Dataset Information

Development and validation of a tool to predict high-need, high-cost patients hospitalised with ischaemic heart disease.

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-R², respectively. LL-based pseudo-R² 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-R² 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-R² 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.

SUBMITTER: Nkemdirim Okere A

PROVIDER: S-EPMC10533782 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Publications

Development and validation of a tool to predict high-need, high-cost patients hospitalised with ischaemic heart disease.

Nkemdirim Okere Arinze A Moussa Richard K RK Ali Askal A Diaby Vakaramoko K VK

BMJ open 20230926 9

<h4>Objective</h4>To develop and validate a tool to predict patients with ischaemic heart disease (IHD) at risk of excessive healthcare resource utilisation.<h4>Design</h4>A retrospective cohort study.<h4>Setting</h4>We identified patients through the State of Florida Agency for Health Care Administration (N=586 518) inpatient dataset.<h4>Participants</h4>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.<h4>Pri ...[more]

PMID: 37751949

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Dataset Information

Development and validation of a tool to predict high-need, high-cost patients hospitalised with ischaemic heart disease.

Objective

Design

Setting

Participants

Primary outcome measures

Results

Conclusions

Publications

Development and validation of a tool to predict high-need, high-cost patients hospitalised with ischaemic heart disease.

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