Predictive risk stratification model: a progressive cluster-randomised trial in chronic conditions management

Trials
|December 17, 2013
PubMed

Insights

This study evaluates Prism, a tool predicting emergency hospital admissions for general practice. It assesses Prism

Area of Science:

  • Health Services Research
  • Predictive Analytics in Healthcare
  • General Practice Innovation

Background:

  • An aging population increases demand on health and social care services.
  • New approaches are needed to shift care from hospital to community and general practice settings.
  • A predictive risk stratification tool (Prism) has been developed to estimate emergency hospital admission risk in general practice.

Purpose of the Study:

  • To evaluate the effectiveness, cost-effectiveness, and implementation of the Prism tool in general practice.
  • To assess Prism's impact on patient outcomes, care processes, and practitioner/policymaker perceptions.
  • To identify barriers and facilitators to Prism implementation in primary care settings.

Main Methods:

  • A mixed-methods progressive cluster-randomised trial comparing usual care with Prism implementation.
  • Data collection includes routine data, postal questionnaires (at baseline, 6, 18 months), focus groups, and interviews.
  • Economic evaluation includes cost-effectiveness and cost-consequence analyses; data analysis uses generalized linear models and survival analysis.

Main Results:

  • Technical performance will be assessed by comparing predicted vs. actual emergency admissions.
  • Patient outcomes, costs, satisfaction, and quality of life will be compared between groups.
  • Qualitative data will explore perceptions and adoption of Prism by practitioners and policymakers.

Conclusions:

  • The study will provide crucial information on the costs and effects of the Prism tool.
  • Findings will illuminate practical use, implementation challenges, and perceived value in managing chronic conditions.
  • Results will inform the integration of predictive tools into primary care for improved patient management.
Abstract

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