Naimark David M J, Bott Michelle, Krahn Murray
Division of Nephrology, Sunny-brook & Women's College Health Sciences Centre, Toronto, Canada.
Med Decis Making. 2008 Sep-Oct;28(5):706-12. doi: 10.1177/0272989X08315241. Epub 2008 Apr 30.
Students of Markov decision models are often taught to add a half-cycle's worth of incremental utility to the cumulative total for each health state. The reason for this "half-cycle correction'' is often illustrated by a graph of the proportion of the hypothetical Markov cohort remaining in a given state. The ideal graph is shown as a smooth, declining, curve that represents the transition of patients randomly throughout each cycle. On the same graph, the effect of the accounting of state membership at the end of each cycle in discrete, computer-based approximations of the ideal Markov process is shown. Students are able to clearly see that the cumulative incremental utility in the discrete case underestimates the desired quantity. Likewise, they find the concept of shifting the ideal curve to the right by one-half cycle to reduce the latter discrepancy to be intuitive. However, students often find the approximate equivalence of shifting the ideal state membership curve and adding a half-cycle's worth of incremental utility to the total for the state at the beginning of a discrete Markov process to be a difficult cognitive leap. This article describes 2 pedagogical devices, algebraic and intuitive/visual approaches, that may assist the instructor of Markov theory to convey the latter concept. Elements of adult learning theory are discussed, which may help the instructor to choose which approach to employ. Implementation of the half-cycle correction in commonly used decision-analytic software is also discussed.
马尔可夫决策模型的学生通常被教导要为每个健康状态的累积总量加上相当于半个周期的增量效用。这种“半周期校正”的原因通常用一张关于假设的马尔可夫队列中处于给定状态的比例的图表来说明。理想的图表显示为一条平滑的、下降的曲线,代表患者在每个周期中随机转移的情况。在同一张图表上,还展示了在基于计算机的理想马尔可夫过程离散近似中,每个周期末状态归属计算的效果。学生能够清楚地看到,离散情况下的累积增量效用低估了所需的数量。同样,他们发现将理想曲线向右移动半个周期以减少后者差异的概念很直观。然而,学生们常常发现,在离散马尔可夫过程开始时,将理想状态归属曲线移动与为该状态的总量加上相当于半个周期的增量效用之间的近似等效性是一个难以跨越的认知障碍。本文介绍了两种教学方法,代数法和直观/视觉法,这可能有助于马尔可夫理论的教师传达后一个概念。还讨论了成人学习理论的要素,这可能有助于教师选择采用哪种方法。同时也讨论了在常用决策分析软件中半周期校正的实现。