Machine Learning and Blockchain in Population Health
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The volume of healthcare data continues to increase exponentially—burdening healthcare organizations with the management of disparate data sets, interoperability challenges between source systems and the complexities of unstructured data.
Machine learning can be used to build models for patient risk scores, cost prediction and patient behavior, optimization and automation of SDoH service referrals, and to tap into unstructured data.
Blockchain generates auditability and traceability between stakeholders. With a single source of truth that reduces errors and the need for reconciliation, it addresses patient privacy concerns and population health data requirements.