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Learning About 30-Day Readmissions From Patients With Repeated Hospitalizations
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Learning About 30-Day Readmissions From Patients With Repeated Hospitalizations

Jeanne T. Black, PhD, MBA
Most 30-day readmissions are experienced by patients who have multiple hospital stays. Efforts to reduce readmissions must look beyond a single 30-day period.

To examine the population of inpatients with multiple hospitalizations at a large urban medical center in order to understand the types of patients who are at highest risk for 30-day readmission.

Study Design

Descriptive retrospective cohort analysis using hospital administrative data.


Bivariate analysis of clinical and sociodemographic characteristics of 19,049 adult inpatients discharged with a medical MS-DRG between July 1, 2009, and December 2010, and all subsequent inpatient admissions in the 180 days following each index discharge.


Patients with 6 or more stays (very frequent readmissions) represented 0.8% of patients and 17.3% of 30-day readmissions. Those with 3 to 5 stays (frequent readmissions) comprised 9.4% of patients and 54.3% of 30-day readmissions. These patients differed significantly from those who had fewer hospitalizations with respect to age, race/ethnicity, gender, English proficiency, and insurance type.


Most 30-day readmissions are experienced by patients who have multiple, frequent hospital admissions. Efforts to reduce readmissions must look beyond the current focus on a single hospital discharge and transition period.

Am J Manag Care. 2014;20(6):e200-e207
Most 30-day readmissions are experienced by patients who experience frequent hospital stays.

  • Efforts to reduce readmissions must look beyond the current focus on a single hospital discharge and 30-day transition period.

  • Commonly recommended transition care solutions may not be sufficient to prevent many readmissions.

  • Patients with frequent readmissions are more likely to be members of minority groups, to be non–English-speaking, and to have Medicaid insurance, along with complex medical problems complicated by mental illness or substance abuse.

  • Reducing readmissions among the most complex patients is likely to require new forms of care in the community.
The finding that nearly 1 in 5 Medicare beneficiaries treated in a hospital is readmitted within 30 days has captured the attention of policy makers concerned with both the cost and quality of health services. Hospital readmissions gained widespread attention with the Medicare Payment Advisory Commission’s June 2007 Report to Congress, which stated that 13.3% of all Medicare 30-day readmissions were potentially preventable and suggested that $12 billion could have been saved in a single year.1 The focus on readmissions intensified with the publication of Steven Jencks’ landmark 2009 paper in the New England Journal of Medicine,2 in which he and his coauthors estimated that unplanned 30-day rehospitalizations cost Medicare $17.4 billion in 2004. Also beginning in 2009, the Hospital Compare website created by CMS began to publish risk-standardized 30-day readmission rates by hospital for Medicare fee-for-service (FFS) patients discharged with a principal diagnosis of heart failure, acute myocardial infarction, or pneumonia. In October 2012, the Medicare Hospital Readmissions Reduction Program (HRRP) began penalizing hospitals for “excessive” readmission rates for these 3 conditions. The National Quality Forum subsequently endorsed a new 30-day readmission metric, the Hospital-Wide All-Cause Readmission Measure, which identifies and excludes specific conditions and procedures for which a hospitalization would be considered planned or expected.3 This measure, added to the Hospital Compare website in 2013, was developed to be applicable to all adult patients, not just those 65 years and older, so it can be used by payers other than Medicare.

National and regional initiatives launched to reduce readmissions to the Society for Hospital Medicine’s Project BOOST (Better Outcomes for Older adults through Safe Transitions),4 State Action on Avoidable Rehospitalizations (STAAR),5 the HHS “Partnership for Patients,”6 and the care transitions project facilitated by the CMS Quality Improvement Organizations (QIOs) in 14 communities.7 Despite all these efforts, between 2007 and 2011, the national Medicare readmission rate remained unchanged, preliminary data for calendar year 2012 show a slight decrease.8

CMS, when finalizing the 3 readmission measures to be used in the HRRP, noted that the 30-day time frame “is a clinically meaningful period for hospitals, in collaboration with their medical communities, to reduce readmission risk. This time period for assessing readmission is an accepted standard in research and measurement.”9 This focus on a single 30-day period has resulted in analyses that assume a patient discharged from the hospital is at risk for a single rehospitalization. It ignores the fact that 25% of Medicare beneficiaries represent 85% of total expenditures.10 Jencks’ analysis was based not on unique patients but on hospital discharges. This traditional encounter-based approach is not patient-centered. It does not reflect the trajectory experienced by some patients who have repeated rehospitalizations. Hospital clinicians are only too aware that certain patients return to their emergency departments (EDs) and nursing units over and over again, but there is a lack of evidence regarding the extent to which these frequently readmitted patients contribute to 30-day readmission rates, whether they differ from other patients, and how those differences may indicate a need for additional or different approaches to prevent their readmissions.


The objective of this descriptive analysis was to understand the population of inpatients with a pattern of repeated hospitalizations at a large urban medical center in order to gain insight into the types of patients who were at the highest risk of readmission and consumed the most inpatient resources. This activity was undertaken as part of a quality improvement initiative and thus was deemed non-reviewable by the medical center’s Institutional Review Board.


A retrospective cohort of 19,049 adult patients (18 years and older) with an inpatient medical discharge between July 1, 2009, and December 31, 2010, was constructed using the medical center’s administrative data warehouse. Medical discharges were defined as a medical Medicare Severity-Diagnosis–Related Group (MS-DRG). The index hospitalization was restricted to those with medical MSDRGs in order to focus on readmissions associated with chronic medical conditions, not surgical complications. Clinical and sociodemographic data from the index hospitalization, plus all subsequent admissions that occurred within 180 days after the index discharge, were extracted from the data warehouse. Sociodemographic variables included age, race, Hispanic ethnicity, preferred language, primary and secondary payer, and residence zip code. Subsequent admissions could include any nonobstetric MS-DRG; however, solid organ transplant patients were excluded to make the results more generalizable. Transplant patients were identified based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) procedure, complication, and status codes. Multiple admissions for the same patient were linked using the patient’s medical record number. The population of interest was defined as patients who had at least 2 subsequent hospital admissions within the 6-month period following the index discharge (ie, a total of 3 or more stays). This population was divided into 2 subgroups: those with 3 to 5 inpatient stays (frequent readmissions) and those with 6 or more (very frequent readmissions). The subgroup of patients with 1 or 2 hospitalizations was the comparison group. For each subgroup, the additional hospital admissions could occur at any interval within the 6-month period. The principal diagnoses for each stay were categorized using the chronic condition definitions developed by Iezzoni, 11 as modified by the Dartmouth Atlas (the 9 Iezzoni/ Dartmouth Atlas chronic conditions are: congestive heart failure, cancer with poor prognosis, chronic pulmonary disease, coronary artery disease, chronic renal disease, peripheral vascular disease, dementia, diabetes with end organ damage, and severe chronic liver disease).12 HIV/ AIDS and sickle cell anemia were added because these conditions were known to have a high prevalence of returning patients at the medical center. For each hospitalization, 9 secondary diagnoses also were examined for the presence of mental health and substance abuse conditions, which were identified using the ICD-9-CM mapping developed by the Agency for Healthcare Research and Quality’s Hospital Cost and Utilization Project,13 and for codes indicating lack of housing, tobacco-use disorder, and morbid obesity (body mass index ≥40 kg/m2). Patients’ chronic conditions were categorized using 3 approaches: by the principal diagnosis of the index stay, by the principal diagnosis of all hospital stays, and by whether the patient had at least 1 stay with a principal diagnosis associated with the chronic condition. The second and third approaches recognize that the patient’s major chronic condition might not be the principal reason for the index stay captured in our cohort. The third approach allowed patients to be counted more than once. Bivariate differences were tested among the subgroups across selected sociodemographic variables as well as the clinical conditions, using χ² tests for categorical variables and the t test for differences in group means for the continuous variable, age. Differences were considered statistically significant at P <.05. All statistical analyses were conducted using Stata, version 11.2 (StataCorp LP, College Station, Texas).14


Patients with 3 or more hospitalizations made up 10.1% of the total cohort, 26.1% of the hospital stays, and 34.3% of the hospital days used. They also incurred 71.6% of the 30-day readmissions (Table 1). The very frequent readmissions subgroup with 6 or more stays comprised only 0.8% of all patients in the cohort, but they accounted for 17.3% of the 30-day readmissions. The patients with multiple readmissions differed significantly from the comparison patients who had 1 or 2 inpatient stays with respect to multiple sociodemographic characteristics (Table 2). The very frequent readmission subgroup was significantly younger (mean age 53.5 years) compared with the frequent readmissions subgroup (mean age 65.8 years) and the comparison group (mean age 62.4 years). Both frequent readmissions subgroups included a significantly larger proportion of patients whose preferred language was not English. The most common non-English languages were Russian, Farsi (Persian), and Spanish, which each represented approximately 5% of patients with 3 or more hospital stays. Overall, Hispanics did not have more frequent readmissions; although the proportion in the subgroup with very frequent readmissions appears larger, there were only 20 Hispanic patients in this subgroup. African Americans and other black patients comprised 28.3% of the very frequent readmission subgroup and 21.1% of the frequent readmission subgroup versus 17.3% of the comparison group.

Patients with Medicaid coverage alone made up 27.6% of the very frequent readmission group, more than double the proportion among the frequent readmission subgroup (13.4%), while only 10.0% of the comparison patients with 1 or 2 hospital stays had Medicaid coverage. The proportion of dual-eligible patients also was significantly higher in the frequent readmissions subgroups. The geographic distribution of patients with frequent readmissions was generally similar to that of the comparison patients. There was a trend toward a larger proportion of those with 3 to 5 hospitalizations living in the area immediately surrounding the hospital, while a smaller percentage of those in the very frequent readmission subgroup lived in this core service area. A significantly higher proportion of patients in the very frequent readmission subgroup did not live within the hospital’s primary service area, but further away within the county.

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