Whole Disease Modeling for Health Technology Management: the need for Open Source approaches

20 January 2021

Whole Disease Models (WDMs) are designed to address the broader decision environment around a given technology adoption question – how do ‘upstream’ and ‘downstream’ policy changes impact the cost-effectiveness of an intervention of interest? As HTA agencies consider a shift toward the management of technologies (i.e., considering the implications of their full life cycle beyond adoption), WDMs have a clear application. The complexity of WDMs, especially in the presence of rapidly-evolving changes in the structure of the health care system and the availability of new technologies, means that WDMs might be obsolete by the time they can be built.

In this presentation, Dr. Cromwell will describe the design, construction, and use of a WDM for this purpose in the context of oral cancer, and the necessary role that collaboration through Open Source decision modeling approaches will play if the full potential of this approach is to be realized.

Whole Disease Modeling for Health Technology Management: the need for Open Source approaches


Ian completed his MSc in epidemiology at Queen’s, specializing in health economics and decision modeling. From there, Ian moved to his current home of Vancouver, BC to begin working as a health economist at BC Cancer conducting model-based and RWE-based economic evaluations in oncology as part of the ARCC network. Ian’s PhD work at UBC focused on the use of Whole Disease Modeling to evaluate the impact of multiple policy adoption within oral cancer. In his current role at CADTH, Ian oversees evidence appraisal and synthesis projects for drugs and other health technologies to inform Canadian health care decision-making.

Outside of work, Ian is a seasoned performer on violin and guitar, and is the creator and host of Locals Lounge, a collective focused on broadening participation within Vancouver’s local music scene. Ian tweets at @HlthyUncert, and blogs at http://healthyuncertainty.github.io