This paper is in the following e-collection/theme issue:

Systematic Review Protocols (funded) (27) Clinical Informatics (1015) Adoption and Change Management of eHealth Systems (711) Quality Improvement (253) Methods and Instruments in Medical Informatics (126) Patient-Reported Outcome Measures (PROMs) (288)

Published on in Vol 12 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48155, first published .
Clinical Integration of Digital Patient-Reported Outcome Measures in Primary Health Care for Chronic Disease Management: Protocol for a Systematic Review

Clinical Integration of Digital Patient-Reported Outcome Measures in Primary Health Care for Chronic Disease Management: Protocol for a Systematic Review

Clinical Integration of Digital Patient-Reported Outcome Measures in Primary Health Care for Chronic Disease Management: Protocol for a Systematic Review

Authors of this article:

Maxime Sasseville1, 2 Author Orcid Image ;   Wilfried Supper1 Author Orcid Image ;   Jean-Baptiste Gartner1 Author Orcid Image ;   Géraldine Layani3 Author Orcid Image ;   Samira Amil2 Author Orcid Image ;   Peter Sheffield4 Author Orcid Image ;   Marie-Pierre Gagnon1, 2 Author Orcid Image ;   Catherine Hudon5 Author Orcid Image ;   Sylvie Lambert6, 7 Author Orcid Image ;   Eugène Attisso1 Author Orcid Image ;   Victoria Bureau Lagarde1 Author Orcid Image ;   Mylaine Breton5 Author Orcid Image ;   Marie-Eve Poitras5 Author Orcid Image ;   Pierre Pluye6 Author Orcid Image ;   Pierre-Henri Roux-Levy5 Author Orcid Image ;   James Plaisimond1 Author Orcid Image ;   Frédéric Bergeron1 Author Orcid Image ;   Rachelle Ashcroft4 Author Orcid Image ;   Sabrina Wong8 Author Orcid Image ;   Antoine Groulx1 Author Orcid Image ;   Nicolas Beaudet9 Author Orcid Image ;   Jean-Sébastien Paquette1 Author Orcid Image ;   Natasha D'Anjou1 Author Orcid Image ;   Sylviane Langlois1 ;   Annie LeBlanc1, 2 Author Orcid Image
Article Authors Cited by (2) Tweetations (3) Metrics

    Protocol

    1Université Laval, Québec, QC, Canada

    2VITAM Research Center, Québec, QC, Canada

    3Université de Montréal, Montréal, QC, Canada

    4University of Toronto, Toronto, ON, Canada

    5Université de Sherbrooke, Sherbrooke, QC, Canada

    6Université McGill, Montréal, QC, Canada

    7St. Mary's Research Center, Montréal, QC, Canada

    8Division of Intramural Research, National Institute of Nursing Research, National Institute of Health, Bethesda, WA, United States

    9Omnimed, Sherbrooke, QC, Canada

    Corresponding Author:

    Maxime Sasseville, PhD

    Université Laval

    1050, rue de la Médecine

    Québec, QC, G1V 0A6

    Canada

    Phone: 1 418 656 2131

    Email: maxime.sasseville@fsi.ulaval.ca


    Background: Health measurement guides policies and health care decisions are necessary to describe and attain the quintuple aim of improving patient experience, population health, care team well-being, health care costs, and equity. In the primary care setting, patient-reported outcome measurement allows outcome comparisons within and across settings and helps improve the clinical management of patients. However, these digital patient-reported outcome measures (PROMs) are still not adapted to the clinical context of primary health care, which is an indication of the complexity of integrating these tools in this context. We must then gather evidence of their impact on chronic disease management in primary health care and understand the characteristics of effective implementation.

    Objective: We will conduct a systematic review to identify and assess the impact of electronic PROMs (ePROMs) implementation in primary health care for chronic disease management. Our specific objectives are to (1) determine the impact of ePROMs in primary health care for chronic disease management and (2) compare and contrast characteristics of effective ePROMs’ implementation strategies.

    Methods: We will conduct a systematic review of the literature in accordance with the guidelines of the Cochrane Methods Group and in compliance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines for its reporting. A specific search strategy was developed for relevant databases to identify studies. Two reviewers will independently apply the inclusion criteria using full texts and will extract the data. We will use a 2-phase sequential mixed methods synthesis design by conducting a qualitative synthesis first, and use its results to perform a quantitative synthesis.

    Results: This study was initiated in June 2022 by assembling the research team and the knowledge transfer committee. The preliminary search strategy will be developed and completed in September 2022. The main search strategy, data collection, study selection, and application of inclusion criteria were completed between October and December 2022.

    Conclusions: Results from this review will help support implementation efforts to accelerate innovations and digital adoption for primary health care and will be relevant for improving clinical management of chronic diseases and health care services and policies.

    Trial Registration: PROSPERO International Prospective Register of Systematic Reviews CRD42022333513; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=333513

    International Registered Report Identifier (IRRID): DERR1-10.2196/48155

    JMIR Res Protoc 2023;12:e48155

    doi:10.2196/48155

    Keywords

    systematic review; patient-reported outcome measure; primary healthcare; health care; implementation science 


    Primary health care is essential, comprehensive, and universally available to a community [1]. For most of the Canadian population, primary health care represents the first contact with the health care system, and in 2016, overall, 88.5% of the Canadian population had access to a family physician attached to a primary health care service [2]. Mostly managed in primary health care, chronic diseases affect 3 out of 5 Canadian adults, significantly impacting their quality of life, and account for approximately 80% of disability and 70% of deaths in Canada [3]. Primary health care management of chronic diseases remains a challenge at the core of the health care system.

    Health measurement guides policies and health care decisions and is necessary to describe and attain the quintuple aim of improving patient experience, population health, care team well-being, health care costs, and equity [4]. In the primary care setting, health measurement allows outcome comparisons within and across settings and helps improve the clinical management of patients [4,5]. However, for these outcomes to be informative, researchers, key stakeholders, clinicians, and patients must codevelop a measurement framework integrating the perspectives of end users [5,6] and for outcome measurement to deliver on the promise of addressing the quintuple aim [5].

    Patient-reported outcome measures (PROMs) are health reports of patients’ conditions, capturing their perception of their own health, without clinician input [5]. PROMs enable patients to report on their quality of life, daily functioning, symptoms, and other aspects of their health and well-being [5]. A body of evidence shows that effective use of PROMs in the clinical context reduces consultation time [7], improves patient-provider communication [8], identifies patient needs and allows for a patient-centered practice [9], decreases symptom severity, increases survival, and decreases emergency department visits [10,11].

    The development of integrated digital solutions to care pathways is essential for PROMs to have a clinical impact [8,12,13]. It has been reaffirmed in the 2021-2026 Canadian Institutes for Health Research’s strategic plan that researchers must accelerate digital transformation of health care systems for efficient health measurement and data analysis [4]. Electronic PROMs (ePROMs) can bring several benefits to the use of pen-and-paper PROMs: higher motivation to complete the task of self-reporting, lower rates of missing data and errors, improved chronology on historical patients' data [14], remote and quick data collection, integrated data analysis, and availability of reports for care teams [15].

    However, ePROMs are still not adapted to the clinical context of primary health care, which is an indication of the complexity of integrating these tools in this context [16,17]. The effectiveness of including ePROMs in routine clinical care has been studied in contexts of specialized care among homogenous patient groups based on diagnoses such as cancer [18-24]. Whereas successful ePROMs implementation in Canada has been noted (eg, Cancer Care Alberta), unfortunately, there are additional implementation challenges specific to primary health care, including the heterogeneity of the patient population [25]. There are also significant disparities among patients regarding their ability to understand and use digital tools [26]. The development of ePROMs is expected to increase the existing digital divide and reduce the ability to self-report outcomes among certain populations [26]. Understanding the extent to which ePROMs provide outcomes for clinicians and patients and prioritize the adaptation of additional ePROMs in this context is critical to present exhaustive evidence of what works and how to implement ePROMs in primary health care. Consequently, to address these abovementioned critical needs and challenges, we must gather evidence of the impact of ePROMs on chronic disease management in primary health care and understand the characteristics of effective implementation.

    With the goal of accelerating the integration of ePROMs to optimize the delivery of primary health care and bring about rapid and meaningful benefits to patients, we will conduct a systematic review to identify and assess the impact of ePROMs implementation in primary health care for chronic disease management.

    Our objectives are to (1) determine the impact of ePROMs in primary health care for chronic disease management and (2) compare and contrast the characteristics of effective ePROMs implementation strategies. We expect that our results will directly contribute to providing decision makers with high-quality, timely, accessible, and relevant evidence to inform policies and practices.


    We will conduct a systematic review of the literature in accordance with the guidelines of the Cochrane Methods Group and in compliance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for its reporting [27,28]. We have registered the study protocol to the PROSPERO systematic review registry (CRD42022333513) [29].

    Conceptual Underpinnings

    This review will be grounded in the integrated knowledge translation approach to pursue its objectives [30]. According to this approach, knowledge users (KUs) will be involved in all aspects of the research process to enhance its relevance and usability in practice. The Strategy for Patient-Oriented Research framework for patient engagement will be used to complete integrated knowledge translation in promoting a respectful climate between researchers and KUs, including decision makers and patient partners [31].

    Synthesis Questions

    The following questions will be addressed: (1) what are the outcomes of ePROMs in primary health care in chronic disease management? (2) What are the effective strategies to implement ePROMs in primary health care? (3) What are the challenges, barriers, and facilitators to successful implementation of ePROMs in primary health care?

    Eligibility Criteria

    We will address all types of evidence matching the Population, Intervention, Comparison, Outcomes, and Setting/context criteria [28]. Participants include all studies reporting on the implementation of an ePROM among adults for chronic disease management. We have no restrictions regarding the Interventions/phenomena of interest; we will include all types of implementations, theoretical models, structures or PROMs. We have no restrictions regarding the Comparator; we will consider all outcomes reported in the studies. We will seek outcomes related to patients, caregivers, health care providers, policy makers, barriers, facilitators, acceptability, feasibility, adoption, fidelity, morbidity, mortality, quality of life, satisfaction, cost and cost-effectiveness. Regarding Setting, we will only include studies taking place in primary health care settings in any geographical setting and extract information regarding implementation. All types of studies will be included (ie, those using qualitative, quantitative, and mixed methods), which were published in French, English, or Spanish.

    Search Strategy

    We will develop the search strategy under the leadership and guidance of an experienced information specialist (FB). An iterative process of revision by the research team members and a revision by another experienced information specialist will be carried out (per the PRESS [Peer Review of Electronic Search Strategies] checklist) [32]. All relevant comments will be integrated in the final version of the search strategy. Specific search strategies will be formulated for the following databases: Cochrane Database of Systematic Reviews, MEDLINE (Ovid), CINAHL (EBSCO), Embase, PsycINFO (Ovid), Web of Science, and ProQuest Dissertations & Theses. Considering the recent nature of the topic, a time limit of 20 years will be applied to the search strategies. No restriction on language will be applied. We will develop and include a gray literature search strategy. We will perform an internet search in the following sources and search engines: Google, Google Scholar, Canadian Evaluation Society, EuroScan, OpenGrey, Grey Literature Report, GreyNet, and Grey Matters. Since innovation implementations are often conducted by government entities or large health care systems, we will search within the websites of key governmental agencies (eg, US Agency for Healthcare Research and Quality’s studies on health care systems [eg, Kaiser Permanente]). Furthermore, we will perform backward citation searches of included studies and recent literature reviews for additional relevant references.

    Data Collection and Screening

    We will export all citations in the web-based collaboration tool Covidence, where duplicated entries will be removed with the automation function [33]. Titles and abstracts will be screened independently by pairs of reviewers. A pilot testing to validate the screening process will be completed on 5% of a random sample of all studies. Variability in reviewer assessment will be documented using the Cohen κ statistic [34]. Ambiguous or incomplete abstracts will be retained to be reviewed in full and additional information could be obtained from the authors. We will search and obtain all the full texts of the selected references and will import the PDF files in Covidence. Pairs of reviewers will independently apply the inclusion criteria using the full texts following a pilot testing using the process outlined above. At any moment in the overall screening process, a third reviewer will help resolve any discrepancy. All the reasons for exclusion will be recorded in Covidence. A PRISMA flowchart will be used to describe study identification, screening, inclusions, and exclusions [35].

    Data Extraction and Appraisal

    We will codevelop the extraction form with all KUs and team members to ensure that we are capturing relevant information (ie, what matters the most for them). Pairs of reviewers will independently complete data extraction following a pilot testing (see above). We will extract descriptive data (title, year of publication, authors, funding, conflicts of interests, and country), study types (published or gray literature), methodological data (design, sample size, measure constructs, and name of the instrument), setting data (clinical setting, type health professionals, and patient population), implementation data (description of implementation activities, facilitators, and barriers), outcomes (patient health, providers workflow, and cost), and outcome types (qualitative and quantitative). The quality of the included studies will be evaluated using the mixed methods appraisal tool [36]—a tool adapted to systematic reviews synthesizing data from qualitative, quantitative, and mixed methods studies.

    Data Synthesis

    We will use the RE-AIM (reach, effectiveness, adoption, implementation, maintenance/sustainability) framework as a data analysis framework. The RE-AIM framework has been developed to evaluate the public health impacts of interventions and has been used in systematic reviews to help structure the assessment of the different implementation factors at play in complex contexts and settings [37,38]. This framework includes 5 dimensions: reach (how willing the targeted population is to participate in the intervention; ie, ePROMs), efficacy (what is the impact of the intervention on outcomes?), adoption (can this be adopted by new groups with ease and minimal changes?), implementation (what are the special issues and barriers?), and maintenance (can the intervention be maintained and its impact sustained?). The use of the RE-AIM framework will enable us to provide an overview of the parameters strengthening (review questions 2 and 3) the efficiency (review question 1) of ePROMs’ integration in primary health care and its impact on outcomes associated with the quintuple aim.

    We will use a 2-phase sequential mixed methods synthesis design (ie, conduct a qualitative synthesis) and use its results to perform a quantitative synthesis [39]. In phase 1 (qualitative), we will use a thematic synthesis procedure [40] wherein we will summarize and describe methods and approaches designed to implement and integrate ePROMs in primary care. The qualitative data synthesis will produce structured narrative summaries of main themes of data in accordance with the RE-AIM framework. In phase 2 (quantitative), for each phase 1 theme, we will synthesize quantitative data with study subgroups centered around the theme in a descriptive manner when statistics and calculation methods are available. We will summarize study characteristics and methodological differences and similarities to highlight the following points: strengths and weaknesses of each implementation method, main outcomes of implementation, main conclusions regarding the relationship between methods and outcomes, main resources used and their impacts, and whether any trade-offs are described and their effect on the results of the study. If data are available in the primary studies, sex and gender similarities and differences (eg, adoption and satisfaction) will be included in our synthesis. The diversity in team expertise, clinical background, and gender will contribute to the orientation of the synthesis and choices that could lead to inclusive recommendations for clinical choices and policies. This study will also follow the Canadian Institutes for Health Research’s SAGER (Sex and Gender Equity in Research) for study design and reporting of the results. If needed, we will also provide training in sex and gender equity for the trainees and the patient partners on the team [41].


    The study was initiated in June 2022 by assembling the research team and the knowledge transfer committee. The preliminary search strategy was developed and completed in September 2022. The main search strategy, data collection, study selection, and application of inclusion criteria were completed between October and December 2022. Data analysis will be completed and reports, briefs, and papers will be written from January to September 2023. The knowledge translation committee meets throughout the study period, once every 2 months, but more actively, from January to March 2023.


    In order to not only impact but also document the extent of success toward the abovementioned quintuple aim, health measurements must include patients’ self-evaluation of health, well-being, and behaviors that contribute to care quality, service comparability, provider performance, patient engagement, and general patient status. Effective implementation of relevant ePROMs in primary health care is necessary to orient chronic disease management that is patient-centered and personalized in a contemporary and modern context of care. This study aims to synthesize the learning from using ePROMs in primary health care organizations. This information will be useful in supporting the adoption of PROMs in clinical settings. Optimal implementation of PROMs in primary health care would improve perceived relevance and adoption by health care providers and patients. Results from this review will orient the delivery, accountability, effective implementation, and contextualized usefulness of PROMs for the implementation of ePROMs in clinical settings. Optimal implementation of ePROMs in primary health care would improve perceived relevance and adoption by health care providers and patients. Results from this review will orient the delivery, accountability, effective implementation, and contextualized usefulness of PROMs. The patient-centered approach facilitated by PROM use will greatly improve health equity for populations needing a personalized care approach of primary health care.

    Results from this review will help support implementation efforts to accelerate innovations and digital adoption for primary health care and will be relevant for improving clinical management of chronic diseases, health care services, and policies. Efficient ePROM implementation has a direct impact on the quintuple aim of improving patient experience, improving health, improving health professionals experience, improving care value, and advancing health equity.

    Data Availability

    The data sets generated during and/or analyzed during this study are available from the corresponding author on reasonable request.

    Conflicts of Interest

    NB is the director of scientific affairs for the electronic medical records provider Omni-Med.Com Inc.

    Multimedia Appendix 1

    Peer-review report.

    PDF File (Adobe PDF File), 419 KB
    1. Declaration of ALMA-ATA. Lancet. Nov 1978;312(8098):1040-1041. [CrossRef]
    2. Primary Health Care in Canada: A Chartbook of Selected Indicator Results, 2016. Ottawa, ON. Canadian Institute for Health Information; 2016.
    3. Betancourt M, Roberts K, Bennett T, Driscoll E, Jayaraman G, Pelletier L. Monitoring chronic diseases in Canada: the Chronic Disease Indicator Framework. Chronic Diseases and Injuries in Canada. 2014;34(1) [CrossRef]
    4. Plan statégique 2021-2026. 2021. URL: https:/​/cdn-contenu.​quebec.ca/​cdn-contenu/​curateur-public/​pdf/​plan_strat/​plan-stra tegique-2021-2026.​pdf [accessed 2023-05-18]
    5. Black N, Burke L, Forrest CB, Sieberer UHR, Ahmed S, Valderas JM, et al. Patient-reported outcomes: pathways to better health, better services, and better societies. Qual Life Res. May 13, 2016;25(5):1103-1112. [CrossRef] [Medline]
    6. Cuthbertson L. Patient-centred measurement in British Columbia: statistics without the tears wiped off. Healthc Pap. 2015;14(4):46-54. [Medline]
    7. Abernethy AP, Herndon JE, Wheeler JL, Patwardhan M, Shaw H, Lyerly HK, et al. Improving health care efficiency and quality using tablet personal computers to collect research-quality, patient-reported data. Health Serv Res. Dec 2008;43(6):1975-1991. [FREE Full text] [CrossRef] [Medline]
    8. Boyce MB, Browne JP, Greenhalgh J. The experiences of professionals with using information from patient-reported outcome measures to improve the quality of healthcare: a systematic review of qualitative research. BMJ Qual Saf. Jun 06, 2014;23(6):508-518. [FREE Full text] [CrossRef] [Medline]
    9. Suh S, LeBlanc TW, Shelby RA, Samsa GP, Abernethy AP. Longitudinal patient-reported performance status assessment in the cancer clinic is feasible and prognostic. JOP. Nov 2011;7(6):374-381. [CrossRef]
    10. Basch E, Deal AM, Kris MG, Scher HI, Hudis CA, Sabbatini P, et al. Symptom monitoring with patient-reported outcomes during routine cancer treatment: a randomized controlled trial. JCO. Feb 20, 2016;34(6):557-565. [CrossRef]
    11. Basch E, Deal AM, Dueck AC, Scher HI, Kris MG, Hudis C, et al. Overall survival results of a trial assessing patient-reported outcomes for symptom monitoring during routine cancer treatment. JAMA. Jul 11, 2017;318(2):197-198. [FREE Full text] [CrossRef] [Medline]
    12. McGrail K, Bryan S, Davis J. Let's all go to the PROM: the case for routine patient-reported outcome measurement in Canadian healthcare. Healthc Pap. Jan 2, 2011;11(4):8-18; discussion 55. [CrossRef] [Medline]
    13. Wu A, Snyder C. Getting ready for patient-reported outcomes measures (PROMs) in clinical practice. Healthc Pap. Jan 2, 2011;11(4):48-53; discussion 55. [CrossRef] [Medline]
    14. Gwaltney CJ, Shields AL, Shiffman S. Equivalence of electronic and paper-and-pencil administration of patient-reported outcome measures: a meta-analytic review. Value Health. Mar 2008;11(2):322-333. [FREE Full text] [CrossRef] [Medline]
    15. Kurt R, Bogner HR, Straton JB, Tien AY, Gallo JJ. Computer-assisted assessment of depression and function in older primary care patients. Comput Methods Programs Biomed. Feb 2004;73(2):165-171. [FREE Full text] [CrossRef] [Medline]
    16. Watson L, Qi S, Delure A, Link C, Photitai E, Chmielewski L, et al. Virtual cancer care during the COVID-19 pandemic in Alberta: evidence from a mixed methods evaluation and key learnings. JCO Oncology Practice. Sep 2021;17(9):e1354-e1361. [CrossRef]
    17. Watson L, Qi S, DeIure A, Link C, Chmielewski L, Hildebrand A, et al. Using Autoregressive Integrated Moving Average (ARIMA) modelling to forecast symptom complexity in an ambulatory oncology clinic: harnessing predictive analytics and patient-reported outcomes. Int J Environ Res Public Health. Aug 07, 2021;18(16):8365. [FREE Full text] [CrossRef] [Medline]
    18. Duman-Lubberding S, van Uden-Kraan CF, Jansen F, Witte BI, Eerenstein SEJ, van Weert S, et al. Durable usage of patient-reported outcome measures in clinical practice to monitor health-related quality of life in head and neck cancer patients. Support Care Cancer. Dec 12, 2017;25(12):3775-3783. [FREE Full text] [CrossRef] [Medline]
    19. Leahy AB, Feudtner C, Basch E. Symptom monitoring in pediatric oncology using patient-reported outcomes: why, how, and where next. Patient. Apr 25, 2018;11(2):147-153. [FREE Full text] [CrossRef] [Medline]
    20. Girgis A, Durcinoska I, Levesque JV, Gerges M, Sandell T, Arnold A, et al. PROMPT-Care Program Group. eHealth system for collecting and utilizing patient reported outcome measures for personalized treatment and care (PROMPT-Care) among cancer patients: mixed methods approach to evaluate feasibility and acceptability. J Med Internet Res. Oct 02, 2017;19(10):e330. [FREE Full text] [CrossRef] [Medline]
    21. Kotronoulas G, Kearney N, Maguire R, Harrow A, Di Domenico D, Croy S, et al. What is the value of the routine use of patient-reported outcome measures toward improvement of patient outcomes, processes of care, and health service outcomes in cancer care? A systematic review of controlled trials. JCO. May 10, 2014;32(14):1480-1501. [CrossRef]
    22. Chen J, Ou L, Hollis SJ. A systematic review of the impact of routine collection of patient reported outcome measures on patients, providers and health organisations in an oncologic setting. BMC Health Serv Res. Jun 11, 2013;13(1):211. [FREE Full text] [CrossRef] [Medline]
    23. Howell D, Molloy S, Wilkinson K, Green E, Orchard K, Wang K, et al. Patient-reported outcomes in routine cancer clinical practice: a scoping review of use, impact on health outcomes, and implementation factors. Ann Oncol. Sep 2015;26(9):1846-1858. [FREE Full text] [CrossRef] [Medline]
    24. Hubbard JM, Grothey AF, McWilliams RR, Buckner JC, Sloan JA. Physician perspective on incorporation of oncology patient quality-of-life, fatigue, and pain assessment into clinical practice. JOP. Jul 2014;10(4):248-253. [CrossRef]
    25. Murphy M, Hollinghurst S, Salisbury C. Identification, description and appraisal of generic PROMs for primary care: a systematic review. BMC Fam Pract. Mar 15, 2018;19(1):41. [FREE Full text] [CrossRef] [Medline]
    26. Ehrari H, Tordrup L, Müller S. The digital divide in healthcare: a socio-cultural perspective of digital literacy. 2022. URL: https://scholarspace.manoa.hawaii.edu/bitstreams/845332bf-9633-4d5a-80b6-19872633d150/download [accessed 2023-05-18]
    27. Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. Updating guidance for reporting systematic reviews: development of the PRISMA 2020 statement. J Clin Epidemiol. Jun 2021;134:103-112. [CrossRef] [Medline]
    28. Higgins J, Thomas J, Chandler J, Cumpston M, Li T, Page M, et al. Cochrane Handbook for Systematic Reviews of Interventions. Hoboken, NJ. Wiley Blackwell; 2019.
    29. Chien P, Khan K, Siassakos D. Registration of systematic reviews: PROSPERO. BJOG. Jul 2012;119(8):903-905. [CrossRef] [Medline]
    30. Guide to Knowledge Translation Planning at CIHR: Integrated and End-of-Grant Approaches. Canadian Institute for Health Information. 2012. URL: https://cihr-irsc.gc.ca/e/45321.html [accessed 2023-05-18]
    31. Strategy for Patient-Oriented Research - Patient Engagement Framework. Canadian Institute for Health Information. 2014. URL: https://cihr-irsc.gc.ca/e/48413.html [accessed 2023-05-18]
    32. McGowan J, Sampson M, Salzwedel DM, Cogo E, Foerster V, Lefebvre C. PRESS peer review of electronic search strategies: 2015 guideline statement. J Clin Epidemiol. Jul 2016;75:40-46. [FREE Full text] [CrossRef] [Medline]
    33. Hupe M. EndNote X9. J Electron Resour Medical Libr. Nov 26, 2019;16(3-4):117-119. [CrossRef]
    34. McHugh ML. Interrater reliability: the kappa statistic. Biochem Med. 2012:276-282. [CrossRef]
    35. Page M, McKenzie J, Bossuyt P, Boutron I, Hoffmann T, Mulrow C, et al. Updating guidance for reporting systematic reviews: development of the PRISMA 2020 statement. MetaArXiv. Preprint posted online September 14, 2020. [CrossRef]
    36. Hong QN, Pluye P, Fàbregues S, Bartlett G, Boardman F, Cargo M, et al. Improving the content validity of the mixed methods appraisal tool: a modified e-Delphi study. J Clin Epidemiol. Jul 2019;111:49-59.e1. [FREE Full text] [CrossRef] [Medline]
    37. Glasgow RE, Vogt TM, Boles SM. Evaluating the public health impact of health promotion interventions: the RE-AIM framework. Am J Public Health. Sep 1999;89(9):1322-1327. [CrossRef] [Medline]
    38. Glasgow RE, Dickinson P, Fisher L, Christiansen S, Toobert DJ, Bender BG, et al. Use of RE-AIM to develop a multi-media facilitation tool for the patient-centered medical home. Implement Sci. Oct 21, 2011;6(1):118. [FREE Full text] [CrossRef] [Medline]
    39. Hong QN, Pluye P, Bujold M, Wassef M. Convergent and sequential synthesis designs: implications for conducting and reporting systematic reviews of qualitative and quantitative evidence. Syst Rev. Mar 23, 2017;6(1):61. [FREE Full text] [CrossRef] [Medline]
    40. Laux G, Kuehlein T, Rosemann T, Szecsenyi J. Co- and multimorbidity patterns in primary care based on episodes of care: results from the German CONTENT project. BMC Health Serv Res. Jan 18, 2008;8(1):14. [FREE Full text] [CrossRef] [Medline]
    41. Heidari S, Babor TF, Castro PD, Tort S, Curno M. Equidade de sexo e gênero na pesquisa: fundamentação das diretrizes SAGER e uso recomendado*. Epidemiologia e Serviços de Saúde. Jul 2017;26(3):665-676. [CrossRef]

    ‎
    ePROM: electronic patient-reported outcome measure
    KU: knowledge user
    PRESS: Peer Review of Electronic Search Strategies
    PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses
    PROM: patient-reported outcome measure
    RE-AIM: reach, effectiveness, adoption, implementation, maintenance/sustainability
    SAGER: Sex and Gender Equity in Research

    Edited by T Leung; The proposal for this study was peer-reviewed by Catalyst Grant: Quadruple Aim and Equity/Subvention Catalyseur: Quatre objectifs et équité - Canadian Institutes of Health Research/Instituts de recherche en santé du Canada (CIHR/IRSC, Canada). See the Multimedia Appendix for the peer-review report;submitted 13.04.23; accepted 10.05.23; published 18.08.23.

    Copyright

    ©Maxime Sasseville, Wilfried Supper, Jean-Baptiste Gartner, Géraldine Layani, Samira Amil, Peter Sheffield, Marie-Pierre Gagnon, Catherine Hudon, Sylvie Lambert, Eugène Attisso, Victoria Bureau Lagarde, Mylaine Breton, Marie-Eve Poitras, Pierre Pluye, Pierre-Henri Roux-Levy, James Plaisimond, Frédéric Bergeron, Rachelle Ashcroft, Sabrina Wong, Antoine Groulx, Nicolas Beaudet, Jean-Sébastien Paquette, Natasha D'Anjou, Sylviane Langlois, Annie LeBlanc. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 18.08.2023.

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