影像室及其他:门诊医生的测试订购行为背后的潜在经济学

Tinglong Dai, Mustafa Akan, S. Tayur
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引用次数: 55

摘要

在美国最全面的眼科成像项目之一的合作研究的推动下,我们调查了医生在决定订购成像检查时,在操作、临床和财务考虑之间潜在的三方权衡。实验室检查可能同时进行,因此对病人等待时间的影响有限;相比之下,影像学检查需要患者在场,因此直接影响患者的等待时间。我们使用一个战略排队框架来模拟医生订购影像学检查的决定,并表明保险范围是过度检查的关键驱动因素。我们进一步的分析揭示了以下几点:尽管现有的研究认为较低的自付费用导致较高的消费水平,但我们通过显示共同支付和共同保险费率推动消费的不同方向来完善这一说法。因此,简单地扩大患者费用分担并不能解决过度检测问题。仅设置较低的报销上限并不能消除过度测试。误诊问题和保险范围的共同影响可能导致检测过度和检测不足,即使不存在报销上限。这些和其他结果在更一般的条件下仍然成立,因此是可靠的。我们沿着两个扩展丰富了我们的模型:一个是诊断精度的患者异质性,另一个是健康保险覆盖范围的差异。我们的研究结果对其他具有类似权衡的医疗保健机构具有启示意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Imaging Room and Beyond: The Underlying Economics Behind Physicians' Test-Ordering Behavior in Outpatient Services
Motivated by a collaborative study with one of the most comprehensive ocular imaging programs in the United States, we investigate the underlying three-way trade-off among operational, clinical, and financial considerations in physicians' decisions about ordering imaging tests. Laboratory tests may be processed in parallel and thus have a limited effect on patients' waiting times; imaging tests, by contrast, require patient presence and thus directly influence patients' waiting times. We use a strategic queueing framework to model a physician's decision of ordering imaging tests and show that insurance coverage is the key driver of overtesting. Our further analysis reveals the following: i Whereas existing studies hold that lower out-of-pocket expenses lead to higher consumption levels, we refine this statement by showing the copayment and the coinsurance rate drive the consumption in different directions. Thus, simply expanding patient cost sharing is not the solution to overtesting. ii Setting a low reimbursement ceiling alone cannot eliminate overtesting. iii The joint effect of misdiagnosis concerns and insurance coverage can lead to both overtesting and undertesting even when no reimbursement ceiling exists. These and other results continue to hold under more general conditions and are therefore robust. We enrich our model along two extensions: one with patient heterogeneity in diagnostic precision, and the other with disparities in health insurance coverage. Our findings have implications for other healthcare settings with similar trade-offs.
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