Journal article
Identification of risk factors of 30-day readmission and 180-day in-hospital mortality, and its corresponding relative importance in patients with Ischemic heart disease: a machine learning approach
Expert review of pharmacoeconomics & outcomes research, Vol.21(5), pp.1043-1048
09/03/2021
DOI: 10.1080/14737167.2021.1842200
PMID: 33131344
Abstract
Background: The primary objective of this study is to identify non-laboratory predictors for 30-day hospital readmission and 180-day in-hospital mortality rates among patients hospitalized with ischemic heart disease (IHD).
Research design and methods: This is a retrospective cohort study of hospitalized patients (≥ 40 years) with a primary diagnosis of IHD. Data were extracted from the Florida Agency for Health Care Administration dataset from 2006 to 2016. A machine learning approach was used to identify predictors of 30-day hospital readmission and 180-day in-hospital mortality.
Results: 346,390 patient records for incident IHD cases were identified. The top two predictors of 30-day readmission were the length of stay and the Elixhauser comorbidity index for readmission [ECI] (Area Under the Curve [AUC]=88%) using decision tree algorithms. For in-hospital mortality, the top two predictors were LOS and ECI (AUC=92%) using gradient boosting regressors. The cumulative 30-day readmission and the 180-day probability of mortality rates were 9.82% and 4.6% respectively.
Conclusions: Risk factors of 30-day readmission and 180-day mortality in hospitalized IHD patients identified by machine learning and their relative importance (value) will help pharmacists and other health care providers to prioritize their disease management strategies as they improve the care provided to IHD patients.
Details
- Title: Subtitle
- Identification of risk factors of 30-day readmission and 180-day in-hospital mortality, and its corresponding relative importance in patients with Ischemic heart disease: a machine learning approach
- Creators
- Arinze Nkemdirim Okere - College of Pharmacy and Pharmaceutical Sciences, Institute of Public Health, Tallahassee, FL, USAVassiki Sanogo - University of FloridaHussain Alqhtani - Najran UniversityVakaramoko Diaby - University of Florida
- Resource Type
- Journal article
- Publication Details
- Expert review of pharmacoeconomics & outcomes research, Vol.21(5), pp.1043-1048
- DOI
- 10.1080/14737167.2021.1842200
- PMID
- 33131344
- ISSN
- 1473-7167
- eISSN
- 1744-8379
- Number of pages
- 6
- Language
- English
- Date published
- 09/03/2021
- Academic Unit
- Pharmacy Practice and Science; Internal Medicine
- Record Identifier
- 9984845212202771
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