Successful demand management in diagnostic immunology testing

Aims We investigated whether we could have a material and sustained impact on immunology test ordering by primary care clinicians by building evidence-based and explanatory algorithms into test ordering software. Methods A service evaluation revealed cases of over-requesting of antinuclear antibody, allergen-specific IgE and total IgE tests, and under-requesting of urine protein electrophoresis. We conducted a quality improvement programme to address this. We determined the most effective and efficient intervention would be to embed evidence-based and advice-based decision-support algorithms in the ordering software. Consultation with general practitioners revealed lack of knowledge and confidence about testing, and an appetite for support. We iteratively designed and implemented algorithms for the four sets of tests for the primary care practices in our catchment and made them available to other hospital trusts in our region. The ordering system now contains links to advice sheets for clinicians and their patients and to an email address for queries to the lab. Results We observe large (36% to 88%) reductions in testing activity (workload) for the over-requested tests and large (28%–135%) increases for the under-requested test. We show that these changes are sustained. There have been no complaints from the clinicians and queries to the lab are now minimal (less than one per month on average). Conclusions Embedding algorithms in the ordering software can be acceptable to clinicians and have a major and sustained impact on overuse or underuse of tests. The algorithms can be replicated by other hospital trusts.