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Optimal cholesterol treatment plans and genetic testing strategies for cardiovascular diseases

Author

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  • Wesley J. Marrero

    (University of Michigan)

  • Mariel S. Lavieri

    (University of Michigan)

  • Jeremy B. Sussman

    (University of Michigan)

Abstract

Atherosclerotic cardiovascular disease (ASCVD) is among the leading causes of death in the US. Although research has shown that ASCVD has genetic elements, the understanding of how genetic testing influences its prevention and treatment has been limited. To this end, we model the health trajectory of patients stochastically and determine treatment and testing decisions simultaneously. Since the cholesterol level of patients is one controllable risk factor for ASCVD events, we model cholesterol treatment plans as Markov decision processes. We determine whether and when patients should receive a genetic test using value of information analysis. By simulating the health trajectory of over 64 million adult patients, we find that 6.73 million patients undergo genetic testing. The optimal treatment plans informed with clinical and genetic information save 5,487 more quality-adjusted life-years while costing $1.18 billion less than the optimal treatment plans informed with clinical information only. As precision medicine becomes increasingly important, understanding the impact of genetic information becomes essential.

Suggested Citation

  • Wesley J. Marrero & Mariel S. Lavieri & Jeremy B. Sussman, 2021. "Optimal cholesterol treatment plans and genetic testing strategies for cardiovascular diseases," Health Care Management Science, Springer, vol. 24(1), pages 1-25, March.
    • Handle: RePEc:kap:hcarem:v:24:y:2021:i:1:d:10.1007_s10729-020-09537-x
    DOI: 10.1007/s10729-020-09537-x
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    1. Jagpreet Chhatwal & Oguzhan Alagoz & Elizabeth S. Burnside, 2010. "Optimal Breast Biopsy Decision-Making Based on Mammographic Features and Demographic Factors," Operations Research, INFORMS, vol. 58(6), pages 1577-1591, December.
    2. Matthew J. Glover & Edmund Jones & Katya L. Masconi & Michael J. Sweeting & Simon G. Thompson, 2018. "Discrete Event Simulation for Decision Modeling in Health Care: Lessons from Abdominal Aortic Aneurysm Screening," Medical Decision Making, , vol. 38(4), pages 439-451, May.
    3. Tat Chan & Chakravarthi Narasimhan & Ying Xie, 2013. "Treatment Effectiveness and Side Effects: A Model of Physician Learning," Management Science, INFORMS, vol. 59(6), pages 1309-1325, June.
    4. Shan Liu & Margaret L. Brandeau & Jeremy D. Goldhaber-Fiebert, 2017. "Optimizing patient treatment decisions in an era of rapid technological advances: the case of hepatitis C treatment," Health Care Management Science, Springer, vol. 20(1), pages 16-32, March.
    5. Lotte Steuten & Gijs Wetering & Karin Groothuis-Oudshoorn & Valesca Retèl, 2013. "A Systematic and Critical Review of the Evolving Methods and Applications of Value of Information in Academia and Practice," PharmacoEconomics, Springer, vol. 31(1), pages 25-48, January.
    6. Jonathan E. Helm & Mariel S. Lavieri & Mark P. Van Oyen & Joshua D. Stein & David C. Musch, 2015. "Dynamic Forecasting and Control Algorithms of Glaucoma Progression for Clinician Decision Support," Operations Research, INFORMS, vol. 63(5), pages 979-999, October.
    7. Fumie Yokota & Kimberly M. Thompson, 2004. "Value of Information Literature Analysis: A Review of Applications in Health Risk Management," Medical Decision Making, , vol. 24(3), pages 287-298, June.
    8. Manaf Zargoush & Mehmet Gümüş & Vedat Verter & Stella S. Daskalopoulou, 2018. "Designing Risk‐Adjusted Therapy for Patients with Hypertension," Production and Operations Management, Production and Operations Management Society, vol. 27(12), pages 2291-2312, December.
    9. 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.
    10. Sarang Deo & Kumar Rajaram & Sandeep Rath & Uday S. Karmarkar & Matthew B. Goetz, 2015. "Planning for HIV Screening, Testing, and Care at the Veterans Health Administration," Operations Research, INFORMS, vol. 63(2), pages 287-304, April.
    11. Fatih Safa Erenay & Oguzhan Alagoz & Adnan Said, 2014. "Optimizing Colonoscopy Screening for Colorectal Cancer Prevention and Surveillance," Manufacturing & Service Operations Management, INFORMS, vol. 16(3), pages 381-400, July.
    12. Elisa F. Long & Eike Nohdurft & Stefan Spinler, 2018. "Spatial Resource Allocation for Emerging Epidemics: A Comparison of Greedy, Myopic, and Dynamic Policies," Manufacturing & Service Operations Management, INFORMS, vol. 20(2), pages 181-198, May.
    13. James C. Felli & Gordon B. Hazen, 1998. "Sensitivity Analysis and the Expected Value of Perfect Information," Medical Decision Making, , vol. 18(1), pages 95-109, January.
    14. Anna Heath & Ioanna Manolopoulou & Gianluca Baio, 2017. "A Review of Methods for Analysis of the Expected Value of Information," Medical Decision Making, , vol. 37(7), pages 747-758, October.
    15. Brian T. Denton & Murat Kurt & Nilay D. Shah & Sandra C. Bryant & Steven A. Smith, 2009. "Optimizing the Start Time of Statin Therapy for Patients with Diabetes," Medical Decision Making, , vol. 29(3), pages 351-367, May.
    16. James C. Felli & Gordon B. Hazen, 1999. "A Bayesian approach to sensitivity analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 263-268, May.
    17. Yan Yang & Jeremy D. Goldhaber-Fiebert & Lawrence M. Wein, 2013. "Analyzing Screening Policies for Childhood Obesity," Management Science, INFORMS, vol. 59(4), pages 782-795, April.
    18. Hoel, Michael & Iversen, Tor & Nilssen, Tore & Vislie, Jon, 2006. "Genetic testing in competitive insurance markets with repulsion from chance: A welfare analysis," Journal of Health Economics, Elsevier, vol. 25(5), pages 847-860, September.
    19. 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.
    20. Gad Abraham & Jason A Tye-Din & Oneil G Bhalala & Adam Kowalczyk & Justin Zobel & Michael Inouye, 2014. "Accurate and Robust Genomic Prediction of Celiac Disease Using Statistical Learning," PLOS Genetics, Public Library of Science, vol. 10(2), pages 1-15, February.
    21. Amy O’Sullivan & Jaime Rubin & Joshua Nyambose & Andreas Kuznik & David Cohen & David Thompson, 2011. "Cost Estimation of Cardiovascular Disease Events in the US," PharmacoEconomics, Springer, vol. 29(8), pages 693-704, August.
    22. Fumie Yokota & Kimberly M. Thompson, 2004. "Value of Information Analysis in Environmental Health Risk Management Decisions: Past, Present, and Future," Risk Analysis, John Wiley & Sons, vol. 24(3), pages 635-650, June.
    23. Allen C. Miller, 1975. "The Value of Sequential Information," Management Science, INFORMS, vol. 22(1), pages 1-11, September.
    24. Turgay Ayer & Oguzhan Alagoz & Natasha K. Stout & Elizabeth S. Burnside, 2016. "Heterogeneity in Women’s Adherence and Its Role in Optimal Breast Cancer Screening Policies," Management Science, INFORMS, vol. 62(5), pages 1339-1362, May.
    25. K. Cooper & S. Brailsford & R. Davies & J. Raftery, 2006. "A review of health care models for coronary heart disease interventions," Health Care Management Science, Springer, vol. 9(4), pages 311-324, November.
    26. Nowok, Beata & Raab, Gillian M. & Dibben, Chris, 2016. "synthpop: Bespoke Creation of Synthetic Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 74(i11).
    27. Alireza Sabouri & Woonghee Tim Huh & Steven M. Shechter, 2017. "Screening Strategies for Patients on the Kidney Transplant Waiting List," Operations Research, INFORMS, vol. 65(5), pages 1131-1146, October.
    28. Elisa F. Long & Naveen K. Vaidya & Margaret L. Brandeau, 2008. "Controlling Co-Epidemics: Analysis of HIV and Tuberculosis Infection Dynamics," Operations Research, INFORMS, vol. 56(6), pages 1366-1381, December.
    29. Memarzadeh, Milad & Pozzi, Matteo, 2016. "Value of information in sequential decision making: Component inspection, permanent monitoring and system-level scheduling," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 137-151.
    30. M. Reza Skandari & Steven M. Shechter & Nadia Zalunardo, 2015. "Optimal Vascular Access Choice for Patients on Hemodialysis," Manufacturing & Service Operations Management, INFORMS, vol. 17(4), pages 608-619, October.
    31. Muge Capan & Anahita Khojandi & Brian T. Denton & Kimberly D. Williams & Turgay Ayer & Jagpreet Chhatwal & Murat Kurt & Jennifer Mason Lobo & Mark S. Roberts & Greg Zaric & Shengfan Zhang & J. Sanford, 2017. "From Data to Improved Decisions: Operations Research in Healthcare Delivery," Medical Decision Making, , vol. 37(8), pages 849-859, November.
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    Cited by:

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