Update on the Global Digital Health Market

Last year’s Update on the Global Digital Health Market, which appeared in the October 2025 issue of MPO, stated that nearly every medical specialty now has digital health applications built for it, and every device needs a digital component. That advice still holds, but the question has changed. Payers and regulators now ask whether the data changes a clinical decision, and whether anyone will pay for the result.

The volume keeps climbing. FDA authorized 331 artificial intelligence (AI)-enabled devices in 2025—a record—bringing the total over 1,400.¹ Digital health startups raised $7.4 billion in the first half of 2026, up from $6.4 billion one year earlier.² However, the evidence is lagging. Only 5.4% of AI devices authorized from 2023 through 2025 have a predetermined change control plan (PCCP),³ and AI devices cleared without a published clinical study were recalled about three times as often (7.8% versus 2.6%).⁴

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Why This Is Important

Between now and the end of 2027, pending payment and regulatory decisions will determine which digital health applications get paid, cleared faster, or restricted. Most point the same way: payment is moving toward outcomes and away from data collection. Following are seven applications with broad reach across medtech, each with a dated milestone and a credible link to better outcomes or lower costs. 

1. Outcome-based payment for chronic-care technology (CMS ACCESS and FDA TEMPO)

What is pending: CMS’s 10-year ACCESS model, launched in July 2026, makes outcome-aligned payments for hypertension and related cardio-kidney-metabolic conditions, diabetes and kidney disease, chronic musculoskeletal pain, and depression and anxiety.⁵ More than 150 companies were approved, and the next cohort was scheduled to start on Oct. 1, 2026.⁶ FDA’s parallel TEMPO pilot lets up to 10 manufacturers offer devices under enforcement discretion while collecting real-world data. The first four, including Dexcom and Cadence, were named July 22, 2026.⁷

Why it helps: ACCESS pays for improved blood pressure, glucose, pain, and depression scores, not for transmitted readings. The evidence supports that design. Hypertension programs in which care teams adjust medications from home readings lowered blood pressure and paid back over 10 years, while monitoring alone raised costs more than it lowered them.⁸ Therapist-guided virtual musculoskeletal programs matched in-person therapy at lower total cost.⁹

2. Separate Medicare payment for clinical software (CY2027 OPPS)

What is pending: The CY2027 outpatient proposed rule designates 36 codes as “Software as a Medical Service,” with separate payment and no multiple procedure discount, and moves 21 of them into New Technology ambulatory payment classification.¹⁰ The final rule is expected around November, effective Jan. 1, 2027.

Why it helps: AI tools that find disease earlier, such as coronary plaque analysis and lung-nodule risk scoring, get used when hospitals are paid for them instead of absorbing the cost. Watch whether CMS finalizes separate payment as proposed. A discounted status would cut revenue per case.

3. A reset of remote patient monitoring (CY2027 Physician Fee Schedule)

What is pending: The proposal (public comments were due Sept. 14, 2026) would require remote monitoring staff to be direct employees of the billing practice, add a face-to-face initiating visit, and consider consolidating 17 remote patient monitoring (RPM) and remote therapeutic monitoring (RTM) codes into four. CMS cites Inspector General findings that about 43% of RPM enrollees did not receive all required services.¹¹

Why it helps: It reads as a restriction, but it matches the evidence: monitoring helps when a clinician who knows the patient acts on the data.⁸ Payment should concentrate on programs that change treatment. Device makers can protect adoption by reducing practice workload through automated triage and EHR integration.

4. AI that finds hidden heart disease from routine tests

EchoNext, cleared June 22, 2026, flags structural heart disease from a standard ECG. In a Nature study, it identified 77% of cases versus 64% for cardiologists.^12,13 In the EAGLE randomized trial, AI-ECG screening in primary care raised new low-ejection-fraction diagnoses from 1.6% to 2.1%.¹⁴ Category I codes and payer coverage are still pending. The appeal is cost: ECGs are cheap, routine, and already in every clinic.

5. Continuous glucose-ketone sensing

What is pending: Abbott’s Libre Duo 10 Day, authorized Aug. 25, 2026, is the first sensor to track glucose and ketones continuously. U.S. launch is planned for later in 2026, with automated insulin delivery integration by year-end.¹⁵

Why it helps: Diabetic ketoacidosis (DKA) can develop within hours. In 2017, the U.S. had 220,340 DKA hospitalizations at a mean cost of $30,836 each.¹⁶ Ketone alerts, especially for insulin and SGLT2 inhibitor users, give patients time to act. The broader lesson is that the CGM form factor can carry more than one analyte.

6. Remote heart failure monitoring meets specialist risk-sharing

What is pending: The mandatory Ambulatory Specialty Model starts Jan. 1, 2027. It puts ±9% of Medicare Part B payments at risk for about 8,600 specialists treating heart failure or low back pain, rising to ±12% by 2031, and scores heart failure admissions and costs.¹⁷ FDA approved Abbott’s lighter CardioMEMS Hero system in March 2026.¹⁸

Why it helps: In the MONITOR-HF trial, care guided by pulmonary artery pressure cut heart failure hospitalizations by 44%.¹⁹ Now the cardiologist’s own payment depends on avoiding those admissions, so the case for remote monitoring reaches the physician, not just the hospital. TEAM, live since January 2026, applies the same 30-day logic to hospitals for joint replacement, spinal fusion, and CABG.²⁰

7. Rules for generative AI devices and faster coverage for breakthroughs

What is pending: FDA’s generative AI discussion paper (comments due Oct. 19, 2026) proposes a two-axis risk framework, benchmarking plus clinical confirmation before launch, and post-market monitoring.²¹ Separately, the proposed RAPID pathway would issue a Medicare coverage decision within about two months of FDA authorizing an eligible Breakthrough device.²²

Why it helps: Clear validation rules let generative AI reduce clinician workload safely. RAPID could shorten a coverage lag that often exceeds a year, though it requires an IDE study enrolling Medicare beneficiaries from the start.

The Medi-Vantage Perspective

Last year, the advice was to add a digital component. This year, the advice is to ensure your digital health device changes a clinical decision that a physician is paid to improve.

• Map your product to a payment: Identify the ACCESS track, software code, TEAM episode, or Ambulatory Specialty Model measure your output improves. If nothing pays for the output, it is a feature, not a business.
• Design for action, not data: Build in triage and EHR integration so practices can run your program with their own staff.
• Buy your evidence up front: Publish clinical validation and file a PCCP.

References

¹ tinyurl.com/mpo261001
² tinyurl.com/mpo261002
³ tinyurl.com/mpo261003
⁴ doi.org/10.1001/jamanetworkopen.
2026.17920
⁵ tinyurl.com/mpo261005
⁶ tinyurl.com/mpo261006
⁷ tinyurl.com/mpo261007 
⁸ tinyurl.com/mpo261008 
⁹ tinyurl.com/mpo261009 
¹⁰ tinyurl.com/mpo261010
¹¹ tinyurl.com/mpo261011 
¹² tinyurl.com/mpo261012 
¹³ tinyurl.com/mpo261013 
¹⁴ tinyurl.com/mpo261014 
¹⁵ tinyurl.com/mpo261015 
¹⁶ tinyurl.com/mpo261016 
¹⁷ tinyurl.com/mpo261017 
¹⁸ tinyurl.com/mpo261018 
¹⁹ tinyurl.com/mpo261019 
²⁰ tinyurl.com/mpo261020 
²¹ tinyurl.com/mpo261021 
²² tinyurl.com/mpo261022

More insights from this author: An Update on Human Factors Usability Testing for Medical Devices

Maria Shepherd has more than 20 years of experience in marketing in small startups and top-tier companies. She founded Medi-Vantage, which provides marketing and business strategy for the medtech industry. She can be reached at [email protected]. Visit her website at www.medi-vantage.com.