Objective: To demonstrate application of data integration technology for observing the effectiveness of interventions to control pathology orders in Emergency Departments.

Background: 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.

Methods: 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).

Results: 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.

Conclusion: 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.