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Successful demand management in diagnostic immunology testing
  1. Kristen Lilly1,
  2. Nathan Proudlove2,
  3. Claire Bethune1
  1. 1Department of Immunology and Allergy, University Hospitals Plymouth NHS Trust, Plymouth, UK
  2. 2Alliance Manchester Business School, The University of Manchester, Manchester, UK
  1. Correspondence to Kristen Lilly, Department of Immunology and Allergy, University Hospitals Plymouth NHS Trust, Plymouth, Plymouth, UK; kristenlilly{at}nhs.net

Abstract

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.

  • Allergy and Immunology
  • Antigen Presentation
  • COMPUTER SYSTEMS
  • DIAGNOSIS
  • QUALITY CONTROL

Data availability statement

All data relevant to the study are included in the article or uploaded as online supplemental information.

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Data availability statement

All data relevant to the study are included in the article or uploaded as online supplemental information.

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Footnotes

  • Handling editor Tahir S Pillay.

  • Contributors KL and CB designed the project. KL obtained the data, which NP analysed. All authors interpreted the data and wrote and reviewed the drafts. CB is the guarantor of the manuscript.

  • Funding An innovation project grant was awarded to CB by University Hospital Plymouth NHS Trust Research and Development Department that funded the IT work underpinning the project. NHS Higher Specialist Scientist Training Programme (HSST) study time was used in the writing up of the report.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.