de Lusignan S, Chan T, Wells S, Cooper A, Harvey M, Brew S, Wright M
Kent, Surrey and Sussex Primary Care Research Network, The Ridgewood Centre, Old Bisley Road, Frimley, Camberley, Surrey GU16 5QE, UK.
Public Health. 2003 Nov;117(6):438-45. doi: 10.1016/S0033-3506(03)00129-X.
Although UK general practice is highly computerized, comprehensive use of these computers is often limited to registration data and the issue of repeat prescriptions. The recording of diagnostic data is patchy. This study examines whether patients with, or at risk of, osteoporosis can be readily identified from general practice computer records. It reports the findings of a pilot study designed to show the variability of recording the diagnosis of osteoporosis and osteopenia, as well as how useful surrogate markers might be to identify these patients. The study also illustrates the difficulties that even skilled practitioners in a primary care research network experience in extracting clinical data from practice information systems. Computer searches were carried out across six practices in a general practice research network in the south-east of England. Two of these practices had previously undertaken research projects in osteoporosis and were consequently expected to have excellent data quality in osteoporosis. These two practices had a combined list size of 27,500 and the remaining practices had a combined practice population of 43,000 patients. The data were found to be variable with over 10-fold differences between practices in the recorded prevalence of osteoporosis diagnosis as well as its surrogate markers-such as fragility fractures, long-term steroid prescription, etc. There was no difference in data quality between the two practices that had conducted osteoporosis research and the rest of the group, other than in the areas of diagnostic recording and prescribing for osteoporosis and recording of fractures. Issues were raised by the practices that struggled to identify patients at risk of osteoporosis about the limitations of Read classification in this disease area. Practices need further assistance if the patients at risk are to be identified. Without urgent action, it will be difficult for practices to identify the patients who are likely to benefit from Standard 6-'Falls' of the National Service Framework for Older People. These findings also have broader implications as UK general practice moves towards the implementation of a quality-based contract.
尽管英国的全科医疗已高度计算机化,但这些计算机的全面应用往往仅限于登记数据和重复处方的开具。诊断数据的记录并不完整。本研究探讨能否从全科医疗计算机记录中轻松识别出患有骨质疏松症或有骨质疏松症风险的患者。它报告了一项试点研究的结果,该研究旨在展示骨质疏松症和骨质减少症诊断记录的变异性,以及替代指标在识别这些患者方面可能有多大用处。该研究还说明了即使是初级保健研究网络中的熟练从业者在从实践信息系统中提取临床数据时所遇到的困难。在英格兰东南部的一个全科医疗研究网络中,对六个诊所进行了计算机检索。其中两个诊所此前曾开展过骨质疏松症研究项目,因此预计其骨质疏松症数据质量优异。这两个诊所的患者名单总数为27500人,其余诊所的患者总数为43000人。研究发现数据存在差异,各诊所记录的骨质疏松症诊断患病率及其替代指标(如脆性骨折、长期使用类固醇处方等)相差10倍以上。除了在骨质疏松症的诊断记录、处方开具和骨折记录方面,开展过骨质疏松症研究的两个诊所与该组其他诊所的数据质量没有差异。那些难以识别骨质疏松症风险患者的诊所提出了关于Read分类法在该疾病领域局限性的问题。如果要识别有风险的患者,诊所需要进一步的帮助。如果不采取紧急行动,诊所将很难识别出可能从《老年人国家服务框架》标准6“跌倒”中受益的患者。随着英国全科医疗朝着实施基于质量的合同迈进,这些发现也具有更广泛的意义。