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A technology-enabled multi-disciplinary team-based care model for the management of Long COVID and other fatiguing illnesses within a federally qualified health center: protocol for a two-arm, single-blind, pragmatic, quality improvement professional cluster randomized controlled trial

BACKGROUND: The clinical burden of Long COVID, myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), and other post-infectious fatiguing illnesses (PIFI) is increasing. There is a critical need to advance understanding of the effectiveness and sustainability of innovative approaches to clinic...

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Autores principales: Godino, Job G., Samaniego, Jane C., Sharp, Sydney P., Taren, Douglas, Zuber, Alexandra, Armistad, Amy J., Dezan, Amanda M., Leyba, Azure J., Friedly, Janna L., Bunnell, Aaron E., Matthews, Eva, Miller, Maureen J., Unger, Elizabeth R., Bertolli, Jeanne, Hinckley, Alison, Lin, Jin-Mann S., Scott, John D., Struminger, Bruce B., Ramers, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423413/
https://www.ncbi.nlm.nih.gov/pubmed/37573421
http://dx.doi.org/10.1186/s13063-023-07550-3
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author Godino, Job G.
Samaniego, Jane C.
Sharp, Sydney P.
Taren, Douglas
Zuber, Alexandra
Armistad, Amy J.
Dezan, Amanda M.
Leyba, Azure J.
Friedly, Janna L.
Bunnell, Aaron E.
Matthews, Eva
Miller, Maureen J.
Unger, Elizabeth R.
Bertolli, Jeanne
Hinckley, Alison
Lin, Jin-Mann S.
Scott, John D.
Struminger, Bruce B.
Ramers, Christian
author_facet Godino, Job G.
Samaniego, Jane C.
Sharp, Sydney P.
Taren, Douglas
Zuber, Alexandra
Armistad, Amy J.
Dezan, Amanda M.
Leyba, Azure J.
Friedly, Janna L.
Bunnell, Aaron E.
Matthews, Eva
Miller, Maureen J.
Unger, Elizabeth R.
Bertolli, Jeanne
Hinckley, Alison
Lin, Jin-Mann S.
Scott, John D.
Struminger, Bruce B.
Ramers, Christian
author_sort Godino, Job G.
collection PubMed
description BACKGROUND: The clinical burden of Long COVID, myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), and other post-infectious fatiguing illnesses (PIFI) is increasing. There is a critical need to advance understanding of the effectiveness and sustainability of innovative approaches to clinical care of patients having these conditions. METHODS: We aim to assess the effectiveness of a Long COVID and Fatiguing Illness Recovery Program (LC&FIRP) in a two-arm, single-blind, pragmatic, quality improvement, professional cluster, randomized controlled trial in which 20 consenting clinicians across primary care clinics in a Federally Qualified Health Center system in San Diego, CA, will be randomized at a ratio of 1:1 to either participate in (1) weekly multi-disciplinary team-based case consultation and peer-to-peer sharing of emerging best practices (i.e., teleECHO (Extension for Community Healthcare Outcomes)) with monthly interactive webinars and quarterly short courses or (2) monthly interactive webinars and quarterly short courses alone (a control group); 856 patients will be assigned to participating clinicians (42 patients per clinician). Patient outcomes will be evaluated according to the study arm of their respective clinicians. Quantitative and qualitative outcomes will be measured at 3- and 6-months post-baseline for clinicians and every 3-months post assignment to a participating clinician for patients. The primary patient outcome is change in physical function measured using the Patient-Reported Outcomes Measurement Information System (PROMIS)-29. Analyses of differences in outcomes at both the patient and clinician levels will include a linear mixed model to compare change in outcomes from baseline to each post-baseline assessment between the randomized study arms. A concurrent prospective cohort study will compare the LC&FIRP patient population to the population enrolled in a university health system. Longitudinal data analysis approaches will allow us to examine differences in outcomes between cohorts. DISCUSSION: We hypothesize that weekly teleECHO sessions with monthly interactive webinars and quarterly short courses will significantly improve clinician- and patient-level outcomes compared to the control group. This study will provide much needed evidence on the effectiveness of a technology-enabled multi-disciplinary team-based care model for the management of Long COVID, ME/CFS, and other PIFI within a federally qualified health center. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05167227. Registered on December 22, 2021. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-023-07550-3.
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spelling pubmed-104234132023-08-14 A technology-enabled multi-disciplinary team-based care model for the management of Long COVID and other fatiguing illnesses within a federally qualified health center: protocol for a two-arm, single-blind, pragmatic, quality improvement professional cluster randomized controlled trial Godino, Job G. Samaniego, Jane C. Sharp, Sydney P. Taren, Douglas Zuber, Alexandra Armistad, Amy J. Dezan, Amanda M. Leyba, Azure J. Friedly, Janna L. Bunnell, Aaron E. Matthews, Eva Miller, Maureen J. Unger, Elizabeth R. Bertolli, Jeanne Hinckley, Alison Lin, Jin-Mann S. Scott, John D. Struminger, Bruce B. Ramers, Christian Trials Study Protocol BACKGROUND: The clinical burden of Long COVID, myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), and other post-infectious fatiguing illnesses (PIFI) is increasing. There is a critical need to advance understanding of the effectiveness and sustainability of innovative approaches to clinical care of patients having these conditions. METHODS: We aim to assess the effectiveness of a Long COVID and Fatiguing Illness Recovery Program (LC&FIRP) in a two-arm, single-blind, pragmatic, quality improvement, professional cluster, randomized controlled trial in which 20 consenting clinicians across primary care clinics in a Federally Qualified Health Center system in San Diego, CA, will be randomized at a ratio of 1:1 to either participate in (1) weekly multi-disciplinary team-based case consultation and peer-to-peer sharing of emerging best practices (i.e., teleECHO (Extension for Community Healthcare Outcomes)) with monthly interactive webinars and quarterly short courses or (2) monthly interactive webinars and quarterly short courses alone (a control group); 856 patients will be assigned to participating clinicians (42 patients per clinician). Patient outcomes will be evaluated according to the study arm of their respective clinicians. Quantitative and qualitative outcomes will be measured at 3- and 6-months post-baseline for clinicians and every 3-months post assignment to a participating clinician for patients. The primary patient outcome is change in physical function measured using the Patient-Reported Outcomes Measurement Information System (PROMIS)-29. Analyses of differences in outcomes at both the patient and clinician levels will include a linear mixed model to compare change in outcomes from baseline to each post-baseline assessment between the randomized study arms. A concurrent prospective cohort study will compare the LC&FIRP patient population to the population enrolled in a university health system. Longitudinal data analysis approaches will allow us to examine differences in outcomes between cohorts. DISCUSSION: We hypothesize that weekly teleECHO sessions with monthly interactive webinars and quarterly short courses will significantly improve clinician- and patient-level outcomes compared to the control group. This study will provide much needed evidence on the effectiveness of a technology-enabled multi-disciplinary team-based care model for the management of Long COVID, ME/CFS, and other PIFI within a federally qualified health center. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05167227. Registered on December 22, 2021. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13063-023-07550-3. BioMed Central 2023-08-12 /pmc/articles/PMC10423413/ /pubmed/37573421 http://dx.doi.org/10.1186/s13063-023-07550-3 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Study Protocol
Godino, Job G.
Samaniego, Jane C.
Sharp, Sydney P.
Taren, Douglas
Zuber, Alexandra
Armistad, Amy J.
Dezan, Amanda M.
Leyba, Azure J.
Friedly, Janna L.
Bunnell, Aaron E.
Matthews, Eva
Miller, Maureen J.
Unger, Elizabeth R.
Bertolli, Jeanne
Hinckley, Alison
Lin, Jin-Mann S.
Scott, John D.
Struminger, Bruce B.
Ramers, Christian
A technology-enabled multi-disciplinary team-based care model for the management of Long COVID and other fatiguing illnesses within a federally qualified health center: protocol for a two-arm, single-blind, pragmatic, quality improvement professional cluster randomized controlled trial
title A technology-enabled multi-disciplinary team-based care model for the management of Long COVID and other fatiguing illnesses within a federally qualified health center: protocol for a two-arm, single-blind, pragmatic, quality improvement professional cluster randomized controlled trial
title_full A technology-enabled multi-disciplinary team-based care model for the management of Long COVID and other fatiguing illnesses within a federally qualified health center: protocol for a two-arm, single-blind, pragmatic, quality improvement professional cluster randomized controlled trial
title_fullStr A technology-enabled multi-disciplinary team-based care model for the management of Long COVID and other fatiguing illnesses within a federally qualified health center: protocol for a two-arm, single-blind, pragmatic, quality improvement professional cluster randomized controlled trial
title_full_unstemmed A technology-enabled multi-disciplinary team-based care model for the management of Long COVID and other fatiguing illnesses within a federally qualified health center: protocol for a two-arm, single-blind, pragmatic, quality improvement professional cluster randomized controlled trial
title_short A technology-enabled multi-disciplinary team-based care model for the management of Long COVID and other fatiguing illnesses within a federally qualified health center: protocol for a two-arm, single-blind, pragmatic, quality improvement professional cluster randomized controlled trial
title_sort technology-enabled multi-disciplinary team-based care model for the management of long covid and other fatiguing illnesses within a federally qualified health center: protocol for a two-arm, single-blind, pragmatic, quality improvement professional cluster randomized controlled trial
topic Study Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10423413/
https://www.ncbi.nlm.nih.gov/pubmed/37573421
http://dx.doi.org/10.1186/s13063-023-07550-3
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