Computer network architecture with benchmark automation, machine learning and artificial intelligence for measurement factors

Abstract

The present disclosure is related generally to computer network architectures for machine learning, and more specifically, to computer network architectures for the automated production and distribution of custom healthcare performance benchmarks for specific patient cohorts. Embodiments allow specification and automated production of benchmarks using any of many dozens of patient, disease process, facility, and physical location attributes. Embodiments may use an analytic module web application and a benchmark service module web application, with other architecture components. Embodiments may include a combination of third-party databases to generate benchmarks and to drive the forecasting models, including social media data, financial data, socio-economic data, medical data, search engine data, e-commerce site data, and other databases.