More Tethered to the EHR: EHR Workload Trends Among Academic Primary Care Physicians, 2019-2023.

PURPOSE: The purpose of this study is to evaluate recent trends in primary care physician (PCP) electronic health record (EHR) workload. METHODS: This longitudinal study observed the EHR use of 141 academic PCPs over 4 years (May 2019 to March 2023). Ambulatory full-time equivalency (aFTE), visit volume, and panel size were evaluated. Electronic health record time and inbox message volume were measured per 8 hours of scheduled clinic appointments. RESULTS: From the pre-COVID-19 pandemic year (May 2019 to February 2020) to the most recent study year (April 2022 to March 2023), the average time PCPs spent in the EHR per 8 hours of scheduled clinic appointments increased (+28.4 minutes, 7.8%), as did time in orders (+23.1 minutes, 58.9%), inbox (+14.0 minutes, 24.4%), chart review (+7.2 minutes, 13.0%), notes (+2.9 minutes, 2.3%), outside scheduled hours on days with scheduled appointments (+6.4 minutes, 8.2%), and on unscheduled days (+13.6 minutes, 19.9%). Primary care physicians received more patient medical advice requests (+5.4 messages, 55.5%) and prescription messages (+2.3, 19.5%) per 8 hours of scheduled clinic appointments, but fewer patient calls (-2.8, -10.5%) and results messages (-0.3, -2.7%). While total time in the EHR continued to increase in the final study year (+7.7 minutes, 2.0%), inbox time decreased slightly from the year prior (-2.2 minutes, -3.0%). Primary care physicians' average aFTE decreased 5.2% from 0.66 to 0.63 over 4 years. CONCLUSIONS: Primary care physicians' time in the EHR continues to grow. While PCPs' inbox time may be stabilizing, it is still substantially higher than pre-pandemic levels. It is imperative health systems develop strategies to change the EHR workload trajectory to minimize PCPs' occupational stress and mitigate unnecessary reductions in effective physician workforce resulting from the increased EHR burden.

Refining Vendor-Defined Measures to Accurately Quantify EHR Workload Outside Time Scheduled With Patients.

Accurately quantifying clinician time spent on electronic health record (EHR) activities outside the time scheduled with patients is critical for understanding occupational stress associated with ambulatory clinic environments. We make 3 recommendations regarding EHR workload measures that are intended to capture time working in the EHR outside time scheduled with patients, formally defined as work outside of work (WOW): (1) separate all time working in the EHR outside of time scheduled with patients from time working in the EHR during time scheduled with patients, (2) do not exclude any time before or after scheduled time with patients, and (3) encourage the EHR vendor and research communities to develop and standardize validated, vendor-agnostic methods for measuring active EHR use. Attributing all EHR work outside time scheduled with patients to WOW, regardless of when it occurs, will produce an objective and standardized measure better suited for use in efforts to reduce burnout, set policy, and facilitate research.

Primary Care Patients' and Staff's Perceptions of Self-Rooming as Alternative to Waiting Rooms.

PURPOSE: Most patients are escorted to exam rooms (escorted rooming) although patients directing themselves to their exam room (self-rooming) saves patient and staff time while increasing patient satisfaction. This study assesses patient and staff perceptions after pragmatic implementation of self-rooming. METHODS: In October-December 2020, we surveyed patients and staff in 25 primary care clinics after our institution expanded self-rooming from 4 specially built clinics during the COVID-19 pandemic. Semi-structured surveys asked about rooming process used, rooming process preferred, and perceptions of self-rooming compared with escorted rooming. RESULTS: Most patients (n = 1,561) preferred self-rooming (86%), especially among patients aged <65 years and in family medicine clinics. Few patients felt less welcomed (10.6%), less cared about (6.8%), more isolated (15.6%), more lost/confused (7.6%), or more frustrated (3.2%) with self-rooming compared with escorted rooming. Early-adopter clinics that implemented self-rooming ≤2016 had even lower rates of patients feeling more isolated, lost/confused, or frustrated with self-rooming compared with escorted rooming.Over one-half of staff (n = 241; 180 clinical, 61 nonclinical) preferred self-rooming (59%) and thought most patients liked self-rooming (65.8%), especially among clinical staff and in early adopter clinics (≤2016). Few staff reported worse waiting times for patients (12.4%), medical assistants (MAs) (15.9%), and clinicians (16.4%) or worse crowding in waiting areas (1.7%) and hallways (10.1%). Unlike patient-reported confusion (7.6%), most staff thought self-rooming led to more patient confusion (63.8%), except in early-adopter clinics (44.4%). CONCLUSIONS: Self-rooming is a patient-centered innovation that is also acceptable to staff. We demonstrated that pragmatic implementation is feasible across primary care without expensive technology or specially designed buildings.

Tethered to the EHR: Primary Care Physician Workload Assessment Using EHR Event Log Data and Time-Motion Observations.

PURPOSE: Primary care physicians spend nearly 2 hours on electronic health record (EHR) tasks per hour of direct patient care. Demand for non-face-to-face care, such as communication through a patient portal and administrative tasks, is increasing and contributing to burnout. The goal of this study was to assess time allocated by primary care physicians within the EHR as indicated by EHR user-event log data, both during clinic hours (defined as 8:00 am to 6:00 pm Monday through Friday) and outside clinic hours. METHODS: We conducted a retrospective cohort study of 142 family medicine physicians in a single system in southern Wisconsin. All Epic (Epic Systems Corporation) EHR interactions were captured from "event logging" records over a 3-year period for both direct patient care and non-face-to-face activities, and were validated by direct observation. EHR events were assigned to 1 of 15 EHR task categories and allocated to either during or after clinic hours. RESULTS: Clinicians spent 355 minutes (5.9 hours) of an 11.4-hour workday in the EHR per weekday per 1.0 clinical full-time equivalent: 269 minutes (4.5 hours) during clinic hours and 86 minutes (1.4 hours) after clinic hours. Clerical and administrative tasks including documentation, order entry, billing and coding, and system security accounted for nearly one-half of the total EHR time (157 minutes, 44.2%). Inbox management accounted for another 85 minutes (23.7%). CONCLUSIONS: Primary care physicians spend more than one-half of their workday, nearly 6 hours, interacting with the EHR during and after clinic hours. EHR event logs can identify areas of EHR-related work that could be delegated, thus reducing workload, improving professional satisfaction, and decreasing burnout. Direct time-motion observations validated EHR-event log data as a reliable source of information regarding clinician time allocation.

Sparse modeling of spatial environmental variables associated with asthma.

Geographically distributed environmental factors influence the burden of diseases such as asthma. Our objective was to identify sparse environmental variables associated with asthma diagnosis gathered from a large electronic health record (EHR) dataset while controlling for spatial variation. An EHR dataset from the University of Wisconsin's Family Medicine, Internal Medicine and Pediatrics Departments was obtained for 199,220 patients aged 5-50years over a three-year period. Each patient's home address was geocoded to one of 3456 geographic census block groups. Over one thousand block group variables were obtained from a commercial database. We developed a Sparse Spatial Environmental Analysis (SASEA). Using this method, the environmental variables were first dimensionally reduced with sparse principal component analysis. Logistic thin plate regression spline modeling was then used to identify block group variables associated with asthma from sparse principal components. The addresses of patients from the EHR dataset were distributed throughout the majority of Wisconsin's geography. Logistic thin plate regression spline modeling captured spatial variation of asthma. Four sparse principal components identified via model selection consisted of food at home, dog ownership, household size, and disposable income variables. In rural areas, dog ownership and renter occupied housing units from significant sparse principal components were associated with asthma. Our main contribution is the incorporation of sparsity in spatial modeling. SASEA sequentially added sparse principal components to Logistic thin plate regression spline modeling. This method allowed association of geographically distributed environmental factors with asthma using EHR and environmental datasets. SASEA can be applied to other diseases with environmental risk factors.

Disparities in Use of Patient Portals Among Adults in Family Medicine.

OBJECTIVE: This study examined patient portal utilization by analyzing the pattern of time and feature use of patients, and thus to identify functionalities of portal use and patient characteristics that may inform future strategies to enhance communication and care coordination through online portals. METHODS: We conducted a retrospective study of patients at 18 family medicine clinics over a 5-year period using access log records in the electronic health record database. Dimensionality reduction analysis was applied to group portal functionalities into 4 underlying feature domains: messaging, health information management, billing/insurance, and resource/education. Negative binomial regression analysis was used to evaluate how patient and practice characteristics affected the use of each feature domain. RESULTS: Patients with more chronic conditions, lab tests, or prescriptions generally showed greater patient portal usage. However, patients who were male, elderly, in minority groups, or living in rural areas persistently had lower portal usage. Individuals on public insurance were also less likely than those on commercial insurance to use patient portals, although Medicare patients showed greater portal usage on health information management features, and uninsured patients had greater usage on viewing resource/education features. Having Internet access only affected the use of messaging features. CONCLUSION: Efforts to enroll patients in online portals do not guarantee patients will use the portals to manage their health. When considering the use of patient portals for improving telehealth, clinicians need to be aware of technological, socioeconomic, and cultural challenges faced by their patients.

Expansion and Evaluation of Pharmacist Services in Primary Care.

Challenges with primary care access and overextended providers present opportunities for pharmacists as patient care extenders for chronic disease management. The primary objective was to align primary care pharmacist services with organizational priorities and improve patient clinical outcomes. The secondary objective was to develop a technological strategy for service evaluation. An interdisciplinary workgroup developed primary care pharmacist services focused on improving performance measures and supporting the care team in alignment with ongoing population health initiatives. Pharmacist collaborative practice agreements (CPAs) were developed and implemented. An electronic dashboard was developed to capture service outcome measures. Blood pressure control to <140/90 mmHg was achieved in 74.15% of patients who engaged with primary care pharmacists versus 41.53% of eligible patients electing to follow usual care pathways. Appropriate statin use was higher in patients engaged with primary care pharmacists than in eligible patients electing to follow usual care pathways both for diabetes and ischemic vascular disease (12.4% and 2.2% higher, respectively). Seventeen of 54 possible process and outcome measures were identified and incorporated into an electronic dashboard. Primary care pharmacist services improve hypertension control and statin use. Service outcomes can be measured with discrete data from the electronic health record (EHR), and should align with organizational priorities.

Metrics for assessing physician activity using electronic health record log data.

Electronic health record (EHR) log data have shown promise in measuring physician time spent on clinical activities, contributing to deeper understanding and further optimization of the clinical environment. In this article, we propose 7 core measures of EHR use that reflect multiple dimensions of practice efficiency: total EHR time, work outside of work, time on documentation, time on prescriptions, inbox time, teamwork for orders, and an aspirational measure for the amount of undivided attention patients receive from their physicians during an encounter, undivided attention. We also illustrate sample use cases for these measures for multiple stakeholders. Finally, standardization of EHR log data measure specifications, as outlined here, will foster cross-study synthesis and comparative research.