News roundup: Amwell narrows Q1 and full year losses, AMA urges Congress for guardrails on mental health chatbots, hospital at home study finds lower ED visits and lower hospital mortality

May 8, 2026 | by

Amwell sees a light at the end of the tunnel while losses continue, as usual. Their Q1 closed with a reduced net loss– $10.3 million versus prior year’s $18.4 million and Q4 2025’s $25.2 million. Revenue was also lower: $54.9 million, down 18%, but exceeding their prior guidance. Revenue from subscriptions, Amwell’s current focus, of $24.9 million decreased about 23% from the prior year. Adjusted EBITDA also moved positively to a loss of $3.1 million versus Q4 2025’s $10.3 million. For their Q2, Amwell projects revenue in the range of $48- $52 million and adjusted EBITDA loss in the range of $2 to $4 million. Full year revenue remains at $195 to $205 million with adjusted EBITDA loss between $12 and $16 million, a reduction from prior projections. Healthcare Dive, Amwell Q1 statement

The American Medical Association (AMA) asks for more guardrails on AI mental health chatbots. In three letters sent to the House and Senate Artificial Intelligence Caucuses and the Congressional Digital Health Caucus, the AMA’s concern was around the emotional dependency on AI systems, the potential distortion of reality through prolonged interaction with chatbots. and the current lack of consistent safety protocols. They outlined several areas needing attention:

  1. Greater transparency in ensuring that users clearly understand when they are interacting with an AI system rather than a human being. Chatbots should not present as a licensed clinician or a human being. [See our earlier article on Pennsylvania’s suit against Character.AI]
  2. Clearer regulatory boundaries around how AI chatbots are used in mental healthcare, including diagnosis and treatment requiring oversight.
  3. Requesting that lawmakers direct agencies to establish a risk-based framework that clarifies when AI tools qualify as medical devices.
  4. Requiring developers to build safeguards, such as crisis-detection capabilities that can identify potential self-harm risk and direct users to appropriate resources and de-escalate harmful situations.
  5. Ongoing safety monitoring, mandatory reporting of adverse events, and stricter standards for tools used by children and adolescents.
  6. Limits on commercial influence, including restrictions or bans on advertising within mental health chatbots, and that chatbots aren’t ‘influenced’ by financial incentives.
  7. Robust data protection standards, including: limits on the amount of data collected and stored, safeguards to prevent unauthorized access or sharing of sensitive information, and clear user consent for data use.

Stanford’s recent research confirmed some common knowledge–that LLMs behind the chatbots pose significant risks by providing inappropriate responses, introducing bias and perpetuating stigma, which can result in dangerous consequences. AMA release, Mobihealthnews

Medicare beneficiary study compares hospital at home outcomes with traditional in-patient stays–and finds some good results. The JAMA Open Network published paper found that in over 15,000 patients (hospital at home, 4,174; in-patient 11, 697), treatment via “hospital at home was associated with significantly lower in-hospital mortality and emergency department (ED) use within 30 days of index admission discharge, with no significant difference in hospital readmissions within 30 days of index admission discharge compared with traditional inpatient care.” The study concluded that may maintain the same or better short term outcomes depending on “appropriately selected patients” (not specified) and that “future studies should evaluate implementation and equity”. The vast majority of patients in the hospital at home sample (nearly 97%) were urban. Healthcare Dive, JAMA Open Network

‘AI doctor’ Doctronic raises $40M Series B, but faces controversy on autonomous Rx renewals in Utah and effectiveness claims

March 26, 2026 | by

Doctronic’s raise impresses, but so do the questions around its AI tech. Earlier this week a hot AI telehealth startup announced a hefty (for these times) $40 million Series B raise that topped off a Series A of $20 million last September and a $5 million seed round in April. The $40 million was funded by Lightspeed Venture Partners, Union Square Ventures, MANTIS Venture Capital, Davidovs Venture Collective, and Abstract. The New York City-based company was founded in 2023 and only constructed its clinician network in early 2025. It claims to be on track to earn $10 million in revenue in 2026.

The basic health tech sounds not that unusual: a chatbot discusses your medical concerns and questions, much like a Claude for Healthcare, Microsoft Copilot Health, Teladoc, Ro, or even Google Gemini. The next step is a clinician referral, available 24/7 in all 50 states, for a low $39. It also claims to securely retain your information and timeline/meds/labs, not using the data for AI training.

Where the controversy centers is Doctronic’s first-ever state-approved autonomous AI test with the state of Utah. Announced in January, it will test whether a chatbot agent can evaluate and renew existing prescriptions for Utahns without human clinical oversight. In the pilot first phase, the renewals, which include 192 drugs for chronic conditions, will be overseen by clinicians before being sent to a pharmacy, but the intent is to move through this phase quickly to a pilot of full prescription renewal autonomy. Utah is permitting this through the Utah Department of Commerce’s Office of Artificial Intelligence Policy. The goal is to speed renewals of maintenance medications, the majority of activity, thus reducing medication noncompliance. Non-compliance is a leading driver of preventable health outcomes and with health decline, avoidable spending. Utah Department of Commerce release, Doctronic blog

Benefit manager Healthesystems outlined the process for its blog, with a view to the issues. “At the Doctronic prescription renewal portal, patients must confirm that they are located in Utah, enter the medication they want refilled, and then select an in-state pharmacy for fulfillment. Users must then upload their ID, along with a verification selfie and proof of an old prescription and then pay a $4 service fee. The AI system reviews the information to ensure a prescription history exists, after which a health assessment is given, where patients must answer certain questions before the program issues a refill. If the AI is uncertain if a prescription should be renewed, it refers the patient to a Utah-licensed human physician.”

A big reveal is here. The physician review prior to being sent to the pharmacy is for only the first 250 patients; the next 1,000 patients will be reviewed retrospectively. After that, only 5-10% of renewals will be audited after the fact, monthly. The issues for the two Healthesystems reviewers are risk–missing a loss of stability or extended renewals beyond original intent, for instance–and maintenance of oversight. Who is ultimately held accountable for the chatbot’s actions? 

A JAMA Health Forum article (19 March) raises additional issues. There apparently has been no pretesting of the prescription chatbot, only simulation testing. The application references a preprint study in medRxiv, written by equity owners in the company and only about the existing website chatbot. Moreover, the agreement is well-hedged to protect Doctronic. FTA:

If prescription errors injure patients, Doctronic’s accountability is murky. Its contract requires it to compensate Utah for any liability costs the state incurs and Doctronic took out a special malpractice insurance policy. Yet, the terms of service that users of the prescription renewal system must agree to—which seem to have been developed for the company’s AI doctor system—currently state that Doctronic disclaims all responsibility and liability for system accuracy or harmful outcomes.

A further oddity is that the Utah contract relieves Doctronic of the obligation to “generate, maintain, and make available to each patient” the patient’s medical records.

It closes with a short discussion of ‘scope creep’ (Editor’s emphasis): “Once an AI system has secured acceptance, vendors may be able to push updates that include substantial changes without attracting the same degree of scrutiny as the initial adoption. Concerns that low-risk pilot programs may legitimize higher-risk deployments at scale have been expressed about the Centers for Medicare & Medicaid Services’ new pilot program using AI to conduct prior authorization reviews of some services in traditional Medicare plans.”

And where is the proof that the AI chatbot can’t be spoofed? STAT (Mario Aguilar), who has been following Doctronic, located a February test by UK-based cybersecurity firm Mindgard that tested Doctronic’s existing chatbot and fooled it into into believing deliberate “official” misinformation, a bogus guideline that allowed triple the standard adult normal dose of Oxycontin, a Schedule II controlled substance. Sergei Polevikov in AI Health Uncut (subscription required, but you should) describes it in far greater and scary detail, including his own test. He also points out and analyzes other Doctronic questionable claims, such as volume (claiming 24 million ‘helped’ not borne out by website traffic), problems with the Utah formulary and refilling several problematic drugs, an odd connection with a Belarus company, and whether this should be regulated by FDA.  To be continued.