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Electronic Health Record Logs Indicate That Physicians Split Time Evenly Between Seeing Patients And Desktop Medicine.

ABSTRACT: Time spent by physicians is a key resource in health care delivery. This study used data captured by the access time stamp functionality of an electronic health record (EHR) to examine physician work effort. This is a potentially powerful, yet unobtrusive, way to study physicians' use of time. We used data on physicians' time allocation patterns captured by over thirty-one million EHR transactions in the period 2011-14 recorded by 471 primary care physicians, who collectively worked on 765,129 patients' EHRs. Our results suggest that the physicians logged an average of 3.08 hours on office visits and 3.17 hours on desktop medicine each day. Desktop medicine consists of activities such as communicating with patients through a secure patient portal, responding to patients' online requests for prescription refills or medical advice, ordering tests, sending staff messages, and reviewing test results. Over time, log records from physicians showed a decline in the time allocated to face-to-face visits, accompanied by an increase in time allocated to desktop medicine. Staffing and scheduling in the physician's office, as well as provider payment models for primary care practice, should account for these desktop medicine efforts.

SUBMITTER: Tai-Seale M

PROVIDER: S-EPMC5546411 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Electronic Health Record Logs Indicate That Physicians Split Time Evenly Between Seeing Patients And Desktop Medicine.

Tai-Seale Ming M Olson Cliff W CW Li Jinnan J Chan Albert S AS Morikawa Criss C Durbin Meg M Wang Wei W Luft Harold S HS

Health affairs (Project Hope) 20170401 4

Time spent by physicians is a key resource in health care delivery. This study used data captured by the access time stamp functionality of an electronic health record (EHR) to examine physician work effort. This is a potentially powerful, yet unobtrusive, way to study physicians' use of time. We used data on physicians' time allocation patterns captured by over thirty-one million EHR transactions in the period 2011-14 recorded by 471 primary care physicians, who collectively worked on 765,129 p ...[more]

PMID: 28373331

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Project description:BACKGROUND:Electronic health record (EHR) access and audit logs record behaviors of providers as they navigate the EHR. These data can be used to better understand provider responses to EHR-based clinical decision support (CDS), shedding light on whether and why CDS is effective. OBJECTIVE:This study aimed to determine the feasibility of using EHR access and audit logs to track primary care physicians' (PCPs') opening of and response to noninterruptive alerts delivered to EHR InBaskets. METHODS:We conducted a descriptive study to assess the use of EHR log data to track provider behavior. We analyzed data recorded following opening of 799 noninterruptive alerts sent to 75 PCPs' InBaskets through a prior randomized controlled trial. Three types of alerts highlighted new medication concerns for older patients' posthospital discharge: information only (n=593), medication recommendations (n=37), and test recommendations (n=169). We sought log data to identify the person opening the alert and the timing and type of PCPs' follow-up EHR actions (immediate vs by the end of the following day). We performed multivariate analyses examining associations between alert type, patient characteristics, provider characteristics, and contextual factors and likelihood of immediate or subsequent PCP action (general, medication-specific, or laboratory-specific actions). We describe challenges and strategies for log data use. RESULTS:We successfully identified the required data in EHR access and audit logs. More than three-quarters of alerts (78.5%, 627/799) were opened by the PCP to whom they were directed, allowing us to assess immediate PCP action; of these, 208 alerts were followed by immediate action. Expanding on our analyses to include alerts opened by staff or covering physicians, we found that an additional 330 of the 799 alerts demonstrated PCP action by the end of the following day. The remaining 261 alerts showed no PCP action. Compared to information-only alerts, the odds ratio (OR) of immediate action was 4.03 (95% CI 1.67-9.72) for medication-recommendation and 2.14 (95% CI 1.38-3.32) for test-recommendation alerts. Compared to information-only alerts, ORs of medication-specific action by end of the following day were significantly greater for medication recommendations (5.59; 95% CI 2.42-12.94) and test recommendations (1.71; 95% CI 1.09-2.68). We found a similar pattern for OR of laboratory-specific action. We encountered 2 main challenges: (1) Capturing a historical snapshot of EHR status (number of InBasket messages at time of alert delivery) required incorporation of data generated many months prior with longitudinal follow-up. (2) Accurately interpreting data elements required iterative work by a physician/data manager team taking action within the EHR and then examining audit logs to identify corresponding documentation. CONCLUSIONS:EHR log data could inform future efforts and provide valuable information during development and refinement of CDS interventions. To address challenges, use of these data should be planned before implementing an EHR-based study.

Dataset Information

Electronic Health Record Logs Indicate That Physicians Split Time Evenly Between Seeing Patients And Desktop Medicine.

Publications

Electronic Health Record Logs Indicate That Physicians Split Time Evenly Between Seeing Patients And Desktop Medicine.

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