Article Text

Data-driven approach to identifying potential laboratory overuse in general internal medicine (GIM) inpatients
  1. Adina S Weinerman1,2,
  2. Yishan Guo3,
  3. Sudipta Saha3,
  4. Paul M Yip4,5,
  5. Lauren Lapointe-Shaw1,6,7,
  6. Michael Fralick1,8,
  7. Janice L Kwan1,8,
  8. Thomas E MacMillan1,6,
  9. Jessica Liu1,6,
  10. Shail Rawal1,6,
  11. Kathleen A Sheehan1,9,10,
  12. Janet Simons11,
  13. Terence Tang1,12,
  14. Sacha Bhatia1,13,
  15. Fahad Razak1,3,7,14,
  16. Amol A Verma1,3,7,14
  1. 1 Department of Medicine, University of Toronto, Toronto, Ontario, Canada
  2. 2 Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
  3. 3 Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada
  4. 4 Precision Diagnostics and Therapeutics Program, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
  5. 5 Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
  6. 6 Department of Medicine, University Health Network, Toronto, Ontario, Canada
  7. 7 Institute for Health Policy, Management, and Evaluation, Toronto, Ontario, Canada
  8. 8 Department of Medicine, Sinai Health System, Toronto, Ontario, Canada
  9. 9 Centre for Mental Health, University Health Network, Toronto, Ontario, Canada
  10. 10 Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada
  11. 11 Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, Ontario, Canada
  12. 12 Institute of Better Health, Trillium Health Partners, Mississauga, Ontario, Canada
  13. 13 Division of Cardiology, University Health Network, Toronto, Ontario, Canada
  14. 14 Department of Medicine, St. Michael's Hospital, Toronto, Ontario, Canada
  1. Correspondence to Dr Adina S Weinerman; Adina.Weinerman{at}sunnybrook.ca

Abstract

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.

  • Healthcare quality improvement
  • Laboratory medicine
  • Quality improvement

Data availability statement

Data are available upon reasonable request. We will endeavour to make data available upon reasonable request, in compliance with research ethics protocols and privacy policies.

http://creativecommons.org/licenses/by-nc/4.0/

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

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Data availability statement

Data are available upon reasonable request. We will endeavour to make data available upon reasonable request, in compliance with research ethics protocols and privacy policies.

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  • Contributors All others contributed in a meaningful way from either design and implementation of the research, to the analysis of the results or to the writing and substantial review of the manuscript. ASW, Guarantor.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • 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.