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

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 co...

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Autores principales: Weinerman, Adina S, Guo, Yishan, Saha, Sudipta, Yip, Paul M, Lapointe-Shaw, Lauren, Fralick, Michael, Kwan, Janice L, MacMillan, Thomas E, Liu, Jessica, Rawal, Shail, Sheehan, Kathleen A, Simons, Janet, Tang, Terence, Bhatia, Sacha, Razak, Fahad, Verma, Amol A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10373691/
https://www.ncbi.nlm.nih.gov/pubmed/37495257
http://dx.doi.org/10.1136/bmjoq-2023-002261
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author Weinerman, Adina S
Guo, Yishan
Saha, Sudipta
Yip, Paul M
Lapointe-Shaw, Lauren
Fralick, Michael
Kwan, Janice L
MacMillan, Thomas E
Liu, Jessica
Rawal, Shail
Sheehan, Kathleen A
Simons, Janet
Tang, Terence
Bhatia, Sacha
Razak, Fahad
Verma, Amol A
author_facet Weinerman, Adina S
Guo, Yishan
Saha, Sudipta
Yip, Paul M
Lapointe-Shaw, Lauren
Fralick, Michael
Kwan, Janice L
MacMillan, Thomas E
Liu, Jessica
Rawal, Shail
Sheehan, Kathleen A
Simons, Janet
Tang, Terence
Bhatia, Sacha
Razak, Fahad
Verma, Amol A
author_sort Weinerman, Adina S
collection PubMed
description 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.
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spelling pubmed-103736912023-07-28 Data-driven approach to identifying potential laboratory overuse in general internal medicine (GIM) inpatients Weinerman, Adina S Guo, Yishan Saha, Sudipta Yip, Paul M Lapointe-Shaw, Lauren Fralick, Michael Kwan, Janice L MacMillan, Thomas E Liu, Jessica Rawal, Shail Sheehan, Kathleen A Simons, Janet Tang, Terence Bhatia, Sacha Razak, Fahad Verma, Amol A BMJ Open Qual Original Research 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. BMJ Publishing Group 2023-07-26 /pmc/articles/PMC10373691/ /pubmed/37495257 http://dx.doi.org/10.1136/bmjoq-2023-002261 Text en © 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. https://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/ (https://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Original Research
Weinerman, Adina S
Guo, Yishan
Saha, Sudipta
Yip, Paul M
Lapointe-Shaw, Lauren
Fralick, Michael
Kwan, Janice L
MacMillan, Thomas E
Liu, Jessica
Rawal, Shail
Sheehan, Kathleen A
Simons, Janet
Tang, Terence
Bhatia, Sacha
Razak, Fahad
Verma, Amol A
Data-driven approach to identifying potential laboratory overuse in general internal medicine (GIM) inpatients
title Data-driven approach to identifying potential laboratory overuse in general internal medicine (GIM) inpatients
title_full Data-driven approach to identifying potential laboratory overuse in general internal medicine (GIM) inpatients
title_fullStr Data-driven approach to identifying potential laboratory overuse in general internal medicine (GIM) inpatients
title_full_unstemmed Data-driven approach to identifying potential laboratory overuse in general internal medicine (GIM) inpatients
title_short Data-driven approach to identifying potential laboratory overuse in general internal medicine (GIM) inpatients
title_sort data-driven approach to identifying potential laboratory overuse in general internal medicine (gim) inpatients
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10373691/
https://www.ncbi.nlm.nih.gov/pubmed/37495257
http://dx.doi.org/10.1136/bmjoq-2023-002261
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