Electronic Health Record Logs Indicate That Physicians Split Time Evenly Between Seeing Patients And Desktop Medicine
01 Apr 2017-Health Affairs (Project HOPE - The People-to-People Health Foundation, Inc.)-Vol. 36, Iss: 4, pp 655-662
TL;DR: Over time, log records from physicians showed a decline in the time allocated to face-to-face visits, accompanied by an increase in time allocation to 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 wo...
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TL;DR: Through their work supporting EHR optimization, the authors have helped to launch EHR software in health systems outside the United States that noted a significantly different interpretation of the EHR abroad: Physicians were more likely to report satisfaction with its use and cite it as a tool that improved efficiency.
Abstract: The widespread adoption of electronic health records (EHRs) has been perceived as driving physician dissatisfaction and burnout. The authors of this essay present data comparing EHR use in other co...
256 citations
Cites background from "Electronic Health Record Logs Indic..."
...physicians now spend as much time on “desktop medicine” (interacting with the computer) as they do face to face with patients (2, 3)....
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01 Mar 2020
TL;DR: The usability of current EHR systems received a grade of F by physician users when evaluated using a standardized metric of technology usability, and a strong dose-response relationship between EHR usability and the odds of burnout was observed.
Abstract: Objective To describe and benchmark physician-perceived electronic health record (EHR) usability as defined by a standardized metric of technology usability and evaluate the association with professional burnout among physicians. Participants and Methods This cross-sectional survey of US physicians from all specialty disciplines was conducted between October 12, 2017, and March 15, 2018, using the American Medical Association Physician Masterfile. Among the 30,456 invited physicians, 5197 (17.1%) completed surveys. A random 25% (n=1250) of respondents in the primary survey received a subsurvey evaluating EHR usability, and 870 (69.6%) completed it. EHR usability was assessed using the System Usability Scale (SUS; range 0-100). SUS scores were normalized to percentile rankings across more than 1300 previous studies from other industries. Burnout was measured using the Maslach Burnout Inventory. Results Mean ± SD SUS score was 45.9±21.9. A score of 45.9 is in the bottom 9% of scores across previous studies and categorized in the "not acceptable" range or with a grade of F. On multivariate analysis adjusting for age, sex, medical specialty, practice setting, hours worked, and number of nights on call weekly, physician-rated EHR usability was independently associated with the odds of burnout with each 1 point more favorable SUS score associated with a 3% lower odds of burnout (odds ratio, 0.97; 95% CI, 0.97-0.98; P Conclusion The usability of current EHR systems received a grade of F by physician users when evaluated using a standardized metric of technology usability. A strong dose-response relationship between EHR usability and the odds of burnout was observed.
226 citations
TL;DR: The extent to which patients’ concerns are elicited across different clinical settings and how shared decision-making tools impact agenda elicitation is described to help clarify the priorities of a clinical encounter.
Abstract: Eliciting patient concerns and listening carefully to them contributes to patient-centered care. Yet, clinicians often fail to elicit the patient’s agenda and, when they do, they interrupt the patient’s discourse. We aimed to describe the extent to which patients’ concerns are elicited across different clinical settings and how shared decision-making tools impact agenda elicitation. We performed a secondary analysis of a random sample of 112 clinical encounters recorded during trials testing the efficacy of shared decision-making tools. Two reviewers, working independently, characterized the elicitation of the patient agenda and the time to interruption or to complete statement; we analyzed the distribution of agenda elicitation according to setting and use of shared decision-making tools. Clinicians elicited the patient’s agenda in 40 of 112 (36%) encounters. Agendas were elicited more often in primary care (30/61 encounters, 49%) than in specialty care (10/51 encounters, 20%); p = .058. Shared decision-making tools did not affect the likelihood of eliciting the patient’s agenda (34 vs. 37% in encounters with and without these tools; p = .09). In 27 of the 40 (67%) encounters in which clinicians elicited patient concerns, the clinician interrupted the patient after a median of 11 seconds (interquartile range 7–22; range 3 to 234 s). Uninterrupted patients took a median of 6 s (interquartile range 3–19; range 2 to 108 s) to state their concern. Clinicians seldom elicit the patient’s agenda; when they do, they interrupt patients sooner than previously reported. Physicians in specialty care elicited the patient’s agenda less often compared to physicians in primary care. Failure to elicit the patient’s agenda reduces the chance that clinicians will orient the priorities of a clinical encounter toward specific aspects that matter to each patient.
191 citations
TL;DR: The time spent using EHRs to support care delivery constitutes a large portion of the physicians' day, and wide variation suggests opportunities to optimize systems and processes.
Abstract: Background The amount of time that providers spend using electronic health records (EHRs) to support the care delivery process is a concern for the U.S. health care system. Given the potential effect on patient care and the high costs related to this time, particularly for medical specialists whose work is largely cognitive, these findings warrant more precise documentation of the time physicians invest in these clinically focused EHR functions. Objective To describe how much time ambulatory medical subspecialists and primary care physicians across several U.S. care delivery systems spend on various EHR functions. Design Descriptive study. Setting U.S.-based, adult, nonsurgical, ambulatory practices using the Cerner Millennium EHR. Participants 155 000 U.S. physicians. Measurements Data were extracted from software log files in the Lights On Network (Cerner) during 2018 that totaled the time spent on each of the 13 clinically focused EHR functions. Averages per encounter by specialty were computed. Results This study included data from approximately 100 million patient encounters with about 155 000 physicians from 417 health systems. Physicians spent an average of 16 minutes and 14 seconds per encounter using EHRs, with chart review (33%), documentation (24%), and ordering (17%) functions accounting for most of the time. The distribution of time spent by providers using EHRs varies greatly within specialty. The proportion of time spent on various clinically focused functions was similar across specialties. Limitation Variation by health system could not be examined, and all providers used the same software. Conclusion The time spent using EHRs to support care delivery constitutes a large portion of the physicians' day, and wide variation suggests opportunities to optimize systems and processes. Primary funding source None.
114 citations
Cites background or methods from "Electronic Health Record Logs Indic..."
...Using EHR logs to measure activity times, Tai-Seale and colleagues (8) found that primary care physicians devoted a mean of 190 minutes (SD, 82) per day (28% of total time assuming an 11....
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...3 patient encounters per day to provide a direct comparison, primary care providers in TaiSeale and colleagues' study (8) spent similar time per day (3....
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TL;DR: Primary care physicians spent more time working in the EHR than they spent in face-to-face time with patients in clinic visits, and Multivariable linear regression analysis revealed many factors associated with total visit time including patient, physician, and clinic infrastructure factors.
Abstract: Background and objectives Electronic health records (EHRs) have had mixed effects on the workflow of ambulatory primary care In this study, we update previous research on the time required to care for patients in primary care clinics with EHRs Methods We directly observed family physician (FP) attendings, residents, and their ambulatory patients in 982 visits in clinics affiliated with 10 residencies of the Residency Research Network of Texas The FPs were purposely chosen to reflect a diversity of patient care styles We measured total visit time, previsit chart time, face-to-face time, non-face time, out-of-hours EHR work time, and total EHR work time Results The mean (SD) visit length was 358 (166) minutes, not counting resident precepting time The mean time components included 29 (38) minutes working in the EHR prior to entering the room, 165 (92) minutes of face-to-face time not working in the EHR, 20 (21) minutes working in the EHR in the room (which occurred in 734% of the visits), 75 (75) minutes of non-face time (mostly EHR time), and 69 (76) minutes of EHR work outside of normal clinic operational hours (which occurred in 646% of the visits) The total time and total EHR time varied only slightly between faculty physicians, third-year and second-year residents Multivariable linear regression analysis revealed many factors associated with total visit time including patient, physician, and clinic infrastructure factors Conclusions Primary care physicians spent more time working in the EHR than they spent in face-to-face time with patients in clinic visits
109 citations
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TL;DR: It is concluded that the adapted comorbidity index will be useful in studies of disease outcome and resource use employing administrative databases.
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Abstract: The traditional ABC model has been difficult for many organizations to implement because of the high costs incurred to interview and survey people for the initial ABC model, the use of subjective and costly-to-validate time allocations, and the difficulty of maintaining and updating the model as (i) processes and resource spending change, (ii) new activities are added, and (iii) increases occur in the diversity and complexity of individual orders, channels and customers. Time-driven ABC requires estimates of only two parameters: (1) the unit cost of supplying capacity and (2) the time required to perform a transaction or an activity. A time-driven ABC model: - can be estimated and installed quickly - is easily updated to reflect changes in processes, order variety, and resource costs - can be data fed from transactional ERP and CRM systems - can be validated by direct observation of the model's estimates of unit times - can scale easily to handle millions of transactions while still delivering fast processing times and real-time reporting - explicitly incorporates resource capacity and highlights unused resource capacity for management action - exploits time equations that incorporate variation in orders and customer behavior without expanding model complexity The paper uses simple numerical examples to articulate the fundamentals of time-driven ABC and provides several examples of companies that have implemented the approach and enjoyed rapid and significant profit improvements.
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