Building the Business Case for an Inclusive Approach to Digital Health Measurement With a Web App (Market Opportunity Calculator): Instrument Development Study

BACKGROUND

The use of digital health measurement tools has grown substantially in recent years. However, there are concerns that the promised benefits from these products will not be shared equitably. Underserved populations, such as those with lower education and income, racial and ethnic minorities, and those with disabilities, may find such tools poorly suited for their needs. Because underserved populations shoulder a disproportionate share of the US disease burden, they also represent a substantial share of digital health companies' target markets. Incorporating inclusive principles into the product development process can help ensure that the resulting tools are broadly accessible and effective. In this context, inclusivity not only maximizes societal benefit but also leads to greater commercial success.

OBJECTIVE

A critical element in fostering inclusive product development is building the business case for why it is worthwhile. The Digital Health Measurement Collaborative Community (DATAcc) Market Opportunity Calculator was developed as an open-access resource to enable digital health measurement product developers to build a business case for incorporating inclusive practices into their research and development processes.

METHODS

The DATAcc Market Opportunity Calculator combines data on population demographics and disease prevalence and health status from the US Census Bureau and the US Centers for Disease Control and Prevention (CDC). Together, these data are used to calculate the share of US adults with specific conditions (eg, diabetes) falling into various population segments along key "inclusion vectors" (eg, race and ethnicity).

RESULTS

A free and open resource, the DATAcc Market Opportunity Calculator can be accessed from the DATAcc website. Users first select the target health condition addressed by their product, and then an inclusion vector to segment the patient population. The calculator displays each segment as a share of the overall US adult population and its share specifically among adults with the target condition, quantifying the importance of underserved patient segments to the target market. The calculator also estimates the value of improvements to product inclusivity by modeling the downstream impact on the accessible market size. For example, simplifying prompts on a hypertension-focused product to make it more accessible for adults with lower educational attainment is shown by the calculator to increase the target market by 2 million people and the total addressable market opportunity by US $200 million.

CONCLUSIONS

Digital health measurement is still in its infancy. Now is the time to establish a precedent for inclusive product development to maximize societal benefit and build sustainable commercial returns. The Market Opportunity Calculator can help build the business case for "why"-showing how inclusivity can translate to financial opportunity. Once the decision has been made to pursue inclusive design, other components of the broader DATAcc toolkit for inclusive product development can support the "how."

Optimization of Protein Quality of Plant-Based Foods Through Digitalized Product Development

With the increasing availability of plant-based protein products that should serve as alternatives to animal-based protein products, it is necessary to develop not only environmentally friendly but also nutritious foods. Especially the protein content and quality are of concern in these products. The algorithm of NutriOpt was developed using linear programming to support the development of food products with a balanced amino acid profile while considering digestibility. The current version contains a database with 84 plant protein sources from different food groups (legumes, cereals, nuts, seeds) and with different grades of purification (flours, concentrates, isolates) from which NutriOpt can create mixtures with high protein quality while complying with constraints such as protein content, number of ingredients, and weight of the mixture. The program was tested through different case studies based on commercial plant-based drinks. It was possible to obtain formulations with a Protein Digestibility Corrected Amino Acid Score (PDCAAS) over 100 with ingredients and quantities potentially suitable for plant-based analogs. Our model can help to develop the second generation of plant-based product alternatives that can really be used as an alternative on long-term consumption. Further, there is still a great potential of expansion of the program for example to use press cakes or even to model whole menus or diets in the future.