--- title: "Evaluating Impact of POC Cardiometabolic Clinical Care tool | Sutter Health" description: "This study aimed to evaluate a Cardiometabolic Sutter Health Advanced Reengineered Encounter (CM-SHARE), a web-based application to visualize key EHR data use." url: "https://www.sutterhealth.org/research/publications/evaluating-impact-of-poc-cardiometabolic-clinical-care-tool-1055312804" --- 1. [Home](https://www.sutterhealth.org/) / 2. [Research](https://www.sutterhealth.org/research) / 3. [Research publications](https://www.sutterhealth.org/research/publications) / 4. Evaluating Impact of POC Cardiometabolic Clinical Care tool # Evaluating the Impact of a Point-of-Care Cardiometabolic Clinical Decision Support Tool on Clinical Efficiency Using Electronic Health Record Audit Log Data: Algorithm Development and Validation _JMIR Medical Informatics_ 2022-09-06 ## Abstract Background: Electronic health record (EHR) systems are becoming increasingly complicated, leading to concerns about rising physician burnout, particularly for primary care physicians (PCPs). Managing the most common cardiometabolic chronic conditions by PCPs during a limited clinical time with a patient is challenging. Objective: This study aimed to evaluate a Cardiometabolic Sutter Health Advanced Reengineered Encounter (CM-SHARE), a web-based application to visualize key EHR data, on the EHR use efficiency. Methods: We developed algorithms to identify key clinic workflow measures (eg, total encounter time, total physician time in the examination room, and physician EHR time in the examination room) using audit data, and we validated and calibrated the measures with time-motion data. We used a pre-post parallel design to identify propensity score-matched CM-SHARE users (cases), nonusers (controls), and nested-matched patients. Cardiometabolic encounters from matched case and control patients were used for the workflow evaluation. Outcome measures were compared between the cases and controls. We applied this approach separately to both the CM-SHARE pilot and spread phases. Results: Time-motion observation was conducted on 101 primary care encounters for 9 PCPs in 3 clinics. There was little difference (<0.8 minutes) between the audit data-derived workflow measures and the time-motion observation. Two key unobservable times from audit data, physician entry into and exiting the examination room, were imputed based on time-motion studies. CM-SHARE was launched with 6 pilot PCPs in April 2016. During the prestudy period (April 1, 2015, to April 1, 2016), 870 control patients with 2845 encounters were matched with 870 case patients and encounters, and 727 case patients with 852 encounters were matched with 727 control patients and 3754 encounters in the poststudy period (June 1, 2016, to June 30, 2017). Total encounter time was slightly shorter (mean -2.7, SD 1.4 minutes, 95% CI -4.7 to -0.9; mean -1.6, SD 1.1 minutes, 95% CI -3.2 to -0.1) for cases than controls for both periods. CM-SHARE saves physicians approximately 2 minutes EHR time in the examination room (mean -2.0, SD 1.3, 95% CI -3.4 to -0.9) compared with prestudy period and poststudy period controls (mean -1.9, SD 0.9, 95% CI -3.8 to -0.5). In the spread phase, 48 CM-SHARE spread PCPs were matched with 84 control PCPs and 1272 cases with 3412 control patients, having 1119 and 4240 encounters, respectively. A significant reduction in total encounter time for the CM-SHARE group was observed for short appointments (≤20 minutes; 5.3-minute reduction on average) only. Total physician EHR time was significantly reduced for both longer and shorter appointments (17%-33% reductions). Conclusions: Combining EHR audit log files and clinical information, our approach offers an innovative and scalable method and new measures that can be used to evaluate clinical EHR efficiency of digital tools used in clinical settings. [PubMed abstract](https://pubmed.ncbi.nlm.nih.gov/36066940/) ![J.B. Jones, Ph.D., MBA](https://dyn.mktgcdn.com/p/rIQfkoa5XfKJYCHSVrDKsACQSNJ7jTljZTHKC4Lae2E/fit=crop,gravity=auto,dpr=2,width=188,height=250,quality=100) J.B. Jones, Ph.D., MBA Principal investigator [View profile](https://www.sutterhealth.org/research/investigators/jb-jones-phd-mba-1049680984) ![Xiaowei (Sherry) Yan, Ph.D.](https://dyn.mktgcdn.com/p/NTWox_hkmxIRiqJEc5PXKeBkfR_WMtpSQbEI4J69Xls/fit=crop,gravity=auto,dpr=2,width=188,height=250,quality=100) Xiaowei (Sherry) Yan, Ph.D. Principal investigator [View profile](https://www.sutterhealth.org/research/investigators/xiaowei-sherry-yan-phd-1049681042) ## Research topics - [Cardiovascular Diseases](https://www.sutterhealth.org/research-search-results?query=%22%5C%22Cardiovascular+Diseases%5C%22%22) - [EHR Data](https://www.sutterhealth.org/research-search-results?query=%22%5C%22EHR+Data%5C%22%22) ## Related publications [View all publications](https://www.sutterhealth.org/research-search-results?verticalKey=research_publication) - Publication ### [Medication non-adherence and therapeutic inertia independently contribute to poor disease control for cardiometabolic diseases](https://www.sutterhealth.org/research/publications/medication-non-adherence-cardiometabolic-disease-1055312898) Scientific Reports 2022 Nov 07 - Publication ### [Home blood pressure monitoring among adults—American Heart Association Cardiovascular Health Consumer Survey, 2012](https://www.sutterhealth.org/research/publications/home-blood-pressure-monitoring-among-adults-1055312805) The Journal of Clinical Hypertension 2017 Jun 19 - Publication ### [No beneficial effects of pine bark extract on cardiovascular disease risk factors](https://www.sutterhealth.org/research/publications/pine-bark-extract-on-cardiovascular-disease-1055312556) Drieling RL, Gardner CD, Ma J, Ahn DK, Stafford RS. Arch Intern Med. 170(17):1541-7. doi: 10.1001/archinternmed.2010.310. 2010 Sep 27 - Publication ### [Self-gated fat-suppressed cardiac cine MRI.](https://www.sutterhealth.org/research/publications/self-gated-fat-suppressed-cardiac-cine-mri-1055312491) Ingle RR, Santos JM, Overall WR, McConnell MV, Hu BS, Nishimura DG. Magn Reson Med. 73(5):1764-74. doi: 10.1002/mrm.25291. Epub 2014 May 7. 2015 May 01 - Publication ### [Nonrigid motion correction with 3D image-based navigators for coronary MR angiography.](https://www.sutterhealth.org/research/publications/motion-correction-3d-image-navig-ht-mra-1055312449) Luo J, Addy NO, Ingle RR, Baron CA, Cheng JY, Hu BS, Nishimura DG. Magn Reson Med. doi: 10.1002/mrm.26273. \[Epub ahead of print\] 2016 May 13 [View all publications](https://www.sutterhealth.org/research-search-results?verticalKey=research_publication) ```json {"@context":"https://schema.org","@type":"MedicalOrganization","name":"Sutter Health","@id":"https://www.sutterhealth.org/#medicalorganization","url":"https://www.sutterhealth.org","logo":"https://www.sutterhealth.org/static/images/sutter-health-logo.svg","address":{"@type":"PostalAddress","streetAddress":"2200 River Plaza Drive","addressLocality":"Sacramento","addressRegion":"CA","postalCode":"95833","addressCountry":"US"},"areaServed":{"@type":"AdministrativeArea","name":"California"},"sameAs":["https://www.facebook.com/SutterHealth","https://www.instagram.com/sutterhealth/","https://x.com/SutterHealth","https://www.youtube.com/sutterhealth","https://www.linkedin.com/company/sutter-health","https://en.wikipedia.org/wiki/Sutter_Health"]} ``` ```json {"@context":"https://schema.org","@type":"BreadcrumbList","@id":"https://www.sutterhealth.org/research/publications/evaluating-impact-of-poc-cardiometabolic-clinical-care-tool-1055312804#breadcrumblist","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://www.sutterhealth.org/"},{"@type":"ListItem","position":2,"name":"Research","item":"https://www.sutterhealth.org/research"},{"@type":"ListItem","position":3,"name":"Research publications","item":"https://www.sutterhealth.org/research/publications"},{"@type":"ListItem","position":4,"name":"Evaluating Impact of POC Cardiometabolic Clinical Care tool"}]} ``` ```json {"@context":"https://schema.org","@type":"MedicalScholarlyArticle","@id":"https://www.sutterhealth.org/research/publications/evaluating-impact-of-poc-cardiometabolic-clinical-care-tool-1055312804#medicalscholarlyarticle","name":"Evaluating the Impact of a Point-of-Care Cardiometabolic Clinical Decision Support Tool on Clinical Efficiency Using Electronic Health Record Audit Log Data: Algorithm Development and Validation","headline":"Evaluating Impact of POC Cardiometabolic Clinical Care tool","abstract":"Background: Electronic health record (EHR) systems are becoming increasingly complicated, leading to concerns about rising physician burnout, particularly for primary care physicians (PCPs). Managing the most common cardiometabolic chronic conditions by PCPs during a limited clinical time with a patient is challenging. Objective: This study aimed to evaluate a Cardiometabolic Sutter Health Advanced Reengineered Encounter (CM-SHARE), a web-based application to visualize key EHR data, on the EHR use efficiency. Methods: We developed algorithms to identify key clinic workflow measures (eg, total encounter time, total physician time in the examination room, and physician EHR time in the examination room) using audit data, and we validated and calibrated the measures with time-motion data. We used a pre-post parallel design to identify propensity score-matched CM-SHARE users (cases), nonusers (controls), and nested-matched patients. Cardiometabolic encounters from matched case and control patients were used for the workflow evaluation. Outcome measures were compared between the cases and controls. We applied this approach separately to both the CM-SHARE pilot and spread phases. Results: Time-motion observation was conducted on 101 primary care encounters for 9 PCPs in 3 clinics. There was little difference (\u003c0.8 minutes) between the audit data-derived workflow measures and the time-motion observation. Two key unobservable times from audit data, physician entry into and exiting the examination room, were imputed based on time-motion studies. CM-SHARE was launched with 6 pilot PCPs in April 2016. During the prestudy period (April 1, 2015, to April 1, 2016), 870 control patients with 2845 encounters were matched with 870 case patients and encounters, and 727 case patients with 852 encounters were matched with 727 control patients and 3754 encounters in the poststudy period (June 1, 2016, to June 30, 2017). Total encounter time was slightly shorter (mean -2.7, SD 1.4 minutes, 95% CI -4.7 to -0.9; mean -1.6, SD 1.1 minutes, 95% CI -3.2 to -0.1) for cases than controls for both periods. CM-SHARE saves physicians approximately 2 minutes EHR time in the examination room (mean -2.0, SD 1.3, 95% CI -3.4 to -0.9) compared with prestudy period and poststudy period controls (mean -1.9, SD 0.9, 95% CI -3.8 to -0.5). In the spread phase, 48 CM-SHARE spread PCPs were matched with 84 control PCPs and 1272 cases with 3412 control patients, having 1119 and 4240 encounters, respectively. A significant reduction in total encounter time for the CM-SHARE group was observed for short appointments (≤20 minutes; 5.3-minute reduction on average) only. Total physician EHR time was significantly reduced for both longer and shorter appointments (17%-33% reductions). 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