of NAS rates, counts, cost, and length of stay include all payer types.

• In the 2021 National Inpatient Sample (NIS), the percentages of NAS-related newborn hospitalizations that are not presented by expected payer are: 1.4% for Other, 0.3% for Medicare, and 0.1% for missing or invalid. The corresponding percentages of all newborn hospitalizations are: 2.7% for Other, 0.2% for Medicare, and 0.2% for missing or invalid.
• In the 2021 States Inpatient Databases (SID):
  • The percentages of NAS-related newborn hospitalizations that are not presented by expected payer are: an average of 1.3% for Other (range of 0.0% to 9.1% across States), 0.2% for Medicare (range of 0.0% to 1.2% across States), and 0.3% for missing or invalid (range of 0.0% to 9.6% across States).
  • The corresponding percentages of all newborn hospitalizations by expected payer are: an average of 3.5% for Other (range of 0.9% to 27.5% across States), 0.2% for Medicare (range of 0.0% to 1.7% across States), and 0.4% for missing or invalid (range of 0.0% to 7.9% across States).

Self-pay/no charge newborn hospitalizations include records that have an expected primary payer of self-pay, no charge, charity, or no expected payment. The self-pay/no charge records may also include those with an expected payer of Indian Health Services, county indigent, migrant health programs, Ryan White Act, Hill-Burton Free Care, or other Federal, State, and local programs for the indigent when those programs are identifiable in the Partner-provided coding of expected payer. This reclassification of patients is only possible for some States and not for national estimates. More information on identifying programs reported in HCUP data that may cover the self-pay/no charge category is available in HCUP Methods Series Reports by Topic “User Guide – An Examination of Expected Payer Coding in HCUP Databases” (multiple documents; updated annually).

Community-level income is based on the median household income of the patient’s ZIP Code of residence. Quartiles are defined so that the total U.S. population is evenly distributed across four groups. Over time, the data element in the NIS for community-level income has changed definitions. The cut-offs for the quartile designation are determined annually using ZIP Code demographic data obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. The value ranges for the national income quartiles vary by year. Income quartile is missing if the patient is homeless or foreign. Records missing the income quartile are excluded from results reported by community-level income.

For Inpatient data, information by community-level income is only reported from 2002 forward because of inconsistent definitions over time in the income-related data elements in the NIS.

Patient location is based on the six-category, county-level scheme developed by the National Center for Health Statistics (NCHS) to study the relationship between urbanization and health:

• Large central metropolitan: Counties in metropolitan statistical areas (MSAs) of 1 million or more population that contain the entire population of the largest principal city of the MSA, have their entire population contained in the largest principal city of the MSA, or contain at least 250,000 inhabitants of any principal city of the MSA
• Large fringe metropolitan (suburbs): Counties in MSAs of 1 million or more population that did not qualify as large central metropolitan counties
• Medium metropolitan: Counties in MSAs of populations of 250,000 to 999,999
• Small metropolitan: Counties in MSAs of population less than 250,000
• Micropolitan: Counties in micropolitan statistical areas
• Noncore: Nonmetropolitan counties that did not qualify as micropolitan

The micropolitan and noncore categories are combined into a single category (“Rural”) in order to preserve results when cell sizes are too small. For rates prior to 2014, the NCHS classification is based on population density from the 2000 Census. Starting in 2014, the NCHS classification is based on population density from the 2010 Census. Newborn hospitalizations missing patient location are excluded from results reported by patient location.
Patient location categories may include out-of-state patients because the classification is based on patient residence county but reported by the State for the hospital. Additional information on the patient location classification system is available at NCHS Urban-Rural Classification Scheme for Counties.

The interactive map of NAS among newborn hospitalizations provides annual rates of NAS per 1,000 newborn hospitalizations. States are color-coded to identify each State’s NAS-related inpatient rate relative to the distribution across all States providing 2016 data. States are classified into one of five categories based on the distribution of rates in 2016: lowest 20 percent, 2nd lowest 20 percent, middle 20 percent, 2nd highest 20 percent, highest 20 percent. States in grey do not have data available; this may include States that are not currently HCUP Partners, are not participating in Fast Stats, or participate but have not provided data for the year displayed. (Note: prior to the August 2020 update to this topic, the quintiles were based on a distribution of States that provided 2015 data.)

In-hospital deliveries involving severe maternal morbidity (SMM) require that the discharge record includes both of the following:

• Female patient, aged 12-55 years
• A diagnosis or procedure indicating SMM
• A diagnosis or procedure indicating an in-hospital delivery

The specific coding used to define SMM and delivery is provided in the clinical coding definitions (“Clinical Coding Definitions”) and in the Excel data download file located under the “HCUP Fast Stats Complete Excel Download Tables.”

State-level statistics on in-hospital deliveries are drawn from the HCUP State Inpatient Databases (SID). The SID are limited to patients treated in community hospitals in the State. Community hospitals are defined as short-term, non-Federal, general, and other hospitals, excluding hospital units of other institutions (e.g., prisons). Included among community hospitals are obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are community hospitals that are also long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals.

State-level statistics are based on the hospital State and not the patient resident State. This means that State-level statistics include all deliveries in the State’s community hospitals—deliveries among in-State residents and deliveries by residents of other States. State-level statistics do not include deliveries by in-State residents that occurred at hospitals in other States. Thus, the statistics reported here may differ from other SMM-related statistics that are based on the State of the patient’s residence.

We adjust the discharge counts for hospitals that were not included in the SID. Across all States, the SID are missing about 7 percent of community hospitals and about 1.5 percent of discharges. Weighting for missing hospitals uses the following information from the American Hospital Association (AHA) Annual Survey of Hospitals to define strata within the State:

• Ownership: government, private nonprofit, and private investor-owned
• Size of the hospital based on the number of beds: small, medium, and large categories defined within region
• Location combined with teaching status: rural, urban nonteaching, urban teaching

If a stratum is missing one or more hospitals in the State data, then we set the discharge weight to the total number of discharges reported in the AHA divided by the total number of discharges in the State data. If all hospitals in a stratum are represented in the State data, then we set the discharge weight to 1. We also adjust the discharge weights for hospitals that have missing discharge quarters of data, provided there is no indication in the AHA Annual Survey that the facility had closed.

Discharge weights are specific to the data year for SID through 2019 (e.g., discharge weights for the 2019 SID use 2019 AHA data).

National statistics on in-hospital deliveries are drawn from the HCUP National (Nationwide) Inpatient Sample (NIS). The NIS is sampled from the HCUP State Inpatient Databases (SID). Beginning with the 2012 data year, the NIS is a 20 percent sample of discharges from community hospitals, excluding rehabilitation and long-term acute care (LTAC) hospitals, that participate in HCUP in the corresponding data year. For data years 1988 through 2011, the NIS was a 20 percent sample of community, nonrehabilitation hospitals and included all discharges from sampled hospitals. The national estimates on in-hospital deliveries were developed using the NIS Trend Weight Files for consistent estimates across all data years (e.g., LTACs were removed from earlier data years using trend weights).

The number of years of data reported for each individual State and the United States depends on the availability of the corresponding HCUP database. For example, the HCUP nationwide databases for the most recent data year can only be created after all of the necessary State databases are available. State-level data are included in Fast Stats when they become available. It is possible for a State’s annual SID to be updated. As a result, previously reported statistics for a given State may change.

Counts are un-rounded with any counts less than or equal to 10 suppressed for confidentiality. This will cause a discontinuity in the trend lines displayed in the figures.

The unit of analysis is the hospital discharge (i.e., the hospital inpatient stay) or an emergency department (ED) visit, not a person or patient. This means that a person who is admitted to the hospital or visits the ED multiple times in one year is counted each time as a separate discharge from the hospital or a separate visit in the ED.

For Fast Stats, all stays and visits are counted one time only, regardless of the number of relevant diagnosis or procedure codes that appear on the record. For instance, when identifying injury-related inpatient stays and ED visits, a record may include more than one of the injury-specific codes; in such a case, the record is only included once in the injury counts.

On October 1, 2015, the United States transitioned from ICD-9-CM¹ to ICD-10-CM/PCS². The graphs demarcate this transition with statistics reported using ICD-9-CM coding identified as “ICD-9-CM” on the graphs and statistics reported using ICD-10-CM/PCS coding identified as “ICD-10-CM/PCS” on the graphs. The 2015 rates of SMM per 10,000 in-hospital deliveries in this section of HCUP Fast Stats are based on three quarters of data with ICD-9-CM codes only (January 1, 2015 to September 30, 2015). The number of SMM deliveries in 2015 is not reported because the statistics are not based on full year data. Users may observe discontinuity in trends between SMM records defined by ICD-9-CM coding (ending in 2015) and ICD-10-CM/PCS coding (starting in 2016). More information on the impact of ICD-10-CM/PCS is available on the HCUP User Support (HCUP-US) web page for ICD-10-CM/PCS Resources.

¹ International Classification of Diseases, Ninth Revision, Clinical Modification

² International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System

The coding for SMM and delivery is identified by any diagnosis or procedure (all-listed) in the following ranges of ICD-10-CM and ICD-9-CM codes:

ICD-10-CM Codes Starting October 1, 2015

To identify SMM under ICD-10-CM/PCS, the delivery record must include any diagnosis or procedure of:

Diagnosis codes

• A32.7: Listerial sepsis
• A40 series: Streptococcal sepsis
• A41 series: Other sepsis
• A81.2: Progressive multifocal leukoencephalopathy
• D57 series: Sickle-cell disorders
  • All codes are included except D57.03, D57.09, D57.1, D57.20, D57.213, D57.218, D57.3, D57.40, D57.413, D57.418, D57.42, D57.43, D57.44, D57.45, D57.80, D57.813, D57.818
• D65: Disseminated intravascular coagulation
• D68.8: Other specified coagulation defects
• D68.9 Coagulation defect, unspecified
• G45 series: Transient cerebral ischemic attacks and related syndromes
• G46 series: Vascular syndromes of brain in cerebrovascular diseases
• G93.49: Other encephalopathy
• H34.00-H34.03: Transient retinal artery occlusion
• I21 series: Acute myocardial infarction
• I22 series: Subsequent ST elevation (STEMI) and non-ST elevation (NSTEMI) myocardial infarction
• I26 series: Pulmonary embolism
• I46 series: Cardiac arrest
• I49.01-I49.02: Ventricular fibrillation and flutter
• I50 series: Heart failure
  • All codes are included except those codes related to chronic heart failure (I50.22, I50.32, I50.42, I50.812)
• I60-I68 series: Cerebrovascular diseases
  • All codes are included except I63.02 and I63.03
• I71 series: Aortic aneurysm and dissection
• I76: Septic arterial embolism
• I79.0: Aneurysm of aorta in diseases classified elsewhere
• I97.120-I97.121: Postprocedural cardiac arrest
• I97.130-I97.131: Postprocedural heart failure
• I97.710-I97.711: Intraoperative cardiac arrest
• I97.810-I97.811: Intraoperative cerebrovascular infarction
• I97.820-I97.821: Postprocedural cerebrovascular infarction
• J80: Acute respiratory distress syndrome
• J81.0: Acute pulmonary edema
• J95.1: Acute pulmonary insufficiency following thoracic surgery
• J95.2: Acute pulmonary insufficiency following nonthoracic surgery
• J95.3: Chronic pulmonary insufficiency following surgery
• J95.821-J95.822: Postprocedural respiratory failure
• J96 series: Respiratory failure, not elsewhere classified
  • All codes are included except J96.1, Chronic respiratory failure
• N17 series: Acute kidney failure
• O15 series: Eclampsia
• O22.50-O22.53: Cerebral venous thrombosis in pregnancy
  • All codes are included except O22.51, First trimester
• O29.1 series: Cardiac complications of anesthesia during pregnancy
  • All codes are included except those codes related to the first trimester (O29.111, O29.121, O29.191)
• O29.2 series: Central nervous system complications of anesthesia during pregnancy
  • All codes are included except those codes related to the first trimester (O29.211, O29.291)
• O45.0 series: Premature separation of placenta with coagulation defect
  • All codes are included except those codes related to the first trimester (O45.001, O45.011, O45.021, O45.091)
• O46.0 series: Antepartum hemorrhage with coagulation defect
  • All codes are included except those codes related to the first trimester (O46.001, O46.011, O46.021, O46.091)
• O67.0: Intrapartum hemorrhage with coagulation defect
• O72.3: Postpartum coagulation defects
• O74.0-O74.3: Complications of anesthesia during labor and delivery
• O75.1: Shock during or following labor or delivery
• O85: Puerperal sepsis
• O86.04: Sepsis following an obstetrical procedure
• O87.3: Cerebral venous thrombosis in the puerperium
• O88 series: Obstetric embolism
  • All codes are included except those codes related to the first trimester (O88.011, O88.111, O88.211, O88.311, O88.811)
• O89.0-O89.2: Complications of anesthesia during the puerperium
• O90.4: Postpartum acute kidney failure
• R06.03: Acute respiratory distress syndrome
• R09.2: Respiratory arrest
• R57 series: Shock, not elsewhere classified
• R65.20-R65.21: Severe sepsis
• T78.2XXA: Anaphylactic shock, unspecified, initial encounter
• T80.0XXA: Air embolism following infusion, transfusion and therapeutic injection, initial encounter
• T81.1 series: Postprocedural shock
  • Only includes codes indicating initial encounter (T81.10XA, T81.11XA, T81.12XA, T81.19XA)
• T81.44XA: Sepsis following a procedure, initial encounter
• T88.2XXA: Shock due to anesthesia, initial encounter
• T88.3XXA: Malignant hyperthermia due to anesthesia, initial encounter
• T88.6XXA: Anaphylactic reaction due to adverse effect of correct drug or medicament properly administered, initial encounter

Procedure codes

• 0B110F4: Bypass trachea to cutaneous with tracheostomy device, open approach
• 0B113F4: Bypass trachea to cutaneous with tracheostomy device, percutaneous approach
• 0B114F4: Bypass trachea to cutaneous with tracheostomy device, percutaneous endoscopic approach
• 0UT90ZL-0UT90ZZ: Resection of uterus, open approach
• 0UT97ZL-0UT97ZZ: Resection of uterus, via natural or artificial opening
• 5A12012: Performance of cardiac output, single, manual
• 5A1935Z-5A1955Z: Respiratory ventilation
• 5A2204Z: Restoration of cardiac rhythm, single

Delivery records under ICD-10-CM are identified by any diagnosis, Medicare Severity Diagnosis Related Group (MS-DRG), or procedure of:

Diagnosis codes

• Z37 series: Outcome of delivery
• O80: Encounter for full-term uncomplicated delivery
• O82: Encounter for cesarean delivery without indication
• O7582: Onset of labor after 37 completed weeks of gestation but before 39 completed weeks gestation, with delivery by planned cesarean section

MS-DRGs

Starting Fiscal Year (FY) 2016 (MS-DRG version 33-35)

• 765: Cesarean section with CC/MCC
• 766: Cesarean section without CC/MCC
• 767: Vaginal delivery with sterilization and/or D&C
• 768: Vaginal delivery with O.R. procedure except sterilization and/or D&C
• 774: Vaginal delivery with complicating diagnoses
• 775: Vaginal delivery without complicating diagnoses

Starting Fiscal Year (FY) 2019 (MS-DRG version 36)

• 768: Vaginal delivery with O.R. procedure except sterilization and/or D&C
• 783: Cesarean section with sterilization with MCC
• 784: Cesarean section with sterilization with CC
• 785: Cesarean section with sterilization without CC/MCC
• 786: Cesarean section without sterilization with MCC
• 787: Cesarean section without sterilization with CC
• 788: Cesarean section without sterilization without CC/MCC
• 796: Vaginal delivery with sterilization/D&C with MCC
• 797: Vaginal delivery with sterilization/D&C with CC
• 798: Vaginal delivery with sterilization/D&C without CC/MCC
• 805: Vaginal delivery without sterilization/D&C with MCC
• 806: Vaginal delivery without sterilization/D&C with CC
• 807: Vaginal delivery without sterilization/D&C without CC/MCC

Procedure codes

• 10D00Z0-10D00Z2: Extraction of products of conception
• 10D07Z3-0D07Z8: Extraction of products of conception via natural or artificial opening
• 10E0XZZ: Delivery of products of conception, external approach

Blood transfusion codes are not included in the SMM definition.

ICD-9-CM Codes Prior to October 1, 2015

To identify SMM under ICD-9-CM, the delivery record must include any diagnosis or procedure of:

Diagnosis codes

• 038 series: Septicemia
• 046.3: Progressive multifocal leukoencephalopathy
• 282.42: Sickle-cell thalassemia with crisis
• 282.62: Hb-SS disease with crisis
• 282.64: Sickle-cell/Hb-C disease with crisis
• 282.69: Other sickle-cell disease with crisis
• 286.6: Defibrination syndrome
• 286.9: Other and unspecified coagulation defects
• 289.52: Splenic sequestration
• 348.39: Other encephalopathy
• 362.34: Transient retinal arterial occlusion
• 410 series: Acute myocardial infarction
• 415 series: Acute pulmonary heart disease
• 427.41-427.42: Ventricular fibrillation and flutter
• 427.5: Cardiac arrest
• 428 series: Heart failure
  • All codes are included except those codes related to chronic heart failure (428.22, 428.32, 428.42)
• 430-437 series: Cerebrovascular disease
• 441 series: Aortic aneurysm and dissection
• 449: Septic arterial embolism
• 518.4: Acute edema of lung, unspecified
• 518.51-518.53: Pulmonary insufficiency following trauma and surgery
• 518.81: Acute respiratory failure
• 518.82: Other pulmonary insufficiency, not elsewhere classified
• 518.84: Acute and chronic respiratory failure
• 584 series: Acute kidney failure
• 641.30-641.33: Antepartum hemorrhage associated with coagulation defects
• 642.60-642.64: Eclampsia complicating pregnancy childbirth or puerperium
• 666.30-666.34: Postpartum coagulation defects
• 668.00-668.24: Complications of the administration of anesthetic or other sedation in labor and delivery
• 669.10-669.14: Obstetric shock
• 669.30-669.34: Acute kidney failure following labor and delivery
• 670.20-670.24: Puerperal sepsis
• 671.50-671.54: Other phlebitis and thrombosis in pregnancy and puerperium
• 673 series: Obstetrical pulmonary embolism
• 674.00-674.04: Cerebrovascular disorders in the puerperium
• 785.50-785.59: Shock without mention of trauma
• 799.1: Respiratory arrest
• 995.0: Other anaphylactic reaction
• 995.4: Shock due to anesthesia, not elsewhere classified
• 995.86: Malignant hyperthermia
• 995.91: Sepsis
• 995.92: Severe sepsis
• 997.02: Iatrogenic cerebrovascular infarction or hemorrhage
• 997.1: Cardiac complications, not elsewhere classified
• 998.00-998.09: Postoperative shock not elsewhere classified

Procedure codes

• 31.1: Temporary tracheostomy
• 68.39: Other and unspecified subtotal abdominal hysterectomy
• 68.49: Other and unspecified total abdominal hysterectomy
• 68.59: Other and unspecified vaginal hysterectomy
• 68.69: Other and unspecified radical abdominal hysterectomy
• 68.79: Other and unspecified radical vaginal hysterectomy
• 68.9: Other and unspecified hysterectomy
• 96.70-96.72: Other continuous invasive mechanical ventilation
• 99.60-99.69: Conversion of cardiac rhythm

Delivery records under ICD-9-CM are identified by any diagnosis, MS-DRG, or procedure of:

Diagnosis codes

• V27 series: Outcome of delivery
• 650: Normal delivery
• 66970, 66971: Cesarean section

MS-DRGs

Starting FY 2008 (MS-DRG version 25-32)

• 765: Cesarean section with CC/MCC
• 766: Cesarean section without CC/MCC
• 767: Vaginal delivery with sterilization and/or D&C
• 768: Vaginal delivery with O.R. procedure except sterilization and/or D&C
• 774: Vaginal delivery with complicating diagnoses
• 775: Vaginal delivery without complicating diagnoses

Prior to FY 2008 (MS-DRG versions prior to 25)

• 370: Cesarean section with CC
• 371: Cesarean section without CC
• 372: Vaginal delivery with complicating diagnoses
• 373: Vaginal delivery without complicating diagnoses
• 374: Vaginal delivery with sterilization and/or D&C
• 375: Vaginal delivery with O.R. procedure except sterilization and/or D&C

Procedure codes

• 720, 720, 721, 7221, 7229, 7231, 7239, 724, 7251, 7252, 7253, 7254, 726, 7271, 7279, 728, 729, 7322, 7359, 736: Extraction
• 740, 741, 742, 744, 7499: Cesarean section

Blood transfusion codes are not included in the SMM definition.

Excluded Codes

Records under ICD-10-CM/PCS or ICD-9-CM that indicate abortion are not included in the delivery definition.

Rates per 10,000 in-hospital deliveries are presented overall and by select patient and hospital characteristics. Patient characteristics are age, race/ethnicity, expected payer, community-level income, and patient location. Hospital characteristics are safety-net hospital status, hospital location/teaching status, hospital ownership, and hospital delivery volume. The rate includes the HCUP number of in-hospital deliveries with SMM in the numerator and the total number of in-hospital deliveries in the denominator (with a multiplier of 10,000). The denominator is consistently defined with the numerator (e.g., rates for non-Hispanic Black patients use SMM and in-hospital delivery counts specific to non-Hispanic Black patients).

Rates are suppressed for confidentiality when the denominator is less than or equal to 25. For hospital characteristics, rates are suppressed for any category that does not include at least two hospitals.

National Inpatient Stays:
Age refers to the age of the patient at admission. Discharges missing age are excluded from results reported by age.

National Emergency Department Visits:
Age refers to the age of the patient at admission to the ED. ED visits missing age are excluded from results reported by age.

Opioids Hospital Use:
Age refers to the age of the patient at admission. Discharges or visits missing age are excluded from results reported by age.

It should be noted that beginning with the transition to the ICD-10-CM/PCS coding system on October 1, 2015, a noticeable increase in opioid-related inpatient stays was observed for adults aged 65 years and older in most States. Additional information regarding this pattern is available on the HCUP-US web page for ICD-10-CM/PCS Resources in the report Preliminary Case Study: Exploring How Opioid-Related Diagnosis Codes Translate from ICD-9-CM to ICD-10-CM.

Hurricane Impact:
Age refers to the age (in years) of the patient at admission. Discharges or visits missing age are excluded from results reported by age. Age is grouped into three categories: 0-17 years, 18-64 years, and 65+ years. Less than 0.05 percent of records are missing information on age.

Race/ethnicity refers to the race/ethnicity of the patient on the discharge record. National statistics are reported based on all State data included in the NIS. The percent of records missing race/ethnicity in the 2016-2018 NIS is approximately 5 percent or less: 5.1 percent in 2016, 4.3 percent in 2017, and 3.3 percent in 2018. For State-specific reporting, States must meet the following criteria:

• The State’s discharge data must include reporting on Hispanic ethnicity;
• Less than 10 percent of records can be missing race reporting.

Data on Hispanic ethnicity are collected differently among the States and also can differ from the census methodology of collecting information on race (White, Black, Asian/Pacific Islander, American Indian/Alaska Native, Other [including mixed race]) separately from ethnicity (Hispanic, non-Hispanic). State data organizations often collect Hispanic ethnicity as one of several categories that include race. Therefore, for multistate analyses, HCUP creates the combined categorization of race and ethnicity for data from States that report ethnicity separately. When a State data organization collects Hispanic ethnicity separately from race, HCUP uses Hispanic ethnicity to override any other race category to create a Hispanic category for the uniformly coded race/ethnicity data element, while also retaining the original race and ethnicity data.

Trends in SMM among in-hospital deliveries by race/ethnicity are presented by the following categories: Black, non-Hispanic; Hispanic; White, non-Hispanic; and Other, non-Hispanic. The non-Hispanic Other category includes Asian or Pacific Islander, American Indian/Alaska Native, and other non-Hispanic race identified as “other”. Discharges missing race/ethnicity are excluded from results reported by race/ethnicity.

Race/ethnicity statistics are not reported prior to data year 2016 because of missing and/or inconsistent data. Race/ethnicity statistics for some States may be reported for an even smaller timeframe if race/ethnicity is missing and/or inconsistent for data year 2016 and forward.

The “expected payer” data element in HCUP databases provides information on the type of payer that the hospital expects to be the source of payment for the hospital bill. Trends in SMM among in-hospital deliveries by expected primary payer are presented by the following categories: Medicaid and Medicare, private insurance, and other. On average, Medicare represents fewer than 1% of in-hospital deliveries. The “other” category includes self-pay/no charge, other government programs and Workers’ Compensation, and missing or invalid payers. Self-pay/no charge includes records that have an expected primary payer of self-pay, no charge, charity, and no expected payment.

Community-level income is based on the median household income of the patient’s ZIP Code of residence. Quartiles are defined so that the total U.S. population is evenly distributed across four groups. Over time, the data element in the NIS for community-level income has changed definitions. The cut-offs for the quartile designation are determined annually using ZIP Code demographic data obtained from Claritas, a vendor that produces population estimates and projections based on data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. The value ranges for the national income quartiles vary by year. Income quartile is missing if the patient is homeless or foreign. Records missing the income quartile are excluded from results reported by community-level income.

For Inpatient data, information by community-level income is only reported from 2002 forward because of inconsistent definitions over time in the income-related data elements in the NIS.

Patient location is based on the six-category, county-level scheme developed by the National Center for Health Statistics (NCHS) to study the relationship between urbanization and health:

• Large central metropolitan: Counties in metropolitan statistical areas (MSAs) of 1 million or more population that contain the entire population of the largest principal city of the MSA, have their entire population contained in the largest principal city of the MSA, or contain at least 250,000 inhabitants of any principal city of the MSA
• Large fringe metropolitan (suburbs): Counties in MSAs of 1 million or more population that did not qualify as large central metropolitan counties
• Medium metropolitan: Counties in MSAs of populations of 250,000 to 999,999
• Small metropolitan: Counties in MSAs of population less than 250,000
• Micropolitan: Counties in micropolitan statistical areas
• Noncore: Nonmetropolitan counties that did not qualify as micropolitan

The micropolitan and noncore categories are combined into a single category (“Rural”) in order to preserve results when cell sizes are too small. For rates prior to 2014, the NCHS classification is based on population density from the 2000 Census. Starting in 2014, the NCHS classification is based on population density from the 2010 Census. Newborn hospitalizations missing patient location are excluded from results reported by patient location.
Patient location categories may include out-of-state patients because the classification is based on patient residence county but reported by the State for the hospital. Additional information on the patient location classification system is available at NCHS Urban-Rural Classification Scheme for Counties.

Safety-net hospital status indicates whether the in-hospital delivery occurred at a safety-net hospital or a non-safety-net hospital. Safety-net hospitals are defined as hospitals in the top quartile within each State (for both national and State-level reporting) for the percentage of all discharges, including delivery and non-delivery stays, with an expected payer of Medicaid or with no expected insurance payer (i.e., uninsured)³. Uninsured discharges include those with an expected payer of self-pay/no charge and discharges with an expected payer of Indian Health Services, county indigent, migrant health programs, Ryan White Act, Hill-Burton Free Care, or other Federal, State, and local programs for the indigent when those programs are identifiable in the Partner-provided coding of expected payer. The identification of other local and indigent programs is only possible for some States and not for national estimates. More information on identifying programs reported in HCUP data that may cover the self-pay/no charge category is available in HCUP Methods Series Reports by Topic “User Guide – An Examination of Expected Payer Coding in HCUP Databases” (multiple documents; updated annually).

Safety-net hospitals are redefined each year based on the distribution of Medicaid and self-pay/no charge discharges at hospitals in each year. For the national statistics, safety-net hospital status is determined using the data from all available SID. National statistics are not reported prior to data year 2012 because the NIS was only a 20 percent sample of hospitals at that time. National and State-level rates are suppressed for any category that does not include at least two hospitals.

³ Popescu I, Fingar, KR, Cutler E, Guo J, Jiang J. Comparison of 3 Safety-Ney Hospital Definitions and Association With Hospital Characteristics. JAMA Network Open. 2019;2(8).

Hospital location and teaching status is derived from the AHA Annual Survey of Hospitals. Trends in SMM among in-hospital deliveries by hospital location/teaching status are presented by the following categories: metropolitan non-teaching hospitals, metropolitan teaching hospitals, and nonmetropolitan hospitals.

The classification of whether a hospital is in a metropolitan area or nonmetropolitan area is based on the Core Based Statistical Area (CBSA) definition of rurality developed by the Office of Management and Budget. Hospitals located in counties with a CBSA type of “Division” or “Metropolitan” were considered metropolitan, and hospitals with a CBSA type of “Rural” or “Micropolitan” were classified as nonmetropolitan. The CBSA classification released in 2011 was based on the 2000 Census; the CBSA classification released in 2014 was based on the 2010 Census.

A hospital is considered a teaching hospital if it has one or more Accreditation Council for Graduate Medical Education (ACGME) approved residency programs, is a member of the Council of Teaching Hospitals (COTH), or has a ratio of full-time equivalent interns and residents to beds of .25 or higher.

Nonmetropolitan hospitals are not split according to teaching status because nonmetropolitan teaching hospitals are rare. Hospitals with missing hospital location or teaching status as reported by the AHA are excluded from results reported by hospital location/teaching status. Rates are suppressed for any category that does not include at least two hospitals.

Hospital ownership is derived from the AHA Annual Survey of Hospitals and includes the following categories:

• Government, nonfederal (public)
• Private, not-for-profit (voluntary)
• Private, investor-owned (proprietary)

In this section of Fast Stats, the two private categories are combined into a single private ownership category. Hospitals with missing hospital ownership as reported by the AHA are excluded from results reported by hospital ownership. Rates are suppressed for any category that does not include at least two hospitals.

Trends in SMM among in-hospital deliveries by hospital delivery volume are presented by the following categories: hospitals with less than 500 deliveries, hospitals with 500 through 1,000 deliveries, and hospitals with greater than 1,000 deliveries. For the national statistics, delivery volume is determined using the data from all available SID. Rates are suppressed for any category that does not include at least two hospitals.

States are color-coded to identify each State’s SMM-related inpatient rate relative to the distribution across all States providing 2018 data. States are classified into one of five categories based on the distribution of rates in 2018: lowest 20 percent, 2nd lowest 20 percent, middle 20 percent, 2nd highest 20 percent, highest 20 percent. States in grey do not have data available; this may include States that are not currently HCUP Partners, are not participating in Fast Stats, or participate but have not provided data for the year displayed.

This Fast Stats topic provides general descriptive statistics on changes in rates of hospital utilization following historical U.S. hurricanes. Information on hospital utilization is based on data from the HCUP State Inpatient Databases (SID) and State Emergency Department Databases (SEDD). Information about the proximity of counties to hurricane paths was derived from the National Oceanic and Atmospheric Association (NOAA) Best Track datasets and the Federal Emergency Management Agency (FEMA) Disaster Declaration Summary database. In order to calculate hospital utilization rates, estimates of the resident population were taken from the U.S. Census Bureau’s American Community Survey (ACS).

The hospital utilization statistics reported here may be influenced by a number of factors such as hurricane-related evacuations and hospital closures for which the source data have not been adjusted. These limitations may cause imprecision in the estimates. Please refer to the “Caveats on Data Analysis” section below for more information.

Eleven hurricanes that impacted the mainland of the United States between 2005 and 2017 are included. States that were affected by these hurricanes were identified based on information on hurricane activity from the National Oceanic and Atmospheric Association (NOAA) and information on counties identified by the Federal Emergency Management Agency (FEMA) as major disaster areas caused by the hurricane. The start date of hurricane activity was identified by the date of the first record that indicated hurricane activity for a State in the NOAA Storm Best Track dataset. Hurricane activity was defined as any one of the following: a tropical cyclone of hurricane intensity with winds greater than 64 knots, a tropical cyclone of tropical storm intensity with winds of 34-64 knots, or an extratropical cyclone with winds of at least 34 knots.

¹    Hospital utilization data for this State are not included either because the State did not provide data to HCUP for that time period or because the State’s data did not include admission date for the hospital records (so time of visit relative to the hurricane could not be determined).

²    Indicates State had at least one county declared as a FEMA disaster area, but no counties with hurricane activity in the NOAA Best Track database; dates were assigned based on neighboring States.

Hospital utilization data from neighboring States not impacted by a hurricane may be included with utilization data from the States impacted by the hurricane. If a patient who resided in a hurricane-impacted State was treated at a hospital in another State, the hospital encounter is included in the utilization count for the patient’s county of residence if the hospital was located within 250 miles of the patient’s residence. Distance was determined based on the centroids of the ZIP Codes of the hospital and patient’s residence.

Counties in States impacted by the hurricane were classified into one of four proximity categories: direct path, near path, remote/FEMA disaster, and remote/not disaster. These proximity designations were derived from two data sources:

• The Federal Emergency Management Agency (FEMA) Disaster Declaration Summary database identifies whether a county was declared a major disaster area for any one of the 11 hurricanes. For some of these hurricanes, FEMA separately reports major disaster areas under the hurricane’s downgraded status of tropical storm. In this analysis, major disaster areas are based on both the hurricane and tropical storm status, where applicable. A county may be declared a major disaster area by FEMA if any one or more of the following types of assistance are needed: individual assistance, individual and household assistance, public assistance, and/or hazard mitigation. FEMA reports data on all emergency declarations and major disaster declarations declared under the Stafford Act.³
• The National Oceanic and Atmospheric Association (NOAA) Best Track datasets provide trajectory and wind speed information for the hurricane.⁴ These hurricane-specific datasets include measurements of the hurricane’s location taken at six-hour intervals corresponding to standard synoptic times of 0000, 0600, 1200, and 1800. For some hurricanes, landfall records are recorded with the exact time. Each standard synoptic time observation includes information on the latitude and longitude of the measurement point, in addition to the status of the storm (e.g., tropical cyclone of hurricane intensity, extratropical cyclone, subtropical cyclone), maximum wind speed sustained, minimum central pressure, and distance in nautical miles for three wind radii (34 knots, 50 knots, and 64 knots). Occasionally, non-synoptic time records (for landfall) do not include wind radii information.

  Using ESRI Geographic Information Software (ArcGIS),⁵ the latitude and longitude were mapped for each NOAA Best Track measurement point to the corresponding county. The ESRI ArcGIS “USA Counties” layer included detail on coastal landforms. Starting in 2015, NOAA began providing final Best Track “line” files that track the path of a hurricane between measurement points. Because they were publicly available, these files were used to plot the trajectories of the three most recent hurricanes presented in HCUP Fast Stats (Matthew, Harvey, and Irma). For earlier hurricanes, ArcGIS was used to infer the trajectory of the hurricane assuming the shortest possible path between two NOAA Best Track measurement points.

Counties were classified into one of the four hurricane proximity categories as follows:

• Direct path: Counties were classified as being in the direct path of the hurricane based on either of the following criteria:
  • The county was identified by the longitude and latitude of a measurement point in the NOAA Best Track dataset and the status and/or wind speed indicated hurricane activity, or
  • The county was crossed by the trajectory line between two measurement points with hurricane activity, as determined by the NOAA trajectory information or ArcGIS.

  The “direct path” designation was based on the hurricane path only, whether or not the county was declared a major disaster area by FEMA. It is possible, but rare, for counties in the direct path of the hurricane to not be designated as major disaster areas by FEMA.

• Near path: Counties were classified as being near the path of the hurricane based on the wind radii recorded at a measurement point indicating hurricane activity in the NOAA Best Track dataset. The distance in nautical miles from the latitude and longitude of the measurement points to the three wind radii was used to calculate concentric circles containing the strongest winds (64 knots) to the weakest winds (34 knots). Counties within these concentric circles that were not identified as in the direct path of the hurricane were categorized as being near the hurricane path. The “near path” designation was based on the wind radii of the hurricane only, whether or not the county was declared a major disaster area by FEMA. For counties in the near path of the hurricane, some were designated as major disaster areas by FEMA and some were not, depending on the hurricane.
• Remote: Counties were classified as being remote from the hurricane if they were either in States that were affected by the hurricane or in States that had at least one county designated as a FEMA major disaster area and were not classified as in the direct path or near the path of the hurricane. A county remote from the hurricane was then further subdivided into one of two categories, based on whether FEMA declared the county a major disaster area: remote/FEMA disaster designation and remote/not disaster designation. Counties remote from the hurricane were not associated with hurricane activity based on NOAA wind radii data, but they may have been impacted by hurricane-related flooding or secondary storm damage resulting in the FEMA disaster declaration.

Note that one or more proximity categories may not be applicable for some hurricanes if there were no counties classified in a proximity category. For example, all the counties in the affected States could be classified into the direct path, near path, or remote/FEMA disaster proximity categories, and none into the remote/not disaster proximity category.

Hurricane-specific maps displaying the areas designated as direct, near, remote/FEMA disaster, and remote/not disaster are available in an exported data file, which can be downloaded by expanding “Show Data Export Options”. The maps document the population at risk for the hurricane and what hospital utilization data were available from the HCUP State databases.

³ https://www.fema.gov/disasters
⁴ https://www.nhc.noaa.gov/gis/
⁵ https://www.esri.com/en-us/arcgis/about-arcgis/overview

Inpatient stays and emergency department (ED) visits were classified into hurricane proximity categories using the patient’s county of residence. Patient county was assigned based on the ZIP Code of the patient’s residence using the SAS function for ZIP Code to county assignment. For ZIP Codes that cross county boundaries, the SAS function used the geographic centroid of the ZIP Code to assign the county.⁶ A sensitivity test using the 35.4 million records in the 2016 SID demonstrated that the SAS function assigned a county different from the county with the population centroid of the ZIP code in 0.6 percent of SID records. If the patient ZIP Code indicated the patient was homeless (the HCUP data element ZIP = “H”), then the patient county was assigned to be the same as the hospital county. Records for patients with a ZIP Code that was missing, invalid, or indicated the person was from a foreign country were excluded from the tabulated counts. This exclusion dropped less than 1 percent of records in any year.

Additional information on using HCUP data for county-level analyses is available in Method Series Report #2019-04: Conducting County-Level Analyses With HCUP Data: Approaches and Methodological Considerations.

⁶Additional information from SAS on the geocode procedure: https://support.sas.com/documentation/cdl/en/graphref/65389/HTML/default/viewer.htm#n1cqwrpowwd4l6n1lmw39ughjpuh.htm

The unit of analysis is the hospital discharge (i.e., the hospital inpatient stay) or an emergency department (ED) visit, not a person or patient. This means that a person who is admitted to the hospital or visits the ED multiple times in one year is counted each time as a separate discharge from the hospital or a separate visit in the ED.

For Fast Stats, all stays and visits are counted one time only, regardless of the number of relevant diagnosis or procedure codes that appear on the record. For instance, when identifying injury-related inpatient stays and ED visits, a record may include more than one of the injury-specific codes; in such a case, the record is only included once in the injury counts.

The percent change in the rate of inpatient stays or ED visits compares hospital utilization during and post-hurricane to the pre-hurricane average utilization rates. Time periods are calculated based on the State-specific start date of the hurricane activity (documented under the section on Hurricanes).

• The pre-hurricane rate (“Avg. Pre-Hurr.”) was calculated as an average of the rates for the four weeks immediately preceding the start date of the hurricane.
• The rate for the week of the hurricane (“Hurr. Week”) includes seven days from the start date of the hurricane (i.e., the starting day of the hurricane and the following six days).
• The post-hurricane rate was examined for each of the seven weeks following the hurricane week (“Post Wk 1” to “Post Wk 7”).

The rates by hurricane proximity were population-weighted to account for the different sizes of counties. Population data were obtained from the U.S. Census Bureau, American Community Survey (ACS) overall and by specific age groups. The rate of inpatient stays or rate of ED visits includes the HCUP number of stays or ED visits in the numerator and the U.S. resident population in the denominator (with a multiplier of 10,000). For age, population rates were based on the population for that age group. Population-based rates by hurricane proximity always include data from two or more counties and two or more hospitals. Counties and hospitals may be within the same State or from different States.

The percent change from the pre-hurricane weekly average is presented as the baseline value 0 for the pre-hurricane period. The percent change for the hurricane and each post-hurricane week is calculated from the pre-hurricane weekly average and demonstrates how utilization varied each week from the pre-hurricane period.

Detailed information on the population-based rates and percent change are available in the exported data file (under “Show Data Export Options”). For the pre-hurricane period, the export file includes the 4-week average rate, the average number of weekly encounters (i.e., the average numerator count of HCUP inpatient stays or ED visits), and the Census population count (the population denominator for the rate). For the hurricane week, the export file includes the number of encounters, the population-based rate, and the percent change from the pre-hurricane average rate to the rate for the hurricane week. For each post-hurricane week, the export file includes the number of encounters, the population-based rate, and the percent change from the pre-hurricane average rate to the rate for the post-hurricane week. Counts are rounded to the nearest 10 discharges or ED visits, with any counts less than or equal to 10 or representing fewer than two hospitals suppressed for confidentiality. The exception is raw counts of 11-14, which are rounded to 11.

Suppression Rules for Confidentiality

If the average number of encounters in the pre-hurricane period is less than or equal to 10, or represents fewer than two hospitals, the percent changes for the hurricane week and each post-hurricane week are suppressed. This will result in one or more missing trend lines in a graph. If the number of encounters for the hurricane week or any post-hurricane week is less than or equal to 10, or represents fewer than two hospitals, the percent change is suppressed. This will result in one or more missing data points in a graph and will cause a discontinuity in the trend lines. When three or more data points are suppressed, the trend line is omitted from the graph and none of the data values are provided in the underlying data tables and exported data file. Suppression of multiple trend lines is particularly common in the inpatient setting for age 0-17 years. For some hurricanes, all trend lines may be omitted from certain graphs due to data suppression; in these instances, the graph includes a note indicating that “Data are insufficient for presentation.”

Statistics on inpatient stays for each hurricane are from the HCUP State Inpatient Databases (SID) and quarterly data if available. Information based on quarterly data should be considered preliminary. Quarterly data will be replaced by the State’s complete annual SID for the year when it is available. As a result, previously reported statistics for a given hurricane may change. For this analysis, the SID are limited to patients treated in community hospitals in the State. Community hospitals are defined as short-term, non-Federal, general, and other hospitals, excluding hospital units of other institutions (e.g., prisons). Included among community hospitals are obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are community hospitals that are also rehabilitation and long-term acute care facilities. If a patient was transferred from one community hospital to another, then the SID records for both the transferring and receiving hospitals were included in the analysis.

In any data year for the hurricane-impacted States, an average of 0.6 percent of inpatient stays from community hospitals7 are missing from the SID (range of 0.0 to 4.7 percent). These missing discharges represent an average of 3.0 percent of community hospitals⁷ (range of 0.0 to 31.4 percent). One State is missing a total of 4.7 percent of discharges, due to missing 31.4 percent of the community hospitals in the state7 (predominately small hospitals with fewer than 50 beds).

⁷Excluded are community hospitals that are also rehabilitation and long-term acute care facilities.

Emergency department (ED) visits are defined as ED encounters that do not result in a hospital admission to the same hospital (i.e., treat-and-release ED visits).

Statistics on treat-and-release ED visits for each hurricane are from the HCUP State Emergency Department Databases (SEDD) and quarterly data if available. Information based on quarterly data should be considered preliminary. Quarterly data will be replaced by the State’s complete annual SEDD for the year when it is available. As a result, previously reported statistics for a given hurricane may change. The SEDD are limited to patients treated in community hospital-owned EDs in the State. Excluded are community hospitals that are also rehabilitation and long-term acute care facilities. If a patient was transferred from the ED, then records for both the transferring and receiving facilities were included in the analysis. There would be a SEDD record from the transferring ED. Most of the time (91 percent), ED transfers result in an inpatient stay. In these cases, the record for the receiving hospital would be included in the SID; otherwise, there would be a second SEDD record.

In any data year for the hurricane-impacted States, an average of 0.4 percent of the ED visits from community hospital-owned EDs⁸ are missing from the SEDD (range of 0.0 to 1.7 percent). These missing ED visits represent an average of 1.0 percent of community hospital-owned EDs8 (range of 0.0 to 3.1 percent).

Information on ED utilization is not presented for all hurricanes. Gustav, Ike, Isaac, and Rita lack ED utilization information because none of the impacted states provided ED data corresponding to the hurricane time period. Additionally, some states impacted by hurricanes Harvey, Irene, Matthew, and Sandy provided inpatient data, but no ED data. In this situation, the ED information incorporates data from a smaller set of states than the inpatient information; accordingly the population count is smaller for the ED setting than the inpatient setting.

⁸Excluded are community hospitals that are also rehabilitation and long-term acute care facilities.

In October 2015, the United States transitioned coding systems for reporting diagnoses and inpatient procedures from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS). The following hurricanes would have had diagnoses and procedures reported using ICD-9-CM: Dennis, Rita, Wilma, Gustav, Ike, Irene, Isaac, and Sandy. The following hurricanes would have had diagnoses and procedures reported using ICD-10-CM/PCS: Matthew, Harvey, and Irma. No hurricane has clinical data that crossed coding systems. More information about the use of data across the two coding system may be found on the HCUP User Support (HCUP-US) web page for ICD-10-CM/PCS Resources.

Circulatory is defined using the following Clinical Classifications Software (CCS) for ICD-9-CM categories or Clinical Classifications Software Refined (CCSR) for ICD-10-CM default categorization scheme for the principal (or first-listed) diagnosis as appropriate for the time period of the hurricane. The circulatory condition must be reported as the principal diagnosis on an inpatient stay or the first-listed diagnosis on an emergency department visit. The principal or first-listed diagnosis is used so that a record is only assigned to one specific clinical condition.

Percent change in population rates for circulatory conditions is not reported for age 0-17 years because these conditions are relatively uncommon for this age group.

CCSR for ICD-10-CM Diagnoses Starting October 1, 2015

• CIR001: Chronic rheumatic heart disease
• CIR002: Acute rheumatic heart disease
• CIR003: Nonrheumatic and unspecified valve disorders
• CIR004: Endocarditis and endocardial disease
• CIR005: Myocarditis and cardiomyopathy
• CIR006: Pericarditis and pericardial disease
• CIR009: Acute myocardial infarction
• CIR010: Complications of acute myocardial infarction
• CIR011: Coronary atherosclerosis and other heart disease
• CIR012: Nonspecific chest pain
• CIR013: Acute pulmonary embolism
• CIR014: Pulmonary heart disease
• CIR016: Conduction disorders
• CIR017: Cardiac dysrhythmias
• CIR018: Cardiac arrest and ventricular fibrillation
• CIR019: Heart failure
• CIR020: Cerebral infarction
• CIR021: Acute hemorrhagic cerebrovascular disease
• CIR022: Sequela of hemorrhagic cerebrovascular disease
• CIR023: Occlusion or stenosis of precerebral or cerebral arteries without infarction
• CIR025: Sequela of cerebral infarction and other cerebrovascular disease
• CIR026: Peripheral and visceral vascular disease
• CIR027: Arterial dissections
• CIR029: Aortic; peripheral; and visceral artery aneurysms
• CIR030: Aortic and peripheral arterial embolism or thrombosis
• CIR033: Acute phlebitis; thrombophlebitis and thromboembolism
• CIR034: Chronic phlebitis; thrombophlebitis and thromboembolism
• NVS012: Transient cerebral ischemia

CCS for ICD-9-CM Prior to October 1, 2015

• 96: Heart valve disorders
• 97: Peri-; endo-; and myocarditis; cardiomyopathy (except that caused by tuberculosis or sexually transmitted disease)
• 100: Acute myocardial infarction
• 101: Coronary atherosclerosis and other heart disease
• 102: Nonspecific chest pain
• 103: Pulmonary heart disease
• 105: Conduction disorders
• 106: Cardiac dysrhythmias
• 107: Cardiac arrest and ventricular fibrillation
• 108: Congestive heart failure; nonhypertensive
• 109: Acute cerebrovascular disease
• 110: Occlusion or stenosis of precerebral arteries
• 112: Transient cerebral ischemia
• 114: Peripheral and visceral atherosclerosis
• 115: Aortic; peripheral; and visceral artery aneurysms
• 116: Aortic and peripheral arterial embolism or thrombosis
• 118: Phlebitis; thrombophlebitis and thromboembolism

Infection is defined using the following Clinical Classifications Software (CCS) for ICD-9-CM categories or Clinical Classifications Software Refined (CCSR) for ICD-10-CM default categorization scheme for the principal (or first-listed) diagnosis as appropriate for the time period of the hurricane. An infection must be reported as the principal diagnosis on an inpatient stay or the first-listed diagnosis on an emergency department visit. The principal or first-listed diagnosis is used so that a record is only assigned to one specific clinical condition.

CCSR for ICD-10-CM Diagnoses Starting October 1, 2015

• INF001: Tuberculosis
• INF002: Septicemia
• INF003: Bacterial infections
• INF004: Fungal infections
• INF006: HIV infection
• INF007: Hepatitis
• INF008: Viral infection
• INF009: Parasitic, other and unspecified infections
• INF010: Sexually transmitted infections (excluding HIV and hepatitis)

CCS for ICD-9-CM Prior to October 1, 2015

1. Tuberculosis
2. Septicemia (except in labor)
3. Bacterial infection; unspecified site
4. Mycoses
5. HIV infection
6. Hepatitis
7. Viral infection
8. Other infections, including parasitic
9. Sexually transmitted infections (not HIV or hepatitis)

Injury is defined using the following ICD-9-CM or ICD-10-CM diagnosis codes as appropriate for the time period of the hurricane. The injury must be reported as the principal diagnosis on an inpatient stay or the first-listed diagnosis on an emergency department visit. The principal or first-listed diagnosis is used so that a record is only assigned to one specific clinical condition.

ICD-10-CM Codes Starting October 1, 2015

• S00-S99 series: Injuries to the head; neck; thorax; abdomen, lower back, lumbar spine, pelvis and external genitals; shoulder and upper arm; elbow and forearm; wrist, hand and fingers; hip and thigh; knee and lower leg; ankle and foot
  • Includes only initial encounters with a 7th character of A, B, C, or missing
• T07-T34 series: Injuries involving multiple body regions; injury of unspecified body region; effects of foreign body entering through natural orifice; burns and corrosions of external body surface, specified by site; burns and corrosions confined to eye and internal organs; burns and corrosions of multiple and unspecified body regions; frostbite
  • Includes only initial encounters with a 7th character of A, B, C, or missing
• T36-T50 series: Poisoning by, adverse effect of and underdosing of drugs, medicaments, and biological substances
  • Includes only codes with a 6th character of 1, 2, 3, or 4 indicating poisoning
  • Excludes adverse effects and underdosing of drugs, medicaments and biological substances (codes with the 6th character of 5 or 6) with the following exceptions: T36.9, T37.9, T39.9, T41.4, T42.7, T43.9, T45.9, T47.9, and T49.9 with a 5th character of 1, 2, 3, or 4
  • Includes only initial encounters with a 7th character of A, B, C, or missing
• T51-T76 series: Toxic effects of substances chiefly nonmedicinal as to source; other and unspecified effects of external causes: radiation sickness, unspecified; effects of heat and light; hypothermia; other effects of reduced temperature; effects of air pressure and water pressure; asphyxiation; effects of other deprivation; adult and child abuse, neglect and other maltreatment, confirmed; other and unspecified effects of other external causes; adult and child abuse, neglect and other maltreatment, suspected
  • Includes only initial encounters with a 7th character of A, B, C, or missing
• T79 series: Certain early complications of trauma, not elsewhere classified
  • Includes only initial encounters with a 7th character of A, B, C, or missing
• M97 series (valid as of October 1, 2016) or T8404 series (valid prior to October 1, 2016): Periprosthetic fracture around internal prosthetic joint
  • Includes only initial encounters with a 7th character of A, B, C, or missing
• O9A2-O9A5 series: Injury, poisoning, physical abuse, sexual abuse, psychological abuse, and other consequences of external causes complicating pregnancy, childbirth and the puerperium
  • Includes only initial encounters with a 7th character of A, B, C, or missing

ICD-9-CM Codes Prior to October 1, 2015

• 800-909.2: 909.4: 909.9: Fracture of skull, spine, trunk, upper limb, and lower limb; dislocation; sprains and strains of joints and adjacent muscles; intracranial injury, excluding those with skull fracture; internal injury of chest, abdomen, and pelvis; open wound of the head, neck, trunk, upper limb, and lower limb; injury to blood vessels; late effects of injury, poisonings, toxic effects, and other external causes, excluding those of complications of surgical and medical care and adverse effect of drugs, medicinal or biological substance
• 910-994.9: Superficial injury; contusion with intact skin surface; crushing injury; effects of foreign body entering through orifice; burns; injury to nerves and spinal cord; certain traumatic complications and unspecified injuries; poisoning by drugs, medicinals and biological substances; toxic effects of substances chiefly nonmedicinal as to source; other and unspecified effects of external causes
• 995.50-995.59: Child maltreatment syndrome
• 995.80-995.85: Adult maltreatment, unspecified; adult physical abuse; adult emotional/ psychological abuse; adult sexual abuse; adult neglect (nutritional); other adult abuse and neglect

Respiratory is defined using the following Clinical Classifications Software (CCS) for ICD-9-CM categories or Clinical Classifications Software Refined (CCSR) for ICD-10-CM default categorization scheme for the principal (or first-listed) diagnosis as appropriate for the time period of the hurricane. The respiratory condition must be reported as the principal diagnosis on an inpatient stay or the first-listed diagnosis on an emergency department visit. The principal or first-listed diagnosis is used so that a record is only assigned to one specific clinical condition.

CCSR for ICD-10-CM Diagnoses Starting October 1, 2015

• RSP001: Sinusitis
• RSP002: Pneumonia (except that caused by tuberculosis)
• RSP003: Influenza
• RSP005: Acute bronchitis
• RSP006: Other specified upper respiratory infections
• RSP007: Other specified and unspecified upper respiratory disease
• RSP008: Chronic obstructive pulmonary disease and bronchiectasis
• RSP009: Asthma
• RSP011: Pleurisy, pleural effusion and pulmonary collapse
• RSP012: Respiratory failure; insufficiency; arrest
• RSP014: Pneumothorax
• RSP016: Other specified and unspecified lower respiratory disease

CCS for ICD-9-CM Prior to October 1, 2015

• 122: Pneumonia (except that caused by tuberculosis or sexually transmitted disease)
• 123: Influenza
• 125: Acute bronchitis
• 126: Other upper respiratory infections
• 127: Chronic obstructive pulmonary disease and bronchiectasis
• 128: Asthma
• 130: Pleurisy; pneumothorax; pulmonary collapse
• 131: Respiratory failure; insufficiency; arrest (adult)
• 133: Other lower respiratory disease
• 134: Other upper respiratory disease

National Inpatient Stays:
Age refers to the age of the patient at admission. Discharges missing age are excluded from results reported by age.

National Emergency Department Visits:
Age refers to the age of the patient at admission to the ED. ED visits missing age are excluded from results reported by age.

Opioids Hospital Use:
Age refers to the age of the patient at admission. Discharges or visits missing age are excluded from results reported by age.

It should be noted that beginning with the transition to the ICD-10-CM/PCS coding system on October 1, 2015, a noticeable increase in opioid-related inpatient stays was observed for adults aged 65 years and older in most States. Additional information regarding this pattern is available on the HCUP-US web page for ICD-10-CM/PCS Resources in the report Preliminary Case Study: Exploring How Opioid-Related Diagnosis Codes Translate from ICD-9-CM to ICD-10-CM.

Hurricane Impact:
Age refers to the age (in years) of the patient at admission. Discharges or visits missing age are excluded from results reported by age. Age is grouped into three categories: 0-17 years, 18-64 years, and 65+ years. Less than 0.05 percent of records are missing information on age.

It is important to note that there were certain limitations to the data used for this analysis.

Identifying the Proximity of Counties to the Hurricane’s Path

The six-hour intervals between measurement points in the NOAA Best Track datasets could result in gaps in information if the storm was fast moving. The use of geographic circles defined by wind radii to classify counties as impacted by the hurricane may be overgenerous in identification (e.g., when only the outside edge of the wind radii circle touches the border of the county or one small coastal island) and may not identify counties that would have been detected if a shape other than a circle was used. For some hurricanes, there is incomplete wind radii information as a storm nears dissipation, making the end of the hurricane difficult to determine. For this analysis, NOAA Best Track data records with incomplete wind radii information are not included.

Population at Risk (Denominator for the Population-Based Rates)

The county-specific population data were annual counts from the U.S. Census Bureau, American Community Survey (ACS). The information would not have taken into account evacuations prior to the hurricane making landfall, seasonal migration patterns (e.g., elderly living in Florida during the winter), people who resided in a county impacted by the hurricane but who were not in the area at the time of the hurricane, or people from counties not impacted by the hurricane visiting the area at the time of the hurricane.

Utilization Counts (Numerator for the Population-Based Rates)

Information on hospital closures around the time of the hurricane was unavailable. In addition, hospitals may have had difficulty reporting utilization to the HCUP Partner organization (or were temporarily considered exempt from reporting) resulting in an underestimate of utilization using the SID and SEDD. Hospital care just prior to the hurricane may have been the result of preparing for the hurricane. In contrast, hospital care after the hurricane may not be hurricane related.

Suppression for Confidentiality

Suppression of data points, trend lines, or entire graphs was frequently applied to condition-specific selections for age 0 to 17 years, especially in the inpatient setting. For a detailed description of the suppression rules used in this topic, refer to the section “Percent Change from Pre-Hurricane Average for Inpatient Stays or ED Visits” above.