Readmissions are common, costly and often detrimental to patients, yet the relationship of patient, hospital and community factors to hospita readmission rates is unclear. As interest in reducing hospital readmissions rises, it is crucial to understand the type and extent of hospital and community influence on readmission rates so that the best targets for interventions can be identified. Nationally, there is intense focus on reducing readmission rates and in increasing coordination of care, spearheaded by major Federal policy initiatives such as Hospital Engagement Networks, the Community Care Transitions Program, and the Hospital Readmission Reduction Program. Individual hospitals are also engaged in local efforts that maximize area strengths to reduce readmissions. The investigative team has previously developed a new all-condition 30-day risk-standardized hospital-wide unplanned readmission measure. The measure has been endorsed by the National Quality Forum and will be publicly reported by Medicare in 2013. This measure can be used as a validated, risk-standardized assay to compare hospital readmission rates while accounting for differences in diagnoses and case mix among hospitals. Furthermore, the measure is a composite of five specialty-specific sub-measures, allowing us to stratify results by specialty. We will use this assay to examine the influence of hospitals and communities on readmission rates and to study the impact of major policy changes. Specifically, using national Medicare administrative claims data, along with several complementary data sources, our objectives are to: 1) identify characteristics of hospitals and communities associated with readmission rates;2) determine which hospital and community factors are relevant for each of five clinical specialty cohorts (cardiovascular disease, cardiorespiratory disease, neurological disease, other medical disease, and surgical conditions);and 3) characterize trends in readmission rates between 2007 and 2016, determine the association of improvements with policy changes, and conduct in-depth qualitative analysis of hospitals with greatest and least change over time. This proposal is relevant to several AHRQ priority populations, including low income groups, minority groups, women, older patients, and individuals with special health care needs, and will provide information that advances our understanding of hospital readmissions, enabling clinicians, hospitals, and policymakers to improve healthcare delivery for all patients.
Readmissions are common, costly and often detrimental to patients, and there is now intense national and local focus on reducing readmission rates and in increasing coordination of care. The proposed work will advance our understanding of hospital readmissions through the study of characteristics of patients, hospitals and communities associated with readmissions, determining whether associations differ by clinical conditions, and examining the impact of federal and local efforts to reduce readmissions, using quantitative and qualitative analysis. The results of this work will enable clinicians, hospitals, and policymakers o improve healthcare delivery for all patients.
|Ross, Joseph S; Waldstreicher, Joanne; Bamford, Stephen et al. (2018) Overview and experience of the YODA Project with clinical trial data sharing after 5 years. Sci Data 5:180268|
|Horwitz, Leora I; Wang, Yongfei; Altaf, Faseeha K et al. (2018) Hospital Characteristics Associated With Postdischarge Hospital Readmission, Observation, and Emergency Department Utilization. Med Care 56:281-289|
|Angraal, Suveen; Khera, Rohan; Zhou, Shengfan et al. (2018) Trends in 30-Day Readmission Rates for Medicare and Non-Medicare Patients in the Era of the Affordable Care Act. Am J Med 131:1324-1331.e14|
|Blecker, Saul; Herrin, Jeph; Kwon, Ji Young et al. (2018) Effect of Hospital Readmission Reduction on Patients at Low, Medium, and High Risk of Readmission in the Medicare Population. J Hosp Med 13:537-543|
|Blecker, Saul; Kwon, Ji Young; Herrin, Jeph et al. (2018) Seasonal Variation in Readmission Risk for Patients Hospitalized with Cardiopulmonary Conditions. J Gen Intern Med 33:599-601|
|Ross, Joseph S; Krumholz, Harlan M (2018) Bringing Vioxx back to market. BMJ 360:k242|
|Krumholz, Harlan M; Wang, Kun; Lin, Zhenqiu et al. (2017) Hospital-Readmission Risk - Isolating Hospital Effects from Patient Effects. N Engl J Med 377:1055-1064|
|Elysee, Gerald; Herrin, Jeph; Horwitz, Leora I (2017) An observational study of the relationship between meaningful use-based electronic health information exchange, interoperability, and medication reconciliation capabilities. Medicine (Baltimore) 96:e8274|
|Salerno, Amy M; Horwitz, Leora I; Kwon, Ji Young et al. (2017) Trends in readmission rates for safety net hospitals and non-safety net hospitals in the era of the US Hospital Readmission Reduction Program: a retrospective time series analysis using Medicare administrative claims data from 2008 to 2015. BMJ Open 7:e016149|
|Dharmarajan, Kumar; Wang, Yongfei; Lin, Zhenqiu et al. (2017) Association of Changing Hospital Readmission Rates With Mortality Rates After Hospital Discharge. JAMA 318:270-278|
Showing the most recent 10 out of 14 publications