Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR)

Emeka Chukwu; Lalit Garg; Nkiruka Obande-Ogbuinya; Vijay Kumar Chattu

doi:10.2196/28510

Standardizing Primary Health Care Referral Data Sets in Nigeria: Practitioners' Survey, Form Reviews, and Profiling of Fast Healthcare Interoperability Resources (FHIR)

JMIR Form Res. 2022 Jul 7;6(7):e28510. doi: 10.2196/28510.

Authors

Emeka Chukwu^{1

2}, Lalit Garg¹, Nkiruka Obande-Ogbuinya³, Vijay Kumar Chattu^{4

5

6}

Affiliations

¹ Department of Computer Information Systems, Faculty of Information Communication Technology, University of Malta, Msida, Malta.
² Digital Health Interoperability Network, Abuja, Nigeria.
³ Department of Science Education, Alex-Ekwueme Federal University Ndufu-Alike, Ikwo, Ebonyi, Nigeria.
⁴ Department of Occupational Science & Occupational Therapy, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
⁵ Center for Transdisciplinary Research, Saveetha Institute of Medical and Technological Sciences, Saveetha University, Chennai, India.
⁶ Department of Community Medicine, Faculty of Medicine, Datta Meghe Institute of Medical Sciences, Wardha, India.

PMID: 35797096
PMCID: PMC9305397
DOI: 10.2196/28510

Abstract

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.

Keywords: BlockMom; COVID-19; FHIR; Nigeria; digital health; eHealth; health information; health information exchange; interoperability; mHealth; primary health care.

©Emeka Chukwu, Lalit Garg, Nkiruka Obande-Ogbuinya, Vijay Kumar Chattu. Originally published in JMIR Formative Research (https://formative.jmir.org), 07.07.2022.