Manitoba Centre for Health Policy, Dept of Community Health Sciences, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 3P5 Canada.
Department of Family Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R33 0W2 Canada.
Int J Popul Data Sci. 2023 Oct 16;8(1):2123. doi: 10.23889/ijpds.v8i1.2123. eCollection 2023.
The healthcare system in Manitoba, Canada has faced long wait times for many surgical procedures and investigations, including orthopedic and ophthalmology surgeries. Wait times for surgical procedures is considered a significant barrier to accessing healthcare in Canada and can have negative health outcomes for patients. We developed models to forecast anticipated surgical procedure demands up to 2027. This paper explores the opportunities and challenges of using administrative data to describe forecasts of surgical service delivery.
This study used whole population linked administrative health data to predict future orthopedic and ophthalmology surgical procedure demands up to 2027. Procedure codes (CCI) from hospital discharge abstracts and medical claims data were used in the modelling. A Seasonal Autoregressive Integrated Moving Average model provided the best fit to the data from April 1, 2004 to March 31, 2020.
Initial analyses of only hospital-based procedures excluded a significant portion of provider workload, namely those services provided in clinics. We identified 500,732 orthopedic procedures completed between April 1, 2004 and March 31, 2020 (349,171 procedures identified from hospital discharge abstracts and 151,561 procedures from medical claims). Procedure volumes for these services are expected to rise 17.7% from 2020 (36,542) to 2027 (43,011), including the forecasted 43.9% increase in clinic-based procedures. Of the 660,127 ophthalmology procedures completed between April 1, 2004 and March 31, 2020, 230,717 procedures were identified from hospital discharge abstracts and 429,410 from medical claims. Models forecasted a 27.7% increase from 2020 (69,598) to 2027 (88,893) with most procedures being performed in clinics.
Researchers should consider including multiple datasets to add information that may have been missing from the presumed data source in their research approach. Confirming the completeness of the data is critical in modelling accurate predictions. Forecast modelling techniques have evolved but still require validation.
加拿大马尼托巴省的医疗体系在许多外科手术和检查方面都面临着长时间的等待，包括矫形和眼科手术。手术等待时间被认为是在加拿大获得医疗保健的一个重大障碍，并且会对患者的健康产生负面影响。我们开发了模型来预测到 2027 年的预期手术需求。本文探讨了使用行政数据来描述手术服务提供预测的机会和挑战。
本研究使用全人群链接的行政健康数据来预测到 2027 年的未来矫形和眼科手术需求。手术程序代码（CCI）来自医院出院摘要和医疗索赔数据，用于建模。季节性自回归综合移动平均模型对 2004 年 4 月 1 日至 2020 年 3 月 31 日的数据提供了最佳拟合。
仅对基于医院的程序进行的初步分析排除了很大一部分提供者工作量，即那些在诊所提供的服务。我们确定了 2004 年 4 月 1 日至 2020 年 3 月 31 日期间完成的 500,732 例矫形手术（从医院出院摘要中确定了 349,171 例手术，从医疗索赔中确定了 151,561 例手术）。这些服务的程序量预计将从 2020 年的 36,542 例增加到 2027 年的 43,011 例，包括诊所基础程序预计增加的 43.9%。在 2004 年 4 月 1 日至 2020 年 3 月 31 日期间完成的 660,127 例眼科手术中，从医院出院摘要中确定了 230,717 例手术，从医疗索赔中确定了 429,410 例手术。模型预测从 2020 年的 69,598 例增加到 2027 年的 88,893 例，增加了 27.7%，其中大部分手术是在诊所进行的。
研究人员在研究方法中应考虑包含多个数据集，以补充假定数据源中可能缺失的信息。确认数据的完整性对于建模准确预测至关重要。预测建模技术已经发展，但仍需要验证。
