The first step is recognizing there is a problem: a methodology for adjusting for variability in disease severity when estimating clinician performance

Amaral, LAN (通讯作者),Northwestern Univ, Northwestern Inst Complex Syst, 2145 Sheridan Rd,Room E136, Evanston, IL 60208 USA.;Weiss, CH (通讯作者),NorthShore Univ HealthSyst, Div Pulm Crit Care Allergy & Immunol, 1001 Univ Pl,Suite 162, Evanston, IL 60201 USA.;Amaral, LAN (通讯作者),Northwestern Univ, Dept Chem & Biol Engn, Evanston, IL 60208 USA.;Amaral, LAN (通讯作者),Northwestern Univ, Dept Phys & Astron, Evanston, IL 60208 USA.
2022-3-16
Background Adoption of innovations in the field of medicine is frequently hindered by a failure to recognize the condition targeted by the innovation. This is particularly true in cases where recognition requires integration of patient information from different sources, or where disease presentation can be heterogeneous and the recognition step may be easier for some patients than for others. Methods We propose a general data-driven metric for clinician recognition that accounts for the variability in patient disease severity and for institutional standards. As a case study, we evaluate the ventilatory management of 362 patients with acute respiratory distress syndrome (ARDS) at a large academic hospital, because clinician recognition of ARDS has been identified as a major barrier to adoption to evidence-based ventilatory management. We calculate our metric for the 48 critical care physicians caring for these patients and examine the relationships between differences in ARDS recognition performance from overall institutional levels and provider characteristics such as demographics, social network position, and self-reported barriers and opinions. Results Our metric was found to be robust to patient characteristics previously demonstrated to affect ARDS recognition, such as disease severity and patient height. Training background was the only factor in this study that showed an association with physician recognition. Pulmonary and critical care medicine (PCCM) training was associated with higher recognition (beta = 0.63, 95% confidence interval 0.46-0.80, p < 7 x 10(- 5)). Non-PCCM physicians recognized ARDS cases less frequently and expressed greater satisfaction with the ability to get the information needed for making an ARDS diagnosis (p < 5 x 10(- 4)), suggesting that lower performing clinicians may be less aware of institutional barriers. Conclusions We present a data-driven metric of clinician disease recognition that accounts for variability in patient disease severity and for institutional standards. Using this metric, we identify two unique physician populations with different intervention needs. One population consistently recognizes ARDS and reports barriers vs one does not and reports fewer barriers.
BMC MEDICAL RESEARCH METHODOLOGY
卷号:22|期号:1
收录类别:SCIE
语种
英语
来源机构
Northwestern University; Feinberg School of Medicine; Northwestern University; Northwestern University; Northwestern University; Feinberg School of Medicine; Northwestern University; Feinberg School of Medicine; NorthShore University Health System; Northwestern University; Northwestern University
资助信息
This project was supported by the National Institute of General Medical Sciences, Grant T32GM008152 (MB); the National Heart, Lung, and Blood Institute, Grant K23HL118139 and Grant R01HL140362-01A1 (CHW); the Francis Family Foundation (Parker B. Francis Fellowship Program, CHW); the Department of Defense Army Research Office, Grant W911NF-14-1-0259 (MB, LANA, CHW); the National Center for Research Resources, Grant 5UL1RR025741, which is now at the National Center for Advancing Translational Sciences, Grant 8UL1TR000150 (Northwestern University Clinical and Translational Sciences Institute Enterprise Data Warehouse); and John and Leslie McQuown (MB, LANA). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health, the Francis Family Foundation, or the Department of Defense. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
被引频次(WOS)
0
被引频次(其他)
0
180天使用计数
0
2013以来使用计数
0
EISSN
1471-2288
出版年
2022-3-16
DOI
10.1186/s12874-022-01543-7
WOS学科分类
Health Care Sciences & Services
学科领域
循证公共卫生
关键词
Clinical medicine Performance measure Data science Social network analysis Critical care
资助机构
National Institute of General Medical Sciences(United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Institute of General Medical Sciences (NIGMS)) National Heart, Lung, and Blood Institute(United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Heart Lung & Blood Institute (NHLBI)) Francis Family Foundation Department of Defense Army Research Office(United States Department of Defense) National Center for Research Resources(United States Department of Health & Human ServicesNational Institutes of Health (NIH) - USANIH National Center for Research Resources (NCRR))