IDEAS home Printed from https://ideas.repec.org/a/plo/pdig00/0000509.html
   My bibliography  Save this article

Construction of the Digital Health Equity-Focused Implementation Research Conceptual Model - Bridging the Divide Between Equity-focused Digital Health and Implementation Research

Author

Listed:
  • Lisa L Groom
  • Antoinette M Schoenthaler
  • Devin M Mann
  • Abraham A Brody

Abstract

Digital health implementations and investments continue to expand. As the reliance on digital health increases, it is imperative to implement technologies with inclusive and accessible approaches. A conceptual model can be used to guide equity-focused digital health implementations to improve suitability and uptake in diverse populations. The objective of this study is expand an implementation model with recommendations on the equitable implementation of new digital health technologies. The Digital Health Equity-Focused Implementation Research (DH-EquIR) conceptual model was developed based on a rigorous review of digital health implementation and health equity literature. The Equity-Focused Implementation Research for Health Programs (EquIR) model was used as a starting point and merged with digital equity and digital health implementation models. Existing theoretical frameworks and models were appraised as well as individual equity-sensitive implementation studies. Patient and program-related concepts related to digital equity, digital health implementation, and assessment of social/digital determinants of health were included. Sixty-two articles were analyzed to inform the adaption of the EquIR model for digital health. These articles included digital health equity models and frameworks, digital health implementation models and frameworks, research articles, guidelines, and concept analyses. Concepts were organized into EquIR conceptual groupings, including population health status, planning the program, designing the program, implementing the program, and equity-focused implementation outcomes. The adapted DH-EquIR conceptual model diagram was created as well as detailed tables displaying related equity concepts, evidence gaps in source articles, and analysis of existing equity-related models and tools. The DH-EquIR model serves to guide digital health developers and implementation specialists to promote the inclusion of health-equity planning in every phase of implementation. In addition, it can assist researchers and product developers to avoid repeating the mistakes that have led to inequities in the implementation of digital health across populations.Author summary: Digital health is becoming increasingly prevalent in our society, and it is essential that these technologies are designed with inclusivity and accessibility in mind. There are currently no comprehensive implementation models in digital health geared towards equity. To address this need, we developed a conceptual model called the Digital Health Equity-Focused Research Implementation framework. We completed a comprehensive review of existing literature on digital health implementation and digital health equity. The model merges the findings from this review into the existing Equity-focused Implementation Research model. The resulting digital health equity-focused implementation framework consists of five phases: assessing population health status, planning the program, designing the program, implementing the program, and equity-based outcomes. By promoting inclusivity and accessibility, the framework has the potential to improve the suitability and uptake of digital health technologies in diverse communities. By following this framework, researchers and developers can ensure that digital health equity planning is integrated into every step of the implementation process.

Suggested Citation

  • Lisa L Groom & Antoinette M Schoenthaler & Devin M Mann & Abraham A Brody, 2024. "Construction of the Digital Health Equity-Focused Implementation Research Conceptual Model - Bridging the Divide Between Equity-focused Digital Health and Implementation Research," PLOS Digital Health, Public Library of Science, vol. 3(5), pages 1-21, May.
  • Handle: RePEc:plo:pdig00:0000509
    DOI: 10.1371/journal.pdig.0000509
    as

    Download full text from publisher

    File URL: https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000509
    Download Restriction: no

    File URL: https://journals.plos.org/digitalhealth/article/file?id=10.1371/journal.pdig.0000509&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pdig.0000509?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Yin Paradies & Jehonathan Ben & Nida Denson & Amanuel Elias & Naomi Priest & Alex Pieterse & Arpana Gupta & Margaret Kelaher & Gilbert Gee, 2015. "Racism as a Determinant of Health: A Systematic Review and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-48, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yuqi Wang & Laurent Reyes & Emily A. Greenfield & Sarah R. Allred, 2022. "Municipal Ethnic Composition and Disparities in COVID-19 Infections in New Jersey: A Blinder–Oaxaca Decomposition Analysis," IJERPH, MDPI, vol. 19(21), pages 1-25, October.
    2. Malat, Jennifer & Mayorga-Gallo, Sarah & Williams, David R., 2018. "The effects of whiteness on the health of whites in the USA," Social Science & Medicine, Elsevier, vol. 199(C), pages 148-156.
    3. Hamed, Sarah & Bradby, Hannah & Thapar-Björkert, Suruchi & Ahlberg, Beth Maina, 2024. "Healthcare staff's racialized talk: The perpetuation of racism in healthcare," Social Science & Medicine, Elsevier, vol. 355(C).
    4. Caryn N. Bell & Jordan Kerr & Jessica L. Young, 2019. "Associations between Obesity, Obesogenic Environments, and Structural Racism Vary by County-Level Racial Composition," IJERPH, MDPI, vol. 16(5), pages 1-17, March.
    5. Ricci B Harris & James Stanley & Donna M Cormack, 2018. "Racism and health in New Zealand: Prevalence over time and associations between recent experience of racism and health and wellbeing measures using national survey data," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-22, May.
    6. Nazan Ulusoy & Anja Schablon, 2020. "Discrimination in In-Patient Geriatric Care: A Qualitative Study on the Experiences of Employees with a Turkish Migration Background," IJERPH, MDPI, vol. 17(7), pages 1-14, March.
    7. Lubna Rashid & Silvia Cepeda-García, 2021. "Self-Categorising and Othering in Migrant Integration: The Case of Entrepreneurs in Berlin," Sustainability, MDPI, vol. 13(4), pages 1-14, February.
    8. Ebrahimi, Chantel T. & Song, Hannah & Machado, Monica & Segura, Pamela & Espinosa, Adriana & Polanco-Roman, Lillian, 2024. "Racism-related experiences and substance use: A systematic and meta-analytic review," Social Science & Medicine, Elsevier, vol. 362(C).
    9. Uršula Lipovec Čebron, 2021. "Language as a Trigger for Racism: Language Barriers at Healthcare Institutions in Slovenia," Social Sciences, MDPI, vol. 10(4), pages 1-17, March.
    10. D'Costa, Ieta & Truong, Mandy & Russell, Lynette & Adams, Karen, 2023. "Employee perceptions of race and racism in an Australian hospital," Social Science & Medicine, Elsevier, vol. 339(C).
    11. Bastos, João L. & Harnois, Catherine E. & Paradies, Yin C., 2018. "Health care barriers, racism, and intersectionality in Australia," Social Science & Medicine, Elsevier, vol. 199(C), pages 209-218.
    12. Jill Furzer & Boriana Miloucheva, 2020. "The Long Arm of the Clean Air Act: Pollution Abatement and COVID-19 Racial Disparities," Working Papers tecipa-668, University of Toronto, Department of Economics.
    13. Chen, Shanting & Mallory, Allen B., 2021. "The effect of racial discrimination on mental and physical health: A propensity score weighting approach," Social Science & Medicine, Elsevier, vol. 285(C).
    14. Rachel Hennein & Jessica Bonumwezi & Max Jordan Nguemeni Tiako & Petty Tineo & Sarah R. Lowe, 2021. "Racial and Gender Discrimination Predict Mental Health Outcomes among Healthcare Workers Beyond Pandemic-Related Stressors: Findings from a Cross-Sectional Survey," IJERPH, MDPI, vol. 18(17), pages 1-14, September.
    15. Ana Isabel Maldonado & Carol B. Cunradi & Anna María Nápoles, 2020. "Racial/Ethnic Discrimination and Intimate Partner Violence Perpetration in Latino Men: The Mediating Effects of Mental Health," IJERPH, MDPI, vol. 17(21), pages 1-17, November.
    16. Susan B. Sisson & Adrien Malek-Lasater & Timothy G. Ford & Diane Horm & Kyong-Ah Kwon, 2023. "Predictors of Overweight and Obesity in Early Care and Education Teachers during COVID-19," IJERPH, MDPI, vol. 20(3), pages 1-16, February.
    17. World Bank, 2024. "Examining Racism and Discrimination in the Middle East and North Africa Region," World Bank Publications - Reports 42028, The World Bank Group.
    18. Katrina D Hopkins & Carrington C J Shepherd & Catherine L Taylor & Stephen R Zubrick, 2015. "Relationships between Psychosocial Resilience and Physical Health Status of Western Australian Urban Aboriginal Youth," PLOS ONE, Public Library of Science, vol. 10(12), pages 1-16, December.
    19. Lanqin Yuan & Tianyu Wang & Gabriela Ferraro & Hanna Suominen & Marian-Andrei Rizoiu, 2023. "Transfer learning for hate speech detection in social media," Journal of Computational Social Science, Springer, vol. 6(2), pages 1081-1101, October.
    20. Gilbert, Paul A. & Zemore, Sarah E., 2016. "Discrimination and drinking: A systematic review of the evidence," Social Science & Medicine, Elsevier, vol. 161(C), pages 178-194.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pdig00:0000509. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: digitalhealth (email available below). General contact details of provider: https://journals.plos.org/digitalhealth .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.