Ebbert, Jon O

Conventional cigarette smoking remains a leading preventable cause of morbidity and mortality despite declining prevalence, yet evidence-based treatments remain underused. This narrative review examines guideline-supported therapies and emerging approaches, including digital tools, neuromodulation, and harm-reduction strategies. Standard care typically combines FDA-approved pharmacotherapy with behavioral counseling. Digital interventions can extend access and support adherence, particularly when integrated with pharmacotherapy and follow-up. Repetitive transcranial magnetic stimulation (rTMS) can be considered as an adjunctive option for patients who do not respond to pharmacotherapy and is FDA-approved. For patients unable to quit, structured harm-reduction strategies may help reduce risk while supporting progression toward eventual abstinence. These approaches should be used alongside, not in place of, guideline-recommended pharmacotherapy and behavioral counseling, which remain the gold standard for care. This review outlines a pragmatic, primary care–oriented model that integrates stepped-care with harm-reduction strategies.

Video-based care has become a routine part of outpatient care delivery, yet older adults continue to face barriers in accessing and engaging with this modality. This study analyzed the comments provided within 7155 patient experience surveys from adults aged ≥65 years across a large, multi-specialty medical practice to identify challenges experienced with video-based visits. Thematic analysis revealed the highest proportion of positive comments were related to experience with people (71%), while barriers were often related to technical issues with video tools (73%). Most comments related to processes were positive, often highlighting convenience (67%). Using design thinking, we mapped the patient journey and proposed both immediate solutions, such as testing environments and clearer instructions, and long-term innovations like voice-guided support and emotionally intelligent interfaces. Our findings suggest that while video visits offer convenience, they must be redesigned with older adults in mind to ensure equitable, effective, and human-centered care.

Objectives: To identify patient characteristics, health concerns, and barriers to care based on overweight or obesity. Methods: A 50-question anonymous survey was administered to patients. Data were compared by body mass index (BMI). Results: Among 3976 distributed surveys, 899 were returned and 682 were analyzed. Most respondents were women (60%), White (94%), and married/partnered (65%) and had some college education (80%). Younger and unmarried persons had higher BMI ( P < .001). Concern for quality of life ( P < .001) and importance of lifestyle changes ( P = .006) increased with BMI, but confidence in making changes decreased as BMI increased ( P < .001). Perceived good health decreased with increasing BMI ( P < .001), whereas depression and other comorbid conditions increased. Self-esteem decreased and stigma increased with higher BMI (both P < .001). Weight discussions with clinicians ( P < .001) and belief that clinicians should be involved in weight management ( P = .002) increased with BMI, yet self-perception of being judged by clinicians also increased ( P < .001). As BMI increased, delays in seeking health care increased ( P < .001). Conclusions: This survey study highlights perceived health concerns and barriers to care among persons with overweight and obesity. With higher BMI, self-esteem decreased, and stigma, self-perception of poor health, perception of being judged by clinicians, and delay in seeking medical care increased.

Guideline-recommended screening programs exist for only a few cancer types. Although all these programs are understood to lead to reductions in cancer-related mortality, standard-of-care screening tests vary in accuracy, adherence and effectiveness. Recent advances in high-throughput technologies and machine learning have facilitated the development of blood-based multi-cancer cancer early detection (MCED) tests. MCED tests are positioned to be complementary to standard-of-care screening and they may broaden screening availability, especially for individuals who are not adherent with current screening programs and for individuals who may harbor cancers with no available screening options. In this article, we outline some key features that should be considered for study design and MCED test development, provide an example of the developmental pathway undertaken for an emerging multi-biomarker class MCED test and propose a clinical algorithm for an imaging-based diagnostic resolution strategy following MCED testing.

Background Chronic pain in cancer survivors negatively impacts quality of life. This study sought to investigate the relationship between high-impact chronic pain (HICP) -- defined as chronic pain that limits life or work activities on most days or every day in the past 3 months -- and cannabis in cancer survivors. Methods An electronic survey was developed in conjunction with the National Cancer Institute Comprehensive Cancer Centers in the United States. This survey was distributed to cancer survivors within a multi-site, single institution setting. Results The survey response rate was 23.0% (2304/10,000); 72.7% of these patients (1676/2304) did in fact have a confirmed cancer diagnosis. Among these cancer survivors, 16.5% (unweighted 278/1676) had HICP, and 12.4% (208/1676) reported cannabis use since their cancer diagnosis. The prevalence of past 30-day cannabis use was 12.3% (206/1676). Compared to cancer survivors without pain, those with HICP were more likely to believe in the benefits of cannabis (unweighted 92.1% vs. 74.7%; age-adjusted odds ratio [OR] = 3.1; 95% CI: 1.9-5.1) and less likely to believe in its risks (unweighted 48.2% vs. 58.4%; age-adjusted OR = 0.6; 95% CI: 0.4-0.7). Conclusions Cancer survivors with HICP have a higher prevalence of cannabis use compared to those patients without pain. More research is needed to advance pain and symptom management among cancer survivors and to identify clinical scenarios in which benefit is greater than potential harm.

Objective: Chronic daily pain is experienced by 11.2% of United States adults and psychosocial factors have significant impact on self-reported pain. Most research in this area has focused on pain-related conditions, not the general population. This study sought to understand the associations between clinically significant chronic pain and multiple dimensions of social relationship quality in a general population. Methods: A cross-sectional survey was deployed and adjusted logistic regression models were constructed for chronic pain against independent social support domains. The moderating effect of self-rated health on social support quality was explored. Results: Of all, 26.1% of surveys were completed (3920/15 000) and 18.8% reported clinically significant chronic pain. Patients with chronic pain had lower friendship quality (aOR = 0.78; 0.64-0.94) and higher perceived rejection (aOR = 1.26; 1.04-1.53) and perceived hostility (aOR = 1.26; 1.05-1.52). Within our moderation analysis, chronic pain patients with low self-rated health had higher odds of low friendship quality, high loneliness, and high perceived rejection. Conclusions: Chronic pain patients experience social relationships differently than those without, and self-rated health differentially impacts these perceptions.

ObjectivesTo evaluate the ability of claims‐based risk adjustment and incremental components of clinical data to identify 90‐day episode costs among lower extremity joint replacement (LEJR) patients according to the Centers for Medicare & Medicaid Services (CMS) Comprehensive Care for Joint Replacement (CJR) program provisions.Data SourcesMedicare fee‐for‐service (FFS) data for qualifying CJR episodes in the United States, and FFS data linked with clinical data from CJR‐qualifying LEJR episodes performed at High Value Healthcare Collaborative (HVHC) and Mayo Clinic in 2013. HVHC and Mayo Clinic populations are subsets of the total FFS population to assess the additive value of additional pieces of clinical data in correctly assigning patients to cost groups.Study DesignMultivariable logistic models identified high‐cost episodes.Data Collection/Extraction MethodsClinical data from participating health care systems merged with Medicare FFS data.Principal FindingsOur three populations consisted of 363 621 patients in the CMS population, 4881 in the HVHC population, and 918 in the Mayo population. When modeling per CJR specifications, we observed low to moderate model performance (CMS C‐Stat = 0.714; HVHC C‐Stat = 0.628; Mayo C‐Stat = 0.587). Adding CMS‐HCC categories improved identification of patients in the top 20% of episode costs (CMS C‐Stat = 0.758, HVHC C‐Stat = 0.692, Mayo C‐Stat = 0.677). Clinical variables, particularly functional status in the population for which this was available (Mayo C‐Stat = 0.783), improved ability to identify patients within cost groups.ConclusionsPolicy makers could use these findings to improve payment adjustments for bundled LEJR procedures and in consideration of new data elements for reimbursement.