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

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 health information for coordinated exchange amongst stakeholders. OBJECTIVE The objective of this study is to profile, present methodology and the profiled FHIR resource for Maternal and Child Health (MNCH) referral use case in a typical Low-and-Middle-Income-Country (LMIC). METHODS Practicing doctors, midwives, and nurses were interviewed, and different referral forms reviewed. In this study, we have introduced the FHIR and its relation to the WHO International Classification for Disease (ICD). The union of datasets were aggregated and mapped to base patient FHIR resource elements, and extensions were created for datasets not in the core FHIR specification. RESULTS We found that there were many different data elements from the referral forms and interview responses. The resulting FHIR standard profile is published on GitHub for adaptation or adoption as necessary. Understanding datasets used in healthcare and clinical practice for information sharing is crucial in properly standardizing information sharing particularly as the world manage COVID-19 and other infectious diseases. This methodology and profiled dataset can be used by development organizations, and governments to fast-track FHIR standards adoption for paper and electronic information sharing at PHCs 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 mapped to the FHIR profile helped contextualize the standardized profile.