Case study: Fabricated Economic Evaluation Case Studies
Please note that the details below are fabricated for the purposes of illustrating health economic methodology.
Company X has developed an online rehabilitation platform and digital assessment technology for stroke survivors. Patients are able to use the platform and technology for exercises without the supervision of healthcare professionals, such as occupational therapists and physiotherapists. Previous studies have revealed that repetitive exercise is essential for increasing strength, however this is not always possible for stroke survivors. Reasons for this may be due to the strain on NHS resources or due to stroke survivors not being able to engage in independent exercise or rehabilitation activities.
Context: Company X has recently conducted a clinical trial to evaluate whether the technology enabled an increase in exercise. Results from the clinical trial were positive, with a 300% increase in exercise repetitions. Company X wants to understand the impact in a real world setting and the potential savings to the NHS from implementing their technology and platform in stroke rehabilitation services.
Health economic solution: To understand the impact of implementing Company X’s technology and platform in stroke rehabilitation services, an ex-ante cost-benefit analysis (CBA) is developed using results from implementation at its first site. The CBA will explore benefits in a long-time horizon (3 or 5 years) and will incorporate the financial benefits to the NHS, in addition to social benefits delivered through the technology. Problems caused by strokes can significantly impact survivors, making daily tasks more difficult and limit independence. The cost benefit analysis will allow for exploration of all benefits, for example relating to independence, such as reduced care costs or the improved quality of life of the survivor. Some of the costs and benefits will be calculated based on the data from the first site or clinical trial, although some may be gathered from other sources. This may for example, include populating assumptions where data does not exist with similar intervention examples, project types or literature, with the aim to monetise the potential impact.
The CBA may then include a sensitivity analysis, a process through which the robustness of an economic model is assessed by examining the changes in results when key variables are varied over a specified range. Conducting a sensitivity analysis will demonstrate the potential variability of results and can help determine the key factors which have the greatest incremental effect on the economic impact of the solution. Overall, the CBA will demonstrate the system wide impact of the rehabilitation platform and technology and will facilitate the spread and adoption.
Context: Company X has conducted multiple clinical trials with positive results in increasing daily exercises. The platform and technology are at an advanced stage of development and are unlikely to have significant material changes. Results from previous pilots have been positive and has demonstrated a clear demand for the platform and technology to be widely spread in rehabilitation services. Company X has developed a sustainability and growth plan with a robust company infrastructure and is currently implemented in multiple sites. Company X has already conducted a cost effectiveness or benefit analysis and wishes to highlight to commissioners their potential return on investment based on their given demographic and assumptions.
Health economic solution: To understand the impact of implementing Company X’s technology and platform from the commissioner perspective, a budget impact model (BIM) is developed. The BIM will help to ascertain the in-year financial (and could also look at longer term net present value if required) implications, for example the hours saved for occupational therapists and physiotherapists, or a reduced length of rehabilitation. Using the evidence base and data previously generated, (through the prior health economic analysis across multiple sets), a tool will be developed to help easily input assumptions and generate results. It can be easily calibrated to input their own service values, for example the number of physiotherapists, or the average length of rehabilitation for different providers. This will help understand the likely or even desired outputs that the intervention could achieve if taken up and consequently whether it is worth procuring Company X’s platform from a financial perspective.