Assessing and ranking private health insurance companies provides insurance agencies, insurance customers, and authorities with a reliable instrument for the insurance decision-making process. Moreover, because the world’s insurance sector suffers from a gap of evaluation of private health insurance companies during the COVID-19 outbreak, the need for a reliable, useful, and comprehensive decision tool is obvious. Accordingly, this article aims to identify insurance companies’ priority ranking in terms of healthcare services in Turkey during the COVID-19 outbreak through a multi-criteria performance evaluation methodology. Herein, alternatives are evaluated and then ranked as per 7 criteria and assessments of 5 experts. Experts’ judgments and assessments are full of uncertainties. We propose a Measurement of Alternatives and Ranking according to the Compromise Solution (MARCOS) technique under an intuitionistic fuzzy environment to rank insurance companies. The outcomes yielded ten insurance companies ranking in terms of healthcare services in the era of COVID-19. The payback period, premium price, and network are determined as the most crucial factors. Finally, a comprehensive sensitivity analysis is performed to verify the proposed methodology’s stability and effectiveness. The introduced approach met the insurance assessment problem during the COVID-19 pandemic very satisfactory manner based on sensitivity analysis findings.

对私营健康保险公司进行评估和排名为保险机构、保险客户和当局提供了可靠的保险决策过程工具。此外，由于世界保险业在 COVID-19 爆发期间对私营健康保险公司的评估存在差距，因此显然需要一种可靠、有用且全面的决策工具。因此，本文旨在通过多标准绩效评估方法确定保险公司在 COVID-19 爆发期间在土耳其医疗保健服务方面的优先排名。在此，对备选方案进行评估，然后根据 7 个标准和 5 位专家的评估进行排名。专家的判断和评估充满不确定性。我们提出了一种在直觉模糊环境下根据妥协解决方案 (MARCOS) 技术对替代方案和排名进行衡量，以对保险公司进行排名。结果产生了 10 家保险公司在 COVID-19 时代的医疗保健服务方面的排名。投资回收期、溢价和网络被确定为最关键的因素。最后，进行了全面的敏感性分析，以验证所提出方法的稳定性和有效性。基于敏感性分析结果，引入的方法非常令人满意地解决了 COVID-19 大流行期间的保险评估问题。结果产生了 10 家保险公司在 COVID-19 时代的医疗保健服务方面的排名。投资回收期、溢价和网络被确定为最关键的因素。最后，进行了全面的敏感性分析，以验证所提出方法的稳定性和有效性。基于敏感性分析结果，引入的方法非常令人满意地解决了 COVID-19 大流行期间的保险评估问题。结果产生了 10 家保险公司在 COVID-19 时代的医疗保健服务方面的排名。投资回收期、溢价和网络被确定为最关键的因素。最后，进行了全面的敏感性分析，以验证所提出方法的稳定性和有效性。基于敏感性分析结果，引入的方法非常令人满意地解决了 COVID-19 大流行期间的保险评估问题。