Literature DB >> 29350509

Measuring overuse with electronic health records data.

Thomas Isaac1, Meredith B Rosenthal, Carrie H Colla, Nancy E Morden, Alexander J Mainor, Zhonghe Li, Kevin H Nguyen, Elizabeth A Kinsella, Thomas D Sequist.   

Abstract

OBJECTIVES: To measure overuse of low-value care using electronic health record (EHR) data and manual chart review and to evaluate whether certain low-value services are better captured using EHR data. STUDY
DESIGN: We implemented algorithms to extract performance on 13 Choosing Wisely-identified healthcare services using EHR data at a large physician practice group between 2011 and 2013.
METHODS: We calculated rates of overuse using automated EHR extracts. We manually reviewed the charts for 200 cases of overuse for each measure to determine if they had clinical risk factors that could explain use of the low-value service and then calculated adjusted rates of overuse. We explored trends in overuse for each low-value service in the 3-year duration using logistic regression.
RESULTS: Unadjusted rates of overuse ranged from 0.2% to 92%. Automated EHR extracts and manual chart review identified explanatory risk factors for most measures, although the magnitude varied: for some measures (eg, bone densitometry exam for women younger than 65 years), manual chart review did not identify many additional risks (3.0%). In contrast, in patients who had sinus computed tomography or an antibiotic prescription for uncomplicated acute rhinosinusitis, manual chart review identified more explanatory risk factors (22.5%) than the automated EHR extract (9.5%). Adjusted rates of overuse ranged from 0.2% to 61.9%. Eight services demonstrated a statistically significant decrease in overuse over 3 years, while 1 increased significantly.
CONCLUSIONS: The use of EHR data, both extracted and manually abstracted, provides an opportunity to more accurately and reliably identify overuse of low-value healthcare services.

Entities:  

Mesh:

Year:  2018        PMID: 29350509

Source DB:  PubMed          Journal:  Am J Manag Care        ISSN: 1088-0224            Impact factor:   2.229


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