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Background: Increasingly, decision-making in healthcare relies on computermodels, be it clinical prediction models at point of care or decision-analyticmodels at the policymaking level. Given the important role models play in bothcontexts, their structure and implementation be rigorously scrutinized. Theability to interrogate input/output associations without facing barriers canimprove quality assurance mechanisms while satisfying privacy/confidentialityconcerns and facilitating the integration of models into decision-making. Thispaper reports on the development of Programmable Interface for Statistical &Simulation Models (PRISM), a cloud-based platform for model accessibility.Methods: PRISM emphasizes two main principles: 1) minimal specifications on theside of model developer to make the model fit for cloud hosting, and 2) makingclient access completely independent of the resource requirement and softwaredependencies of the model. The server architecture integrates a RESTfulApplication Programming Interface (API) infrastructure, JSON for data transfer,a routing layer for access management, container technology for management ofcomputer resources and package dependencies, and the capacity for synchronousor asynchronous model calls. Results: We discuss the architecture, the minimalAPI standards that enable a universal language for access to such models, theunderlying server infrastructure, and the standards used for data transfer. Aninstance of PRISM is available as a service via the Peer Models Networkhttp://peermodelsnetwork.com. Through a series of case studies, we demonstratehow interrogating models becomes possible in standardized fashion, in a waythat is irrespective of the specifics of any model. Conclusions: We havedeveloped a publicly accessible platform and minimalist standards thatfacilitate model accessibility for both clinical and policy models.

Programmable Interface for Statistical & Simulation Models (PRISM): Towards Greater Accessibility of Clinical and Healthcare Decision Models