Scaling up a decentralized offline patient ID generation and matching algorithm to accelerate universal health coverage: Insights from a literature review and health facility survey in Nigeria - Chukwu, Emeka; Ekong, Iniobong; Garg, Lalit (Frontiers in Digital Health, 2022)
Background: Quality of health service delivery data remains sub-optimal in many Low and middle-income countries (LMIC) despite over a decade of progress in digitization and Health Management Information Systems (HMIS). Identifying everyone residing in a country, for example utilizing universal civil registration and/or national unique identification number systems for patients seeking care with the care continuum, is an essential part of pursuing universal health coverage (UHC) especially for vulnerable members of the population. Many different strategies or candidate digital technologies exist for uniquely identifying and tracking patients within a health system, and the different strategies also have their advantages and trade-offs. The recent approval of Decentralized identifier (DID) core specification by World Wide Web Consortium (W3C) heralds the search for consensus on standard interoperable DID methods. Objective: This paper uses Nigeria, a LMIC country, to demonstrate how leading candidates for Patient identification fit in the digital Patient ID desirable attributes framework and uses insights to propose the scale-up an offline, interoperable decentralized Patient ID generation and matching model for addressing- network reliability challenges in LMICs as well as accelerate achievement of universal health coverage. Methods: We reviewed the extant literature to identify the characteristics of leading candidates for Patient ID systems in Nigeria, combined with a quantitative survey of general hospitals (n=14) in Nigeria's Federal Capital Territory to understand the model(s) of patient ID strategies currently adopted or implemented by public health facilities Results: Analysis from both the literature review and the hospitals survey showed that no current Patient ID strategy in Nigeria simultaneously meets the six attributes of uniqueness, unchanging, uncontroversial, inexpensive, ubiquitous, and uncomplicated required for ensuring the reliability of unique patient identification systems and of the HMIS more generally. Conclusions: The findings are used to propose a model of algorithms for universal-offline Patient ID generation and matching models that can be easily scaled-up throughout Nigeria. The prototype has promise for generating and validating a universally unique Patient ID given a set of Patient characteristics without a central rigid authority. The model can also help to fast-track the implementation of a Master Patient Index (MPI) in LMICs.