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A decentralized Offline Patient ID Generation and Matching Algorithm: The Nigeria phone-based model (Preprint)


 UNSTRUCTURED
 Quality of health service delivery data remains sub-optimal in many developing countries despite over a decade of progress in digitization and Health Management Information System (HMIS). Uniquely identifying Patients within the care continuum is the only way to guarantee better outcomes hinged on shared health records. Many different strategies exist for uniquely identifying and tracking a patient in a health system, and they also have their trade-offs. Nigeria, a typical low-and-middle-income country is used to demonstrate the survey of how leading candidates for Patient identification fit in the digital Patient ID desirable attributes framework. The network resource constraints inherent in low-and-middle-income countries is illustrated. We show that no current Patient ID strategy simultaneously meets the six attributes of uniqueness, unchanging, uncontroversial, inexpensive, ubiquitous, and uncomplicated. We designed and prototyped decentralized algorithms for universal-offline, unique Patient ID generation with a dual deterministic and probabilistic patient matching model.
