A Quantitative Framework to Identify and Prioritize Opportunities in Biomedical Product Innovation: A...

Area of Science:

• Health Services Research
• Biomedical Innovation
• Health Economics

Background:

• Prioritization of health initiatives, including biomedical innovation, may not consistently align with unmet public health needs.
• A need exists for a quantitative framework to guide investment decisions in biomedical product development.

Purpose of the Study:

• To develop and pilot a data-driven framework for identifying and prioritizing biomedical product innovation investments.
• The model incorporates multicriteria decision-making (MCDM) to balance public health burden and healthcare costs with innovation levels.

Main Methods:

• A longitudinal pilot study (2012-2019) analyzed data for 13 medical disorders from the Global Burden of Disease (GBD) and National Center for Health Statistics (NCHS).
• A multicriteria decision-making (MCDM) model, specifically Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), was used.
• Key metrics included public health burden (mortality, prevalence, disability, disparities) and healthcare costs, contrasted with 16 innovation pipeline metrics.

Main Results:

• Diabetes, osteoarthritis, and drug-use disorders exhibited the highest gap scores, indicating high public health burden or costs relative to biomedical innovation.
• Chronic kidney disease, chronic obstructive pulmonary disease, and cirrhosis showed the least biomedical product innovation despite significant public health burden and costs.

Conclusions:

• A proof-of-concept, data-driven model was developed to quantify and prioritize opportunities for biomedical product innovation.
• Aligning biomedical innovation investments with public health burden and healthcare costs can enhance public health benefits.