Development of a social and environmental determinants of health informatics maturity model
Abstract Introduction: Integrating social and environmental determinants of health (SEDoH) into enterprise-wide clinical workflows and decision-making is one of the most important and challenging aspects of improving health equity. We engaged domain experts to develop a SEDoH informatics maturity...
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| Format: | Article |
| Language: | English |
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Cambridge University Press
2023-01-01
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| Series: | Journal of Clinical and Translational Science |
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| Online Access: | https://www.cambridge.org/core/product/identifier/S205986612300691X/type/journal_article |
| _version_ | 1797367827480444928 |
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| author | Juan C. Espinoza Shruti Sehgal Jimmy Phuong Neil Bahroos Justin Starren Adam Wilcox Daniella Meeker |
| author_facet | Juan C. Espinoza Shruti Sehgal Jimmy Phuong Neil Bahroos Justin Starren Adam Wilcox Daniella Meeker |
| author_sort | Juan C. Espinoza |
| collection | DOAJ |
| description |
Abstract
Introduction:
Integrating social and environmental determinants of health (SEDoH) into enterprise-wide clinical workflows and decision-making is one of the most important and challenging aspects of improving health equity. We engaged domain experts to develop a SEDoH informatics maturity model (SIMM) to help guide organizations to address technical, operational, and policy gaps.
Methods:
We established a core expert group consisting of developers, informaticists, and subject matter experts to identify different SIMM domains and define maturity levels. The candidate model (v0.9) was evaluated by 15 informaticists at a Center for Data to Health community meeting. After incorporating feedback, a second evaluation round for v1.0 collected feedback and self-assessments from 35 respondents from the National COVID Cohort Collaborative, the Center for Leading Innovation and Collaboration’s Informatics Enterprise Committee, and a publicly available online self-assessment tool.
Results:
We developed a SIMM comprising seven maturity levels across five domains: data collection policies, data collection methods and technologies, technology platforms for analysis and visualization, analytics capacity, and operational and strategic impact. The evaluation demonstrated relatively high maturity in analytics and technological capacity, but more moderate maturity in operational and strategic impact among academic medical centers. Changes made to the tool in between rounds improved its ability to discriminate between intermediate maturity levels.
Conclusion:
The SIMM can help organizations identify current gaps and next steps in improving SEDoH informatics. Improving the collection and use of SEDoH data is one important component of addressing health inequities.
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| first_indexed | 2024-03-08T17:23:41Z |
| format | Article |
| id | doaj.art-5bcb98ff5cbf48349011d4c6bf7e69be |
| institution | Directory Open Access Journal |
| issn | 2059-8661 |
| language | English |
| last_indexed | 2024-03-08T17:23:41Z |
| publishDate | 2023-01-01 |
| publisher | Cambridge University Press |
| record_format | Article |
| series | Journal of Clinical and Translational Science |
| spelling | doaj.art-5bcb98ff5cbf48349011d4c6bf7e69be2024-01-03T02:27:44ZengCambridge University PressJournal of Clinical and Translational Science2059-86612023-01-01710.1017/cts.2023.691Development of a social and environmental determinants of health informatics maturity modelJuan C. Espinoza0https://orcid.org/0000-0003-0513-588XShruti Sehgal1https://orcid.org/0000-0001-6352-8628Jimmy Phuong2Neil Bahroos3Justin Starren4Adam Wilcox5Daniella Meeker6Stanley Manne Children’s Research Institute, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA Northwestern University Feinberg School of Medicine, Chicago, IL, USANorthwestern University Feinberg School of Medicine, Chicago, IL, USADivision of Biomedical and Health Informatics, University of Washington, Seattle, WA, USA Harborview Injury Prevention Research Center, University of Washington, Seattle, WA, USAUniversity of Southern California Keck School of Medicine, Los Angeles, CA, USANorthwestern University Feinberg School of Medicine, Chicago, IL, USAInstitute for Informatics, Department of Medicine, Washington University in St. Louis, St. Louis, MO, USADepartment of Biomedical Informatics & Data Science, Yale University School of Medicine, New Haven, CT, USA Abstract Introduction: Integrating social and environmental determinants of health (SEDoH) into enterprise-wide clinical workflows and decision-making is one of the most important and challenging aspects of improving health equity. We engaged domain experts to develop a SEDoH informatics maturity model (SIMM) to help guide organizations to address technical, operational, and policy gaps. Methods: We established a core expert group consisting of developers, informaticists, and subject matter experts to identify different SIMM domains and define maturity levels. The candidate model (v0.9) was evaluated by 15 informaticists at a Center for Data to Health community meeting. After incorporating feedback, a second evaluation round for v1.0 collected feedback and self-assessments from 35 respondents from the National COVID Cohort Collaborative, the Center for Leading Innovation and Collaboration’s Informatics Enterprise Committee, and a publicly available online self-assessment tool. Results: We developed a SIMM comprising seven maturity levels across five domains: data collection policies, data collection methods and technologies, technology platforms for analysis and visualization, analytics capacity, and operational and strategic impact. The evaluation demonstrated relatively high maturity in analytics and technological capacity, but more moderate maturity in operational and strategic impact among academic medical centers. Changes made to the tool in between rounds improved its ability to discriminate between intermediate maturity levels. Conclusion: The SIMM can help organizations identify current gaps and next steps in improving SEDoH informatics. Improving the collection and use of SEDoH data is one important component of addressing health inequities. https://www.cambridge.org/core/product/identifier/S205986612300691X/type/journal_articleSocial determinants of healthinformaticsmaturity modelshealth equityclinical and translational research |
| spellingShingle | Juan C. Espinoza Shruti Sehgal Jimmy Phuong Neil Bahroos Justin Starren Adam Wilcox Daniella Meeker Development of a social and environmental determinants of health informatics maturity model Journal of Clinical and Translational Science Social determinants of health informatics maturity models health equity clinical and translational research |
| title | Development of a social and environmental determinants of health informatics maturity model |
| title_full | Development of a social and environmental determinants of health informatics maturity model |
| title_fullStr | Development of a social and environmental determinants of health informatics maturity model |
| title_full_unstemmed | Development of a social and environmental determinants of health informatics maturity model |
| title_short | Development of a social and environmental determinants of health informatics maturity model |
| title_sort | development of a social and environmental determinants of health informatics maturity model |
| topic | Social determinants of health informatics maturity models health equity clinical and translational research |
| url | https://www.cambridge.org/core/product/identifier/S205986612300691X/type/journal_article |
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