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

Autor:	Weinerman AS; Department of Medicine, University of Toronto, Toronto, Ontario, Canada Adina.Weinerman@sunnybrook.ca.; Department of Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada., Guo Y; Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada., Saha S; Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada., Yip PM; Precision Diagnostics and Therapeutics Program, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada., Lapointe-Shaw L; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Department of Medicine, University Health Network, Toronto, Ontario, Canada.; Institute for Health Policy, Management, and Evaluation, Toronto, Ontario, Canada., Fralick M; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Department of Medicine, Sinai Health System, Toronto, Ontario, Canada., Kwan JL; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Department of Medicine, Sinai Health System, Toronto, Ontario, Canada., MacMillan TE; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Department of Medicine, University Health Network, Toronto, Ontario, Canada., Liu J; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Department of Medicine, University Health Network, Toronto, Ontario, Canada., Rawal S; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Department of Medicine, University Health Network, Toronto, Ontario, Canada., Sheehan KA; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Centre for Mental Health, University Health Network, Toronto, Ontario, Canada.; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada., Simons J; Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, Ontario, Canada., Tang T; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Institute of Better Health, Trillium Health Partners, Mississauga, Ontario, Canada., Bhatia S; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Division of Cardiology, University Health Network, Toronto, Ontario, Canada., Razak F; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.; Institute for Health Policy, Management, and Evaluation, Toronto, Ontario, Canada.; Department of Medicine, St. Michael's Hospital, Toronto, Ontario, Canada., Verma AA; Department of Medicine, University of Toronto, Toronto, Ontario, Canada.; Li Ka Shing Knowledge Institute, St Michael's Hospital, Toronto, Ontario, Canada.; Institute for Health Policy, Management, and Evaluation, Toronto, Ontario, Canada.; Department of Medicine, St. Michael's Hospital, Toronto, Ontario, Canada.
Jazyk:	angličtina
Zdroj:	BMJ open quality [BMJ Open Qual] 2023 Jul; Vol. 12 (3).
DOI:	10.1136/bmjoq-2023-002261
Abstrakt:	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. Competing Interests: Competing interests: None declared. (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Databáze:	MEDLINE
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