Sunil Kripalani1, Guanhua Chen2, Philip Ciampa3, Cecelia Theobald4, Aize Cao5, Megan McBride6, Robert S Dittus7, Theodore Speroff8. 1. Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Center for Clinical Quality and Implementation Research, Vanderbilt University Medical Center, USA; Center for Health Services Research, Vanderbilt University Medical Center, USA. Electronic address: sunil.kripalani@vanderbilt.edu. 2. Department of Biostatistics & Medical Informatics, University of Wisconsin - Madison, Madison, WI, USA. 3. Atrius Health, Center for Healthcare Innovation, Newton, MA, USA. 4. Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Center for Clinical Quality and Implementation Research, Vanderbilt University Medical Center, USA. 5. Department of Biomedical Informatics, Vanderbilt University Medical Center, USA. 6. Office of Population Health, Vanderbilt University Medical Center, USA. 7. Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Center for Clinical Quality and Implementation Research, Vanderbilt University Medical Center, USA; Center for Health Services Research, Vanderbilt University Medical Center, USA; Department of Veterans Affairs, Valley Healthcare System Geriatric Research Education and Clinical Center (GRECC), TN, USA. 8. Division of General Internal Medicine and Public Health, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Center for Clinical Quality and Implementation Research, Vanderbilt University Medical Center, USA; Center for Health Services Research, Vanderbilt University Medical Center, USA; Department of Biostatistics & Medical Informatics, University of Wisconsin - Madison, Madison, WI, USA; Department of Veterans Affairs, Valley Healthcare System Geriatric Research Education and Clinical Center (GRECC), TN, USA.
Abstract
BACKGROUND: The optimal structure and intensity of interventions to reduce hospital readmission remains uncertain, due in part to lack of head-to-head comparison. To address this gap, we evaluated two forms of an evidence-based, multi-component transitional care intervention. METHODS: A quasi-experimental evaluation design compared outcomes of Transition Care Coordinator (TCC) Care to Usual Care, while controlling for sociodemographic characteristics, comorbidities, readmission risk, and administrative factors. The study was conducted between January 1, 2013 and April 30, 2015 as a quality improvement initiative. Eligible adults (N = 7038) hospitalized with pneumonia, congestive heart failure, or chronic obstructive pulmonary disease were identified for program evaluation via an electronic health record algorithm. Nurse TCCs provided either a full intervention (delivered in-hospital and by post-discharge phone call) or a partial intervention (phone call only). RESULTS: A total of 762 hospitalizations with TCC Care (460 full intervention and 302 partial intervention) and 6276 with Usual Care was examined. In multivariable models, hospitalizations with TCC Care had significantly lower odds of readmission at 30 days (OR = 0.512, 95% CI 0.392 to 0.668) and 90 days (OR = 0.591, 95% CI 0.483 to 0.723). Adjusted costs were significantly lower at 30 days (difference = $3969, 95% CI $5099 to $2691) and 90 days (difference = $5684, 95% CI $7602 to $3627). The effect was similar whether patients received the full or partial intervention. CONCLUSION: An evidence-based multi-component intervention delivered by nurse TCCs reduced 30- and 90-day readmissions and associated health care costs. Lower intensity interventions delivered by telephone after discharge may have similar effectiveness to in-hospital programs.
BACKGROUND: The optimal structure and intensity of interventions to reduce hospital readmission remains uncertain, due in part to lack of head-to-head comparison. To address this gap, we evaluated two forms of an evidence-based, multi-component transitional care intervention. METHODS: A quasi-experimental evaluation design compared outcomes of Transition Care Coordinator (TCC) Care to Usual Care, while controlling for sociodemographic characteristics, comorbidities, readmission risk, and administrative factors. The study was conducted between January 1, 2013 and April 30, 2015 as a quality improvement initiative. Eligible adults (N = 7038) hospitalized with pneumonia, congestive heart failure, or chronic obstructive pulmonary disease were identified for program evaluation via an electronic health record algorithm. Nurse TCCs provided either a full intervention (delivered in-hospital and by post-discharge phone call) or a partial intervention (phone call only). RESULTS: A total of 762 hospitalizations with TCC Care (460 full intervention and 302 partial intervention) and 6276 with Usual Care was examined. In multivariable models, hospitalizations with TCC Care had significantly lower odds of readmission at 30 days (OR = 0.512, 95% CI 0.392 to 0.668) and 90 days (OR = 0.591, 95% CI 0.483 to 0.723). Adjusted costs were significantly lower at 30 days (difference = $3969, 95% CI $5099 to $2691) and 90 days (difference = $5684, 95% CI $7602 to $3627). The effect was similar whether patients received the full or partial intervention. CONCLUSION: An evidence-based multi-component intervention delivered by nurse TCCs reduced 30- and 90-day readmissions and associated health care costs. Lower intensity interventions delivered by telephone after discharge may have similar effectiveness to in-hospital programs.
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