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Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR)
BACKGROUND: Referral linkages are crucial for efficient functioning of primary health care (PHC) systems. Fast Healthcare Interoperability Resource (FHIR) is an open global standard that facilitates structuring of health information for coordinated exchange among stakeholders. OBJECTIVE: The objecti...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9305397/ https://www.ncbi.nlm.nih.gov/pubmed/35797096 http://dx.doi.org/10.2196/28510 |
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author | Chukwu, Emeka Garg, Lalit Obande-Ogbuinya, Nkiruka Chattu, Vijay Kumar |
author_facet | Chukwu, Emeka Garg, Lalit Obande-Ogbuinya, Nkiruka Chattu, Vijay Kumar |
author_sort | Chukwu, Emeka |
collection | PubMed |
description | BACKGROUND: Referral linkages are crucial for efficient functioning of primary health care (PHC) systems. Fast Healthcare Interoperability Resource (FHIR) is an open global standard that facilitates structuring of health information for coordinated exchange among stakeholders. OBJECTIVE: The objective of this study is to design FHIR profiles and present methodology and the profiled FHIR resource for Maternal and Child Health referral use cases in Ebonyi state, Nigeria—a typical low- and middle-income country (LMIC) setting. METHODS: Practicing doctors, midwives, and nurses were purposefully sampled and surveyed. Different referral forms were reviewed. The union of data sets from surveys and forms was aggregated and mapped to base patient FHIR resource elements, and extensions were created for data sets not in the core FHIR specification. This study also introduced FHIR and its relation to the World Health Organization’s (WHO’s) International Classification of Diseases. RESULTS: We found many different data elements from the referral forms and survey responses even in urban settings. The resulting FHIR standard profile is published on GitHub for adaptation or adoption as necessary to aid alignment with WHO recommendations. Understanding data sets used in health care and clinical practice for information sharing is crucial in properly standardizing information sharing, particularly during the management of COVID-19 and other infectious diseases. Development organizations and governments can use this methodology and profile to fast-track FHIR standards adoption for paper and electronic information sharing at PHC systems in LMICs. CONCLUSIONS: We presented our methodology for profiling the referral resource crucial for the standardized exchange of new and expectant moms’ information. Using data from frontline providers and mapping to the FHIR profile helped contextualize the standardized profile. |
format | Online Article Text |
id | pubmed-9305397 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-93053972022-07-23 Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR) Chukwu, Emeka Garg, Lalit Obande-Ogbuinya, Nkiruka Chattu, Vijay Kumar JMIR Form Res Original Paper BACKGROUND: Referral linkages are crucial for efficient functioning of primary health care (PHC) systems. Fast Healthcare Interoperability Resource (FHIR) is an open global standard that facilitates structuring of health information for coordinated exchange among stakeholders. OBJECTIVE: The objective of this study is to design FHIR profiles and present methodology and the profiled FHIR resource for Maternal and Child Health referral use cases in Ebonyi state, Nigeria—a typical low- and middle-income country (LMIC) setting. METHODS: Practicing doctors, midwives, and nurses were purposefully sampled and surveyed. Different referral forms were reviewed. The union of data sets from surveys and forms was aggregated and mapped to base patient FHIR resource elements, and extensions were created for data sets not in the core FHIR specification. This study also introduced FHIR and its relation to the World Health Organization’s (WHO’s) International Classification of Diseases. RESULTS: We found many different data elements from the referral forms and survey responses even in urban settings. The resulting FHIR standard profile is published on GitHub for adaptation or adoption as necessary to aid alignment with WHO recommendations. Understanding data sets used in health care and clinical practice for information sharing is crucial in properly standardizing information sharing, particularly during the management of COVID-19 and other infectious diseases. Development organizations and governments can use this methodology and profile to fast-track FHIR standards adoption for paper and electronic information sharing at PHC systems in LMICs. CONCLUSIONS: We presented our methodology for profiling the referral resource crucial for the standardized exchange of new and expectant moms’ information. Using data from frontline providers and mapping to the FHIR profile helped contextualize the standardized profile. JMIR Publications 2022-07-07 /pmc/articles/PMC9305397/ /pubmed/35797096 http://dx.doi.org/10.2196/28510 Text en ©Emeka Chukwu, Lalit Garg, Nkiruka Obande-Ogbuinya, Vijay Kumar Chattu. Originally published in JMIR Formative Research (https://formative.jmir.org), 07.07.2022. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Chukwu, Emeka Garg, Lalit Obande-Ogbuinya, Nkiruka Chattu, Vijay Kumar Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR) |
title | Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR) |
title_full | Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR) |
title_fullStr | Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR) |
title_full_unstemmed | Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR) |
title_short | Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR) |
title_sort | standardizing primary health care referral data sets in nigeria: practitioners' survey, form reviews, and profiling of fast healthcare interoperability resources (fhir) |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9305397/ https://www.ncbi.nlm.nih.gov/pubmed/35797096 http://dx.doi.org/10.2196/28510 |
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