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Examining chronic kidney disease screening frequency among diabetics: a POMDP approach

Author

Listed:
  • Chou-Chun Wu

    (University of Southern California)

  • Yiwen Cao

    (University of Southern California)

  • Sze-chuan Suen

    (University of Southern California)

  • Eugene Lin

    (University of Southern California
    University of Southern California)

Abstract

Forty percent of diabetics will develop chronic kidney disease (CKD) in their lifetimes. However, as many as 50% of these CKD cases may go undiagnosed. We developed screening recommendations stratified by age and previous test history for individuals with diagnosed diabetes and unknown proteinuria status by race and gender groups. To do this, we used a Partially Observed Markov Decision Process (POMDP) to identify whether a patient should be screened at every three-month interval from ages 30-85. Model inputs were drawn from nationally-representative datasets, the medical literature, and a microsimulation that integrates this information into group-specific disease progression rates. We implement the POMDP solution policy in the microsimulation to understand how this policy may impact health outcomes and generate an easily-implementable, non-belief-based approximate policy for easier clinical interpretability. We found that the status quo policy, which is to screen annually for all ages and races, is suboptimal for maximizing expected discounted future net monetary benefits (NMB). The POMDP policy suggests more frequent screening after age 40 in all race and gender groups, with screenings 2-4 times a year for ages 61-70. Black individuals are recommended for screening more frequently than their White counterparts. This policy would increase NMB from the status quo policy between $1,000 to $8,000 per diabetic patient at a willingness-to-pay of $150,000 per quality-adjusted life year (QALY).

Suggested Citation

  • Chou-Chun Wu & Yiwen Cao & Sze-chuan Suen & Eugene Lin, 2024. "Examining chronic kidney disease screening frequency among diabetics: a POMDP approach," Health Care Management Science, Springer, vol. 27(3), pages 391-414, September.
  • Handle: RePEc:kap:hcarem:v:27:y:2024:i:3:d:10.1007_s10729-024-09677-4
    DOI: 10.1007/s10729-024-09677-4
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    References listed on IDEAS

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    1. Jing Li & Ming Dong & Yijiong Ren & Kaiqi Yin, 2015. "How patient compliance impacts the recommendations for colorectal cancer screening," Journal of Combinatorial Optimization, Springer, vol. 30(4), pages 920-937, November.
    2. Sarah Elshahat & Paul Cockwell & Alexander P Maxwell & Matthew Griffin & Timothy O’Brien & Ciaran O’Neill, 2020. "The impact of chronic kidney disease on developed countries from a health economics perspective: A systematic scoping review," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-19, March.
    3. Hossein Kamalzadeh & Vishal Ahuja & Michael Hahsler & Michael E. Bowen, 2021. "An Analytics‐Driven Approach for Optimal Individualized Diabetes Screening," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 3161-3191, September.
    4. Lisa M. Maillart & Julie Simmons Ivy & Scott Ransom & Kathleen Diehl, 2008. "Assessing Dynamic Breast Cancer Screening Policies," Operations Research, INFORMS, vol. 56(6), pages 1411-1427, December.
    5. Friede, A. & Reid, J.A. & Ory, H.W., 1993. "CDC WONDER: A comprehensive on-line public health information system of the Centers for Disease Control and Prevention," American Journal of Public Health, American Public Health Association, vol. 83(9), pages 1289-1294.
    6. Sze-chuan Suen & Margaret L. Brandeau & Jeremy D. Goldhaber-Fiebert, 2018. "Optimal timing of drug sensitivity testing for patients on first-line tuberculosis treatment," Health Care Management Science, Springer, vol. 21(4), pages 632-646, December.
    7. Eugene Lin & Glenn M Chertow & Brandon Yan & Elizabeth Malcolm & Jeremy D Goldhaber-Fiebert, 2018. "Cost-effectiveness of multidisciplinary care in mild to moderate chronic kidney disease in the United States: A modeling study," PLOS Medicine, Public Library of Science, vol. 15(3), pages 1-29, March.
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