Cinaroglu Songul
Hacettepe University, Department of Health Care Management, Assistant Professor of Health Care Management, Faculty of Economics and Administrative Sciences (FEAS) Beytepe, Ankara, 06800, Turkey.
J Cancer Policy. 2021 Mar;27:100262. doi: 10.1016/j.jcpo.2020.100262. Epub 2020 Nov 30.
Developing countries face great challenges in health care because of changing disease dynamics and the increasing burden of chronic diseases such as cancers. Thus, effective operational design of health services is critical to better manage scarce health care resources. This study aimed to examine the spatial distribution of the efficiency of Turkey's oncology services.
Data was collected from the 2017 Public Hospitals Statistical Yearbook, and a total of 55 provinces with advanced centers for cancer were analyzed. This study applied Charnes, Cooper, and Rhodes's input-oriented data envelopment analysis (DEA) and performed jackknifing for robustness check of DEA scores.
The iteration procedure generated four models. The final model included 38 decision-making units (DMUs), and 50 % of provinces were found to have efficient oncology services. The final model's average conventional efficiency score was 0.79. Next, bootstrapped DEA procedure was incorporated into the final model to gather bias-corrected efficiency scores. After applying the bootstrapping approach, efficiency scores are significantly improved and the difference between conventional and bias-corrected efficiency scores are statistically significant (U = 475; p < 0.05).
Geographic planning of cancer care services is a relevant principle in health operations design that requires specific health service configurations for preparedness of health crisis such as pandemic. The results highlighted that health policymakers must be aware of regional imbalances and eliminate them to provide advanced oncology care services for population groups in poor areas of the country.
Health policy makers should prioritize a balanced geographical distribution of professional oncology services to provide vulnerable groups better access to critical care.
由于疾病动态变化以及癌症等慢性病负担日益加重，发展中国家在医疗保健方面面临巨大挑战。因此，卫生服务的有效运营设计对于更好地管理稀缺的医疗资源至关重要。本研究旨在考察土耳其肿瘤服务效率的空间分布。
数据收集自《2017年公立医院统计年鉴》，共分析了55个设有癌症高级中心的省份。本研究应用了查恩斯、库珀和罗兹的投入导向型数据包络分析（DEA），并进行了刀切法以检验DEA得分的稳健性。
迭代过程生成了四个模型。最终模型包括38个决策单元（DMU），发现50%的省份拥有高效的肿瘤服务。最终模型的平均传统效率得分为0.79。接下来，将自举DEA程序纳入最终模型以获取偏差校正后的效率得分。应用自举方法后，效率得分显著提高，传统效率得分与偏差校正后的效率得分之间的差异具有统计学意义（U = 475；p < 0.05）。
癌症护理服务的地理规划是卫生运营设计中的一项相关原则，需要针对大流行等健康危机的防范制定特定的卫生服务配置。结果强调，卫生政策制定者必须意识到地区不平衡并消除这些不平衡，以便为该国贫困地区的人群提供先进的肿瘤护理服务。
卫生政策制定者应优先考虑专业肿瘤服务的均衡地理分布，以使弱势群体更好地获得重症护理。
