Journal article
Development and validation of a tool to predict high-need, high-cost patients hospitalised with ischaemic heart disease
BMJ open, Vol.13(9), e073485
09/26/2023
DOI: 10.1136/bmjopen-2023-073485
PMCID: PMC10533782
PMID: 37751949
Abstract
Objective To develop and validate a tool to predict patients with ischaemic heart disease (IHD) at risk of excessive healthcare resource utilisation.Design A retrospective cohort study.Setting We identified patients through the State of Florida Agency for Health Care Administration (N=586 518) inpatient dataset.Participants Adult patients (at least 40 years of age) admitted to the hospital with a diagnosis of IHD between 1 January 2007 and 31 December 2016.Primary outcome measures We identified patients whose healthcare utilisation is higher than presumed (analysis of residuals) and used logistic regression (binary and multinomial) in estimating the predictive models to classify individual as high-need, high-care (HNHC) patients relative to inpatient visits (frequency of hospitalisation), cost and hospital length of stay. Discrimination power, prediction accuracy and model improvement for the binary logistic model were assessed using receiver operating characteristic statistic, the Brier score and the log-likelihood (LL)-based pseudo-R-2, respectively. LL-based pseudo-R-2 and Brier score were used for multinomial logistic models.Results The binary logistic model had good discrimination power (c-statistic=0.6496), an accuracy of probabilistic predictions (Brier score) of 0.0621 and an LL-based pseudo-R-2 of 0.0338 in the development cohort. The model performed similarly in the validation cohort (c-statistic=0.6480), an accuracy of probabilistic predictions (Brier score) of 0.0620 and an LL-based pseudo-R-2 of 0.0380. A user-friendly Excel-based HNHC risk predictive tool was developed and readily available for clinicians and policy decision-makers.Conclusions The Excel-based HNHC risk predictive tool can accurately identify at-risk patients for HNHC based on three measures of healthcare expenditures.
Details
- Title: Subtitle
- Development and validation of a tool to predict high-need, high-cost patients hospitalised with ischaemic heart disease
- Creators
- Arinze Nkemdirim Okere - Florida Agricultural and Mechanical UniversityRichard K. Moussa - École Nationale Supérieure de Statistique et d'Économie AppliquéeAskal Ali - Florida Agricultural and Mechanical UniversityVakaramoko K. Diaby - University of Florida
- Resource Type
- Journal article
- Publication Details
- BMJ open, Vol.13(9), e073485
- DOI
- 10.1136/bmjopen-2023-073485
- PMID
- 37751949
- PMCID
- PMC10533782
- NLM abbreviation
- BMJ Open
- ISSN
- 2044-6055
- eISSN
- 2044-6055
- Publisher
- Bmj Publishing Group
- Number of pages
- 10
- Grant note
- Florida A&M University RCMI
- Language
- English
- Date published
- 09/26/2023
- Academic Unit
- Pharmacy Practice and Science; Internal Medicine
- Record Identifier
- 9984845213202771
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