A new study from Juniper Research has found that digital therapeutics revenue from health insurers will increase to $8 billion by 2026, up from $1.1 billion in 2022, representing a growth of 610% over the next four years.
Digital therapeutics are clinically validated software programs for the treatment of chronic medical conditions, either independently or in conjunction with other therapies.
The report, titled Digital Therapeutics & Wellness: Key Trends, Business Models & Market Forecasts 2022-2026, found that digital therapeutics facilitate the proactive mitigation of chronic medical conditions before they require costly interventions; enabling health insurers to reduce long-term costs per patient.
However, it highlighted that these savings will be limited to health insurers in developed regions, where consumer devices and digitalised health infrastructure are ubiquitous. As such, it noted that health insurers in Africa and Latin America will contribute less than 2% towards health insurer-led digital therapeutics revenue in 2026.
This new research also identified that insurers will also benefit from an ongoing shift among digital therapeutics vendors towards engagement- and results-based payments.
It therefore recommends that therapeutics providers looking to leverage this trend prioritise the development of performance benchmarks, as demonstrating improvement and preventing patient abandonment will become a direct monetary issue.
Machine Learning to play Advisory Role
The report forecasts that the number of people using digital therapeutics will increase by 381% over the next four years, and recognises that machine learning will be key to this growth by facilitating advanced data analytics, remote patient monitoring, and real-time conversational coaching.
However, it cautioned that an ongoing lack of standards surrounding the use of machine learning within digital therapeutics will result in vendors limiting its role in their offerings.
Research author Adam Wears explained: “As developers and healthcare providers increasingly grapple with issues of liability and malpractice, machine learning will transition from a patient-facing role to a diagnostic tool offered through provider-facing dashboards; to be used by clinicians and specialists in a manner akin to traditional computer-aided diagnostics.”
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