Evidence map›Paper›PMID 35705186›Full record

ArticleApplied clinical informatics2022

Physician Electronic Health Record Usage as Affected by the COVID-19 Pandemic.

Elise Ruan, Moshe Beiser, Vivian Lu, Soaptarshi Paul, Jason Ni, Nijas Nazar, Jianyou Liu, Mimi Kim, Eric Epstein, Marla Keller and 3 more

Abstract read
In one paragraph

Article in Applied clinical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Measuring Documentation Burden in Healthcare.Journal of general internal medicine · 2024
    Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Elise RuanDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.
Moshe BeiserDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.
Vivian LuDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.
Soaptarshi PaulDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.
Jason NiDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.
Nijas NazarDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.
Jianyou LiuDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States.
Mimi KimDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, New York, United States.
Eric EpsteinDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.
Marla KellerDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.
Elizabeth KitsisDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.
Yaron TomerDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.
Sunit P JariwalaDepartment of Medicine, Albert Einstein College of Medicine/Montefiore Medical Center, Bronx, New York, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo utilize metrics from physician action logs to analyze volume, physician efficiency and burden as impacted by telemedicine implementation during the COVID-19 (coronavirus disease 2019) pandemic, and physician characteristics such as gender, years since graduation, and specialty category.

methodsWe selected 11 metrics from Epic Signal, a functionality of the Epic electronic health record (EHR). Metrics measuring time spent in the EHR outside working hours were used as a correlate for burden. We performed an analysis of these metrics among active physicians at our institution across three time periods-prepandemic and telehealth implementation (August 2019), postimplementation of telehealth (May 2020), and follow-up (July 2020)-and correlated them with physician characteristics.

resultsAnalysis of 495 physicians showed that after the start of the pandemic, physicians overall had fewer appointments per day, higher same day visit closure rates, and spent less time writing notes in the EHR outside 7 a.m. to 7 p.m. on patient scheduled days. Across all three time periods, male physicians had better EHR-defined "efficiency" measures and spent less time in the EHR outside working hours. Years since graduation only had modest associations with higher same day visit closure rates and appointments per day in May 2020. Specialty category was significantly associated with appointments per day and same day closure visit rates and also was a significant factor in the observed changes seen across the three time periods.

conclusionUtilizing EHR-generated reports may provide a scalable and nonintrusive way to monitor trends in physician usage and experience to help guide health systems in increasing productivity and reducing burnout.

Indexed as

Burnout, ProfessionalCOVID-19PhysiciansElectronic Health RecordsHumansMalePandemics

Identifiers

PMID35705186
PMCPMC9411035

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.