Defining \u2018actionable\u2019 high- costhealth care use: results using the Canadian Institute for Health Information population grouping methodology

Maureen Anderson,Crawford W Revie,Wenbin Li,Meriç Osman,David L Buckeridge,Cordell Neudorf,Henrik Stryhn,Laura C Rosella,Walter P Wodchis,Yvonne Rosehart

doi:10.1186/s12939-019-1074-3

Abstract

BackgroundA small proportion of the population consumes the majority of health care resources. High-cost health care users are a heterogeneous group. We aim to segment a provincial population into relevant homogenous sub-groups to provide actionable information on risk factors associated with high-cost health care use within sub-populations.MethodsThe Canadian Institute for Health Information (CIHI) Population Grouping methodology was used to define mutually exclusive and clinically relevant health profile sub-groups. High-cost users (> = 90th percentile of health care spending) were defined within each sub-group. Univariate analyses explored demographic, socio-economic status, health status and health care utilization variables associated with high-cost use. Multivariable logistic regression models were constructed for the costliest health profile groups.ResultsFrom 2015 to 2017, 1,175,147 individuals were identified for study. High-cost users consumed 41% of total health care resources. Average annual health care spending for individuals not high-cost were $642; high-cost users were $16,316. The costliest health profile groups were ‘long-term care’, ‘palliative’, ‘major acute’, ‘major chronic’, ‘major cancer’, ‘major newborn’, ‘major mental health’ and ‘moderate chronic’. Both ‘major acute’ and ‘major cancer’ health profile groups were largely explained by measures of health care utilization and multi-morbidity. In the remaining costliest health profile groups modelled, ‘major chronic’, ‘moderate chronic’, ‘major newborn’ and ‘other mental health’, a measure of socio-economic status, low neighbourhood income, was statistically significantly associated with high-cost use.InterpretationModel results point to specific, actionable information within clinically meaningful subgroups to reduce high-cost health care use. Health equity, specifically low socio-economic status, was statistically significantly associated with high-cost use in the majority of health profile sub-groups. Population segmentation methods, and more specifically, the CIHI Population Grouping Methodology, provide specificity to high-cost health care use; informing interventions aimed at reducing health care costs and improving population health.

Highlights

Increasing health care costs are challenging health care systems in Canada and around the world
We explored all interaction terms analytically; only those deemed biologically plausible by clinician contributors and previous studies were included in the models
We identified a total of 1,175,147 individuals, residents of Saskatchewan, excluding residents of long-term care, with health insurance coverage of at least 1 day from April 1, 2015 to March 31, 2017 and person-level costing data (Fig. 1)

Summary

Introduction

Increasing health care costs are challenging health care systems in Canada and around the world. Evidence has long demonstrated that a small proportion of the population (< 10%) accounts for the majority (50–70%) of total health care spending [7, 20, 21, 26]; individuals commonly referred to as ‘high-cost users’. A recent systematic review on highcost health care users identified similar patterns: multimorbidity, mental health and addictions, increasing age, end-of-life care and socio-economic status were the predominant factors associated with high-cost use across 55 countries globally [29]. High-cost health care users are a heterogeneous group. We aim to segment a provincial population into relevant homogenous sub-groups to provide actionable information on risk factors associated with high-cost health care use within sub-populations

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Discussion

Conclusion