  Background: Increasingly, decision-making in healthcare relies on computer
models, be it clinical prediction models at point of care or decision-analytic
models at the policymaking level. Given the important role models play in both
contexts, their structure and implementation be rigorously scrutinized. The
ability to interrogate input/output associations without facing barriers can
improve quality assurance mechanisms while satisfying privacy/confidentiality
concerns and facilitating the integration of models into decision-making. This
paper 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 the
side of model developer to make the model fit for cloud hosting, and 2) making
client access completely independent of the resource requirement and software
dependencies of the model. The server architecture integrates a RESTful
Application Programming Interface (API) infrastructure, JSON for data transfer,
a routing layer for access management, container technology for management of
computer resources and package dependencies, and the capacity for synchronous
or asynchronous model calls. Results: We discuss the architecture, the minimal
API standards that enable a universal language for access to such models, the
underlying server infrastructure, and the standards used for data transfer. An
instance of PRISM is available as a service via the Peer Models Network
http://peermodelsnetwork.com. Through a series of case studies, we demonstrate
how interrogating models becomes possible in standardized fashion, in a way
that is irrespective of the specifics of any model. Conclusions: We have
developed a publicly accessible platform and minimalist standards that
facilitate model accessibility for both clinical and policy models.
