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Home»Startup»Digital health leaders share predictions on what to expect in 2023 – Startup
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Digital health leaders share predictions on what to expect in 2023 – Startup

December 29, 2022No Comments6 Mins Read
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Digital health leaders share predictions on what to expect in 2023 – GeekWire
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Clockwise, from high left: College of Washington professor Shyam Gollakota; WRF Capital managing director Loretta Little; Amazon vice chairman Taha Kass-Hout; UW professor Su-In Lee; and Hurone AI founder Kingsley Ndoh. (Amazon, Hurone AI, WRF Capital and UW Pictures)

Funding for digital well being startups and initiatives soared in the course of the pandemic as entrepreneurs and customers more and more embraced telehealth, distant monitoring, and a collection of units from sleep trackers to train bands.

Complete enterprise capital funding in digital well being hit an all time excessive of $29.2 billion in 2021, in line with Rock Well being. Funding cooled in 2022, to $12.6 billion by the tip of the third quarter, however advances in expertise equivalent to synthetic intelligence and the rising curiosity of huge tech firms are certain to propel innovation sooner or later.

Seattle-area startups equivalent to CalmWave, Rippl Care, Outbound AI and Birch AI emerged in 2022 to assist remedy medical issues starting from extra noise in hospitals, to psychological healthcare for seniors. Bigger firms additionally signaled main ambitions; Amazon this 12 months introduced its bid to amass major care firm One Medical for $3.9 billion and rolled out a brand new on-line well being service, Amazon Clinic.

What tendencies do specialists see for digital well being nationally and within the Seattle space for 2023? We requested 5 to weigh in with their predictions. 

Taha Kass-Hout, vice chairman of technology-health AI, and chief medical officer at Amazon Net Companies
Taha Kass-Hout. (Amazon Picture)

Unprecedented innovation and collaboration throughout the healthcare and life sciences industries is pushing the trade to transfer from sick care to prevention by means of a affected person expertise that’s exact, personalised, and human. The trade has been experimenting with cloud for a decade and understands how expertise and machine studying can allow extra focused diagnostics and coverings, generally known as precision drugs; personalize affected person journeys; and enhance well being outcomes.

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In 2023 and past, we count on healthcare and life sciences organizations to proceed to make investments in modernizing their infrastructure, derive actionable insights from information, and internalize what it means to personalize well being. This may contain integrating genomics and different omics information into therapeutic growth, leveraging machine studying and analytics to enhance clinician workflows, incorporating social determinants information into illness administration on the affected person or inhabitants ranges, and utilizing structured and unstructured information to foretell illness with a lot better accuracy — serving to transfer the trade from reactive to preventive affected person care.

Kingsley Ndoh, founder and chief strategist, Hurone AI
Kingsley I. Ndoh. (Hurone AI Picture)

We must always count on to see extra people-centered improvements in digital well being to help scientific resolution making, equivalent to diagnostic predictive applied sciences or instruments to foretell scientific outcomes for sure most cancers medicine. These instruments will more and more incorporate extra variety in coaching datasets for machine studying fashions and put the precise wants of the goal person on the coronary heart of the event course of, together with taking into consideration cultural views.

There will even be higher integration of information generated from wearables, smartphone apps and digital medical data to help scientific selections, behavioral change, and personalization at scale by means of the ability of synthetic intelligence.

Loretta Little, managing director of WRF Capital
Loretta Little. (WRF Capital Picture / Mel Curtis)

Funding for many early-stage digital startups will proceed to be tight in 2023, however I see alternatives for progress in a number of areas. We are going to proceed to see extra firms that provide entry to psychological well being providers by means of revolutionary merchandise and approaches, equivalent to Joon and Rippl Care, and corporations centered on bettering connectivity and instruments for higher distant care equivalent to Valorant Well being and Wavely Diagnostics. 

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Distant care is particularly vital for underserved rural communities which have restricted or no entry to close by well being assets. This want is just rising, pushed partially by demographic shifts within the affected person inhabitants. The proportion of seniors in Washington state and throughout the nation is projected to develop, significantly in rural areas. This rural senior inhabitants represents a big proportion of continual illness victims and can should be linked up with providers.  

Shyam Gollakota, co-founder of Wavely Diagnostics and Sound Life Sciences (acquired by Google), professor on the College of Washington’s Allen Faculty
Shyam Gollakota. (Startup Picture / James Thorne)

The adoption of telehealth that accelerated throughout COVID is probably going right here to remain. We may additionally see an elevated variety of distant in-home exams like COVID-19 or blood exams that can convey telehealth nearer to an in-person go to. Whereas there was a number of deal with utilizing smartphones and smartwatches for cellular well being, earbuds would be the subsequent thrilling platform for monitoring well being and wellness in addition to probably, within the subsequent few years, electroencephalography (EEG) indicators that may open up new alternatives for mind interfaces.

We are going to hopefully additionally see a lot of startups apply giant language fashions to handle varied ache factors within the healthcare system with the purpose of bettering effectivity and decreasing value. Deep studying methods will proceed bettering and we are going to begin seeing extra promising outcomes for addressing vital issues like utilizing AI to find medicine and vaccines.

Su-In Lee, UW professor of pc science and engineering
Su-In Lee. (UW Picture)

Subsequent 12 months we are going to see AI units with explainable AI (XAI) performance, enabling people to know the reasoning technique of advanced, black-box machine studying fashions. I additionally see FDA approval processes incorporating XAI evaluation to engender belief, transparency, equity, and actionability of machine studying fashions.

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Elevated reimbursement by insurance coverage suppliers and the U.S. Facilities for Medicare & Medicaid Companies will drive a rise within the variety of FDA-approved AI units. In the long run, the success and equity of medical AI units will depend on the extent to which FDA approval processes are up to date to mirror machine learning-specific points. For instance, if there aren’t necessities to guage an AI dermatology machine on a variety of pores and skin tones, it appears doubtless that AI units that carry out poorly on darker pores and skin will change into publicly accessible and disproportionately misdiagnosis individuals with darker pores and skin.



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