Dataset Information

Bundle in the Bronx: Impact of a Transition-of-Care Outpatient Parenteral Antibiotic Therapy Bundle on All-Cause 30-Day Hospital Readmissions.

ABSTRACT: A streamlined transition from inpatient to outpatient care can decrease 30-day readmissions. Outpatient parenteral antibiotic therapy (OPAT) programs have not reduced readmissions; an OPAT bundle has been suggested to improve outcomes. We implemented a transition-of-care (TOC) OPAT bundle and assessed the effects on all-cause, 30-day hospital readmission.Retrospectively, patients receiving postdischarge intravenous antibiotics were evaluated before and after implementation of a TOC-OPAT program in Bronx, New York, between July, 2015 and February, 2016. Pearson's ?2 test was used to compare 30-day readmissions between groups, and logistic regression was used to adjust for covariates. Time from discharge to readmission was analyzed to assess readmission risk, using log-rank test to compare survival curves and Cox proportional hazards model to adjust for covariates. Secondary outcomes, 30-day emergency department (ED) visits, and mortality were analyzed similarly.Compared with previous standard care (n = 184), the TOC-OPAT group (n = 146) had significantly lower 30-day readmissions before (13.0% vs 26.1%, P < .01) and after adjustment for covariates (odds ratio [OR] = 0.51; 95% confidence interval [CI], 0.27-0.94; P = .03). In time-dependent analyses, TOC-OPAT patients were at significantly lower risk for readmission (log-rank test, P < .01; hazard ratio = 0.56; 95% CI, 0.32-0.97; P = .04). Propensity-matched sensitivity analysis showed lower readmissions in the TOC-OPAT group (13.6% vs 24.6%, P = .04), which was attenuated after adjustment (OR = 0.51; 95% CI, 0.25-1.05; P = .07). Mortality and ED visits were similar in both groups.Our TOC-OPAT patients had reduced 30-day readmissions compared with the previous standard of care. An effective TOC-OPAT bundle can successfully improve patient outcomes in an economically disadvantaged area.

SUBMITTER: Madaline T

PROVIDER: S-EPMC5570156 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Bundle in the Bronx: Impact of a Transition-of-Care Outpatient Parenteral Antibiotic Therapy Bundle on All-Cause 30-Day Hospital Readmissions.

Madaline Theresa T Nori Priya P Mowrey Wenzhu W Zukowski Elisabeth E Gohil Shruti S Sarwar Uzma U Weston Gregory G Urrely Riganni R Palombelli Matthew M Pierino Vinnie Frank VF Parsons Vanessa V Ehrlich Amy A Ostrowsky Belinda B Corpuz Marilou M Pirofski Liise-Anne LA

Open forum infectious diseases 20170629 2

<h4>Background</h4>A streamlined transition from inpatient to outpatient care can decrease 30-day readmissions. Outpatient parenteral antibiotic therapy (OPAT) programs have not reduced readmissions; an OPAT bundle has been suggested to improve outcomes. We implemented a transition-of-care (TOC) OPAT bundle and assessed the effects on all-cause, 30-day hospital readmission.<h4>Methods</h4>Retrospectively, patients receiving postdischarge intravenous antibiotics were evaluated before and after im ...[more]

PMID: 28852672

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Project description:BackgroundAs an effort to reduce hospital readmissions, early follow-up visits were recommended by the Society of Hospital Medicine. However, published literature on the effect of follow-up visits is limited with mixed conclusions. Our goal here is to fully explore the relationship between follow-up visits and the all-cause non-elective 30-day readmission rate (RR) after adjusting for confounders.Methods and resultsTo conduct this retrospective observational study, we extracted data for 55,378 adult inpatients from Advocate Health Care, a large, multi-hospital system serving a diverse population in a major metropolitan area. These patients were discharged to Home or Home with Home Health services between June 1, 2013 and April 30, 2015. Our findings from time-dependent Cox proportional hazard models showed that follow-up visits were significantly associated with a reduced RR (adjusted hazard ratio: 0.86; 95% CI: 0.82-0.91), but in a complicated way because the interaction between follow-up visits and a readmission risk score was significant with p-value < 0.001. Our analysis using logistic models on an adjusted data set confirmed the above findings with the following additional results. First, time matter. Follow-up visits within 2 days were associated with the greatest reduction in RR (adjusted odds ratio: 0.72; 95% CI: 0.63-0.83). Visits beyond 2 days were also associated with a reduction in RR, but the strength of the effect decreased as the time between discharge and follow-up visit increased. Second, the strength of such association varied for patients with different readmission risk scores. Patients with a risk score of 0.113, high but not extremely high risk, had the greatest reduction in RR from follow-up visits. Patients with an extremely high risk score (> 0.334) saw no RR reduction from follow-up visits. Third, a patient was much more likely to have a 2-day follow-up visit if that visit was scheduled before the patient was discharged from the hospital (30% versus < 5%).ConclusionsFollow-up visits are associated with a reduction in readmission risk. The timing of follow-up visits can be important: beyond two days, the earlier, the better. The effect of follow-up visits is more significant for patients with a high but not extremely high risk of readmission.

Project description:BACKGROUND:Readmissions after hospitalization for pneumonia are common, but the few risk-prediction models have poor to modest predictive ability. Data routinely collected in the electronic health record (EHR) may improve prediction. OBJECTIVE:To develop pneumonia-specific readmission risk-prediction models using EHR data from the first day and from the entire hospital stay ("full stay"). DESIGN:Observational cohort study using stepwise-backward selection and cross-validation. SUBJECTS:Consecutive pneumonia hospitalizations from 6 diverse hospitals in north Texas from 2009-2010. MEASURES:All-cause nonelective 30-day readmissions, ascertained from 75 regional hospitals. RESULTS:Of 1463 patients, 13.6% were readmitted. The first-day pneumonia-specific model included sociodemographic factors, prior hospitalizations, thrombocytosis, and a modified pneumonia severity index; the full-stay model included disposition status, vital sign instabilities on discharge, and an updated pneumonia severity index calculated using values from the day of discharge as additional predictors. The full-stay pneumonia-specific model outperformed the first-day model (C statistic 0.731 vs 0.695; P = 0.02; net reclassification index = 0.08). Compared to a validated multi-condition readmission model, the Centers for Medicare and Medicaid Services pneumonia model, and 2 commonly used pneumonia severity of illness scores, the full-stay pneumonia-specific model had better discrimination (C statistic range 0.604-0.681; P < 0.01 for all comparisons), predicted a broader range of risk, and better reclassified individuals by their true risk (net reclassification index range, 0.09-0.18). CONCLUSIONS:EHR data collected from the entire hospitalization can accurately predict readmission risk among patients hospitalized for pneumonia. This approach outperforms a first-day pneumonia-specific model, the Centers for Medicare and Medicaid Services pneumonia model, and 2 commonly used pneumonia severity of illness scores. Journal of Hospital Medicine 2017;12:209-216.

Dataset Information

Bundle in the Bronx: Impact of a Transition-of-Care Outpatient Parenteral Antibiotic Therapy Bundle on All-Cause 30-Day Hospital Readmissions.

Publications

Bundle in the Bronx: Impact of a Transition-of-Care Outpatient Parenteral Antibiotic Therapy Bundle on All-Cause 30-Day Hospital Readmissions.

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