Evidence map›Paper›PMID 36198309›Full record

ArticleApplied clinical informatics2022

Accuracy of Physician Electronic Health Record Usage Analytics using Clinical Test Cases.

Brian Lo, Lydia Sequeira, Gillian Strudwick, Damian Jankowicz, Khaled Almilaji, Anjchuca Karunaithas, Dennis Hang, Tania Tajirian

Abstract readCase Reports
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

8 authors.

Brian LoInformation Management Group, Centre for Addiction and Mental Health, Toronto, Canada.
Lydia SequeiraInformation Management Group, Centre for Addiction and Mental Health, Toronto, Canada.
Gillian StrudwickInformation Management Group, Centre for Addiction and Mental Health, Toronto, Canada.
Damian JankowiczInformation Management Group, Centre for Addiction and Mental Health, Toronto, Canada.
Khaled AlmilajiInformation Management Group, Centre for Addiction and Mental Health, Toronto, Canada.
Anjchuca KarunaithasInformation Management Group, Centre for Addiction and Mental Health, Toronto, Canada.
Dennis HangInformation Management Group, Centre for Addiction and Mental Health, Toronto, Canada.
Tania TajirianInformation Management Group, Centre for Addiction and Mental Health, Toronto, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Usage log data are an important data source for characterizing the potential burden related to use of the electronic health record (EHR) system. However, the utility of this data source has been hindered by concerns related to the real-world validity and accuracy of the data. While time-motion studies have historically been used to address this concern, the restrictions caused by the pandemic have made it difficult to carry out these studies in-person. In this regard, we introduce a practical approach for conducting validation studies for usage log data in a controlled environment. By developing test runs based on clinical workflows and conducting them within a test EHR environment, it allows for both comparison of the recorded timings and retrospective investigation of any discrepancies. In this case report, we describe the utility of this approach for validating our physician EHR usage logs at a large academic teaching mental health hospital in Canada. A total of 10 test runs were conducted across 3 days to validate 8 EHR usage log metrics, finding differences between recorded measurements and the usage analytics platform ranging from 9 to 60%.

Indexed as

Electronic Health RecordsPhysiciansData CollectionHospitals, TeachingHumansRetrospective Studies

Identifiers

PMID36198309
PMCPMC9534596

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.