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Diagnostic Policies Optimization for Chronic Diseases Based on POMDP Model.

Wenqian Zhang1, Haiyan Wang1

  • 1School of Economics and Management, Southeast University, Nanjing 211189, China.

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Summary

This study introduces a new model for diagnosing chronic diseases to improve patient outcomes and reduce healthcare costs. It reveals that optimal diagnostic thresholds vary unexpectedly with age and sex, challenging current clinical intuition.

Keywords:
chronic diseasesdiagnostic policiesdiagnostic thresholdpartially observable Markov decision processpolicies optimization

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Area of Science:

  • * Decision analysis
  • * Health economics
  • * Chronic disease management

Background:

  • * Overdiagnosis and underdiagnosis of chronic diseases lead to adverse patient outcomes and increased healthcare costs.
  • * Current diagnostic policies often lack personalization, failing to account for individual patient characteristics.
  • * Optimizing diagnostic strategies is crucial for maximizing patient quality of life and minimizing healthcare expenditure.

Purpose of the Study:

  • * To develop an optimal diagnostic policy for chronic diseases using a partially observable Markov decision process (POMDP) model.
  • * To maximize patient quality-adjusted life years (QALYs) by determining optimal diagnostic thresholds and ages.
  • * To apply and validate the model for coronary heart disease (CHD) management and compare it with clinical practices.

Main Methods:

  • * Construction of a partially observable Markov decision process (POMDP) model incorporating individual patient characteristics.
  • * Derivation of structural properties, including diagnostic thresholds and optimal diagnosis age.
  • * Application and validation of the model using clinical data for coronary heart disease.

Main Results:

  • * The study identified age- and sex-dependent diagnostic thresholds for chronic diseases.
  • * Optimal diagnostic thresholds decrease and then increase with patient age, contrary to common assumptions.
  • * Women, particularly younger women, exhibit higher diagnostic thresholds compared to men.

Conclusions:

  • * The developed POMDP model provides a quantitative tool for optimizing chronic disease diagnosis.
  • * Findings challenge traditional diagnostic approaches and offer actionable insights for physicians and policymakers.
  • * Personalized diagnostic strategies based on age and sex can improve patient outcomes and resource allocation.