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Quasi-Experimental Evaluation of the Effectiveness of a Large-Scale Readmission Reduction Program
Grace Y Jenq1, Margaret M Doyle2, Beverly M Belton3
1Section of Geriatrics, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
Importance:
Feasibility, effectiveness, and sustainability of large-scale readmission reduction efforts are uncertain. The Greater New Haven Coalition for Safe Transitions and Readmission Reductions was funded by the Center for Medicare & Medicaid Services (CMS) to reduce readmissions among all discharged Medicare fee-for-service (FFS) patients.
Objective:
To evaluate whether overall Medicare FFS readmissions were reduced through an intervention applied to high-risk discharge patients.
Design, Setting, And Participants:
This quasi-experimental evaluation took place at an urban academic medical center. Target discharge patients were older than 64 years with Medicare FFS insurance, residing in nearby zip codes, and discharged alive to home or facility and not against medical advice or to hospice; control discharge patients were older than 54 years with the same zip codes and discharge disposition but without Medicare FFS insurance if older than 64 years. High-risk target discharge patients were selectively enrolled in the program.
Interventions:
Personalized transitional care, including education, medication reconciliation, follow-up telephone calls, and linkage to community resources.
Measurements:
We measured the 30-day unplanned same-hospital readmission rates in the baseline period (May 1, 2011, through April 30, 2012) and intervention period (October 1, 2012, through May 31, 2014).
Results:
We enrolled 10 621 (58.3%) of 18 223 target discharge patients (73.9% of discharge patients screened as high risk) and included all target discharge patients in the analysis. The mean (SD) age of the target discharge patients was 79.7 (8.8) years. The adjusted readmission rate decreased from 21.5% to 19.5% in the target population and from 21.1% to 21.0% in the control population, a relative reduction of 9.3%. The number needed to treat to avoid 1 readmission was 50. In a difference-in-differences analysis using a logistic regression model, the odds of readmission in the target population decreased significantly more than that of the control population in the intervention period (odds ratio, 0.90; 95% CI, 0.83-0.99; P = .03). In a comparative interrupted time series analysis of the difference in monthly adjusted admission rates, the target population decreased an absolute -3.09 (95% CI, -6.47 to 0.29; P = .07) relative to the control population, a similar but nonsignificant effect.
Conclusions And Relevance:
This large-scale readmission reduction program reduced readmissions by 9.3% among the full population targeted by the CMS despite being delivered only to high-risk patients. However, it did not achieve the goal reduction set by the CMS.
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