Callie Rockey-Bartlett

BACKGROUND CMS temporarily expanded telehealth coverage during the COVID-19 pandemic; that coverage is scheduled to expire in December 2027. Federal policymakers are actively evaluating whether to make these expansions permanent, and direct evidence from stakeholders is needed to inform coverage decisions. OBJECTIVE To identify patient, provider, and policymaker/administrator perspectives on expanded CMS telehealth coverage and to characterize the policy priorities of each stakeholder group. METHODS Semi-structured interviews with patients, clinicians, and policymakers/administrators who have used or worked with telehealth in the U.S. Interviews were conducted online from August 2024 to August 2025. Themes were identified through inductive thematic analysis of interview transcripts, independently coded by two coders in Dedoose and adjudicated by consensus. RESULTS Sixty-two stakeholders completed interviews (40 [65%] patients, 15 [24%] providers, and 7 [11%] policymakers/administrators). Three themes emerged. Telehealth produces cost savings for patients and health systems. Federal and state policies shape telehealth access, particularly for rural, low-income, and disabled populations. Reimbursement parity between virtual and in-person care is essential for sustainable telehealth delivery. CONCLUSIONS Patients, providers, and policymakers/administrators consistently supported policies that expand and sustain telehealth access. Reimbursement parity, interstate licensure reform, and broadband infrastructure investment emerged as the highest-priority policy levers across stakeholder groups. Federal policymakers, including CMS, should incorporate direct stakeholder evidence when evaluating permanent telehealth coverage ahead of the December 2027 expiration.

Background: Cancer survivorship is a complicated, chronic, and long-lasting experience, causing uncertainty and a wide range of physical and emotional health concerns. Due to the complexity of cancer, patients often seek out multiple sources of health information to better understand the aspects of their cancer diagnosis. The high variability among patients with cancer presents significant challenges in treatment, prognosis, and overall disease management. Artificial intelligence (AI) chatbots can further personalize cancer care delivery. However, there is a knowledge gap regarding cancer survivors’ perceived facilitators and barriers to adopting and using AI chatbots. Objective: In this study, we examined cancer survivors’ experiences of using existing AI chatbots and identified their facilitators and barriers to the adoption of AI chatbots. Methods: We conducted a qualitative study to investigate the perceptions of cancer survivors, conducting semistructured interviews to understand their prior use of existing AI chatbots in general. We asked the participants about their perceptions regarding AI chatbot acceptability and comfort level; trust and adherence; and concerns, barriers, and suggestions. We used the Consolidated Criteria for Reporting Qualitative Research (COREQ) checklist for this qualitative report. Results: Of 21 participants, 17 (81%) were female patients with breast cancer, 15 (71%) were aged 50 to 64 years, 19 (90%) were White, and 9 (43%) had a graduate degree. Participants’ responses were grouped into three overarching themes: (1) patients’ perceptions of interacting with chatbots compared to health care professionals, (2) patient-chatbot interaction, and (3) chatbot information processing. All participants who were interviewed reported that they would prefer interacting with health care professionals over a chatbot. The lack of empathy shown by chatbots was a major concern among cancer survivors. Many patients criticized chatbots for tending to provide a general overarching response to their questions rather than being specific to their cancer diagnosis. The main concerns of cancer survivors with using chatbots were the overabundance of general information that was often not relevant to their diagnosis and privacy of patient information. Conclusions: The findings of this study underscore the critical importance of empathetic responses during AI chatbot interactions for cancer survivors, as the lack of personalized and emotional responses can lead to distrust and frustration. Clinically, these tools should be integrated as supplementary resources to enhance patient engagement while preserving essential human support. Policymakers need to develop guidelines that promote responsible use of AI in cancer care, prioritizing patient confidentiality and trustworthiness. AI chatbots have the potential to significantly improve the support provided to cancer survivors, but it is crucial to address the identified barriers and enhance user acceptance.

Purpose: Remote patient monitoring (RPM) allows healthcare providers to monitor patient outcomes outside of a traditional healthcare setting, potentially supporting reductions in acute care utilization. This systematic review aims to assess whether RPM use among cancer patients reduces hospitalizations and length of stay (LOS). Methods: A systematic review was conducted to identify articles published in PubMed and CINAHL between 2019 and 2024 that evaluated the impacts of RPM in cancer patients compared to the standard care. The primary outcomes examined were hospitalizations and LOS. Secondary outcomes were emergency department (ED) visits and hospital readmissions. Two reviewers screened and assessed the studies. Evidence strength was assessed using the Grading of Recommendations Assessment, Development and Evaluation approach. Risk of bias was assessed using the Newcastle-Ottawa Scale and the Cochrane risk-of-bias tool for randomized trials (RoB 2). While statistical tests were not conducted on results, outcomes were categorized as having increased, decreased, or no change. Results: This review included one randomized controlled trial, seven cohort studies, and one case-control study. RPM was associated with reductions in healthcare utilization among cancer patients. There were significant reductions in hospitalizations, LOS, ED visits, and hospital readmissions in 67% (4/6), 67% (4/6), 75% (3/4), and 67% (2/3) of studies, respectively. Conclusion: This systematic review builds upon existing literature that demonstrates the effectiveness of using RPM to manage acute conditions such as cancer. RPM may support management of various cancer-related conditions and, in turn, potentially reduce acute care use. However, study homogeneity and additional rigorous study designs are necessary to draw more definitive conclusions about the impacts of RPM in cancer care.