使用电子病历数据评估慢性肾脏疾病、2型糖尿病和心血管疾病的检测、识别和管理,记录在澳大利亚的一般做法:横断面分析。

IF 2.6 3区 医学 Q1 PRIMARY HEALTH CARE
Julia L Jones, Natalie G Lumsden, Koen Simons, Anis Ta'eed, Maximilian P de Courten, Tissa Wijeratne, Nicholas Cox, Christopher J A Neil, Jo-Anne Manski-Nankervis, Peter Shane Hamblin, Edward D Janus, Craig L Nelson
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引用次数: 2

摘要

目的:评价全科医生(GP)电子病历(EMR)数据在相关慢性血管疾病——慢性肾脏疾病(CKD)、2型糖尿病(T2D)和心血管疾病的危险因素检测、疾病诊断检测、诊断、监测和药物治疗方面的能力。设计:对2017年4月12日至2017年4月18日期间每个实践的单一日期提取的数据进行横断面分析,纳入数据提取当天或之前的任何时间的数据,使用来自初级保健慢性病早期发现和改进管理项目的基线数据。使用Pen计算机系统临床审计工具从GP电子病历中提取未识别的数据,并使用描述性统计来描述研究人群。背景:澳大利亚维多利亚州的八名全科医生。参与者:患者年龄≥18岁,24个月内就诊GP≥3次。共纳入37946例患者。结果:风险因素和疾病检测/监测/治疗按照澳大利亚指南进行评估(如果没有美国指南,则按美国指南进行评估),并在需要时由于数据可用性的限制而对指南进行了简化。需要者的危险因素评估:30%的患者体重指数和46%的血压在指南推荐的时间范围内。高危人群的诊断检测:17%的人按照CKD的建议进行了诊断检测,37%的人进行了T2D的诊断检测。可能未确诊的疾病:6.7%的CKD患者、1.6%的T2D患者和0.33%的家族性高胆固醇血症患者的病理检查显示可能存在未确诊的疾病。总体患病率:CKD的编码诊断为3.8%,T2D为6.6%,缺血性心脏病为4.2%,心力衰竭为1%,缺血性卒中为1.7%,外周血管疾病为0.46%,家族性高胆固醇血症为0.06%,房颤为2%。药物处方:患者使用指南推荐药物的比例从44%(缺血性心脏病患者的-受体阻滞剂)到78%(缺血性卒中患者的抗血小板或抗凝剂)不等。结论:利用GP EMR数据,本研究确定了慢性血管疾病的记录诊断通常与报告的全国患病率相似或更高。它建议进行低水平的可提取的记录在案的风险因素评估,对有风险的人进行诊断测试,并对某些情况开具指南推荐的药物治疗处方。这些基线数据突出了GP电子病历数据在流行病学研究中的潜在用途,并通过个人实践指导有针对性的质量改进。它还强调了使用GP电子病历数据的一些挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Using electronic medical record data to assess chronic kidney disease, type 2 diabetes and cardiovascular disease testing, recognition and management as documented in Australian general practice: a cross-sectional analysis.

Using electronic medical record data to assess chronic kidney disease, type 2 diabetes and cardiovascular disease testing, recognition and management as documented in Australian general practice: a cross-sectional analysis.

Using electronic medical record data to assess chronic kidney disease, type 2 diabetes and cardiovascular disease testing, recognition and management as documented in Australian general practice: a cross-sectional analysis.

Using electronic medical record data to assess chronic kidney disease, type 2 diabetes and cardiovascular disease testing, recognition and management as documented in Australian general practice: a cross-sectional analysis.

Objectives: To evaluate the capacity of general practice (GP) electronic medical record (EMR) data to assess risk factor detection, disease diagnostic testing, diagnosis, monitoring and pharmacotherapy for the interrelated chronic vascular diseases-chronic kidney disease (CKD), type 2 diabetes (T2D) and cardiovascular disease.

Design: Cross-sectional analysis of data extracted on a single date for each practice between 12 April 2017 and 18 April 2017 incorporating data from any time on or before data extraction, using baseline data from the Chronic Disease early detection and Improved Management in PrimAry Care ProjecT. Deidentified data were extracted from GP EMRs using the Pen Computer Systems Clinical Audit Tool and descriptive statistics used to describe the study population.

Setting: Eight GPs in Victoria, Australia.

Participants: Patients were ≥18 years and attended GP ≥3 times within 24 months. 37 946 patients were included.

Results: Risk factor and disease testing/monitoring/treatment were assessed as per Australian guidelines (or US guidelines if none available), with guidelines simplified due to limitations in data availability where required. Risk factor assessment in those requiring it: 30% of patients had body mass index and 46% blood pressure within guideline recommended timeframes. Diagnostic testing in at-risk population: 17% had diagnostic testing as per recommendations for CKD and 37% for T2D. Possible undiagnosed disease: Pathology tests indicating possible disease with no diagnosis already coded were present in 6.7% for CKD, 1.6% for T2D and 0.33% familial hypercholesterolaemia. Overall prevalence: Coded diagnoses were recorded in 3.8% for CKD, 6.6% for T2D, 4.2% for ischaemic heart disease, 1% for heart failure, 1.7% for ischaemic stroke, 0.46% for peripheral vascular disease, 0.06% for familial hypercholesterolaemia and 2% for atrial fibrillation. Pharmaceutical prescriptions: the proportion of patients prescribed guideline-recommended medications ranged from 44% (beta blockers for patients with ischaemic heart disease) to 78% (antiplatelets or anticoagulants for patients with ischaemic stroke).

Conclusions: Using GP EMR data, this study identified recorded diagnoses of chronic vascular diseases generally similar to, or higher than, reported national prevalence. It suggested low levels of extractable documented risk factor assessments, diagnostic testing in those at risk and prescription of guideline-recommended pharmacotherapy for some conditions. These baseline data highlight the utility of GP EMR data for potential use in epidemiological studies and by individual practices to guide targeted quality improvement. It also highlighted some of the challenges of using GP EMR data.

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来源期刊
CiteScore
9.70
自引率
0.00%
发文量
27
审稿时长
19 weeks
期刊介绍: Family Medicine and Community Health (FMCH) is a peer-reviewed, open-access journal focusing on the topics of family medicine, general practice and community health. FMCH strives to be a leading international journal that promotes ‘Health Care for All’ through disseminating novel knowledge and best practices in primary care, family medicine, and community health. FMCH publishes original research, review, methodology, commentary, reflection, and case-study from the lens of population health. FMCH’s Asian Focus section features reports of family medicine development in the Asia-pacific region. FMCH aims to be an exemplary forum for the timely communication of medical knowledge and skills with the goal of promoting improved health care through the practice of family and community-based medicine globally. FMCH aims to serve a diverse audience including researchers, educators, policymakers and leaders of family medicine and community health. We also aim to provide content relevant for researchers working on population health, epidemiology, public policy, disease control and management, preventative medicine and disease burden. FMCH does not impose any article processing charges (APC) or submission charges.
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