Kathryn Nicholson, Amanda L Terry, Martin Fortin, Tyler Williamson, Michael Bauer, Amardeep Thind
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引用次数: 26
摘要
在许多发达国家,疾病负担已从急性疾病转向长期或慢性疾病,这给患者、卫生保健提供者和卫生保健系统带来了新的更广泛的挑战。多重发病,即个体内同时存在两种或两种以上的慢性疾病,被认为是公共卫生和研究的重要重点。本研究方案旨在利用电子病历(EMR)数据研究成人初级保健(PHC)患者中多病的患病率、特征和变化负担。目的有两个:(1)测量成人PHC患者的多点患病率和多病聚集性;(2)研究成人PHC患者多重发病的自然历史和随时间变化的负担。数据将来自加拿大初级保健哨点监测网络(cpcsn)。cpcsn数据库包含来自加拿大各地电子病历的纵向护理点数据。为了确定患有多种疾病的成年患者,将使用20种慢性病类别清单(以及相应的ICD-9代码)。计算聚类分析将使用用JAVA编写的定制计算机程序进行。Cox比例风险分析将用于模拟事件时间数据,同时调整提供者和患者水平的预测因子。所有分析将使用STATA SE 13.1进行。这项研究是同类研究中首次使用泛加拿大电子病历数据库,这将为国际证据库提供贡献机会。未来的工作应该使用类似的可靠方法系统地比较国际研究,以确定多病流行病学的国际和地理差异。
Examining the prevalence and patterns of multimorbidity in Canadian primary healthcare: a methodologic protocol using a national electronic medical record database.
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.