Time From Authorization by the US Food and Drug Administration to Medicare Coverage for Novel Technologies

JAMA Health Forum · 2023 · 21 citations

• Computer Security
• Computer Science
• Medicine

Importance: A wide variety of novel medical diagnostics and devices are determined safe and effective by the US Food and Drug Administration (FDA) each year, but to our knowledge the literature lacks evidence documenting how long it takes to establish new Medicare coverage for these technologies. Objective: To measure time from FDA authorization to at least nominal Medicare coverage for technologies requiring a new reimbursement pathway. Design, Setting, and Participants: In this cross-sectional study, public databases were used to associate each technology to billing codes, determine the effective date of each code and Medicare coverage decisions, and stratify by the maturity of the Medicare coverage. At least nominal coverage was defined as achievement of explicit coverage milestones through a national coverage determination, local coverage determinations by Medicare administrative contractors, or by implicit coverage aligned to a new billing code. Characterization by product type (acute treatment, chronic or ongoing treatment, diagnostic assay, and diagnostic device), manufacturer size, and evidence level were assessed for association with coverage achievement. The study included new product applications authorized by the FDA through the premarket approval pathway, the de novo pathway, or with breakthrough designation in the 510(k) pathway from January 1, 2016, to December 31, 2019. Data analysis took place between May 1, 2022, and December 31, 2022. Main Outcome Measurement: Time from FDA authorization to the first coverage milestone. Results: Among 281 identified technologies in the total sample, 64 (23%) were deemed novel technologies based on the absence of coverage determinations and/or the use of temporary or miscellaneous billing codes. Twenty-eight of 64 technologies (44%) successfully achieved explicit or implicit coverage following FDA authorization. The median time to at least nominal coverage for the analysis cohort was 5.7 years (90% CI, 4.4-NA years). Analysis of time-to-coverage data highlighted company size (log-rank P<.001) and product type (log-rank P = .01) as significant covariates associated with coverage achievement. No association was observed for technologies with level 1 evidence at FDA authorization and subsequent coverage milestone achievement (log-rank P = .40). Conclusions and Relevance: In this cross-sectional study of 64 novel technologies, only 28 (44%) achieved coverage milestones over the study timeline. The several-year period observed to establish at least nominal coverage suggests existing coverage processes may affect timely reimbursement of new technologies.

Comparison of History of Present Illness Summaries Generated by a Chatbot and Senior Internal Medicine Residents

JAMA Internal Medicine · 2023 · 59 citations

• Medicine
• Family medicine
• World Wide Web

This prognostic study assesses the ability of a chatbot to write a history of present illness compared with senior internal medicine residents.

Beyond Politics — Promoting Covid-19 Vaccination in the United States

New England Journal of Medicine · 2021 · 170 citations

• Political Science
• Political Science
• Computer Science

Promoting Covid-19 Vaccination in the United States Consumer research and behavioral economics suggest 12 key strategies for effective vaccine promotion. We should combine relevant strategies for v...

When Vaccine Apathy, Not Hesitancy, Drives Vaccine Disinterest

JAMA · 2021 · 61 citations

• Medicine
• Family medicine
• Psychiatry

This Viewpoint explains how vaccine apathy rather than hesitancy may lead to population undervaccination, and uses marketing principles to explain how public health messaging might differ to persuade apathetic persons to be immunized to achieve more widespread COVID-19 protection.

Global maps of travel time to healthcare facilities

Nature Medicine · 2020 · 490 citations

• Computer Science
• Business
• Computer Science

Ethical issues in using ambient intelligence in health-care settings

The Lancet Digital Health · 2020 · 151 citations

• Computer Science
• Computer Science
• Internet privacy

Ambient intelligence is increasingly finding applications in health-care settings, such as helping to ensure clinician and patient safety by monitoring staff compliance with clinical best practices or relieving staff of burdensome documentation tasks. Ambient intelligence involves using contactless sensors and contact-based wearable devices embedded in health-care settings to collect data (eg, imaging data of physical spaces, audio data, or body temperature), coupled with machine learning algorithms to efficiently and effectively interpret these data. Despite the promise of ambient intelligence to improve quality of care, the continuous collection of large amounts of sensor data in health-care settings presents ethical challenges, particularly in terms of privacy, data management, bias and fairness, and informed consent. Navigating these ethical issues is crucial not only for the success of individual uses, but for acceptance of the field as a whole.