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Patient-facing, Semi-automated, solutions to enhance patient participation in measurement-based care practice standards in a tele-mental health specialty clinic for populations at higher risk for self-harm.
- Source :
-
International journal of medical informatics [Int J Med Inform] 2023 Sep; Vol. 177, pp. 105155. Date of Electronic Publication: 2023 Jul 17. - Publication Year :
- 2023
-
Abstract
- Purpose: Collecting validated surveys that describe symptom severity (measurement based care) during evidence-based psychotherapy is crucial to allow a therapist to tailor the speed and intensity of treatment. COVID clinic closures mandated we create a flexible, remote system to conduct measurement-based care, which was accomplished via RedCap.<br />Methods: RedCap was used to create a semi-automated workflow allowing all clinically-indicated evidence-based surveys (including the PHQ-9) to be delivered via email to patients; with results automatically sent to their provider. Importantly, indications of suicidal ideation were automatically escalated to the provider.<br />Results: PHQ-9 completion improved, while provider burden for collecting surveys was greatly reduced; however, depending largely upon initial provider-patient 'training', overall compliance could still be significantly improved.<br />Conclusion: This workflow gave providers additional information compared to the typical telemedicine environment, and in fact, improved data collection rates over our in-person environment. However, when patients did not complete measures on their own, the burden on providers increased.<br />Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1872-8243
- Volume :
- 177
- Database :
- MEDLINE
- Journal :
- International journal of medical informatics
- Publication Type :
- Academic Journal
- Accession number :
- 37467589
- Full Text :
- https://doi.org/10.1016/j.ijmedinf.2023.105155