Schell Greggory J, Marrero Wesley J, Lavieri Mariel S, Sussman Jeremy B, Hayward Rodney A
Center for Naval Analyses, Arlington, Virginia (GJS).
Industrial and Operations Engineering (WJM, MSL) and Department of Internal Medicine (JBS, RAH), University of Michigan, Ann Arbor, Michigan.
MDM Policy Pract. 2016 Oct 17;1(1):2381468316674214. doi: 10.1177/2381468316674214. eCollection 2016 Jul-Dec.
Markov decision process (MDP) models are powerful tools. They enable the derivation of optimal treatment policies but may incur long computational times and generate decision rules that are challenging to interpret by physicians. In an effort to improve usability and interpretability, we examined whether Poisson regression can approximate optimal hypertension treatment policies derived by an MDP for maximizing a patient's expected discounted quality-adjusted life years. We found that our Poisson approximation to the optimal treatment policy matched the optimal policy in 99% of cases. This high accuracy translates to nearly identical health outcomes for patients. Furthermore, the Poisson approximation results in 104 additional quality-adjusted life years per 1000 patients compared to the Seventh Joint National Committee's treatment guidelines for hypertension. The comparative health performance of the Poisson approximation was robust to the cardiovascular disease risk calculator used and calculator calibration error. Our results are based on Markov chain modeling. Poisson model approximation for blood pressure treatment planning has high fidelity to optimal MDP treatment policies, which can improve usability and enhance transparency of more personalized treatment policies.
马尔可夫决策过程（MDP）模型是强大的工具。它们能够推导出最优治疗策略，但可能会导致较长的计算时间，并生成医生难以解释的决策规则。为了提高可用性和可解释性，我们研究了泊松回归是否可以近似由MDP推导的最优高血压治疗策略，以最大化患者的预期贴现质量调整生命年。我们发现，我们对最优治疗策略的泊松近似在99%的情况下与最优策略相匹配。这种高精度转化为患者几乎相同的健康结果。此外，与第七届全国联合委员会的高血压治疗指南相比，泊松近似每1000名患者可额外增加104个质量调整生命年。泊松近似的比较健康表现对于所使用的心血管疾病风险计算器和计算器校准误差具有稳健性。我们的结果基于马尔可夫链建模。用于血压治疗规划的泊松模型近似对最优MDP治疗策略具有高保真度，这可以提高可用性并增强更个性化治疗策略的透明度。
