Iwasaki Masaki, Saito Takashi, Tsubota Akiko, Murata Tatsunori, Fukuoka Yuta, Jin Kazutaka
Department of Neurosurgery, National Center Hospital, National Center of Neurology and Psychiatry.
Department of Child Neurology, National Center Hospital, National Center of Neurology and Psychiatry.
J Health Econ Outcomes Res. 2021 Jun 10;8(1):80-87. doi: 10.36469/jheor.2021.24061.
We developed a Markov model to simulate a treatment flow of epilepsy patients who refer to specialized care from non-specialized care, and to surgery from specialized care for estimation of patient distributions and expenditures caused by increasing the referral rate for specialized care. This budget impact analysis of treatment flow optimization in epilepsy patients was performed as a long-term simulation using the Markov model by comparing the current treatment flow and the optimized treatment flow. In the model, we simulated the prognosis of new onset 5-year-old epilepsy patients (assuming to represent epilepsy occurring between 0 and 10 years of age) treated over a lifetime period. Direct costs of pharmacotherapies, management fees and surgeries are included in the analysis to evaluate the annual budget impact in Japan. In the current treatment flow, the number of refractory patients treated with four drugs by non-specialized care were estimated as 8766 and yielded JPY5.8 billion annually. However, in the optimized treatment flow, the number of patients treated with four drugs by non-specialized care significantly decreased and who continued the monotherapy increased. The costs for the four-drug therapy by non-specialized care were eliminated. Hence cost-saving of JPY9.5 billion (-5% of the current treatment flow) in total national expenditures would be expected. This study highlights that any policy decision-making for referral optimization to specialized care in appropriate epilepsy patients would be feasible with a cost-savings or very few budget impacts. However, important information in the decision-making such as transition probability to the next therapy or excuse for sensitive limitations is not available currently. Therefore, further research with reliable data such as big data analysis or a national survey with real-world treatment patterns is needed.
我们开发了一个马尔可夫模型，以模拟癫痫患者从非专科护理转诊至专科护理，再从专科护理转诊至手术的治疗流程，从而估计因提高专科护理转诊率而导致的患者分布和费用情况。通过比较当前治疗流程和优化后的治疗流程，使用马尔可夫模型对癫痫患者治疗流程优化进行了长期模拟的预算影响分析。在该模型中，我们模拟了新确诊的5岁癫痫患者（假设代表0至10岁之间发生的癫痫）一生的预后情况。分析中纳入了药物治疗、管理费和手术的直接成本，以评估日本的年度预算影响。在当前治疗流程中，估计非专科护理使用四种药物治疗的难治性患者数量为8766人，每年产生58亿日元的费用。然而，在优化后的治疗流程中，非专科护理使用四种药物治疗的患者数量显著减少，而继续接受单一疗法的患者数量增加。非专科护理的四联疗法成本得以消除。因此，预计全国总支出可节省95亿日元（占当前治疗流程的-5%）。本研究强调，对于适当的癫痫患者，任何优化转诊至专科护理的政策决策都是可行的，且能节省成本或对预算影响极小。然而，目前决策中重要的信息，如下一治疗的转移概率或敏感局限性的理由等尚不可用。因此，需要通过大数据分析或全国真实世界治疗模式调查等可靠数据进行进一步研究。
