User Support

April 2013

Anne Elixhauser, Ph.D. and Claudia Steiner, M.D., M.P.H.



Introduction

The problem of readmissions to the hospital is receiving increased attention as a potential way to address problems in quality of care, cost of care, and care transitions.^1,2 Medicare reports 30-day hospital readmissions for acute myocardial infarction, congestive failure, and pneumonia for individual hospitals across the country.³ Interventions are underway to reduce hospital readmissions at the state and national level.^4,5

Prior research reports have focused on readmissions for specific conditions such as congestive heart failure, pneumonia, chronic obstructive pulmonary disease (COPD), and psychoses.^6,7,8 This Statistical Brief provides an overview of 30-day all-payer, all-cause readmissions to U.S. hospitals for a range of conditions in 2010, thereby presenting the most comprehensive national estimates on readmissions by condition.

In this Statistical Brief, readmission was defined as a subsequent hospital admission within 30 days following an original admission (or index stay) that occurred from January through November 2010. All-cause readmissions were examined; thus, readmissions may or may not include conditions that were listed as the principal diagnosis during the index stay. Readmissions were tracked across the same or different hospitals. Some readmissions may be planned or unavoidable-no attempt was made to remove these types of readmissions from the analysis.

Readmission rates using Healthcare Cost and Utilization Project (HCUP) data are presented for the most frequently treated conditions in U.S. hospitals during 2010 and for the conditions with the highest readmission rates. All estimates were taken from HCUPnet, the online query system that provides free access to information from HCUP.⁹ For a subset of conditions, readmission rates are presented by age group and expected payer (insurance status). Patients younger than 1 year were excluded from this analysis. Readmission rates were calculated without risk adjustment.

Appendix A provides detailed information on readmission rates for most conditions treated in U.S. hospitals in 2010. The table provides information on the number of index stays for each condition, the number of all-cause readmissions within 30 days, and the percentage of index stays that were followed by a readmission within 30 days for any cause. Excluded were nonspecific conditions and any conditions with fewer than 5,000 index stays or fewer than 500 readmissions. Conditions are organized by etiology or body system.

Findings

Readmission rates for the most frequently treated conditions
Table 1 lists the 30 most frequently treated conditions in U.S. hospitals, with their 30-day readmission rates. The most frequent conditions and their readmission rates were pneumonia (15.7 percent), mood disorders (14.8 percent), osteoarthritis (4.8 percent), congestive heart failure (24.7 percent), and cardiac dysrhythmias (14.8 percent).

Among these most frequent conditions, the highest readmission rates were seen for congestive heart failure (24.7 percent), schizophrenia (22.3 percent), and acute and unspecified renal failure (21.7 percent). In other words, for these conditions over one in five patients were readmitted to the hospital within 30 days.

The lowest readmission rates were for childbirth-related procedures (trauma to perineum and vulva during childbirth, 0.8 percent; C-section, 1.5 percent), osteoarthritis (4.8 percent), and appendicitis (4.9 percent).

Conditions with the highest readmission rates
Table 2 lists conditions ranked by the highest readmission rates. Because cancer readmissions are often planned, cancer is excluded from this table (although cancer-related conditions are included in the Appendix).

The five conditions with the highest readmission rates were sickle cell anemia (31.9 percent), gangrene (31.6 percent), hepatitis (30.9 percent), diseases of the white blood cells (30.9 percent), and chronic renal failure (27.4 percent). In other words, over one in four patients were readmitted to the hospital within 30 days for these conditions.

Readmission rates by age and insurance status for selected conditions
Figures 1-5 provide details on 30-day all-cause readmission rates for the five conditions from Table 2 that involved more than 300,000 index stays and had overall readmission rates of at least 20 percent.¹⁰

Figure 1 shows that readmission rates for congestive heart failure were relatively uniform across age groups, ranging from 24.2 percent to 26.1 percent. The highest readmission rate was seen for patients with an expected payer of Medicaid (30.1 percent) compared to 25.0 percent for Medicare-covered patients, 19.5 percent for privately insured patients, and 17.1 percent for the uninsured.

Readmission rates for schizophrenia are shown in figure 2. The highest readmission rates were seen for patients aged 18-44 years (22.6 percent) and 45-64 years (23.4 percent). Readmission rates for patients with an expected payer of Medicare (23.7 percent) and Medicaid (24.0 percent) were about 50 percent higher than for other patients (15.1-16.1 percent).

Readmission rates for acute and unspecified renal failure are depicted in figure 3. Readmission rates were similar for all adult age groups (19.0-22.1 percent), but again were substantially higher for patients with an expected payer of Medicare (22.7 percent) or covered by Medicaid (25.0 percent) than for other patients (13.3-17.0 percent).

Figure 4 shows readmission rates for diabetes mellitus with complications. The highest readmission rate was for patients aged 18-44 years (22.6 percent), followed closely by patients aged 65 years and older (20.6 percent) and 45-64 years (19.9 percent). Readmission rates were nearly identical for patients covered by Medicare (23.6 percent) and Medicaid (23.5 percent); these rates were about 70 percent higher than rates for the privately insured and uninsured (13.6-14.1 percent).

Finally, figure 5 depicts readmission rates for patients with an index stay during which their principal diagnosis was complication of device, implant, or graft. The highest readmission rate was for children aged 1-17 years (25.5 percent). Similarly, the readmission rate for Medicaid-covered patients was 25.4 percent; this rate was nearly 20 percent higher than rates for Medicare (21.4 percent) and over 60 percent higher than those for privately insured and uninsured patients (15.6-15.7 percent).

Data Source

The estimates in this Statistical Brief are based on a readmissions analysis file that was created with the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID). These databases include reliable, verified synthetic patient identifiers that can be used to track a person across hospitals within a State. Estimates were taken from HCUPnet, the online query system that provides free access to information from HCUP: https://datatools.ahrq.gov/hcupnet. HCUPnet provides access to health statistics and information on hospital inpatient and emergency department utilization, and it includes analytic tables using the readmissions analysis file. HCUPnet provides additional detailed results and sortable tables that provide instant information on readmissions to the hospital within 30 days of discharge.

For 2010, readmissions data were available from 18 States: Alaska, Arkansas, California, Florida, Georgia, Hawaii, Louisiana, Massachusetts, Mississippi, Missouri, Nebraska, New Mexico, New York, South Carolina, Tennessee, Utah, Virginia, and Washington. These 18 States are geographically dispersed and accounted for 46 percent of the total U.S. resident population and 45 percent of the total U.S. hospitalizations. The readmissions analysis file included 14.0 million unweighted discharges.

The study population in this readmissions analysis file included discharges from community, non-rehabilitation, non-specialty hospitals. Weights for national estimates were developed using poststratification on hospital characteristics (Census region, urban-rural location, teaching capabilities, bed size, and control/ownership) and patient age groups.

Definitions

Diagnoses, ICD-9-CM, and Clinical Classifications Software (CCS)
For the index stay, the diagnoses examined in this Statistical Brief are based on the CCS for the principal diagnosis. The principal diagnosis is that condition established after study to be chiefly responsible for the patient's admission to the hospital.

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 diagnoses into a manageable number of clinically meaningful categories.¹¹ 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.

Readmissions
The 30-day readmission rate is defined as the number of admissions for each condition for which there was at least one subsequent hospital admission within 30 days divided by the total number of admissions from January through November 2010. That is, when patients are discharged from the hospital, they are followed for 30 days in the data. If any readmission to the same or different hospital occurs during this time period, the admission is counted as a readmission. No more than one readmission is counted within the 30-day period, because the outcome measure assessed here is "percentage of admissions who are readmitted." If a patient was transferred to a different hospital on the same day or was transferred within the same hospital, the two events were combined as a single stay and the second event was not counted as a readmission; that is, transfers were not considered a readmission. In the case of admissions for which there was more than one readmission in the 30-day period, the data presented in this Statistical Brief reflect the characteristics and costs of the first readmission.

Every qualifying hospital stay is counted as a separate index (starting point) admission. Thus, a single patient can be counted multiple times during the course of the January through November observation period. In addition, index admissions do not require a prior "clean period" with no hospitalizations; that is, a hospital stay may be a readmission for a prior stay and the index admission for a subsequent readmission. Admissions were disqualified from the analysis as index admissions if they could not be followed for 30 days for one of the following reasons: (1) admissions in which the patient died in the hospital, (2) admissions missing information on length of stay, and (3) admissions discharged in December 2010.

Types of hospitals included in HCUP
HCUP 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). HCUP data include obstetrics and gynecology, otolaryngology, orthopedic, cancer, pediatric, public, and academic medical hospitals. Excluded are long-term care, rehabilitation, psychiatric, and alcoholism and chemical dependency hospitals.

Payer (Insurance Status)
Payer is the expected payer for the hospital stay. To make coding uniform across all HCUP data sources, payer combines detailed categories into more general groups:

• Medicare: includes patients covered by fee-for-service and managed care Medicare
• Medicaid: includes patients covered by fee-for-service and managed care Medicaid. Patients covered by the State Children's Health Insurance Program (SCHIP) may be included here. Because most State data do not identify SCHIP patients specifically, it is not possible to present this information separately.
• Private Insurance: includes Blue Cross, commercial carriers, and private health maintenance organizations (HMOs) and preferred provider organizations (PPOs)
• Other: includes Worker's Compensation, TRICARE/CHAMPUS, CHAMPVA, Title V, and other government programs
• Uninsured: includes an insurance status of "self-pay" and "no charge."

For this Statistical Brief, a hierarchy was used to assign the payer category based on the primary and secondary expected payer:

• If the primary or secondary expected payer indicates Medicare, then the payer category is assigned to Medicare. This categorization includes patients who are dually eligible for Medicare and Medicaid under Medicare.
• If not Medicare and the primary or secondary expected payer indicates Medicaid, then the payer category is Medicaid.
• If not Medicare or Medicaid and the primary or secondary expected payer indicates private insurance, then the payer category is private.
• If not Medicare, Medicaid, or private and the primary expected payer indicates self-pay or no charge, then the payer category is uninsured.
• Stays for other types of payers are not reported in this Statistical Brief because this is a mixed payer group and small numbers.

For this Statistical Brief, categorization of the readmission counts by expected payer was based on the index stay.

About HCUP

HCUP is a family of powerful healthcare databases, software tools, and products for advancing research. Sponsored by the Agency for Healthcare Research and Quality (AHRQ), HCUP includes the largest all-payer encounter-level collection of longitudinal healthcare data (inpatient, ambulatory surgery, and emergency department) in the United States, beginning in 1988. HCUP is a Federal-State-Industry Partnership that brings together the data collection efforts of many organizations—such as State data organizations, hospital associations, private data organizations, and the Federal government—to create a national information resource.

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
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 Health Policy and Research
Pennsylvania Health Care Cost Containment Council
Rhode Island Department of Health
South Carolina Budget & Control Board
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 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 of all U.S. community hospital discharges in 2010. 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 HCUPnet

HCUPnet is an online query system that offers instant access to the largest set of all-payer healthcare databases publicly available. HCUPnet has an easy step-by-step query system, allowing for tables and graphs to be generated on national and regional statistics as well as trends for community hospitals in the United States. HCUPnet generates statistics using data from HCUP's Nationwide Inpatient Sample (NIS), the Kids' Inpatient Database (KID), the Nationwide Emergency Department Sample (NEDS), the State Inpatient Databases (SID), and the State Emergency Department Databases (SEDD).

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. HCUPnet provides ready-to-use tables on readmission rates by condition and procedure (using Clinical Classification Software categories), diagnosis related groups (DRGs), and major diagnostic categories (MDCs).

Suggested Citation

Elixhauser A (AHRQ), Steiner C (AHRQ). Readmissions to U.S. Hospitals by Diagnosis, 2010. HCUP Statistical Brief #153. April 2013. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb153.pdf.

Acknowledgements

The authors would like to acknowledge the contributions of Marguerite Barrett and Minya Sheng for work on programming.

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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 healthcare 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:

Irene Fraser, Ph.D., Director
Center for Delivery, Organization, and Markets
Agency for Healthcare Research and Quality
540 Gaither Road
Rockville, MD 20850



¹ Boutwell A, Jencks S. It's Not Six of One, Half-Dozen of the Other: A Comparative Analysis of Three Rehospitalization Measurement Systems for Massachusetts. 2011 AcademyHealth Annual Research Meeting and National Quality Forum. www.qualityforum.org. Accessed March 21, 2013.
² 3M Health Information Systems. Potentially Preventable Readmissions Classification System, Methodology Overview, Document number GRP-139, May, 2008. http://www.illinois.gov/hfs/SiteCollectionDocuments/3MPotentiallyPreventableReadmissions.pdf. Accessed March 21, 2013.
³ Hospital Compare. Medicare website. https://www.medicare.gov/hospitalcompare/search.html. Accessed November 8, 2017.
⁴ Boutwell AE, Johnson MB, Rutherford P, Watson SR, Vecchioni N, Auerbach BS, Griswold P, Noga P, Wagner C. An early look at a four-state initiative to reduce avoidable hospital readmissions. Health Aff (Millwood). 2011 Jul;30(7):1272-80.
⁵ Partnership for Patients: Better Care, Lower Costs. April, 2011. http://www.healthcare.gov/news/factsheets/2011/04/partnership04122011a.html. Accessed March 21, 2013.
⁶ Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med 2009;360:1418-28.
⁷ Stranges E, Barrett ML, Wier LM, Andrews RM. Readmissions for Heart Attack, 2009. HCUP Statistical Brief #140. August 2012. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb140.pdf. Accessed March 21, 2013.
⁸ Elixhauser A, Au D, Podulka J. Readmissions for Chronic Obstructive Pulmonary Disease, 2008. HCUP Statistical Brief #121. September, 2011. Agency for Healthcare Research and Quality, Rockville, MD. http://www.hcup-us.ahrq.gov/reports/statbriefs/sb121.pdf. Accessed March 21, 2013.
⁹ https://datatools.ahrq.gov/hcupnet
¹⁰ Two additional conditions met these criteria; however, these conditions are the subject of separate HCUP Statistical Briefs. (Chronic obstructive pulmonary disease: http://www.hcup-us.ahrq.gov/reports/statbriefs/sb121.jsp and Septicemia: forthcoming in 2013).
¹¹ HCUP Clinical Classifications Software (CCS). Healthcare Cost and Utilization Project (HCUP). U.S. Agency for Healthcare Research and Quality, Rockville, MD. Updated March 2013. http://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp. Accessed March 21, 2013.