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HCUP Fast Stats - Trends in Inpatient Stays
HCUP Fast Stats provides easy access to the latest HCUP-based statistics for health care information topics. This section examines national trends in inpatient utilization, costs, and mortality across a variety of patient characteristics.

Trends in Inpatient Stays

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U.S. National: Cost per Stay (Actual) for All Inpatient Stays
Year All inpatient stays
2000 6,073
2001 6,333
2002 6,889
2003 7,277
2004 7,614
2005 8,036
2006 8,305
2007 8,653
2008 9,106
2009 9,111
2010 9,681
2011 9,973
2012 10,355
2013 10,730
2014 10,889
2015 11,259
2016 11,728

2015 Caution: Transition from ICD-9-CM to ICD-10-CM/PCS Coding

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" on the graphs and statistics reported using ICD-10-CM/PCS coding identified as "ICD-10" on the graphs. The 2015 rates of stays per 100,000 population and average statistics for hospitalization type in this section of HCUP Fast Stats 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. 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

Data Source

The national estimates presented in this section of Fast Stats are 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 participating in HCUP in that 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 presented in this section of Fast Stats 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).

Inpatient Stays

The unit of analysis in the NIS is the hospital discharge (i.e., the inpatient stay), not a person or patient. This means that a person who is admitted to the hospital multiple times in one year will be counted each time as a separate "discharge" from the hospital. Counts are summarized by discharge year. There were no exclusions applied to the data (e.g., transfers to another acute care hospital are included as separate hospital stays).


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


All nonmale, nonfemale responses are set to missing. Discharges with missing values for sex are excluded from results reported by sex.

Expected Payer

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 the uninsured. Uninsured discharges include records in which the expected primary payer was no insurance, self-pay, charity, no charge, Hill Burton free care, research (e.g., clinical trial or donor), refusal to pay, or no payment. Discharges for other types of payers (e.g., Workers' compensation, Indian Health Service, State and local programs) are not reported. 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.

Community-Level Income

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. Starting in data year 2002, the cut-offs for the quartile designation are determined annually using ZIP Code demographic data 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. The value ranges for the national income quartiles vary by year. 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. Income quartile is missing if the patient is homeless or foreign. Discharges missing the income quartile are excluded from results reported by community-level income.

Hospitalization Type

Coding criteria for the six hospitalization types are based on ICD-9-CM and ICD-10-CM diagnosis codes, Clinical Classifications Software (CCS) categories, and diagnosis-related groups (DRGs). There are approximately 14,000 ICD-9-CM diagnosis codes and over 70,000 ICD-10-CM diagnosis codes. The CCS categorizes ICD-9-CM and ICD-10-CM diagnosis codes into a manageable number of clinically meaningful categories, which may be more useful for presenting descriptive statistics and understanding patterns of diagnoses. DRGs group patients according to diagnosis, type of treatment (procedure), age, and other relevant criteria. Each hospital stay has one assigned DRG.

Each discharge was assigned to a single hospitalization type hierarchically, based on the following order: maternal, neonatal, mental health, injury, surgical, and medical. All discharges are categorized in one of the six mutually exclusive types of service lines.

Because of the transition from ICD-9-CM to ICD-10-CM/PCS on October 1, 2015, the rate of stays, cost per stay, length of stay, and in-hospital mortality for hospitalization type in 2015 are based on the first three quarters of 2015 data (Q1-3) only. The number of inpatient stays by hospitalization type in 2015 is not available.

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.

Rate of Stays per 100,000

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 payer-specific population denominators are not consistently available for payers in a way that is consistent with how payers are recorded in administrative data. 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 compiles and adds value to data from the U.S. Census Bureau. Claritas estimates intercensal annual household and demographic statistics for geographic areas. Because of the transition from ICD-9-CM to ICD-10-CM/PCS on October 1, 2015, the 2015 rate of stays per 100,000 population for the hospitalization type characteristic is based on the first three quarters of 2015 data (Q1-3) only.

Actual Cost per Stay

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.

Inflation-Adjusted Cost per Stay

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 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.

Length of Stay

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

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.

Use this export feature to download all of the underlying data for national trends in inpatient stays (all measures and characteristics) in Microsoft Excel (.xls) format.

  1. Click this Excel Export link to request the download.
  2. Follow the prompts to save a copy of the Excel file to your computer. Prompting will vary by browser.
  3. If you decide to use these data for publishing purposes please refer to Requirements for Publishing with HCUP Data.

Internet Citation: HCUP Fast Stats. Healthcare Cost and Utilization Project (HCUP). March 2019. Agency for Healthcare Research and Quality, Rockville, MD.
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Last modified 3/12/2019