As the world becomes ever more technology driven, software systems and models can be complex and not necessarily user-friendly, leading to underutilization and impractical approaches for aiding decision making. User centered design (UCD) principles, as the name suggests, are centered in the approach that the end user is an integral part of the design process, and their feedback will aid in the development of a system or model that is easy and enjoyable to use, and most importantly, fits the purpose it is intended for. Systems for aiding decision making in cancer care can provide evidence-based tools for cancer control programs, but again are underutilized. In the realm of cancer survivorship, scientific evidence-based models could provide cancer control programs with effective tools for allocating funding and resources and implementing programs, such as exercise interventions and psychological counselling services, for cancer survivors. While it is understood and acknowledged that the term ‘cancer survivor’ can mean different things to different people, for the purpose of this article, the term refers to a person alive one year after a diagnosis of female breast, colorectal, lung or prostate cancer. A recent study, led by Dr. Zachary Rivers and Dr. Scott Ramsey, Associate Program Leader of the Cancer Epidemiology, Prevention and Control Research Program at the Cancer Consortium, addressed the need for a user friendly system to aid in cost-benefit decision making for public health officials when allocating resources for this population. Their work, recently published in MDM Policy & Practice, utilized UCD principles and end-user focus groups to design a user friendly decision making tool for resource allocation.
Following UCD principles, the authors first designed a model that utilized health outcome data for cancer survivors, as defined above, who were followed over a ten-year timeframe, and assessed the cost of survivorship interventions. Their primary output variable was to compare the cost-benefit ratio of enacting a survivorship intervention versus standard of care and they utilized data from publicly available cancer registries and health outcomes literature for designing input parameters. Taken together, the aspects of their design would allow users to determine the benefits for cancer survivors in QALY (quality adjusted life year, a value that measures both the quality and quantity of life and is often used in health outcomes economic research) and life-years, costs, and monetary benefits of implementing an intervention versus simply continuing standard of care.
The next step for the authors was to convene focus groups of end-users to solicit their feedback and engagement with the model. This occurred over two phases, group 1 – state level participants, and group 2 – national level participants (participants from the Centers for Disease Control and Prevention (CDC)). After testing the model, group 1 provided positive feedback about how they felt a model or a tool of this nature could have an impactful benefit by reaching more cancer survivors with relevant interventions. However, the users also described how technically difficult the first iteration of the model was, and how it was not conducive for someone to use without a background in epidemiology. They provided the authors with suggestions for improving the model including using simplified, plain language, and the ability to be able to access outcome data by individual cancer type. The authors took this feedback on board and developed a revised model, one with a simplified user interface with plain language summaries and explanations, and the ability to view one specific cancer type at a time. The authors also developed a second user interface, with more advanced options, that may be preferable for those with health economics training. After testing the revised iteration of the model, Group 1 felt that the updated version was more needs appropriate and easier to use. Group 2 also provided feedback regarding the use of plain, accessible language and providing support within the model itself. The authors further revised the model with clearer language and a more accessible user guide.
The data derived from this study signify the importance of UCD principles in health economics and cancer survivorship, and further emphasizes the necessity of plain language and support within models/systems designed to aid decision making in survivorship interventions. The authors highlight in their conclusions how this approach is “an opportunity to remove barriers for evidence-based program selection in public health interventions and as a step forward in translating cost-effectiveness modeling into real-world use.”
This work was supported by the American Public Health Association and the Centers for Disease Control and Prevention.
Fred Hutch/University of Washington/Seattle Children's Cancer Consortium member Scott D. Ramsey contributed to this work.
Rivers Z, Roth JA, Wright W, Rim SH, Richardson LC, Thomas CC, Townsend JS, Ramsey SD. Translating an Economic Analysis into a Tool for Public Health Resource Allocation in Cancer Survivorship. MDM Policy Pract. 2023 Feb 9;8(1):23814683231153378. doi: 10.1177/23814683231153378. PMID: 36798090; PMCID: PMC9926380.