Lauren Chan

Lauren Chan reports on how **health care data**, **AI**, and rigorous evidence shape medical care and policy, tying technical developments directly to patient outcomes and real-world decision-making. She is the AAAS Mass Media Science & Engineering Fellow at STAT, where she focuses on health coverage with a particular emphasis on health care AI and data. Her research background in nutrition informs a recurring focus on cardiometabolic disease, prevention, and risk, especially when new tools or policies affect everyday care.

Health care data and AI

Chan’s beat centers on how data-driven tools and artificial intelligence are integrated into health care, and what that means for safety, accuracy, and clinical workflow. Multiple author lines at STAT explicitly note that she “writes about healthcare AI data,” underscoring a consistent focus on technology’s role in medicine rather than on general health features. Her work is cited in STAT’s Health Tech coverage, which tracks how technologies such as decision-support platforms compete with large language models and other AI systems in clinical settings.

Within this theme, Chan pays close attention to how tools are evaluated and validated, not just how they are marketed. Her reporting highlights comparative studies and performance claims, situating AI products within broader questions about evidence quality, bias, and the reliability of algorithmic recommendations. She treats health care AI as part of the clinical evidence ecosystem, stressing how data sources, study design, and regulatory responses determine whether a tool is likely to help or harm patients.

Chronic disease, prevention, and risk

Chan often uses large studies to explain changing risk profiles for chronic conditions, especially cardiovascular disease and diabetes. In her coverage of Covid vaccination and heart health, she breaks down a major study of veterans showing that recent Covid vaccination is associated with a substantially lower risk of Covid-linked major cardiovascular events, as well as a notable reduction in all-cause cardiac events. She translates complex outcomes into clear, concrete numbers, while still flagging which findings are strongest and where further research is needed.

Her reporting on **continuous glucose monitors** for very young children takes a similarly measured approach. In a piece asking “Are glucose monitors a good thing for 2-year-olds? Experts look at risks, benefits,” she examines the arrival of an over-the-counter device that, for the first time in the United States, can be used by children 2 and older without a prescription. Chan draws on pediatric and endocrinology voices to weigh potential benefits of early glucose tracking against concerns about anxiety, over-monitoring, and the lack of clear evidence for children who do not use insulin. She connects these questions to broader trends in consumer health tech and parental interest in preventive monitoring.

Across these stories, Chan’s through-line is careful interpretation of risk: she emphasizes how study design, population, and time frame influence what prevention tools can genuinely deliver, and she consistently grounds discussions of innovation in the lived experience of patients and families.

Access, disability, and health policy

Chan also reports on the points where health policy and funding decisions determine who can get care, with particular attention to disability services and insurance coverage. In a co-authored piece on federal grant delays, she details how postponed funding threatens both essential disability services and the research programs that support them, tracing the impact from agency timelines down to local organizations and the people who rely on them. The story reflects her interest in the infrastructure behind care, not just the clinical side.

Her work on **insurance premiums** brings similar clarity to health economics. In an article on “Another big premium hike on the horizon,” Chan reports that Affordable Care Act Marketplace insurers are proposing a median 14% premium increase, marking a second consecutive year of double-digit hikes. She connects those figures to underlying trends such as the high prevalence of prediabetes and type 2 diabetes among adolescents, showing how chronic disease burdens feed directly into rising costs for households.

Chan’s reporting on access also includes rare disease and compassionate use. In a story on Blood Cancer United’s purchase of a drug stockpile, she explains how the organization acquired both the investigational designation and responsibility for a compassionate-use program for children with a rare blood cancer, distributing the medication at no cost while supplies last. She focuses on the mechanics of access — who controls the drug, how distribution is managed, and what families can expect — rather than treating the story as a simple human-interest piece.

Rapid research coverage and agency response

Alongside deep dives, Chan contributes to faster-turn health news that tracks how new studies land with federal agencies and the public. In an item on the Department of Health and Human Services’ response to a paper on alcohol risk, she distills the study’s claims and HHS’s cautious reaction, showing how scientific findings move — or fail to move — policy and official guidance. This complements her more detailed work on Covid vaccine effectiveness, where she synthesizes multiple studies, including U.S. and European analyses, to give readers a clear picture of how vaccines perform across different populations and seasons.

Taken together, Chan’s body of work is distinguished by its blend of technical literacy and patient-centered framing: she treats health care AI and data as tools that must be judged by their evidence and by their impact on access, cost, and everyday care. Her stories are especially useful when a subject sits at the intersection of analytics, chronic disease, and health policy, and when a clear explanation of risk and benefit is critical.