Halasy Michael, Shafrin Jason
College of Medicine, Spine Center, Mayo Clinic, Rochester, MN.
Center for Healthcare Economics and Policy, FTI Consulting, Los Angeles, CA.
Mayo Clin Proc Innov Qual Outcomes. 2021 Apr 8;5(2):502-510. doi: 10.1016/j.mayocpiqo.2021.01.014. eCollection 2021 Apr.
In order to produce a mathematical model for better understanding of the benefits and utilization of second opinions and to understand the contradiction between the value of second opinions and their perceived underuse, we developed an expected utility theory model to quantify their value. We use a case-based example to find types of biases that could affect second opinions. Although the baseline expected utility theory model presented assumes providers are rational, we relax this and discuss the implications for how these alternative specifications alter predicted use. We found that second opinions are valuable when diagnostic accuracy is variable across physicians or access to high-quality care is restricted. In a stylized simulation example in which about half (50.1%) of diagnoses were incorrect, receipt of 1 second opinion reduced the error rate to 25.8% and receipt of 2 second opinions reduced the error rate to 16.0%. After incorporating potential biases into the model, the value of second opinions increases only when aversion to changing the initial diagnosis is greater than aversion to correcting a mistake. Additionally, this model reveals that second opinions have value even when diagnostic accuracy is perfect. Further, when financial incentives differ from the incentives of the initial consult, a second opinion offers patients a reasonable bound of their treatment options. To conclude, we identify numerous reasons for underuse of second opinions. Specifically, value depends on the degree of diagnostic uncertainty, presence of behavioral biases, and variation in local compensation regimes. Despite their value, recent trends could actually decrease the value of second opinions.
为了建立一个数学模型，以更好地理解二次诊断的益处和利用情况，并了解二次诊断的价值与其被认为未得到充分利用之间的矛盾，我们开发了一个期望效用理论模型来量化其价值。我们通过一个基于案例的例子来找出可能影响二次诊断的偏差类型。尽管所呈现的基线期望效用理论模型假设提供者是理性的，但我们放宽这一假设，并讨论这些替代规范如何改变预测的使用情况及其影响。我们发现，当不同医生的诊断准确性存在差异或获得高质量医疗服务受到限制时，二次诊断是有价值的。在一个程式化的模拟例子中，约一半（50.1%）的诊断是错误的，接受一次二次诊断将错误率降至25.8%，接受两次二次诊断将错误率降至16.0%。在将潜在偏差纳入模型后，只有当对改变初始诊断的厌恶大于对纠正错误的厌恶时，二次诊断的价值才会增加。此外，该模型表明即使诊断准确性完美时二次诊断也有价值。此外，当经济激励与初始咨询的激励不同时，二次诊断为患者提供了其治疗选择的合理范围。总之，我们确定了二次诊断未得到充分利用的众多原因。具体而言，价值取决于诊断不确定性的程度、行为偏差的存在以及当地薪酬制度的差异。尽管二次诊断有价值，但近期趋势实际上可能会降低二次诊断的价值。
