BMJ Open Quality (Sep 2023)

Data-driven approach to identifying potential laboratory overuse in general internal medicine (GIM) inpatients

  • Amol A Verma,
  • Michael Fralick,
  • Lauren Lapointe-Shaw,
  • Yishan Guo,
  • Shail Rawal,
  • Janice L Kwan,
  • Terence Tang,
  • Fahad Razak,
  • Sacha Bhatia,
  • Paul M Yip,
  • Sudipta Saha,
  • Jessica Liu,
  • Kathleen A Sheehan,
  • Thomas E MacMillan,
  • Adina S Weinerman,
  • Janet Simons

DOI
https://doi.org/10.1136/bmjoq-2023-002261
Journal volume & issue
Vol. 12, no. 3

Abstract

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Background Reducing laboratory test overuse is important for high quality, patient-centred care. Identifying priorities to reduce low value testing remains a challenge.Objective To develop a simple, data-driven approach to identify potential sources of laboratory overuse by combining the total cost, proportion of abnormal results and physician-level variation in use of laboratory tests.Design, setting and participants A multicentre, retrospective study at three academic hospitals in Toronto, Canada. All general internal medicine (GIM) hospitalisations between 1 April 2010 and 31 October 2017.Results There were 106 813 GIM hospitalisations during the study period, with median hospital length-of-stay of 4.6 days (IQR: 2.33–9.19). There were 21 tests which had a cumulative cost >US$15 400 at all three sites. The costliest test was plasma electrolytes (US$4 907 775), the test with the lowest proportion of abnormal results was red cell folate (0.2%) and the test with the greatest physician-level variation in use was antiphospholipid antibodies (coefficient of variation 3.08). The five tests with the highest cumulative rank based on greatest cost, lowest proportion of abnormal results and highest physician-level variation were: (1) lactate, (2) antiphospholipid antibodies, (3) magnesium, (4) troponin and (5) partial thromboplastin time. In addition, this method identified unique tests that may be a potential source of laboratory overuse at each hospital.Conclusions A simple multidimensional, data-driven approach combining cost, proportion of abnormal results and physician-level variation can inform interventions to reduce laboratory test overuse. Reducing low value laboratory testing is important to promote high value, patient-centred care.