ORIGINAL ARTICLE Validation of the Potentially Avoidable Hospital Readmission Rate as a Routine Indicator of the Quality of Hospital Care Patricia Halfon, MD, MPH,* Yves Eggli, MD, PhD,† Isaline Pre ˆtre-Rohrbach, MD,* Danielle Meylan, MSc,* Alfio Marazzi, PhD,* and Bernard Burnand, MD, MPH* Background: The hospital readmission rate has been proposed as an important outcome indicator computable from routine statistics. However, most commonly used measures raise conceptual issues. Objectives: We sought to evaluate the usefulness of the computer- ized algorithm for identifying avoidable readmissions on the basis of minimum bias, criterion validity, and measurement precision. Research Design and Subjects: A total of 131,809 hospitalizations of patients discharged alive from 49 hospitals were used to compare the predictive performance of risk adjustment methods. A subset of a random sample of 570 medical records of discharge/readmission pairs in 12 hospitals were reviewed to estimate the predictive value of the screening of potentially avoidable readmissions. Measures: Potentially avoidable readmissions, defined as readmis- sions related to a condition of the previous hospitalization and not expected as part of a program of care and occurring within 30 days after the previous discharge, were identified by a computerized algorithm. Unavoidable readmissions were considered as censored events. Results: A total of 5.2% of hospitalizations were followed by a potentially avoidable readmission, 17% of them in a different hospital. The predictive value of the screen was 78%; 27% of screened readmissions were judged clearly avoidable. The correla- tion between the hospital rate of clearly avoidable readmission and all readmissions rate, potentially avoidable readmissions rate or the ratio of observed to expected readmissions were respectively 0.42, 0.56 and 0.66. Adjustment models using clinical information per- formed better. Conclusion: Adjusted rates of potentially avoidable readmissions are scientifically sound enough to warrant their inclusion in hospital quality surveillance. Key Words: patient readmission, health care quality indicator, risk adjustment, medical errors (Med Care 2006;44: 972–981) T he hospital readmission rate has been proposed as an important outcome indicator computable from routine statistics. 1 The cost of readmissions is high. 2 Financial pres- sure to discharge patients quickly might increase readmis- sions. 3 The improvement of hospital care, particularly inten- sive discharge planning of high-risk patients, reduces them. 4 However, inconsistent definitions, improper adjustment for case mix, and rarity of studies linking data across different hospital networks have severely compromised its utility. The definition of readmission rates has varied markedly across studies. Nonresidents, healthy newborns, 1-day care, deaths, or transfers should not be in the eligible population. 5,6 Overall, we lack a consistent definition of the event of interest. 7 Most studies use unplanned readmissions within 1 month as a proxy of potentially avoidable readmissions, but this approach is flawed. 8 Many unplanned readmissions are unavoidable: readmissions for a new condition unrelated to any diagnoses of the previous stay, readmissions for delivery or transplantation, which although not precisely planned are foreseen. On the contrary, avoidable readmissions caused by complications discovered after discharge like a surgical site infection, appear often planned. Our study, conducted at 1 university hospital, set up an algorithm using routinely col- lected data to screen for only potentially avoidable readmis- sions, ie, those unforeseen at the previous discharge and related to a condition previously treated occurring within 30 days. 9 The review of several hundred medical records showed that the screening algorithm adequately classified readmission status (true and false positive fractions were 96% and 4%). Numerous studies have shown the impact of patient- related factors, such as case mix (medical, surgical or obstet- rical condition), 6,9 severity, 10,11 comorbidities and chronic conditions, 12,13 functional disability, 13 and length of stay, 14 on the risk of readmission. However, adjustment of readmis- sion rates for patient-related risk has been often rough, at best accounting for gender and age. 15,16 The use of inadequately adjusted rates may lead to inappropriate conclusions regard- ing hospitals. Beside the quality of inpatient care, other factors also influence readmission rates, such as variation of hospitaliza- tion propensity for similar conditions. 17 A substantial propor- tion of patients are readmitted to a different hospital than for the first stay, especially if they were dissatisfied with care. 18 From the *Institut Universitaire de Me ´decine Sociale et Pre ´ventive and †Institut d’E ´ conomie et de Management de la Sante ´, University of Lausanne, Lausanne, Switzerland. Reprints: Patricia Halfon, MD, MPH, 17 rue du Bugnon, 1005 Lausanne, Switzerland. E-mail: Patricia.Halfon@chuv.ch. Copyright © 2006 by Lippincott Williams & Wilkins ISSN: 0025-7079/06/4411-0972 Medical Care • Volume 44, Number 11, November 2006 972