Aaron L Leppin1, Michael R Gionfriddo2, Maya Kessler3, Juan Pablo Brito4, Frances S Mair5, Katie Gallacher5, Zhen Wang6, Patricia J Erwin7, Tanya Sylvester8, Kasey Boehmer9, Henry H Ting1, M Hassan Murad6, Nathan D Shippee10, Victor M Montori4. 1. Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota. 2. Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota2Mayo Graduate School, Mayo Clinic, Rochester, Minnesota. 3. Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota3Department of Medicine, Mayo Clinic, Rochester, Minnesota. 4. Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota3Department of Medicine, Mayo Clinic, Rochester, Minnesota4Mayo Clinic Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, Minnesota. 5. General Practice and Primary Care, Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland, United Kingdom. 6. Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota4Mayo Clinic Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, Minnesota. 7. Mayo Clinic Libraries, Mayo Clinic, Rochester, Minnesota. 8. medical student at St Louis University School of Medicine, St Louis, Missouri. 9. Knowledge and Evaluation Research Unit, Mayo Clinic, Rochester, Minnesota8graduate student at University of Minnesota School of Public Health, Minneapolis. 10. Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis.
Abstract
IMPORTANCE: Reducing early (<30 days) hospital readmissions is a policy priority aimed at improving health care quality. The cumulative complexity model conceptualizes patient context. It predicts that highly supportive discharge interventions will enhance patient capacity to enact burdensome self-care and avoid readmissions. OBJECTIVE: To synthesize the evidence of the efficacy of interventions to reduce early hospital readmissions and identify intervention features--including their impact on treatment burden and on patients' capacity to enact postdischarge self-care--that might explain their varying effects. DATA SOURCES: We searched PubMed, Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL, and Scopus (1990 until April 1, 2013), contacted experts, and reviewed bibliographies. STUDY SELECTION: Randomized trials that assessed the effect of interventions on all-cause or unplanned readmissions within 30 days of discharge in adult patients hospitalized for a medical or surgical cause for more than 24 hours and discharged to home. DATA EXTRACTION AND SYNTHESIS: Reviewer pairs extracted trial characteristics and used an activity-based coding strategy to characterize the interventions; fidelity was confirmed with authors. Blinded to trial outcomes, reviewers noted the extent to which interventions placed additional work on patients after discharge or supported their capacity for self-care in accordance with the cumulative complexity model. MAIN OUTCOMES AND MEASURES: Relative risk of all-cause or unplanned readmission with or without out-of-hospital deaths at 30 days postdischarge. RESULTS: In 42 trials, the tested interventions prevented early readmissions (pooled random-effects relative risk, 0.82 [95% CI, 0.73-0.91]; P < .001; I² = 31%), a finding that was consistent across patient subgroups. Trials published before 2002 reported interventions that were 1.6 times more effective than those tested later (interaction P = .01). In exploratory subgroup analyses, interventions with many components (interaction P = .001), involving more individuals in care delivery (interaction P = .05), and supporting patient capacity for self-care (interaction P = .04) were 1.4, 1.3, and 1.3 times more effective than other interventions, respectively. A post hoc regression model showed incremental value in providing comprehensive, postdischarge support to patients and caregivers. CONCLUSIONS AND RELEVANCE: Tested interventions are effective at reducing readmissions, but more effective interventions are complex and support patient capacity for self-care. Interventions tested more recently are less effective.
IMPORTANCE: Reducing early (<30 days) hospital readmissions is a policy priority aimed at improving health care quality. The cumulative complexity model conceptualizes patient context. It predicts that highly supportive discharge interventions will enhance patient capacity to enact burdensome self-care and avoid readmissions. OBJECTIVE: To synthesize the evidence of the efficacy of interventions to reduce early hospital readmissions and identify intervention features--including their impact on treatment burden and on patients' capacity to enact postdischarge self-care--that might explain their varying effects. DATA SOURCES: We searched PubMed, Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL, and Scopus (1990 until April 1, 2013), contacted experts, and reviewed bibliographies. STUDY SELECTION: Randomized trials that assessed the effect of interventions on all-cause or unplanned readmissions within 30 days of discharge in adult patients hospitalized for a medical or surgical cause for more than 24 hours and discharged to home. DATA EXTRACTION AND SYNTHESIS: Reviewer pairs extracted trial characteristics and used an activity-based coding strategy to characterize the interventions; fidelity was confirmed with authors. Blinded to trial outcomes, reviewers noted the extent to which interventions placed additional work on patients after discharge or supported their capacity for self-care in accordance with the cumulative complexity model. MAIN OUTCOMES AND MEASURES: Relative risk of all-cause or unplanned readmission with or without out-of-hospital deaths at 30 days postdischarge. RESULTS: In 42 trials, the tested interventions prevented early readmissions (pooled random-effects relative risk, 0.82 [95% CI, 0.73-0.91]; P < .001; I² = 31%), a finding that was consistent across patient subgroups. Trials published before 2002 reported interventions that were 1.6 times more effective than those tested later (interaction P = .01). In exploratory subgroup analyses, interventions with many components (interaction P = .001), involving more individuals in care delivery (interaction P = .05), and supporting patient capacity for self-care (interaction P = .04) were 1.4, 1.3, and 1.3 times more effective than other interventions, respectively. A post hoc regression model showed incremental value in providing comprehensive, postdischarge support to patients and caregivers. CONCLUSIONS AND RELEVANCE: Tested interventions are effective at reducing readmissions, but more effective interventions are complex and support patient capacity for self-care. Interventions tested more recently are less effective.
Authors: Christiane E Angermann; Stefan Störk; Götz Gelbrich; Hermann Faller; Roland Jahns; Stefan Frantz; Markus Loeffler; Georg Ertl Journal: Circ Heart Fail Date: 2011-09-28 Impact factor: 8.790
Authors: Bonnie J Wakefield; Marcia M Ward; John E Holman; Annette Ray; Melody Scherubel; Trudy L Burns; Michael G Kienzle; Gary E Rosenthal Journal: Telemed J E Health Date: 2008-10 Impact factor: 3.536
Authors: James F Graumlich; Nancy L Novotny; G Stephen Nace; Himangi Kaushal; Waleed Ibrahim-Ali; Shoba Theivanayagam; L William Scheibel; Jean C Aldag Journal: J Hosp Med Date: 2009-09 Impact factor: 2.960
Authors: Mary Courtney; Helen Edwards; Anne Chang; Anthony Parker; Kathleen Finlayson; Kyra Hamilton Journal: J Am Geriatr Soc Date: 2009-02-23 Impact factor: 5.562
Authors: Mona K Pedersen; Gunnar L Nielsen; Lisbeth Uhrenfeldt; Søren Lundbye-Christensen Journal: J Gen Intern Med Date: 2018-12-03 Impact factor: 5.128
Authors: Addie Middleton; James E Graham; Yu-Li Lin; James S Goodwin; Janet Prvu Bettger; Anne Deutsch; Kenneth J Ottenbacher Journal: J Gen Intern Med Date: 2016-07-20 Impact factor: 5.128
Authors: Monica M Vasquez; Leslie A McClure; Duane L Sherrill; Sanjay R Patel; Jerry Krishnan; Stefano Guerra; Sairam Parthasarathy Journal: Am J Med Date: 2017-01-13 Impact factor: 4.965
Authors: Caitlin W Hicks; Jeffrey J Tosoian; Rebecca Craig-Schapiro; Vicente Valero; John L Cameron; Frederic E Eckhauser; Kenzo Hirose; Martin A Makary; Timothy M Pawlik; Nita Ahuja; Matthew J Weiss; Christopher L Wolfgang Journal: Am J Surg Date: 2015-06-29 Impact factor: 2.565
Authors: Jacques D Donzé; Mark V Williams; Edmondo J Robinson; Eyal Zimlichman; Drahomir Aujesky; Eduard E Vasilevskis; Sunil Kripalani; Joshua P Metlay; Tamara Wallington; Grant S Fletcher; Andrew D Auerbach; Jeffrey L Schnipper Journal: JAMA Intern Med Date: 2016-04 Impact factor: 21.873
Authors: Robert E Burke; Jeffrey L Schnipper; Mark V Williams; Edmondo J Robinson; Eduard E Vasilevskis; Sunil Kripalani; Joshua P Metlay; Grant S Fletcher; Andrew D Auerbach; Jacques D Donzé Journal: Med Care Date: 2017-03 Impact factor: 2.983
Authors: David G Brauer; Sarah A Lyons; Matthew R Keller; Matthew G Mutch; Graham A Colditz; Sean C Glasgow Journal: Surgery Date: 2019-01-29 Impact factor: 3.982