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

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.

Fast Healthcare Interoperability Resources for Inpatient Deterioration Detection With Time-Series Vital Signs: Design and Implementation Study

“…The implementation guide is a collection of rules applied by FHIR resources [15] that requires a clear explanation of how to solve a particular problem. In the relevant studies on FHIR [16][17][18], each paper develops and discusses a single customized resource profile on a mobile device. Although FHIR can effectively and rapidly improve health care information system interoperability, it still has not proposed an implementation guide for the machine learning application in FHIR implementation guide registry.…”

“…The PHRs were managed through a cloud server using Azure API for FHIR, and the PHR FHIR resources included Patient, Organization, DiagnosticReport, Observation, Practitioner, Condition, Procedure, MedicationStatement, Medication, and Encounter. In addition, Chukwu et al [18] profiled FHIR resources for maternal and child health referral use cases. Our study is distinguished from these previous works because we provided the IHCA implementation guidance regarding the use of FHIR resources as a conduit for the data required by the early monitoring system and machine learning.…”