Development and practical use of a risk-sensitive population segmentation model for healthcare service planning: application in England

Richard Wood, Theresia Budiman, Nicholas Hassey, Zehra Onen Dumlu, Christos Vasilakis, Fiona Budd, Sarah Hollier, Peter M Thomson, Charlie Kenward

Research output: Contribution to journalArticlepeer-review

Abstract

Population segmentation can be a powerful tool in healthcare management, in helping to match interventions and resources to individuals of a common health state and condition. However, studies to date indicate a lack of alignment to risk stratification – another key tool in Population Health Management – and insufficient demonstration of how segmentation can be used in practice. In this study, we obtain a five-cohort segmentation derived through four incremental thresholds on the risk-based Cambridge Multimorbidity Score, which is calculated for each member of the 762,117 adult population in and around Bristol, England. Appropriately selecting the four thresholds – 0.09, 0.69, 1.59, 2.95 – yields a segmentation with the convenient property that, with increasing risk, segments halve in size and double in per-person spend. The segmentation has been used to support various planning and management activities within the Bristol healthcare system; two of which are detailed here as case studies in demonstrating the practical value of the segmentation model.
Original languageEnglish
JournalInternational Journal of Healthcare Management
Early online date13 Jul 2023
DOIs
Publication statusE-pub ahead of print - 13 Jul 2023

Bibliographical note

Funding
The author(s) reported there is no funding associated with the work featured in this article.

Data availability statement
Data used in this study is protected patient data and not publicly available at the record-level granularity as used in this study.

Keywords

  • Population health management
  • healthcare spend
  • healthcare utilization
  • population segmentation
  • risk stratification

ASJC Scopus subject areas

  • Health Policy
  • Leadership and Management

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