Author: admin

Posted on

Opinion: We need more men in nursing

While the number of Americans in need of care keeps rising, many health systems are struggling to find qualified nurses. The demand for qualified nurses is projected to increase nationwide, with nearly 200,000 annual job openings expected. This is driven, in part, by a mass exodus of nurses reaching retirement age. At this critical juncture facing our nation’s health systems, men remain an untapped group whose recruitment into nursing could make a difference.

Even with these persistent and growing nurse workforce shortages, men remain underrepresented in the profession, accounting for just 12% of nurses nationally. Concerted and sustained efforts are urgently needed to recruit more men to join the nursing profession and be positioned to provide high-quality, evidence-based care across communities nationwide.

Read the rest…

Posted on

Opinion: STAT+: Medicare’s new RAPID pathway is a breakthrough for adults. Children are still waiting

In late April, the Centers for Medicare and Medicaid Services and the Food and Drug Administration announced the Regulatory Alignment for Predictable and Immediate Device, or RAPID, coverage pathway. On paper, it is exactly what the medical device community has been asking for: a synchronized process that could deliver Medicare national coverage as soon as two months after FDA market authorization, rather than the year or more families and manufacturers currently endure.

I want this pathway to succeed. I have spent more than a decade helping small companies bring novel devices through FDA review, including several that earned breakthrough device designation. I have watched reimbursement delay strangle technologies that children desperately need. Faster, more predictable coverage is a real problem, and RAPID is a real step.

But this announcement does not fix the way pediatric and orphan devices chronically lag behind their adult counterparts. In some ways, in fact, it deepens that gap.

Continue to STAT+ to read the full story…

Posted on

Why we left the FDA: Six former officials share their stories

A year after U.S. DOGE Service cuts shook up the federal government, STAT’s FDA reporter Lizzy Lawrence has been speaking with former officials about their time at the agency. Two weeks ago, I hit the road with Lizzy to interview six of them about what drew them to the agency, the important work they did during their career there, and, ultimately, why they decided to leave during the second Trump administration. 

In a special road-trip edition of STATus Report, Lizzy and I travel around the leafy suburbs of Washington to bring you first-person testimonies, including the former director of the FDA’s Center for Drug Evaluation and Research, Richard Pazdur; Sheryl Lard-Whiteford, a leader in the FDA’s biologics center; and Julie Tierney, who worked on Operation Warp Speed.

Posted on

Fully Anonymized Digital Health Data Acquisition in a Research Partnership Using a Blinded Deidentification Proxy in the HerzFit App: Implementation Study

Background: The European General Data Protection Regulation (GDPR) strictly regulates the processing of personal and health-related data, posing challenges for digital health research, especially when data are collected using participants’ own devices. Although scientific data can theoretically be anonymized, standard internet communication protocols inevitably expose transmission metadata, preventing true anonymization. Existing solutions, including virtual private networks, reverse proxies, and trust centers, improve confidentiality but do not technically or legally enable fully anonymized data collection. Consequently, large-scale digital health research often requires extensive organizational measures, complex consent procedures, and high regulatory overhead. Objective: This study aimed to develop a GDPR-compliant concept for fully anonymized scientific data collection, ensuring that no entity has simultaneous access to identifying information and donated data. We also implemented and evaluated this concept in a real-world public-private partnership. Methods: We designed a data donation architecture based on a blinded deidentification proxy that decouples identifying transmission metadata from encrypted user data at the time of donation. The concept combines symmetric (Advanced Encryption Standard-128 in Cipher Block Chaining) and asymmetric (Rivest-Shamir-Adleman with Optimal Asymmetric Encryption Padding) encryption, enabling end-to-end encrypted and anonymized data transfer without persistent identifiers. The system was integrated into the HerzFit app, a mobile lifestyle coach for cardiovascular disease prevention available in German-speaking countries, and evaluated for adoption, technical feasibility, and performance. Performance overhead was assessed using round-trip time benchmarks. Duplicate donations were identified and merged to estimate unique data donors. Results: The solution was integrated and tested in the HerzFit app with more than 200,000 downloads between April 2022 and December 2025. Since the introduction of the data donation feature, more than 13,000 donations have been received, translating to more than 9000 individual users contributing anonymized datasets. Proxy-based transmission resulted in an average round-trip time of 143 ms, compared to 58 ms for direct transfer, representing a modest overhead while maintaining usability. The operator of the donation database did not gain access to identifying information at any stage, demonstrating full technical anonymization. The approach can be operated reliably at scale with minimal server resources due to the stateless proxy design. Conclusions: This work introduces a novel system architecture enabling fully anonymized, GDPR-compliant data donation directly from participants’ devices. By decoupling identifying metadata from encrypted health data, the concept minimizes regulatory effort, strengthens privacy protection, and provides a practical framework for large-scale digital health research in research partnerships, for example, between a private company and a research institution. The real-world deployment in HerzFit demonstrates the feasibility, scalability, and scientific utility of this approach. The concept is broadly transferable to other mobile health apps and has the potential to substantially expand ethically and legally compliant data acquisition.
<img src="https://jmir-production.s3.us-east-2.amazonaws.com/thumbs/267bb1c67eb3b88c5c39fe2585a8cafc" />

Posted on

Impact of a Prototype Combining Recommender Functionality With Structured Documentation on Operator Performance in Calls to Medical Communication Centers: Quasi-Experimental Feasibility Study

<strong>Background:</strong> Management of contacts to medical communication centers relies heavily on clinical judgment, contextual understanding, and communication skills. Decision support systems, intended to complement medical expertise, may, due to their rigidity, impede effective caller interaction and may, together with the obligatory documentation of calls, contribute to a workflow that draws attention away from the communication. Recommender systems have demonstrated potential in supporting decision-making across various domains by nudging individuals toward better choices without undermining autonomy. We built a prototype that combined artificial intelligence–based question recommendations with structured documentation (hereafter: the prototype) and conducted a feasibility study to test its influence on operators’ performance. <strong>Objective:</strong> This study aimed to examine whether the prototype influenced the operators’ performance during telephone triage. We hypothesized that the prototype would affect medical quality without affecting communication quality. <strong>Methods:</strong> A quasi-experimental pre- and posttest feasibility study was conducted in a simulated setting. Twenty-five operators were voluntarily recruited from 5 Norwegian medical communication centers, in which 22 operators contributed to both the pretest (before the prototype) and the posttest (with the prototype). The operators handled the same 15 medical cases presented by simulated callers, with a 5-month interval between the 2 sessions. The question recommender was trained on other data and then fine-tuned on the 15 scenarios used. Audio recordings of the calls were rated using the tool Assessment of Quality in Telephone Triage. Pre- and posttest values were compared, with overall medical and communication quality as the primary outcomes. Secondary outcomes included specific items related to medical content and communication, accuracy of triage, patient safety, call duration, and efficiency. <strong>Results:</strong> A total of 320 paired calls were analyzed. Overall medical quality improved significantly with use of the prototype, from a mean of 6.83 points pretest to 7.16 points posttest rated on a 10-point scale (difference 0.34, 95% CI 0.11-0.57; <i>P</i>=.004). The effect size was small (Cohen <i>dz</i>=0.16). No significant change was observed in overall communication quality, with a mean of 7.06 points pretest and 6.97 points posttest (difference –0.09 points, 95% CI –0.28 to 0.10; <i>P</i>=.35). A significant decrease from pre‑ to posttest was observed in the specific items “Collects information about the patient’s location” (<i>P</i>&lt;.001) and “Ensures that the triage decision is understandable and feasible” (<i>P</i>=.002). None of the remaining secondary outcomes showed significant changes. <strong>Conclusions:</strong> The prototype yielded a modest improvement in medical quality within the scenario‑based test environment. Although overall communication quality remained unchanged, aspects of the interaction were negatively affected. Artificial intelligence–based question recommendations combined with structured documentation may serve as useful functionalities within a decision support system, but each functionality requires further testing and development before such technology can be implemented in the triage of unselected, real‑world calls. <strong>Trial Registration:</strong>