Use of Electronic Health Records and Quality of Ambulatory Healthcare

Autor: Duaa Alammari, Jim E Banta, Huma Shah, Ellen Reibling, Shrenik Talsania
Rok vydání: 2022
Předmět:
Zdroj: Cureus. 14(10)
ISSN: 2168-8184
Popis: Background This study aimed to measure the association between electronic health record (EHR) use and quality measures in ambulatory healthcare. Methodology A quantitative, retrospective, cross-sectional design was used by examining secondary data from the 2015-2016 National Ambulatory Medical Care Survey. The relationship between EHR use and seven quality measures was examined using the Donabedian model as a framework. Quality measures included (a) diabetes measures, (b) obesity measures, (c) blood pressure screening, (d) depression screening, and (e) breast cancer screening. A total of 37,290 office visits were included, representing 817 million national office visits. For each of the quality measures, we determined the (a) associations using unadjusted and adjusted regression models based on subsets of the sample that met the inclusion criteria for quality measures; and (b) the changes in the area under the curve (AUC). Results Approximately 75% of office visits fulfilled all EHR use. Positive associations were found between EHR use and better quality for the following three out of seven measures: higher odds of screening for obesity (odds ratio (OR) = 2.2; p =0.0001), blood pressure (OR = 2.5; p =0.0001), and breast cancer (OR = 1.8; p = 0.0166). Receiver operating curve results showed the highest gain in the AUC for process-grouped measures. Hence, it was considered to be a strong predictor for all quality measures. Conclusions Evidence showed improvement in some quality measures (screening for obesity, blood pressure, and breast cancer). Common and standardized health processes were more likely to be completed and recorded than others. Future policies concerning health information technology can shift the focus from improving EHR use to enhancing patient and quality outcomes. Further research is needed to identify circumstances where quality is improved.
Databáze: OpenAIRE