Faculty Bibliography

As a contingency standard of care, telemedicine use surged during the COVID-19 pandemic. The Medicare telehealth flexibilities introduced during the COVID-19 pandemic expired in September 2025. Any ongoing sustained pivot to telemedicine warrants purposeful attentiveness to ethical considerations and not just technology use as an end unto itself. Telemedicine has the potential to complement face-to-face care practices and enhance clinical interactions when its use is based on shared values. Values such as access, equity, justice, compassion, autonomy, and dignity warrant thoughtful use of telemedicine. Patients and families need to be able to trust that clinicians and health systems will place patient welfare and shared values above technical convenience. As demonstrated in this case description, upholding values fundamental to the practice of medicine in telemedicine can enhance patient connection and foster trustworthy post-pandemic practices.

BACKGROUND:Uncontrolled hypertension (HTN) is a leading preventable cause of death. Interventions are needed that activate patients and motivate them to work with clinicians to control their blood pressure (BP). OBJECTIVE:To test whether mailing patients a letter including information about their hypertension and a summary of computerized algorithm-generated medication adjustment suggestions improves BP control processes and outcomes. DESIGN/METHODS:Randomized quality improvement trial. PARTICIPANTS/METHODS:We identified patients receiving primary care at a large academic medical center with diagnosed HTN and uncontrolled BP (> 140 mmHg systolic or > 90 mmHg diastolic) at both of their last 2 visits. INTERVENTIONS/METHODS:Participants were randomized into three groups. The BP Activate Letter group received a letter containing algorithm-generated BP medication adjustment suggestions, and a recommendation to discuss these suggestions with their provider; the Control Letter group received a letter that recommended they talk to their provider about their HTN, without specific medication suggestions; and the No Letter group received no mailed outreach. MAIN MEASURES/METHODS:The primary outcome was time to occurrence of either a BP medication intensification or documented achievement of BP control to < 140/< 90 mmHg using EHR data extracted 6 months after letters were mailed. KEY RESULTS/RESULTS:The primary outcome, which was time to medication intensification or achievement of BP control, did not occur more frequently in the BP Activate Letter group (hazard ratio = 0.86; 95% confidence interval [CI]: 0.65 to 1.14), or in the Control Letter group (0.78; 0.59 to 1.03) compared to the No Letter group, and we saw no evidence of significant improvement in any secondary outcome or subgroup. Time to medication intensification appeared to be significantly longer in the Control Letter compared to the No Letter group (0.50; 0.30 to 0.85). CONCLUSIONS:Mailing patients one letter with computerized BP medication adjustment suggestions to consider did not lead to effective patient activation.

Standard genome-wide association studies (GWAS) and rare variant burden tests are essential tools for identifying trait-relevant genes¹. Although these methods are conceptually similar, by analysing association studies of 209 quantitative traits in the UK Biobank^2-4, we show that they systematically prioritize different genes. This raises the question of how genes should ideally be prioritized. We propose two prioritization criteria: (1) trait importance - how much a gene quantitatively affects a trait; and (2) trait specificity - the importance of a gene for the trait under study relative to its importance across all traits. We find that GWAS prioritize genes near trait-specific variants, whereas burden tests prioritize trait-specific genes. Because non-coding variants can be context specific, GWAS can prioritize highly pleiotropic genes, whereas burden tests generally cannot. Both study designs are also affected by distinct trait-irrelevant factors, complicating their interpretation. Our results illustrate that burden tests and GWAS reveal different aspects of trait biology and suggest ways to improve their interpretation and usage.

PURPOSE/OBJECTIVE:To evaluate the association of patient characteristics, community-level social determinants of health, and cyst risk categories with completion of follow-up recommendations for incidental Pancreatic Cystic Lesions (PCLs). METHODS:We retrospectively identified consecutive patients (2013-2023) whose MRI radiology reports described PCLs. A fine-tuned LLaMA-3.1 8B Instruct large language model was used to extract PCL features. Lesions were classified using the 2017 ACR white paper: Category 1 (low risk), Category 2 (worrisome features), or Category 3 (high-risk stigmata). We recorded demographics and follow-up imaging or endoscopic ultrasound dates. Community-level factors were characterized by the 2020 CDC Social Vulnerability Index (SVI), stratified into quartiles. The primary outcome, "inappropriate follow-up," combined late and no follow-up. Multivariable binomial regression was applied to evaluate associations with inappropriate follow-up. RESULTS:In 7,745 patients (mean age 66.3 years; 4,796 women), 92.9% (7,198/7,745) of cysts were Category 1, 6.4% (498/7,745) were Category 2, and 0.6% (49/7,745) were Category 3. Only 36.3% of patients completed appropriate follow-up, 12.1% were late, and 51.6% were lost to follow-up. Inappropriate follow-up was high in every cyst category: 64.2% in Category 1, 59.4% in Category 2 and 49.0% in Category 3. In multivariable analysis, non-English primary language (RR 1.08; 95% CI, 1.02-1.14) and residing in more vulnerable communities of the 3rd quartiles of the socioeconomic Social Vulnerability Index subcategory (RR 1.07; 95% CI, 1.02-1.12) were associated with inappropriate follow-up. Higher age-adjusted Charlson Comorbidity Index (CCI ≥ 4) (RR .84; 95% CI, .79-.88), CCI 2-3 (RR .84; 95% CI, .79-.88), and higher-risk cysts in patients under 65 years of age (RR .76; 95% CI, .65-.89) were associated with completed follow-up. CONCLUSION/CONCLUSIONS:Follow-up completion for incidental PCLs was low. Factors most consistently associated with follow-up completion were language barriers, residence in socioeconomically vulnerable communities, age-adjusted CCI and higher-risk features among those under 65 years.

The implementation of guideline-recommended care is associated with improved clinical outcomes for patients with cardiovascular disease. It is well documented that people living in low socioeconomic position have a high burden of cardiovascular disease and higher mortality rates. In this state-of-the-art review, the association of socioeconomic deprivation and guideline implementation is outlined, showing that across a range of settings, countries and clinical scenarios people with low socioeconomic position are further disadvantaged by sub-optimal provision of guideline recommended care. Reducing cardiovascular health inequality and improving population education should be priorities for governments. Greater attention to the provision of guideline-indicated care is recommended by tackling modifiable barriers to care. Broadly, the prioritization of use of advocacy, workforce, broader policy responses, data, randomized clinical trial re-design, quality indicators, and risk scores are recommended to reduce health inequalities for those who live in socioeconomic deprivation. A renewed focus on the provision of high-quality guideline-recommended cardiovascular care has the potential to reduce healthcare inequalities as well as improve clinical outcomes amongst our most socioeconomically deprived populations.

OBJECTIVES/OBJECTIVE:To examine (1) trends in the incidence and duration of Medicare opt-outs among urologic surgeons, (2) the demographic and professional characteristics of urologists opting out, and (3) the surgeon-level predictors associated with the timing of Medicare opt-outs. METHODS:This retrospective study analyzed data from the Centers for Medicare & Medicaid Services (CMS) Opt-Out Affidavits. Surgeon-level data were linked to public professional profiles using National Provider Identifiers to extract information on demographics, training, years in practice, practice type, subspecialty, and geographic location. RESULTS:The incidence of Medicare opt-outs among urologic surgeons remained low between 2012 and 2025, averaging 3.9 opt-outs per year (n=51). Most opt-outs were male (92.2%) generalists (64.7%) in independent practice settings (54.9%) with more than 30 years of experience (56.9%). Opt-out lengths significantly declined over time, from an average of 5113.5 days in 2012 to 730.5 days in 2025. Predictors of later opt-out included female sex (+2.4 years), fewer years in practice (+3.6 years for <19 years), and subspecialty in female urology (+4.8 years) or sexual medicine (+2.3 years). In contrast, earlier opt-out was associated with academic affiliation (-2.3 years) and subspecialty in male infertility (-4.8 years) or urologic oncology (-4.6 years). CONCLUSIONS:Although Medicare opt-outs remain rare among urologic surgeons, temporal trends reveal shortening durations of opt-out and distinct demographic and practice-related patterns in participation. These findings underscore the need for targeted efforts to support late-career and independently practicing urologists, while addressing evolving payment structures and retention strategies within Medicare to maintain workforce engagement. LEVEL OF EVIDENCE/METHODS:Level III.

Artificial intelligence (AI) applications for radiology workflow have the potential to improve patient and health-system-level outcomes through more efficient and accurate diagnosis and clinical decision making. For a variety of time-intensive steps, numerous types of applications are now available with variable reported measures and degrees of success. The tools we highlight aim to accelerate imaging acquisition, reduce cognitive and manual burden on radiologists and others involved in the care pathway, improve diagnostic accuracy, and shorten the time to clinical action based on imaging results. Most existing studies have focused on intermediate outcomes, such as task duration or time to the next step in care. In this article, we present an examination of AI applications across the medical imaging exam workflow, review examples of real-world evidence on these tools, and summarize the relevant performance metrics by application type. Beyond the more immediately acquired measures, to demonstrate benefit to patient health and economic outcomes, a more integrated assessment is necessary, and in an iterative fashion. To evolve beyond early workflow gains, interoperable tools must be tied to measurable downstream impacts, such as reduced disease severity, lower mortality, and shorter hospital stays, while we acknowledge that current empirical evaluations are limited.