Nicholson Kathryn, Terry Amanda L, Fortin Martin, Williamson Tyler, Bauer Michael, Thind Amardeep
Department of Epidemiology and Biostatistics, Schulich School of Medicine and Dentistry, Centre for Studies in Family Medicine, Western University, Ontario, Canada.
Department of Epidemiology and Biostatistics; and Department of Family Medicine, Interfaculty Program in Public Health, Schulich School of Medicine and Dentistry, Western University, Ontario, Canada.
J Comorb. 2015 Dec 22;5:150-161. doi: 10.15256/joc.2015.5.61. eCollection 2015.
In many developed countries, the burden of disease has shifted from acute to long-term or chronic diseases - producing new and broader challenges for patients, healthcare providers, and healthcare systems. Multimorbidity, the coexistence of two or more chronic diseases within an individual, is recognized as a significant public health and research priority. This protocol aims to examine the prevalence, characteristics, and changing burden of multimorbidity among adult primary healthcare (PHC) patients using electronic medical record (EMR) data. The objectives are two-fold: (1) to measure the point prevalence and clusters of multimorbidity among adult PHC patients; and (2) to examine the natural history and changing burden of multimorbidity over time among adult PHC patients. Data will be derived from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN). The CPCSSN database contains longitudinal, point-of-care data from EMRs across Canada. To identify adult patients with multimorbidity, a list of 20 chronic disease categories (and corresponding ICD-9 codes) will be used. A computational cluster analysis will be conducted using a customized computer program written in JAVA. A Cox proportional hazards analysis will be used to model time-to-event data, while simultaneously adjusting for provider- and patient-level predictors. All analyses will be conducted using STATA SE 13.1. This research is the first of its kind using a pan-Canadian EMR database, which will provide an opportunity to contribute to the international evidence base. Future work should systematically compare international research using similar robust methodologies to determine international and geographical variations in the epidemiology of multimorbidity.
在许多发达国家，疾病负担已从急性病转向长期或慢性病，给患者、医疗服务提供者和医疗系统带来了新的、更广泛的挑战。多种慢性病共存（即个体同时患有两种或更多种慢性病）被视为一项重大的公共卫生和研究重点。本方案旨在利用电子病历（EMR）数据，研究成年初级医疗保健（PHC）患者中多种慢性病共存的患病率、特征及其不断变化的负担。目标有两个：（1）测量成年初级医疗保健患者中多种慢性病共存的时点患病率和聚集情况；（2）研究成年初级医疗保健患者中多种慢性病共存的自然病程及其随时间变化的负担。数据将来源于加拿大初级保健哨点监测网络（CPCSSN）。CPCSSN数据库包含来自加拿大各地电子病历的纵向即时医疗数据。为了识别患有多种慢性病的成年患者，将使用一份包含20种慢性病类别（及相应的ICD - 9编码）的清单。将使用用JAVA编写的定制计算机程序进行计算聚类分析。将使用Cox比例风险分析对事件发生时间数据进行建模，同时对医疗服务提供者和患者层面的预测因素进行调整。所有分析将使用STATA SE 13.1进行。这项研究是首次使用全加拿大电子病历数据库，这将为国际证据库做出贡献提供一个机会。未来的工作应系统地比较采用类似稳健方法的国际研究，以确定多种慢性病共存流行病学的国际和地理差异。
