Three members of the Innovation and Value Initiative (IVI) recently published a paper entitled “Open-Source Tools for Value Assessment: A Promising Approach” in the Journal of Clinical Pathways. This paper lays out, in brief, some of the ways that open-source models can contribute to the challenging environment in which value assessment operates in the US.
Unlike many nations where cost-effectiveness analysis is widely used and accepted, the US has a highly decentralized healthcare system. Even when up to date US-based models are available, they are likely not applicable to every patient population. This matters because not only does treatment response vary between populations, but so does the conception of value.
Meanwhile, healthcare decision makers must assess what evidence on value exists while simultaneously trying to assess its applicability to their patients, all without robust guidance on how to adapt the conclusions of modeling studies.
IVI has tried to change this by releasing an open-source microsimulation model for rheumatoid arthritis – a common disease whose treatment with biologics has become a significant driver of drug costs for many payers. This model is extremely flexible and speaks to the needs of healthcare decision makers by allowing for modification of treatment sequences, elements considered in the definition of value, and even whether results are formatted as a cost-effectiveness analysis or a multi-criteria decision analysis. Better still, this software is released as both a convenient web-app and as an R package with fully open code.
This is a tremendous step forward for value assessment in the US and sets a new standard for openness in modeling. Still, I can’t help but wonder how this transition from proprietary, closed models to open models will be funded. After all, IVI is in a unique position, with funding from many large pharmaceutical companies and industry organizations. If every consulting company had to organize a consortium to fund its open-source modeling initiatives, this would quickly become very burdensome.
As the “Open-Source Tools” paper points out, IVI took its inspiration for its rheumatoid arthritis model from open-source software, and we can do the same in thinking about how open-source modeling efforts could be supported. Some companies who develop open-source software support themselves by offering paid support plans for their products. A typical example here would be Canonical, which develops the Ubuntu Linux distribution. While it offers its operating system for free to anyone who wants it, it also offers paid plans that include help with deployment and maintenance.
It’s hard to know whether the scale of a typical model’s distribution would allow for this source of income, though. While Linux users number in the millions, a typical value model may have just dozens of users. Competition is likely to be important to motivate the timely development and updating of models, but the question of funding needs to be solved before more developers can take part.
The real value of an open source model depends too on the data it uses. To truly customize a model to a patient population, more granular data on patient response needs to be made available from clinical trials and disease registries. Until this happens, the conclusions of models may be based on estimated shifts in response from small samples.
The shift toward open-source modeling is an important means of responding to the challenges presented by the US healthcare market. However, many problems remain unsolved that for now still prevent more models from being developed in an open and flexible way.