Development and validation of the Tool for Pharmacists to Predict 30-day hospital readmission in patients with Heart Failure (ToPP-HF). (28th May 2021)

• Record Type: Journal Article
• Authors: Riester, Melissa R; McAuliffe, Laura; Collins, Christine; Zullo, Andrew R
• Is Part Of: American journal of health-system pharmacy. Volume 78:Number 18(2021)
• Page Start: 1691
• Page End: 1700
• Publication Date: 2021-05-28
• Subjects: forecasting -- heart failure -- machine learning -- patient readmission -- pharmacists; Hospital pharmacies -- United States -- Periodicals; 615.1
• DOI: 10.1093/ajhp/zxab223
• Languages: English
• ISSNs: 1079-2082

Abstract

Abstract: Purpose: Pharmacists are well positioned to provide transitions of care (TOC) services to patients with heart failure (HF); however, hospitalizations for patients with HF likely exceed the capacity of a TOC pharmacist. We developed and validated a tool to help pharmacists efficiently identify high-risk patients with HF and maximize their potential impact by intervening on patients at the highest risk for 30-day all-cause readmission. Methods: We conducted a retrospective cohort study including adults with HF admitted to a health system between October 1, 2016, and October 31, 2019. We randomly divided the cohort into development ( n = 2, 114) and validation ( n = 1, 089) subcohorts. Nine models were applied to select the most important predictors of 30-day readmission. The final tool, called the Tool for Pharmacists to Predict 30-day hospital readmission in patients with Heart Failure (ToPP-HF) relied upon multivariable logistic regression. We assessed discriminative ability using the C statistic and calibration using the Hosmer-Lemeshow goodness-of-fit test. Results: The risk of 30-day all-cause readmission was 15.7% ( n = 331) and 18.8% ( n = 205) in the development and validation subcohorts, respectively. The ToPP-HF tool included 13 variables: number of hospital admissions in previous 6 months; admission diagnosis of HF; number of scheduled medications; chronic obstructive pulmonary disease diagnosis; number of comorbidities; estimated glomerular filtration rate; hospital length of stay; left ventricular ejection fraction; critical care requirement; renin-angiotensin-aldosterone system inhibitor use; antiarrhythmic use; hypokalemia; and serum sodium. Discriminatory performance (C statistic of 0.69; 95% confidence interval [CI], 0.65-0.73) and calibration (Hosmer-Lemeshow P = 0.28) were good. Conclusions: The ToPP-HF performs well and can help pharmacists identify high-risk patients with HF most likely to benefit from TOC services.