STATISTICAL BRIEF #195 |
November 2015
Kathryn R. Fingar, Ph.D., M.P.H., Marguerite L. Barrett, M.S., Anne Elixhauser, Ph.D., Carol Stocks, Ph.D., R.N., and Claudia A. Steiner, M.D., M.P.H. Introduction Reducing potentially preventable hospitalizations is important for increasing quality of care and containing hospital costs. Medical conditions such as asthma, urinary tract infections, and complications of diabetes are considered ambulatory care sensitive conditions, meaning that when those conditions are present, primary or preventive can reduce the need for emergency department (ED) visits and inpatient hospitalization. From 2000 through 2012, the rate of potentially preventable hospitalizations among adults aged 18 years and older decreased by 25 percent.1 Although the decrease in potentially preventable hospitalizations could reflect improvements in access to quality ambulatory care, it also may be an artifact of an overall decrease in inpatient admissions in recent years. The total rate of inpatient hospital stays decreased by 0.3 percent per year from 2003 through 2008 and by 1.9 percent per year from 2008 through 2012.2 The Great Recession, which officially began in December 2007, was associated with a decrease in inpatient stays as unemployment increased and access to health insurance decreased.3 For those who had health insurance during the Recession, copayments and deductibles increased.4 Recent initiatives that penalize hospitals for high readmission rates are leading to more scrutiny over potentially preventable hospitalizations.5 EDs and observation services play an important role in evaluating whether hospitalization is necessary. Although overall inpatient hospital stays have declined, increasingly patients are being seen in EDs and placed under observation, which may result in more individuals being discharged home rather than admitted as an inpatient.6,7 From 2006 through 2012, the total rate of ED visits, including those that resulted in the patient being treated and released and those that resulted in the patient being admitted to the hospital, increased by 5 percent from 40,200 to 42,100 per 100,000 population. 8 This Healthcare Cost and Utilization Project (HCUP) Statistical Brief presents rates of potentially preventable inpatient hospital stays from 2005 through 2012 and rates of potentially preventable ED visits that did not result in inpatient admission (i.e., treat-and-release visits) from 2008 through 2012. Potentially preventable stays and ED visits were estimated using the Agency for Healthcare Research and Quality (AHRQ) Prevention Quality Indicators (PQIs) software version 4.4. We examined the rate of potentially preventable inpatient stays for all conditions and for acute and chronic conditions grouped together. We also examined potentially preventable stays and visits for each underlying individual condition separately. Rates of potentially preventable hospitalizations and ED visits are age-sex adjusted and calculated among adults aged 18 years and older. Because the PQIs are defined using the first-listed diagnosis, they exclude records that fall in the maternal/neonatal service line that have a pregnancy-related first-listed diagnosis. For comparison, we present age-sex adjusted rates of total inpatient stays and treat-and-release ED visits, which also were calculated among adults aged 18 years and older and exclude records that fall in the maternal/neonatal service line. Only differences greater than 10 percent are noted in the text. Findings Trends in potentially preventable hospital inpatient stays, 2005-2012 Figure 1 presents the age-sex adjusted rate of potentially preventable inpatient stays among adults aged 18 years and older, for all conditions and for acute and chronic conditions separately, from 2005 through 2012. |
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Figure 1. Age-sex adjusted rate of potentially preventable inpatient stays among adults aged 18 years and older, overall and for acute and chronic conditions, 2005-2012
Source: Agency for Healthcare Research and Quality (AHRQ), Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project (HCUP), Nationwide Inpatient Sample (NIS), 2005-2011; State Inpatient Databases (SID), 2012, weighted to provide national estimates using the same methodology as the 2005-2011 NIS; and the AHRQ Quality Indicators, version 4.4 Figure 1 is a line graph that shows the age-adjusted rate of potentially preventable inpatient stays overall and for acute and chronic conditions for adults 18 years and older from 2005 through 2012. For all conditions, the age-sex adjusted rate of potentially preventable stays declined from 1,941 in 2005 to 1814 in 2007, rose slightly to 1,815 in 2008, declined to 1,658 in 2010, rose to 1,669 in 2011, and declined to 1,582 in 2012, an 18.5% cumulative decrease. For chronic conditions, the age-sex adjusted rate of potentially preventable stays declined from 1,118 in 2005 to 1053 in 2007, rose to 1,078 in 2008, and then declined steadily to 961 in 2012, a cumulative 14.1% decrease. For acute conditions, the age-sex adjusted rate of potentially preventable stays declined steadily from 823 in 2005 to 645 in 2010, rose to 657 in 2011, and declined to 621 in 2012, a cumulative 24.5% decrease.
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Table 1 presents the cumulative change in the rate of all nonmaternal inpatient hospital stays among adults aged 18 years and older from 2005 through 2012, by hospital service line, compared with potentially preventable stays for acute and chronic conditions. |
Table 1. Age-sex adjusted rate of nonmaternal inpatient hospital stays among adults aged 18 years and older, by hospital service line, compared with potentially preventable stays, 2005-2012 | ||||||
Type of inpatient stay | Age-sex adjusted rate per 100,000 population | % change in rate | ||||
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2005 | 2008 | 2012 | 2005-2008 | 2008-2012 | 2005-2012 | |
All nonmaternal inpatient stays by service line | ||||||
Total | 12,303 | 12,227 | 11,385 | -0.6 | -6.9 | -7.5 |
Medical | 7,382 | 7,291 | 6,913 | -1.2 | -5.2 | -6.4 |
Surgical | 3,466 | 3,421 | 2,980 | -1.3 | -12.9 | -14.0 |
Mental health | 752 | 780 | 799 | 3.7 | 2.5 | 6.3 |
Injury | 701 | 707 | 681 | 0.9 | -3.7 | -2.8 |
Potentially preventable inpatient stays | ||||||
All conditions | 1,941 | 1,815 | 1,582 | -6.5 | -12.8 | -18.5 |
Acute conditions | 823 | 736 | 621 | -10.5 | -15.6 | -24.5 |
Chronic conditions | 1,118 | 1,078 | 961 | -3.6 | -10.9 | -14.1 |
Notes: Each discharge was assigned to a single hospital service line hierarchically, based on the following order: maternal and neonatal (excluded), mental health, injury, surgical, and medical. All nonmaternal inpatient stays include potentially preventable stays. Source: Agency for Healthcare Research and Quality (AHRQ), Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project (HCUP), Nationwide Inpatient Sample (NIS), 2005 and 2008; State Inpatient Databases (SID), 2012, weighted to provide national estimates using the same methodology as the 2005 and 2008 NIS; and the AHRQ Quality Indicators, version 4.4 |
Trends in potentially preventable ED visits, 2008-2012 Figure 2 presents the age-sex adjusted rate of potentially preventable treat-and-release ED visits among adults aged 18 years and older, for all conditions and for acute and chronic conditions separately, from 2008 through 2012. |
Figure 2. Age-sex adjusted rate of potentially preventable treat-and-release ED visits among adults aged 18 years and older, overall and for acute and chronic conditions, 2008-2012
Abbreviation: ED, emergency department Figure 2 is a line graph that shows the age-sex adjusted rate of potentially preventable treat-and-release emergency department visits overall and for acute and chronic conditions for adults 18 years and older from 2008 through 2012. For all conditions, the age-sex adjusted rate of potentially preventable treat-and-release emergency department visits increased steadily from 2,350 in 2008 to 2,618 in 2012, an 11.4% cumulative increase. For acute conditions, the age-sex adjusted rate of potentially preventable treat-and-release emergency department visits increased steadily from 1,229 in 2008 to 1,382 in 2012, a 12.5% cumulative increase. For chronic conditions, the age-sex adjusted rate of potentially preventable treat-and-release emergency department visits increased steadily from 1,121 in 2008 to 1,235 in 2012, a 10.2% cumulative increase. |
Table 2 presents the cumulative change in the rate of nonmaternal treat-and-release ED visits among adults aged 18 years and older from 2008 through 2012, by hospital service line, compared with potentially preventable visits for acute and chronic conditions. |
Table 2. Age-sex adjusted rates of nonmaternal treat-and-release ED visits among adults aged 18 years and older, by hospital service line, compared with potentially preventable visits, 2008-2012 | |||
Type of ED visit | Age-sex adjusted rate per 100,000 population | % change in rate, 2008-2012 | |
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2008 | 2012 | ||
All nonmaternal treat-and-release ED visits by service line | |||
Total | 33,692 | 36,208 | 7.5 |
General medical | 24,275 | 26,837 | 10.6 |
Injury | 8,000 | 7,681 | -4.0 |
Mental health | 1,417 | 1,690 | 19.3 |
Potentially preventable treat-and-release ED visits | |||
All conditions | 2,350 | 2,618 | 11.4 |
Acute conditions | 1,229 | 1,382 | 12.5 |
Chronic conditions | 1,121 | 1,235 | 10.2 |
Abbreviation: ED, emergency department Notes: Because the surgical and medical groups are defined using diagnosis-related groups, which are not available in the ED data, ED visits not classified as maternal/neonatal, mental health, or injury were grouped into a general medical category. All nonmaternal treat-and-release ED visits include potentially preventable visits. Source: Agency for Healthcare Research and Quality (AHRQ), Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project (HCUP), Nationwide Emergency Department Sample (NEDS), 2008 and 2012, and the AHRQ Quality Indicators, version 4.4. Although the NEDS is available starting in 2006, this Statistical Brief uses data from 2008 that were compiled for the 2008-2012 National Healthcare Quality and Disparities Reports. |
Comparison of trends in potentially preventable hospital inpatient stays and ED visits, 2008-2012 Figure 3 presents the cumulative percentage change from 2008 through 2012 in the age-sex adjusted rate of potentially preventable inpatient stays and treat-and-release ED visits among adults aged 18 years and older, for all conditions and for acute and chronic conditions separately. |
Figure 3. Cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays and treat-and-release ED visits among adults aged 18 years and older, 2008-2012
Abbreviation: ED, emergency department Figure 3 is a bar chart that shows the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays and treat-and-release emergency department visits for adults aged 18 years and older from 2008 through 2012. For all conditions, the cumulative percentage change in age-sex adjusted rate of potentially preventable inpatient stays was -12.8% and the change in the rate of potentially preventable treat-and-release emergency department visits was +11.4%. For acute conditions, the cumulative percentage change in age-sex adjusted rate of potentially preventable inpatient stays was -15.6% and the change in the rate of potentially preventable treat-and-release emergency department visits was +12.5%. For chronic conditions, the cumulative percentage change in age-sex adjusted rate of potentially preventable inpatient stays was -10.9% and the change in the rate of potentially preventable treat-and-release emergency department visits was +10.2%.
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Table 3 presents the cumulative change in the rate of potentially preventable inpatient stays and treat-and-release ED visits among adults aged 18 years and older from 2008 through 2012, by condition that was the reason for the stay or visit. Figure 4 compares the cumulative percentage change from 2008 through 2012 for rates of potentially preventable inpatient stays and ED visits among adults aged 18 years and older. |
Table 3. Age-sex adjusted rate of potentially preventable inpatient stays and treat-and-release ED visits among adults aged 18 years and older, by condition, 2008-2012 | ||||||
Condition | Rate of potentially preventable inpatient stays per 100,000 population | % change in rate of inpatient stays, 2008-2012 | Rate of potentially preventable ED visits per 100,000 population | % change in rate of ED visits, 2008-2012 | ||
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2008 | 2012 | 2008 | 2012 | |||
All conditions | 1,815 | 1,582 | -12.8 | 2,350 | 2,618 | 11.4 |
Acute conditions | 736 | 621 | -15.6 | 1,229 | 1,382 | 12.5 |
Dehydration | 174 | 121 | -30.5 | 171 | 179 | 4.9 |
Bacterial pneumonia | 360 | 306 | -15.0 | 218 | 223 | 2.1 |
Urinary tract infection | 202 | 195 | -3.9 | 841 | 981 | 16.7 |
Chronic conditions | 1,078 | 961 | -10.9 | 1,121 | 1,235 | 10.2 |
Diabetes with short-term complications | 60 | 73 | 21.7 | 7 | 9 | 20.2 |
Diabetes with long-term complications | 129 | 116 | -9.7 | 123 | 116 | -6.3 |
Uncontrolled diabetes without complications | 23 | 17 | -24.5 | 17 | 23 | 32.3 |
Lower extremity amputations for diabetes | 18 | 17 | -1.1 | DSU | DSU | DSU |
Chronic obstructive pulmonary diseasea | 575 | 507 | -12.0 | 629 | 703 | 11.8 |
Asthmab | 59 | 50 | -15.3 | 527 | 572 | 8.6 |
Hypertension | 61 | 60 | -1.9 | 258 | 318 | 23.3 |
Congestive heart failure | 397 | 341 | -14.2 | 83 | 81 | -3.0 |
Abbreviations: ED, emergency department; DSU, data statistically unreliable. a Rate per 100,000 adults aged 40 years or older. b Rate per 100,000 adults aged 18-39 years. Notes: All rates are per 100,000 population aged 18 years and older, unless otherwise noted. Although angina is included in the rate of potentially preventable stays and visits overall and for chronic conditions grouped together, the individual rate is not presented because this measure is soon to be retired; rates of angina are low in frequency, and coding changes over time make trends less reliable. Source: Agency for Healthcare Research and Quality (AHRQ), Center for Delivery, Organization, and Markets, Healthcare Cost and Utilization Project (HCUP), Nationwide Inpatient Sample (NIS), 2008; State Inpatient Databases (SID), 2012, weighted to provide national estimates using the same methodology as the 2008 NIS; Nationwide Emergency Department Sample (NEDS), 2008 and 2012; and the AHRQ Quality Indicators, version 4.4 |
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Figure 4. Cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays and treat-and-release ED visits among adults aged 18 years and older, by specific condition, 2008-2012
Abbreviation: ED, emergency department Figure 4 is a bar chart that shows the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays and treat-and-release emergency department visits for adults aged 18 years and older by specific condition from 2008 through 2012. The first three conditions are acute conditions. For dehydration, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was -30.5% and treat-and-release emergency department visits was +4.9%. For bacterial pneumonia, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was -15.0% and treat-and-release emergency department visits was +2.1%. For urinary tract infection, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was -3.9% and treat-and-release emergency department visits was +16.7%. The remaining eight conditions are chronic conditions. For diabetes, short-term complications, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was +21.7% and treat-and-release emergency department visits was +20.2%. For diabetes, long-term complications, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was -9.7% and treat-and-release emergency department visits was -6.3%. For uncontrolled diabetes, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was -24.5% and treat-and-release emergency department visits was +32.3%. For lower extremity amputation for diabetes, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was -1.1% and the percentage change was not calculated for treat-and-release emergency department visits because the rate was statistically unreliable. For chronic obstructive pulmonary disease, including adults aged 40 years and older, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was -12.0% and treat-and-release emergency department visits was +11.8%. For asthma, including adults aged 18-39 years, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was -15.3% and treat-and-release emergency department visits was +8.6%. For hypertension, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was -1.9% and treat-and-release emergency department visits was +23.3%. For congestive heart failure, the cumulative percentage change in the age-sex adjusted rate of potentially preventable inpatient stays was -14.2% and treat-and-release emergency department visits was -3.0%.
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Data Source
The estimates in this Statistical Brief are based upon an analysis done for the National Healthcare Quality and Disparities Reports (QDR). Inpatient data came from the Healthcare Cost and Utilization Project (HCUP) 2005-2011 Nationwide Inpatient Sample (NIS). For data year 2012, we used an analysis file derived from the HCUP State Inpatient Databases (SID) that was designed to provide national estimates with weighted records from a sample of hospitals from 44 States via the same methodology employed for the 2003-2011 NIS. We did not use the 2012 National Inpatient Sample (NIS) because the sampling design and universe definition was revised. At the time of this analysis, NIS trend weights to make national estimates compatible between 2003-2011 and 2012 were unavailable. Treat-and-release emergency department (ED) data came from the HCUP 2008-2012 Nationwide Emergency Department Sample (NEDS). Although the NEDS is available starting in 2006, this Statistical Brief uses data from 2008 that were compiled for the 2008-2012 QDR. Supplemental sources included population denominator data from Nielsen, a vendor that compiles and adds value to the U.S. Bureau of Census data.9 If a patient received observation services (OS) prior to being admitted to the hospital or after being seen in the ED, he or she would be included in the inpatient or ED treat-and-release data used in this analysis. OS were not examined in this Statistical Brief because of variation in how these data are collected across States. Definitions Prevention Quality Indicators The Prevention Quality Indicators (PQIs; version 4.4), a component of the AHRQ Quality Indicators (QIs), are a set of measures that can be used with hospital inpatient discharge data to identify access to and quality of care for "ambulatory care-sensitive conditions." These are conditions for which good outpatient care can potentially prevent the need for hospitalization or for which early intervention can prevent complications or more severe disease. PQI rates can also be affected by other factors such as disease prevalence. The PQIs are adjusted for age and sex using the total U.S. resident population for 2010 as the standard population. Although the PQI software was developed to be used with inpatient data, it was applied to ED data in this Statistical Brief to look at utilization across settings. Several other studies have examined ambulatory care-sensitive conditions across acute care settings.10, 11, 12 Note that the PQI for angina is scheduled to be retired in the next version of the PQI software. A review of angina-related hospitalization using Medicare data found that declines were associated with shifts in coding practices, namely, the increased use of codes specific to coronary artery disease (the underlying disease) rather than angina (the manifestation of that disease). Further information on the AHRQ QIs, including documentation and free software downloads, is available at http://www.qualityindicators.ahrq.gov/. This website also includes information on the Pediatric Quality Indicators (PDIs, formerly known as PedQIs). The PDIs contain measures of potentially preventable hospitalizations for children with asthma, gastroenteritis, diabetes with short-term complications, and perforated appendix. Additional information on how the QI software was applied to the HCUP data for the statistics reported in this Statistical Brief is available in Coffey et al., 2012.13 Case definition Coding criteria for the five hospital service lines are provided in Table 4 and are based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) codes, Clinical Classifications Software (CCS) categories, and diagnosis-related groups (DRGs) (see definitions below). Each discharge or visit was assigned to a single hospital service line hierarchically, based on the following order: maternal and neonatal (which were excluded from this Statistical Brief because the PQIs are calculated for nonmaternal stays), mental health, injury, surgical, and medical. Because the surgical and medical groups are defined using DRGs, which are not available in the NEDS, ED visits not classified as maternal/neonatal, mental health, or injury were grouped into an "general medical" category. Diagnoses, ICD-9-CM, Clinical Classifications Software (CCS), and diagnosis-related groups (DRGs) The principal diagnosis is that condition established after study to be chiefly responsible for the patient's admission to the hospital. Secondary diagnoses are concomitant conditions that coexist at the time of admission or develop during the stay. All-listed diagnoses include the principal diagnosis plus these additional secondary conditions. ICD-9-CM is the International Classification of Diseases, Ninth Revision, Clinical Modification, which assigns numeric codes to diagnoses. There are approximately 14,000 ICD-9-CM diagnosis codes. CCS categorizes ICD-9-CM diagnosis codes into a manageable number of clinically meaningful categories. 14 This clinical grouper makes it easier to quickly understand patterns of diagnoses. CCS categories identified as Other typically are not reported; these categories include miscellaneous, otherwise unclassifiable diagnoses that may be difficult to interpret as a group. DRGs comprise a patient classification system that categorizes patients into groups that are clinically coherent and homogeneous with respect to resource use. DRGs group patients according to diagnosis, type of treatment (procedures), age, and other relevant criteria. Each hospital stay has one assigned DRG. |
Table 4. Coding criteria for the five hospital service lines analyzed in this research |
Maternal and neonatal service line |
Maternal and neonatal stays are defined using the following CCS principal diagnosis categories:
Maternal
Neonatal
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Mental health service line |
Mental health visits are defined using the following CCS principal diagnosis categories:
Starting in 2007
2003 through 2006
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Injury service line |
Injuries are identified using the principal diagnosis and a scheme recommended by Safe States Alliance, which was previously known as the State and Territorial Injury Prevention Directors Association (STIPDA). The diagnosis codes in the range 800-999 listed below are used to identify injuries.
Included
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Surgical service line |
Surgical stays are identified by a surgical DRG. The DRG grouper first assigns the discharge to a major diagnostic category (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 service line |
Medical stays 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. |
Abbreviations: CCS, Clinical Classifications Software; DRG, diagnosis-related group; NEC, necrotizing enterocolitis; OB, obstetrics |
Types of hospitals included in the HCUP National (Nationwide) Inpatient Sample The National (Nationwide) Inpatient Sample (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 long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals. Beginning in 2012, long-term acute care hospitals are also excluded. 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. Types of hospitals included in the HCUP Nationwide Emergency Department Sample The Nationwide Emergency Department Sample (NEDS) 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 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. Hospitals included in the NEDS have hospital-owned emergency departments and no more than 90 percent of their ED visits resulting in admission. Types of hospitals included in HCUP State Inpatient Databases This analysis used State Inpatient Databases (SID) limited to 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). Community hospitals include obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded for this analysis are long-term care facilities such as rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals. 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 was included in the analysis. Unit of analysis The unit of analysis is the hospital discharge (i.e., the hospital stay) or the ED encounter, not a person or patient. This means that a person who is admitted to the hospital or seen in the ED multiple times in 1 year will be counted each time as a separate discharge from the hospital or encounter in the ED. About HCUP The Healthcare Cost and Utilization Project (HCUP, pronounced "H-Cup") is a family of databases and related software tools and products developed through a Federal-State-Industry partnership and sponsored by the Agency for Healthcare Research and Quality (AHRQ). HCUP databases bring together the data collection efforts of State data organizations, hospital associations, and private data organizations (HCUP Partners) and the Federal government to create a national information resource of encounter-level data. HCUP includes the largest collection of longitudinal hospital care data in the United States, with all-payer, encounter-level information beginning in 1988. These databases enable research on a broad range of health policy issues, including cost and quality of health services, medical practice patterns, access to programs, and outcomes of treatments at the national, State, and local market levels. HCUP would not be possible without the contributions of the following data collection Partners from across the United States: Alaska State Hospital and Nursing Home Association Arizona Department of Health Services Arkansas Department of Health California Office of Statewide Health Planning and Development Colorado Hospital Association Connecticut Hospital Association District of Columbia Hospital Association Florida Agency for Health Care Administration Georgia Hospital Association Hawaii Health Information Corporation Illinois Department of Public Health Indiana Hospital Association Iowa Hospital Association Kansas Hospital Association Kentucky Cabinet for Health and Family Services Louisiana Department of Health and Hospitals Maine Health Data Organization Maryland Health Services Cost Review Commission Massachusetts Center for Health Information and Analysis Michigan Health & Hospital Association Minnesota Hospital Association Mississippi Department of Health Missouri Hospital Industry Data Institute Montana MHA - An Association of Montana Health Care Providers Nebraska Hospital Association Nevada Department of Health and Human Services New Hampshire Department of Health & Human Services New Jersey Department of Health New Mexico Department of Health New York State Department of Health North Carolina Department of Health and Human Services North Dakota (data provided by the Minnesota Hospital Association) Ohio Hospital Association Oklahoma State Department of Health Oregon Association of Hospitals and Health Systems Oregon Office of Health Analytics Pennsylvania Health Care Cost Containment Council Rhode Island Department of Health South Carolina Revenue and Fiscal Affairs Office South Dakota Association of Healthcare Organizations Tennessee Hospital Association Texas Department of State Health Services Utah Department of Health Vermont Association of Hospitals and Health Systems Virginia Health Information Washington State Department of Health West Virginia Health Care Authority Wisconsin Department of Health Services Wyoming Hospital Association About Statistical Briefs HCUP Statistical Briefs are descriptive summary reports presenting statistics on hospital inpatient and ED use and costs, quality of care, access to care, medical conditions, procedures, patient populations, and other topics. The reports use HCUP administrative data. About the NIS The HCUP National (Nationwide) Inpatient Sample (NIS) is a national (nationwide) database of hospital inpatient stays. The NIS is nationally representative of all community hospitals (i.e., short-term, non-Federal, nonrehabilitation hospitals). The NIS includes all payers. It is drawn from a sampling frame that contains hospitals comprising more than 95 percent of all discharges in the United States. The vast size of the NIS allows the study of topics at the national and regional levels for specific subgroups of patients. In addition, NIS data are standardized across years to facilitate ease of use. Over time, the sampling frame for the NIS has changed; thus, the number of States contributing to the NIS varies from year to year. The NIS is intended for national estimates only; no State-level estimates can be produced. The 2012 NIS was redesigned to optimize national estimates. The redesign incorporates two critical changes:
About the NEDS The HCUP Nationwide Emergency Department Database (NEDS) is a unique and powerful database that yields national estimates of ED visits. The NEDS was constructed using records from both the HCUP State Emergency Department Databases (SEDD) and the State Inpatient Databases (SID). The SEDD capture information on ED visits that do not result in an admission (i.e., 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. The NEDS was created to enable analyses of ED utilization patterns and support public health professionals, administrators, policymakers, and clinicians in their decision making regarding this critical source of care. The NEDS is produced annually beginning in 2006. Over time, the sampling frame for the NEDS has changed; thus, the number of States contributing to the NEDS varies from year to year. The NEDS is intended for national estimates only; no State-level estimates can be produced. About the SID The HCUP State Inpatient Databases (SID) are hospital inpatient databases from data organizations participating in HCUP. The SID contain the universe of the inpatient discharge abstracts in the participating HCUP States, translated into a uniform format to facilitate multistate comparisons and analyses. Together, the SID encompass more than 95 percent of all U.S. community hospital discharges. The SID can be used to investigate questions unique to one State, to compare data from two or more States, to conduct market-area variation analyses, and to identify State-specific trends in inpatient care utilization, access, charges, and outcomes. About the QDR The National Healthcare Quality and Disparities Report (QDR) measures and tracks trends in quality and disparities in seven key areas of : patient safety, person-centered care, care coordination, effective treatment, healthy living, care affordability, and access to . The QDR is an annual report that was commissioned by Congress in 1999 and first published in 2003. Beginning with the 2014 report, findings that previously appeared in two separate reports (the National Healthcare Quality Report and the National Healthcare Disparities Report) have been integrated into a single document that provides a comprehensive overview of the quality of received by the general population and disparities in care experienced by different racial, ethnic, and socioeconomic groups. Information on individual measures will available through chartbooks, which will be posted monthly. The QDR is designed and produced by AHRQ, with support from the Department of Health and Human Services (HHS) and private sector partners. For More Information For more information about HCUP, visit http://www.hcup-us.ahrq.gov/. For additional HCUP statistics, visit HCUPnet, our interactive query system, at https://datatools.ahrq.gov/hcupnet. For information on other hospitalizations in the United States, refer to the following HCUP Statistical Briefs located at http://www.hcup-us.ahrq.gov/reports/statbriefs/statbriefs.jsp:
Agency for Healthcare Research and Quality. Overview of the National (Nationwide) Inpatient Sample (NIS). Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality. Updated November 2014. http://www.hcup-us.ahrq.gov/nisoverview.jsp. Accessed January 7, 2015. Agency for Healthcare Research and Quality. Overview of the Nationwide Emergency Department Sample (NEDS). Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality. Updated December 2014. http://www.hcup-us.ahrq.gov/nedsoverview.jsp. Accessed January 7, 2015. Agency for Healthcare Research and Quality. Overview of the State Inpatient Databases (SID). Healthcare Cost and Utilization Project (HCUP). Rockville, MD: Agency for Healthcare Research and Quality. Updated November 2014. http://www.hcup-us.ahrq.gov/sidoverview.jsp. Accessed January 7, 2015. Suggested Citation Fingar KR (Truven Health Analytics), Barrett ML (M.L. Barrett, Inc.), Elixhauser A (AHRQ), Stocks C (AHRQ), Steiner CA (AHRQ). Trends in Potentially Preventable Inpatient Hospital Admissions and Emergency Department Visits. HCUP Statistical Brief #195. November 2015. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb195-Potentially-Preventable-Hospitalizations.pdf. *** AHRQ welcomes questions and comments from readers of this publication who are interested in obtaining more information about access, cost, use, financing, and quality of in the United States. We also invite you to tell us how you are using this Statistical Brief and other HCUP data and tools, and to share suggestions on how HCUP products might be enhanced to further meet your needs. Please e-mail us at hcup@ahrq.gov or send a letter to the address below:Virginia Mackay-Smith, Acting Director Center for Delivery, Organization, and Markets Agency for Healthcare Research and Quality 540 Gaither Road Rockville, MD 20850 1 U.S. Department of Health & Human Services, Health System Measurement Project. Rate of Hospitalization for Ambulatory Care-Sensitive Conditions per 100,000 People as Defined by the Prevention Quality Indicator Composite for Adults (18+). 2012. Original source is no longer available on the Web; for related information refer to AHRQ's Chartbook on Care Coordination, https://www.ahrq.gov/research/findings/nhqrdr/chartbooks/carecoordination/measure3.html, accessed October 27, 2017. 2 Weiss AJ, Elixhauser A. Overview of Hospital Stays in the United States, 2012. HCUP Statistical Brief #180. October 2014. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb180-Hospitalizations-United-States-2012.pdf. Accessed July 17, 2015. 3 Sussman JB, Halasyamani LK, Davis MM. Hospitals during recession and recovery: vulnerable institutions and quality at risk. Journal of Hospital Medicine. 2010;5(5):302-5. 4 Frontstin P. The Impact of the Recession on Employment-Based Health Coverage. EBRI Issue Brief #342. May 2010. Employee Benefit Research Institute, Washington, DC. 5Minott J. Reducing Hospital Readmissions. 2008. Washington, DC: Academy Health. https://pdfs.semanticscholar.org/06c2/26a64eda220fc2f884ae7ae8cd4fe9788dee.pdf?_ga=1.34645348.430447023.1489614871. Accessed November 8, 2017. 6 Morganti-Gonzalez K, Baufman S, Blanchard J, Abir M, Iyer N, Smith A, et al. The Evolving Role of Emergency Departments in the United States. RAND Corporation Research Report Series RR-280-ACEP. Santa Monica, CA: Rand Corporation; May 2013. 7 Venkatesh AK, Geisler BP, Gibson Chambers JJ, Baugh CW, Bohan JS, et al. Use of Observation Care in US Emergency Departments, 2001 to 2008. PLoS ONE. 2011;6(9):e24326. 8 Skinner H, Blanchard J, Elixhauser A. Trends in Emergency Department Visits, 2006-2011. HCUP Statistical Brief #179. September 2014. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb179-Emergency-Department-Trends.pdf. Accessed July 17, 2015. 9 Barrett M, Lopez-Gonzalez L, Coffey R, Levit K. Population Denominator Data for Use With the HCUP Databases (Updated With 2013 Population Data). HCUP Methods Series Report #2014-02. August 18, 2014. U.S. Agency for Healthcare Research and Quality. http://www.hcup-us.ahrq.gov/reports/methods/2014-02.pdf. Accessed January 7, 2015. 10 Blecker S, Ladapo JA, Doran KM, Goldfeld KS, Katz S. Emergency department visits for heart failure and subsequent hospitalization or observation unit admission. American Heart Journal. 2014 Dec;168(6):901-8.e1 11 Galarraga JE, Mutter R, Pines JM. Costs associated with ambulatory care sensitive conditions across hospital-based settings. Academic Emergency Medicine. 2015 Feb;22(2):172-81 12 Morganti-Gonzalez K, Baufman S, Blanchard J, Abir M, Iyer N, Smith A, et al. The Evolving Role of Emergency Departments in the United States. RAND Corporation Research Report RR-280-ACEP. Santa Monica, CA: Rand Corporation; May 2013. 13 Coffey R, Barrett M, Houchens R, Moy E, Andrews R, Coenen N. Methods Applying AHRQ Quality Indicators to Healthcare Cost and Utilization Project (HCUP) Data for the Eleventh (2013) National Healthcare Quality Report (NHQR) and National Healthcare Disparities Report (NHDR). HCUP Methods Series Report #2012-03. November 12, 2012. U.S. Agency for Healthcare Research and Quality. http://www.hcup-us.ahrq.gov/reports/methods/2012_03.pdf. Accessed January 7, 2015. 14 HCUP Clinical Classifications Software (CCS). Healthcare Cost and Utilization Project (HCUP). U.S. Agency for Healthcare Research and Quality, Rockville, MD. Updated November 2014. http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Accessed January 7, 2015. |
Internet Citation: Statistical Brief #195. Healthcare Cost and Utilization Project (HCUP). May 2016. Agency for Healthcare Research and Quality, Rockville, MD. www.hcup-us.ahrq.gov/reports/statbriefs/sb195-Potentially-Preventable-Hospitalizations.jsp. |
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