Wagholikar Amol, O'Dwyer John, Hansen David, Chu Kevin
The Australian E-Health Research Centre, CSIRO ICT Centre, Brisbane, Australia.
Stud Health Technol Inform. 2011;168:172-8.
To demonstrate application of data integration technology for observing the effectiveness of interventions to control pathology orders in Emergency Departments.
Doctors frequently need to order blood tests in the Emergency Departments as a part of diagnostic set up in Emergency Departments. However, pathology test ordering is excessive and often unnecessary. The excessive ordering of blood test places a significant financial burden on our health care system. It also causes undue discomfort and worry to the patients. There are many interventions employed to control pathology ordering in Emergency Departments. The analysis of effectiveness of interventions is required for improving clinical practices in Emergency Departments. However, the collection and extraction of data on the effects of intervention can be very costly and time consuming. Therefore, there is a need of a technology-based solution to access, query and analyse data residing across different sources.
The research aims to determine efficacy of an intervention called the "Traffic Light System" through a pathology request form used to control the pathology ordering in one adult hospital emergency department. Health Data Integration (HDI) technology was implemented to link and query the data residing at different source systems i.e. pathology and ED information system. The data was extracted from the Emergency Department Information System at an adult tertiary hospital in Queensland. Twenty weeks of pre-intervention data was collected. Twenty weeks of post-intervention data was collected after 32-week transition interval. The data for pre-intervention, transition and post-intervention period was analysed to assess the effectiveness of the intervention in reducing commonly ordered pathology tests such as Full Blood Counts (FBC) and Erythrocyte Sedimentation Rate (ESR).
The total number of FBC tests ordered in the pre-intervention period fell slightly in the post-intervention period (mean 42.3 vs 38.1 per 100 patients). The total number Erythrocyte Sedimentation Rate tests showed a significant declining trend as a result of ED intervention (2.5 vs 1.4 per 100 patients, p=0.001). HDI completed the task of data extraction, manipulation and querying in seconds. A manual check of a sample of 200 pathology test orders shows 95.5% sensitivity, which is considered accurate enough for this purpose.
Pathology ordering can be reduced using sustainable protocols. This work has demonstrated HDI capability to extract and link pathology data efficiently to evaluate an ED intervention.
展示数据集成技术在观察急诊科控制病理检查医嘱干预措施效果方面的应用。
在急诊科，医生经常需要开具血液检查医嘱，作为急诊科诊断流程的一部分。然而，病理检查医嘱过多且往往不必要。过多的血液检查医嘱给我们的医疗保健系统带来了巨大的经济负担。这也给患者带来了不必要的不适和担忧。急诊科采用了多种干预措施来控制病理检查医嘱。为改善急诊科的临床实践，需要对干预措施的效果进行分析。然而，收集和提取干预效果数据可能非常昂贵且耗时。因此，需要一种基于技术的解决方案来访问、查询和分析来自不同来源的数据。
本研究旨在通过一份病理检查申请表，确定一种名为“交通灯系统”的干预措施在一家成人医院急诊科控制病理检查医嘱方面的效果。实施了健康数据集成（HDI）技术，以链接和查询存储在不同源系统（即病理和急诊科信息系统）中的数据。数据从昆士兰州一家成人三级医院的急诊科信息系统中提取。收集了干预前20周的数据。在32周的过渡期后，收集了干预后20周的数据。对干预前、过渡期和干预后的数据进行分析，以评估该干预措施在减少常见病理检查（如全血细胞计数（FBC）和红细胞沉降率（ESR））方面的效果。
干预前开具的FBC检查总数在干预后略有下降（平均每100名患者分别为42.3次和38.1次）。由于急诊科的干预，红细胞沉降率检查总数呈现出显著下降趋势（每100名患者分别为2.5次和1.4次，p = 0.001）。HDI在数秒内完成了数据提取、处理和查询任务。对200份病理检查医嘱样本进行人工检查，显示灵敏度为95.5%，就该目的而言，这被认为足够准确。
可以使用可持续的方案减少病理检查医嘱。这项工作展示了HDI有效提取和链接病理数据以评估急诊科干预措施的能力。
