Evidence map›Paper›PMID 34014169›Full record

ArticleJournal of medical Internet research2021

Digitization of Measurement-Based Care Pathways in Mental Health Through REDCap and Electronic Health Record Integration: Development and Usability Study.

Steve Hawley, Joanna Yu, Nikola Bogetic, Natalia Potapova, Chris Wakefield, Mike Thompson, Stefan Kloiber, Sean Hill, Damian Jankowicz, David Rotenberg

Open access · goldAbstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 2 pooled it
8.0field-weighted citation impact, top 3% of its field
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

23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 37 citations in OpenAlex.

  1. Responsible artificial intelligence integration framework for psychiatric guidelines.The international journal of neuropsychopharmacology · 2026
    Guideline
  2. Digital Health Data Quality Issues: Systematic Review.Journal of medical Internet research · 2023
    Pooled it
  3. Review
  4. Article
  5. Investigating the Applicability of the SAFER-YCL Care Bundle for Transitions From CAMHS Crisis and Liaison Services: The Barriers and Enablers.Health expectations : an international journal of public participation in health care and health policy · 2026
    Article
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  8. Article
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  10. A Taxonomy for Health Information Systems.Journal of medical Internet research · 2024
    Review
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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

10 authors at 1 institution in 1 country.

Steve Hawley *Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0003-2982-4196
Joanna Yu *Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0001-7786-0250
Nikola BogeticKrembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0002-5485-5501
Natalia PotapovaKrembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0002-9205-7893
Chris WakefieldClinical Applications, Centre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0003-0907-5271
Mike ThompsonClinical Applications, Centre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0002-6936-238X
Stefan KloiberGeneral Adult Psychiatry and Health Systems Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0002-6838-4114
Sean HillKrembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0001-8055-860X
Damian JankowiczClinical Applications, Centre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0002-0579-1337
David RotenbergKrembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, Canada.ORCID 0000-0002-9908-064X
Centre for Addiction and Mental Health · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe delivery of standardized self-report assessments is essential for measurement-based care in mental health. Paper-based methods of measurement-based care data collection may result in transcription errors, missing data, and other data quality issues when entered into patient electronic health records (EHRs).

objectiveThis study aims to help address these issues by using a dedicated instance of REDCap (Research Electronic Data Capture; Vanderbilt University)-a free, widely used electronic data capture platform-that was established to enable the deployment of digitized self-assessments in clinical care pathways to inform clinical decision making.

methodsREDCap was integrated with the primary clinical information system to facilitate the real-time transfer of discrete data and PDF reports from REDCap into the EHR. Both technical and administrative components were required for complete implementation. A technology acceptance survey was also administered to capture physicians' and clinicians' attitudes toward the new system.

resultsThe integration of REDCap with the EHR transitioned clinical workflows from paper-based methods of data collection to electronic data collection. This resulted in significant time savings, improved data quality, and valuable real-time information delivery. The digitization of self-report assessments at each appointment contributed to the clinic-wide implementation of the major depressive disorder integrated care pathway. This digital transformation facilitated a 4-fold increase in the physician adoption of this integrated care pathway workflow and a 3-fold increase in patient enrollment, resulting in an overall significant increase in major depressive disorder integrated care pathway capacity. Physicians' and clinicians' attitudes were overall positive, with almost all respondents agreeing that the system was useful to their work.

conclusionsREDCap provided an intuitive patient interface for collecting self-report measures and accessing results in real time to inform clinical decisions and an extensible backend for system integration. The approach scaled effectively and expanded to high-impact clinics throughout the hospital, allowing for the broad deployment of complex workflows and standardized assessments, which led to the accumulation of harmonized data across clinics and care pathways. REDCap is a flexible tool that can be effectively leveraged to facilitate the automatic transfer of self-report data to the EHR; however, thoughtful governance is required to complement the technical implementation to ensure that data standardization, data quality, patient safety, and privacy are maintained.

Indexed as

Major Depressive DisorderPhysiciansElectronic Health RecordsHumansMental HealthSurveys and Questionnaireselectronic health recordhospital information systemsmeasurement-based careREDCapsystems integration

Identifiers

PMID34014169
PMCPMC8176343
OpenAlexW3136112844

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.