PT  - JOURNAL ARTICLE
AU  - Cozine, Elizabeth
AU  - Pham, Van
AU  - Ziegelbauer, Lorelle
AU  - Poe, Justin
AU  - Huschka, Todd
AU  - Theofiles, Meghan
TI  - Quantifying Volume and Disparities in Electronic Workload
AID  - 10.1370/afm.22.s1.6051
DP  - 2024 Nov 20
TA  - The Annals of Family Medicine
PG  - 6051
VI  - 22
IP  - Supplement 1
4099  - http://www.annfammed.org/content/22/Supplement_1/6051.short
4100  - http://www.annfammed.org/content/22/Supplement_1/6051.full
SO  - Ann Fam Med2024 Nov 20; 22
AB  - Context: Electronic health records (EHR) and patient portal systems have resulted in an unrestricted, undefined, and often uncompensated workload for Primary Care providers. Little information exists regarding the volume of work due to electronic portal messaging and if disparities exist among gender, race, age, and specialty of the provider. Objective: Quantify portal messaging patterns across the Rochester, MN Primary Care practices in 2022. Quantify distribution of uncompensated workload based on provider characteristics/demographics. Characterize the impact of uncompensated workload on burnout.Study Design and Analysis: Observational study (cross-sectional survey) and retrospective electronic chart analysis to quantify electronic workload volume and to establish a relationship to a provider’s demographics.Setting: Outpatient primary care practice at 4 clinic sitesPopulation Studied: Primary care providers (physicians and advance practice providers)Intervention/Instrument: Cross-sectional survey and retrospective EHR analysisOutcome Measures: Retrospective EHR analysis and internal data provided data on volumes and types of messages, patient panel characteristics, time spent on EHR tasks. Provider survey data was linked to internal data, de-identified, and analyzed using general linear model and logistic regression model.Results: 192 surveys sent; 67% response rate. Analyzed demographic differences, patient panel characteristics, burden (objective and subjective), in-basket task workload, and total time outside scheduled work hours. Comparisons of means across race, gender, and age for the primary variables of interest showed little statistical differences. Differences were found in burnout rates with increased rates in those with reduced FTE. Women were 3.8 to 4.9 times (95% CI 1.5-15.1) more likely to have reduced FTE.Conclusions: Providers with reduced FTE do not have a statistically significant reduction in direct patient care, but remaining work time has more direct patient care than does that of those with reduced FTE. Those with reduced FTE have higher burnout rates. In-basket tasks per month most strongly correlates to size of patient panel.