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HCUP Fast Stats Frequently Asked Questions
The HCUP Fast Stats FAQs provide quick, concise answers to commonly asked questions about the HCUP Fast Stats tool.
 
HCUP Fast Stats Frequently Asked Questions

This page provides answers to commonly asked questions about HCUP Fast Stats.
 
Contents
 
 
 

General Questions: HCUP Fast Stats

  • How often will HCUP Fast Stats be updated?

    AHRQ plans to update the State Trends in Hospital Use by Payer portion of Fast Stats two to three times a year, as newer data become available. AHRQ plans to update the National Hospital Utilization and Costs portion of Fast Stats annually to coincide with the release of the HCUP National Inpatient Sample (NIS). In the Opioid-Related Hospital Use portion of Fast Stats, State-level estimates will be updated bi-annually and national estimates will be updated annually to coincide with the release of the HCUP NIS and Nationwide Emergency Department Sample (NEDS).

    Update dates for existing Fast Stats topics are noted on the Fast Stats homepage. Typically, Fast Stats updates will include additional data years and/or quarters, if applicable, and occasionally changes to the underlying definitions or methodology that would affect older data. It is important to keep in mind that some differences may be observed when comparing statistics obtained prior to and at the time of a data update. If you would like to receive information regarding Fast Stats data updates, please sign up for the HCUP Mailing List. You can also check the HCUP User Support (HCUP-US) Web site Calendar of Database and Product Releases for updates.


  • Why don't all States appear in the State-level portions of Fast Stats?

    HCUP is a voluntary partnership between the federal government and statewide data organizations. HCUP currently has agreements with 47 States and the District of Columbia, known as "HCUP Partners". At this time, 48 of the HCUP Partners provide inpatient data to HCUP and 37 provide emergency department data. Because HCUP is a voluntary partnership, each State determines how their data are used in HCUP, thus not all States appear in Fast Stats. In addition, for effective presentation a State must have at least two contiguous recent years of data available to appear in HCUP Fast Stats trend topics.


  • Can you display more than two results when doing comparisons?

    To ensure that graphics and tables are readable, Fast Stats is limited to side-by-side comparisons for two sets of results.


  • What other HCUP resources can be used to examine aspects of hospital care?

    HCUP has various resources available for researching hospital care.

    • HCUPnet is an interactive online tool that provides access to national and State-level health statistics and information on hospital inpatient, emergency department, and ambulatory surgery utilization through a step-by-step query process.
    • HCUP Statistical Briefs provide simple descriptive statistics on selected topics with explanatory text. Statistical Briefs are static reports while Fast Stats will be updated on a regular basis.
    • The HCUP Central Distributor facilitates the purchase of HCUP National and State Databases for researchers who have a specific topic of interest.
    • The HCUP User Support Web site includes information on the HCUP databases, tools, software, reports, news, events, and technical assistance.


  • Why does information from HCUPnet sometimes differ from similar information on Fast Stats?

    In some cases, slightly different definitions are used to present the information in Fast Stats and HCUPnet. Five specific instances of differences are in the definitions of the maternal and neonatal hospitalization types, in the version of the HCUP Clinical Classifications Software (CCS) that is used to classify diagnoses and procedures, in the source of data used for the calculation of population-based rates, in how visits are counted when multiple, relevant diagnosis and procedure codes appear on a record, and in the definition of opioid-related hospitalizations.

    Definition of Maternal and Neonatal Hospitalization Types: For Fast Stats, the definitions of maternal and neonatal rely on the CCS categories, whereas the definitions of maternal and neonatal in HCUPnet use Major Diagnostic Categories (MDCs) to classify diagnosis codes. Compared with using MDCs, the CCS approach assigns approximately 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). Similarly, compared with the MDC approach, 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 CCS approach assigns another 0.1 percent fewer cases to "neonatal" than the MDC approach because neonatal septicemia is assigned to the septicemia CCS rather than a neonatal CCS.

    Version of the HCUP Clinical Classifications Software (CCS): When new data are added to the National Hospital Utilization and Costs topic of HCUP Fast Stats, national statistics reported by CCS are based on the most current version of the CCS software that is available at the time of the update. Because tables for HCUPnet are generated as soon as each year's database is completed, HCUPnet uses the CCS version provided on each year of the NIS. This affects the numbering scheme, the counts, and the labels for the CCS.

    Source Used for Population Data: For Fast Stats, all population data are obtained from Claritas, a vendor that compiles and adds value to data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. For HCUPnet, all population data except for community-level income are obtained from the Census; population data for community-level income are obtained from Claritas. Users will notice slight differences in the population-based rates presented in Fast Stats versus those in HCUPnet for characteristics other than community-level income. These differences are the result of different approaches used by the Census and Claritas to interpolate the rate of change in the population from year to year.

    Counting Stays and Visits With Multiple, Relevant Diagnosis/Procedure Codes: 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 opioid-related inpatient stays and ED visits, a record may include more than one of the opioid-specific codes; in such a case, the record is only included once in the counts. However, when performing a query with multiple, all-listed diagnosis or procedure codes in HCUPnet, individual stays or visits will be counted more than once if multiple, specified ICD-9-CM codes appear on the record.

    Definition of Opioid-Related Hospitalizations: The definition of an opioid-related hospitalization, based on ICD-9-CM diagnosis codes, varies between Fast Stats' Opioid-Related Hospital Use topic and HCUPnet's Community-level Statistics pathway that presents statistics on inpatient stays for alcohol and other drugs (specifically, when drilling down to the opioids option under the type of substance or substance-related condition).

    • Fast Stats does not include ICD-9-CM codes indicating opioid dependence and abuse "in remission" (304.03, 304.73, and 305.53); HCUPnet does include these codes.

    • Fast Stats includes ICD-9-CM codes for methadone, other opiates and related narcotics, and opiate antagonists causing adverse effects in therapeutic use (E935.1, E935.2, and E940.1); HCUPnet does not include these codes.

    • Fast Stats does not include codes for narcotics affecting fetus or newborn via placenta or breast milk (760.72) and drug withdrawal syndrome in newborn (779.5); HCUPnet does include these codes.


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Topic Questions: State Trends in Hospital Use by Payer

  • Why don't you summarize the results of the analyses shown in the State Trends in Hospital Use by Payer portion of Fast Stats?

    Fast Stats is intended to provide easy-to-read graphics and simple tables to convey complex information at a glance. Fast Stats focuses on a few preselected topics that are of general interest. The interpretation of the information in the State Trends in Hospital Use by Payer section of Fast Stats is left to the user. Changes in inpatient and emergency department utilization are influenced by many factors including health insurance expansion.


  • What is the data source used for State-level trends in inpatient stays and emergency department visits for patients?

    The estimates in the State-specific trends in inpatient stays are based on data from the HCUP State Inpatient Databases (SID) and inpatient quarterly data, which is available from some HCUP Partner organizations.


  • The estimates in the State-specific trends in emergency department visits are based on data from both the HCUP State Emergency Department Databases (SEDD) and selected records from the SID. The SEDD capture information on emergency department (ED) visits that do not result in an admission (i.e., the data include treat-and-release visits and transfers to another hospital). Information on patients initially seen in the ED and then admitted to the same hospital are obtained from the SID.

    The data are limited to patients treated in community, nonrehabilitation hospitals in the State.

  • Why do some Medicaid expansion dates occur earlier than others?

    Some States implemented Medicaid expansion under the Affordable Care Act earlier than others. Some of these States adopted the early expansion option provided for under the Affordable Care Act to expand their Medicaid programs before January 1, 2014, while others expanded on January 1, 2014, to coincide with the start of Qualified Health Plan Coverage through the Marketplaces. Other States have expanded after January 1, 2014, while others have not expanded their Medicaid programs to date. Finally, please note that some States had been covering the population now eligible as a result of the Medicaid expansion using demonstration authority prior to the passage of the Affordable Care Act. For many States, implementation of the Medicaid expansion under the Affordable Care Act in January 2014 is associated with shifts of people from uninsured status to Medicaid coverage.


  • What are your sources for the Medicaid expansion dates?

    We used information from the Kaiser Family Foundation1 for the Medicaid expansion dates referenced in the State Trends in Hospital Use by Payer section of Fast Stats:



    1 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.


  • Why does it say expected payer?

    A hospital's response to the question, "Who is expected to pay the hospital for a given service?" is reported under the category of expected payer in the HCUP databases. However, who is expected to pay the hospital may be different than who actually pays the bill. In addition, the hospital's answer to this question may be different from the response to, "What company or agency is the patient's insurer?" or "Is the patient insured?" This distinction applies particularly to uninsured patients, whose care may be paid by various State or local programs.


  • Who is included in the category of uninsured?

    Discharges with the expected primary payer of self-pay, charity, and no charge are classified as uninsured. For HCUP Partner organizations that identify State and local programs serving low-income, uninsured populations (e.g., Indian Health Services, county indigent, migrant health programs, Ryan White Act, Hill-Burton Free Care), discharges for these payers also are classified as uninsured. About one-third of the HCUP Partner organizations include this level of detail in their coding of expected payer.


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Inpatient Stay Trends by Payer

  • Why do you present information only for adults? Do you plan to extend this to children?

    Most hospital stays for patients under age 18 are for normal newborns; children are hospitalized at a much lower rate than adults. Excluding normal newborns, patients under age 18 account for roughly 5 percent of inpatient stays. In the future, the Inpatient Stay Trends by Payer section of Fast Stats may be expanded to include health care utilization for children as well.
  • Why is Congestive Heart Failure (CHF) no longer reported in HCUP Fast Stats?

    The reporting of Congestive Heart Failure (CHF) in HCUP Fast Stats has been discontinued as of November 2017 because a change in the ICD-10-CM coding guidelines effective October 1, 2016 has caused a discontinuity in the trend. CHF discharges had been identified by a principal diagnosis CCS code of 108 (congestive heart failure; nonhypertensive) as defined in the Clinical Classifications Software (CCS) for ICD-9-CM and for ICD-10-CM tools. There is a sharp decline in the number of CHF discharges identified by CCS 108 because the revised coding criteria specify that unless it is documented on the medical record that heart failure is unrelated to hypertension, the diagnosis code I110 for "Hypertensive heart disease with heart failure" should be reported instead of a heart failure code in the range I501-I509. The CHF option has been removed from the active query tool, but historical data previously reported in HCUP Fast Stats for CHF (with data reported through 2016 Q3 for some States) is offered in the Excel download file, which can be downloaded by expanding "Show Data Export Options" on the Inpatient Stay Trends by Payer query page.


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Emergency Department Visit Trends by Payer

  • Why do you include emergency department visit results for children?

    Patients under the age of 18 account for roughly 20 percent of total emergency department visits compared to only about 5 percent of inpatient stays (excluding normal newborns).


  • What is the first-listed diagnosis?

    On the SID, the first-listed diagnosis code reflects the condition established to be chiefly responsible for a patients' admission to the hospital and thus is considered the principal diagnosis code. However, on the SEDD, the first-listed diagnosis is the condition, symptom, or problem identified in the medical record to be chiefly responsible for the outpatient visit. For example, chest pain may be the reason for a patient's visit to the emergency department, but if admitted, the principal diagnosis might be acute myocardial infarction.


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Topic Questions: National Hospital Utilization and Costs

  • What is the data source used for national estimates of hospital utilization and costs?

    The estimates in the National portion of Fast Stats are based on data from the HCUP National (Nationwide) Inpatient Sample (NIS). In 2012, the NIS was redesigned to optimize national estimates. As a result, there can be a discontinuity in national trends. In order to generate consistent national estimates across 10 and 20 years, the NIS Trend Weight Files were used. These files include revised weights for the NIS that ensure that weighted national estimates for data years 1993-2011 are comparable to weighted national estimates for data year 2012 and later.


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National Trends in Inpatient Stays

  • Which adjustment year was chosen for the average inflation-adjusted costs?

    The adjustment year used to calculate the average inflation-adjusted costs is 2010.


  • Why is cost information only available beginning with the 2000 data year?

    Average costs are calculated using the HCUP Cost-to-Charge Ratios (CCR), which are unavailable prior to 2000. For additional information on the average actual and inflation-adjusted costs per stay, refer to the Data Notes & Methods section of the Trends in Inpatient Stays portion of Fast Stats.


  • Why is information on community-level income only available beginning with the 2003 data year?

    Information by community-level income is only reported from 2003 forward because of inconsistent definitions over time in the income-related data elements in the NIS.


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Most Common Diagnoses for Inpatient Stays

  • What is the principal diagnosis?

    The principal diagnosis is the condition established after study to be chiefly responsible for the patient's admission to the hospital for care. The principal diagnosis is considered to be the main reason for the hospital stay.


  • What are the diagnoses based on?

    The diagnoses are identified using AHRQ's Clinical Classifications Software (CCS), which categorizes patient diagnoses into a manageable number of clinically meaningful categories. For additional information, please refer to the Data Notes & Methods section of the Most Common Diagnoses for Inpatient Stays portion of Fast Stats.


  • Why are there options to include and exclude maternal/neonatal stays?

    Maternal/Neonatal stays generally account for nearly a fourth of all inpatient hospitalizations in the United States and the majority are low complexity, low cost stays. When examining all inpatient stays, it is important to consider whether the results should factor in maternal and neonatal hospitalizations, which tend to have different characteristics than other types of hospital stays. For instance, if the focus is on hospital use for the treatment of illnesses, it would make sense to exclude maternal/neonatal stays from the analysis.


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Most Common Operations During Inpatient Stays

  • What are all-listed operating room procedures?

    Operating room (OR) procedures are identified using procedure classes that categorize each ICD-9-CM procedure code as major therapeutic, major diagnostic, minor therapeutic, or minor diagnostic. Major therapeutic and diagnostic procedures are considered to be valid OR procedures based on diagnosis-related groups (DRGs). The DRG classification scheme relies on physician panels that classify ICD-9-CM procedure codes according to whether the procedure would be performed in a hospital OR in most hospitals. OR procedures (major therapeutic and diagnostic) are identified using all procedure fields (first-listed and secondary) that were available on the discharge record.


  • What are the procedure names based on?

    The procedures are identified using AHRQ's Clinical Classifications Software (CCS), which categorizes patient procedures into a manageable number of clinically meaningful categories. For additional information, please refer to the Data Notes & Methods section of the Most Common Operations During Inpatient Stays portion of Fast Stats.


  • Why are there options to include and exclude maternal/neonatal stays?

    Maternal/Neonatal stays generally account for nearly a fourth of all inpatient hospitalizations in the United States and the majority are low complexity, low cost stays. When examining all inpatient stays, it is important to consider whether the results should factor in maternal and neonatal hospitalizations, which tend to have different characteristics than other types of hospital stays. For instance, if the focus is on hospital use for the treatment of illnesses, it would make sense to exclude maternal/neonatal stays from the analysis.


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Topic Questions: Opioid-Related Hospital Use

  • What are the data sources used for the estimates of opioid-related hospital use?

    The national estimates in the Opioid-Related Hospital Use portion of Fast Stats are based on data from the HCUP National (Nationwide) Inpatient Sample (NIS) and the HCUP Nationwide Emergency Department Sample (NEDS).

    The State-level estimates in the Opioid-Related Hospital Use portion of Fast Stats are based on data from the HCUP State Inpatient Databases (SID) and HCUP State Emergency Department Databases (SEDD).


  • Interactive Map

    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 of rates across all States providing data in 2015. States are classified into one of five groups based on the distribution of rates in 2015: 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.

  • Why are the emergency department (ED) estimates restricted to only ED visits that do not result in an admission to the same hospital?

    This approach is used to avoid double counting of inpatient stays. The HCUP Nationwide Emergency Department Sample (NEDS) includes ED visits that result in admission to the same hospital, but the HCUP State Emergency Department Databases (SEDD) do not include these records; instead, the SEDD report only "treat-and-release" ED visits. Reporting of opioid-related ED visits was defined consistently for both national and State data to include only ED encounters that do not result in admission to the same hospital (i.e., treat-and-release ED visits). Estimates of opioid-related ED visits resulting in admission to the same hospital are included in the inpatient stay statistics, which are captured consistently in both the HCUP National (Nationwide) Inpatient Sample (NIS) and the State Inpatient Databases (SID).


  • Why are the results presented as population-based rates? What if we are interested in obtaining the discharge counts?

    Since both national and State-level estimates are provided, rates per 100,000 population were chosen in order to make the estimates comparable. In addition, reporting by rates allows comparisons across population subgroups, such as age and sex. Rates are calculated based on the actual quarterly discharge counts, which are available as rounded values in the exported data file and can be downloaded by expanding "Show Data Export Options" on the main query page. The exported data file also includes rates calculated based on annual discharge counts.


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Internet Citation: HCUP Fast Stats Frequently Asked Questions. Healthcare Cost and Utilization Project (HCUP). October 2018. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/faststats/faq_faststats.jsp.
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