Zhen Wang - Academia.edu (original) (raw)

Papers by Zhen Wang

Research paper thumbnail of Preventing 30-Day Hospital Readmissions

JAMA Internal Medicine, 2014

Reducing early (&... more 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. 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. We searched PubMed, Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL, and Scopus (1990 until April 1, 2013), contacted experts, and reviewed bibliographies. 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. 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. Relative risk of all-cause or unplanned readmission with or without out-of-hospital deaths at 30 days postdischarge. 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. 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.

Research paper thumbnail of Patient and service user engagement in research: a systematic review and synthesized framework

Health Expectations, 2013

Background There is growing attention towards increasing patient and service user engagement (PSU... more Background There is growing attention towards increasing patient and service user engagement (PSUE) in biomedical and health services research. Existing variations in language and design inhibit reporting and indexing, which are crucial to comparative effectiveness in determining best practices.

Research paper thumbnail of Preventing 30-Day Hospital Readmissions

JAMA Internal Medicine, 2014

Reducing early (&... more 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. 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. We searched PubMed, Ovid MEDLINE, Ovid EMBASE, EBSCO CINAHL, and Scopus (1990 until April 1, 2013), contacted experts, and reviewed bibliographies. 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. 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. Relative risk of all-cause or unplanned readmission with or without out-of-hospital deaths at 30 days postdischarge. 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. 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.

Research paper thumbnail of Patient and service user engagement in research: a systematic review and synthesized framework

Health Expectations, 2013

Background There is growing attention towards increasing patient and service user engagement (PSU... more Background There is growing attention towards increasing patient and service user engagement (PSUE) in biomedical and health services research. Existing variations in language and design inhibit reporting and indexing, which are crucial to comparative effectiveness in determining best practices.