A Tool for Pharmacists to Predict 30-day Hospital Readmission in Patients with Heart Failure (ToPP-HF)

A Tool for Pharmacists to Predict 30-day Hospital Readmission in Patients with Heart Failure (ToPP-HF)
Angelyn Leipold, PharmD, M Health Fairview

Background: Despite a nationwide effort to improve readmission rates in patients with heart failure (HF), over 20% of these patients still experience 30-day rehospitalizations. Pharmacists are equipped to provide transitions of care (TOC) services to patients with HF which can reduce the burden on other healthcare providers while ensuring safer and higher-quality care for patients. These pharmacist-led TOC services can include medication review, drug monitoring, adherence reinforcement, and patient education. However, interventions for these patients exceed the capacity of some TOC pharmacists due to time constraints and limited resources. Identifying and prioritizing HF patients at highest risk for readmission could help pharmacists to target patients most likely to benefit from their services.
Purpose: This study aimed to develop and validate a user-friendly prediction tool to assist pharmacists in efficiently identifying high-risk patients with HF admitted for any reason for 30-day all-cause unplanned hospital readmission to aid in prioritizing TOC services. This tool was specifically designed to be used by inpatient pharmacists to guide TOC interventions prior to hospital discharge

Study Design: The Tool for Pharmacists to Predict 30-day hospital readmission in patients with Heart Failure (ToPP-HF) was based on a retrospective cohort study which analyzed data of HF patients admitted to a health system over a three year period. The study included adults ( > 18 years old) with HF admitted to two hospitals within a health system and randomly divided the population into two subcohorts of development (n=2,114) and validation (n=1,089). One hundred potential predictor variables were collected, and nine variable selection models were used to determine the final model. The final set of variables were inputted into a logistic regression model. Scores were then assigned by a pharmacist to each level of each variable, allowing both positive and negative values (ranging from -30 to 49), and rounding to the nearest integer.

Final Score Distribution

ToPP-HF Score Ranges

Risk of Readmission

> 90th percentile

17 to 49

High-risk 

81st - 90th percentile

12 to 16

Moderate- to High-risk 

51st - 80th percentile

0 to 11

Moderate-risk

< 50th percentile

-30 to -1

Low-risk

The data was assessed using the C statistic and calibration using the Hosmer-Lemeshow goodness-of-fit test and was then analyzed using SAS and Stata software.

Results: To make the tool user-friendly, the final ToPP-HF scoring was comprised of only 13 variables which included number of hospital admissions in previous six 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 (LVEF); critical care requirement; renin-angiotensin-aldosterone system inhibitor use; antiarrhythmic use; hypokalemia; and serum sodium. The 30-day readmission outcome occurred in 16.7% of the overall study population (15.7% in the development subcohort and 18.8% in the validation subcohort). The risk prediction models showed good discrimination performance (C statistic of 0.69 [95% CI 0.65 – 0.73]) and calibration (Hosmer-Lemeshow P=0.28).

Conclusion: This study concluded that the ToPP-HF is a well-designed and easy-to-use tool for pharmacists to predict 30-day all-cause, unplanned, hospital readmission and can help pharmacists to identify high-risk patients with HF who may benefit from pharmacist-led TOC services. One limitation of this study was that the data collected was from only one health system’s electronic medical records (EMR) which could have missed external readmission records or most recent LVEF if a patient received care outside of the two hospitals within the system. In addition, it may be difficult and time-consuming for pharmacists to calculate the ToPP-HF score by hand as it includes 13 variables, so technology resources to automatically calculate the score would be helpful if EMR integration is possible. However, given that one focus of this study was to make the ToPP-HF tool user-friendly, it may be at the expense of accuracy as it was limited to 13 easy to evaluate variables which were not the most clinically significant predictors for readmission and could result in a less accurate prediction of readmission. Future studies may be warranted to assess generalizability of ToPP-HF to other institutions.

Key Point: Pharmacists are well positioned to transition HF patients from the hospital to an outpatient setting by optimizing guideline-directed pharmacotherapy treatments, encouraging medication adherence, and providing patient education. The ToPP-HF can help to identify HF patients most likely to benefit from pharmacist-led interventions through TOC services to prevent hospital readmission, likely leading to improved patient outcomes and decreased costs for the health system. However, further research should be conducted to evaluate whether pharmacist TOC interventions reduce readmissions for those selected by the ToPP-HF as highest risk.

Reference:

  1. Riester MR, McAuliffe L, Collins C, Zullo AR. Development and validation of the Tool for Pharmacists to Predict 30-day hospital readmission in patients with Heart Failure (ToPP-HF). Am J Health Syst Pharm. 2021;78(18):1691-1700. doi:10.1093/ajhp/zxab223