Impact of a Pharmacist-Led Intervention on 30-Day Readmission and Assessment of Factors Predictive of Readmission in African American Men With Heart Failure
| Autor: | Ayman Akil, Pamela M. Moye-Dickerson, Shondria Davis, DeAngelo Mckinley |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Adult
Male medicine.medical_specialty Georgia Health (social science) Pharmacist lcsh:Medicine Pharmacists Patient Readmission Risk Assessment Machine Learning 03 medical and health sciences 0302 clinical medicine Predictive Value of Tests Intervention (counseling) Electronic Health Records Humans Medicine African american men 030212 general & internal medicine Pharmacist intervention Aged Heart Failure African american Academic Medical Centers 030505 public health readmission business.industry Incidence lcsh:R Public Health Environmental and Occupational Health Middle Aged pharmacist intervention Prognosis medicine.disease Black or African American Hospitalization Case-Control Studies Heart failure Family medicine Original Article 0305 other medical science business predictive modeling |
| Zdroj: | American Journal of Men's Health American Journal of Men's Health, Vol 13 (2019) |
| ISSN: | 1557-9891 1557-9883 |
| DOI: | 10.1177/1557988318814295 |
| Popis: | Heart failure (HF) is responsible for more 30-day readmissions than any other condition. Minorities, particularly African American males (AAM), are at much higher risk for readmission than the general population. In this study, demographic, social, and clinical data were collected from the electronic medical records of 132 AAM patients (control and intervention) admitted with a primary or secondary admission diagnosis of HF. Both groups received guideline-directed therapy for HF. Additionally the intervention group received a pharmacist-led intervention. Data collected from these patients were used to develop and validate a predictive model to evaluate the impact of the pharmacist-led intervention, and identify predictors of readmission in this population. After propensity score matching, the intervention was determined to have a significant impact on readmission, as a significantly smaller proportion of patients in the intervention group were readmitted as compared to the control group (11.5% vs. 42.9%; p = .03). A predictive model for 30-day readmission was developed using K-nearest neighbor (KNN) classification algorithm. The model was able to correctly classify about 71% patients with an AUROC of 0.70. Additionally, the model provided a set of key patient attributes predictive of readmission status. Among these predictive attributes was whether or not a patient received the intervention. A relative risk analysis identified that patients who received the intervention are less likely to be readmitted within 30 days. This study demonstrated the benefit of a pharmacist-led intervention for AAM with HF. Such interventions have the potential to improve quality of life for this patient population. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|