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

Amin Adibi, Stephanie Harvard, Mohsen Sadatsafavi

Abstract:

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.
Keywords: accessibility, transparency, modeling in healthcare, disease modeling, decision-
analytics, health economics