Evidence map›Paper›PMID 37164355›Full record

ArticleApplied clinical informatics2023

Crowdsourcing Electronic Health Record Improvements at Scale across an Integrated Health Care Delivery System.

Geetanjali Rajamani, Molly Diethelm, Melissa A Gunderson, Venkata S M Talluri, Patricia Motz, Jennifer M Steinhaus, Anne E LaFlamme, Bryan Jarabek, Tori Christiaansen, Jeffrey T Blade and 2 more

Abstract read
In one paragraph

Article in Applied clinical informatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Article
  2. Article
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

12 authors.

Geetanjali RajamaniMedical School, University of Minnesota, Minneapolis, Minnesota, United States.
Molly DiethelmCenter for Learning Health Systems Sciences, University of Minnesota, Minneapolis, Minnesota, United States.
Melissa A GundersonInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States.
Venkata S M TalluriInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States.
Patricia MotzInformation Technology, Fairview Health Services, Minneapolis, Minnesota, United States.
Jennifer M SteinhausInformation Technology, Fairview Health Services, Minneapolis, Minnesota, United States.
Anne E LaFlammeInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States.
Bryan JarabekInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States.
Tori ChristiaansenInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States.
Jeffrey T BladeInformation Technology, Fairview Health Services, Minneapolis, Minnesota, United States.
Sameer BadlaniInstitute for Health Informatics, University of Minnesota, Minneapolis, Minnesota, United States.
Genevieve B MeltonCenter for Learning Health Systems Sciences, University of Minnesota, Minneapolis, Minnesota, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveDespite widespread adoption of electronic health records (EHRs), these systems have significant room for improved efficiency and efficacy. While the idea of crowdsourcing EHR improvement ideas has been reported, little is known about how this might work across an integrated health care delivery system in practice.

methodsOur program solicited EHR improvement submissions during two timeframes across 10 hospitals and 60 clinics in an upper-Midwest integrated health care delivery system. Submissions were primarily collected via an EHR help feature.

resultsA total of 262 and 294 submissions were received in 2019 and 2022, with a majority initiated from physicians (73.5 and 46.9%, 2019 and 2022) specializing in family medicine (52.0 and 59.3%). In 2022, the program reached a larger variety of personnel than 2019, with 53.0% of submissions from advanced practice providers, nurses, administrative staff, and other roles (

conclusionOur experience using a crowdsourcing approach for EHR improvement ideas provided clinicians and staff the opportunity to address frustrations with the EHR and offered concrete feedback and solutions. While previous studies have suggested EHR technology improvements as paramount, we observed large numbers of users having a misunderstanding of EHR features, highlighting the need for improved EHR user competency and training.

Indexed as

CrowdsourcingDelivery of Health Care, IntegratedPhysiciansDelivery of Health CareElectronic Health RecordsHospitalsHumans

Identifiers

PMID37164355
PMCPMC10171994

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.