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Optimal Timing of Physician Visits after Hospital Discharge to Reduce Readmission.


ABSTRACT: OBJECTIVE:To identify the optimal timing of in-person physician visit after hospital discharge to yield the largest reduction in readmission among elderly or chronically ill patients. DATA SOURCES/STUDY SETTING/EXTRACTION METHODS:We extracted insurance billing data on 620,656 admissions for any cause from 2002 to 2009 in Quebec, Canada. STUDY DESIGN:We used flexible survival models to estimate inverse probability weights for the precise timing (days) of in-person physician visit after discharge and weighted competing risk outcome models. PRINCIPAL FINDINGS:Readmission reduction associated with in-person physician visits (compared to none) was seen early after discharge, with 67.8 fewer readmissions per 1,000 discharges if physician visit occurred within 7 days (95 percent CI: 66.7-69.0), and 110.0 fewer readmissions within 21 days (95 percent CI: 108.2-111.7). The period of largest contribution to readmission reduction was seen in the first 10 days, while physician visits occurring later than 21 days after discharge did not further contribute to reducing hospital readmissions. Larger risk reductions were observed among patients in the highest morbidity level and for in-person follow-up with a primary care physician rather than a medical specialist. CONCLUSIONS:When provided promptly, postdischarge in-person physician visit can prevent many readmissions. The benefits appear optimal when such visit occurs within the first 10 days, or at least within the first 21 days of discharge.

SUBMITTER: Riverin BD 

PROVIDER: S-EPMC6232431 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Optimal Timing of Physician Visits after Hospital Discharge to Reduce Readmission.

Riverin Bruno D BD   Strumpf Erin C EC   Naimi Ashley I AI   Li Patricia P  

Health services research 20180515 6


<h4>Objective</h4>To identify the optimal timing of in-person physician visit after hospital discharge to yield the largest reduction in readmission among elderly or chronically ill patients.<h4>Data sources/study setting/extraction methods</h4>We extracted insurance billing data on 620,656 admissions for any cause from 2002 to 2009 in Quebec, Canada.<h4>Study design</h4>We used flexible survival models to estimate inverse probability weights for the precise timing (days) of in-person physician  ...[more]

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