Ebbert, Jon O.

AbstractAimsTo compare brief advice (BA), motivational interviewing (MI), rate reduction (RR), and combined MI and RR (MI + RR) to promote smoking cessation in smokers not ready to quit.DesignRandomized controlled trial with four parallel groups of smoking cessation intervention. Participants were randomly assigned 1:2:2:2 to receive one of the following interventions: BA (n = 128), MI (n = 258), RR (n = 257), and MI + RR (n = 260).SettingThe United States. All participant contact occurred over the telephone to be consistent with the typical quit line format.ParticipantsA total of 903 adult smokers. Participants had a mean age of 49 (SD = 13.3) years and were 28.9% male and 63.3% Caucasian.InterventionsThe BA group received advice similar to typical smoking cessation quit lines. The MI group received advice using basic MI principles to elicit language that indicates behavioral change. The RR group received behavioral skills training and nicotine gum. The MI + RR group combined elements of MI and RR conditions. All interventions were six sessions.MeasurementsThe primary outcome measure was self‐reported point prevalence at 12 months. The secondary outcome was self‐reported prolonged abstinence at 12 months.FindingsIntention to treat (ITT) point prevalence at 12 months indicated that BA (10.9%) had significantly lower point prevalence rates than RR (27.2%, OR = 3.17, 1.69–5.94), and MI + RR (26.9%, OR = 3.16, 1.68–5.93). BA did not have a significantly lower point prevalence rate than MI (15.5%, OR = 1.56, 95% CI = 0.81–3.02).ConclusionsThis randomized controlled trial provided evidence that rate reduction, which offers structured behavioral skills and nicotine gum, either alone or combined with motivational interviewing, is the most effective form of cessation intervention for smokers not ready to quit.

Introduction Central sensitization syndromes (CSS) comprise an overlapping group of clinical conditions with the core feature of “pain arising as a direct consequence of a lesion or disease affecting the somatosensory system.” Patients with CSS are known to have challenging interactions with healthcare providers contributing to psychological distress and increased healthcare utilization. CSS symptom severity has been associated with psychologic comorbidities, but little is known about how symptom severity relates to provider interactions. Methods We performed a cross-sectional survey among patients with CSS in our primary care practices to examine the relationship between CSS symptom severity and experiences with doctors. Results A total of 775 respondents completed the survey (775/5000; 15.5%) with 72% reporting high CSS symptom severity. About 44% of respondents had a prior diagnosis of fibromyalgia, 72% had migraines, and 28% had IBS. Patients with high CSS symptom severity were more likely to report that doctor(s) had often/always told them that they don’t need treatment when they feel like they do (OR = 3.6, 95% CI 1.9-7.5), that doctor(s) often/always don’t understand them (OR = 3.1, 95% CI 1.9-5.4), and that doctor(s) often/always seem annoyed with them when compared with respondents with low-moderate CSS symptom severity (OR = 4.8, 95% CI 2.2-12.5). Patients with high CSS symptom severity were at greater than 5 times odds of reporting being told that their symptoms were “all in their head” when compared to patients with low-moderate symptom severity (OR = 5.4, 95% CI 3.3-9.0). Conclusion Patients with CSS spectrum disorders experience frequent pain and decreased quality of life. A high degree of CSS symptom severity is associated with negative experiences with healthcare providers, which deters the establishment of a positive provider-patient relationship. Further research is needed to help understand symptom severity in CSS and harness the power of the therapeutic alliance as a treatment modality.

Abstract Background: Palliative care is a medical specialty centered on improving the quality of life (QOL) of patients with complex or life-threatening illnesses. The need for Palliative care is increasing and with that the rigorous testing of triage tools that can be used quickly and reliably to identify patients that may benefit from palliative care. Methods: To that Aim we will conduct a two-armed stepped-wedge cluster randomized trial rolled out to two inpatient hospitals to evaluate whether a machine learning algorithm accurately identifies patients who may benefit from a comprehensive review by a palliative care specialist, and decreases time to receiving a palliative care consult in hospital. This is a single-center study which will be conducted from August 2019 to November 2020 at Saint Mary’s Hospital & Methodist Hospital, Mayo Clinic, Rochester, Minnesota. Clusters will be nursing units which will be chosen to be a mix of complex patients from Cardiology, Critical Care and Oncology and had previously established relationships with palliative medicine. The stepped wedge design will have 12 units allocated to a design matrix of 5 treatment wedges. Each wedge will last 75 days resulting in a study period of 12 months unless otherwise specified. Data will be analyzed with Bayesian hierarchical models with credible intervals denoting statistical significance.Discussion: This intervention offers a pragmatic approach to delivering specialty palliative care to hospital patients in need using machine learning, thereby leading to high value care and improved outcomes. It is not enough for AI to be utilized by simply publishing research showing predictive performance; Clinical trials demonstrating better outcomes are critically needed. Furthermore, the deployment of an AI algorithm is a complex process that requires multiple teams with varying skill sets. To evaluate a deployed AI, a pragmatic clinical trial can accommodate the difficulties of clinical practice whilst retaining scientific rigor.Trial registration NCT03976297 (ClinicalTrials.gov), registered on June 6, 2019 prior to trial start.

Introduction Telehealth service provision has accelerated during the Coronavirus disease 2019 (COVID-19) pandemic. As the pandemic continues, clinical practices have discovered ways to resume operations. Opportunities exist to understand patient preferences for telehealth clinical services and to tailor offerings to different demographic groups. Methods We conducted a survey of patients receiving telehealth services through our outpatient practice to understand the types of healthcare services for which patients report preferences for telehealth. Results We received 551 survey responses (response rate = 20.8%; 551/2650). More than half of patients indicated being ‘very likely’ to use telehealth services to refill medication(s) (67.3%), prepare for an upcoming visit (66.1%), review test results (60.3%), or receive education (54.2%). Males had lower odds of preferring telehealth services for reviewing test results (odds ratio (OR) = 0.57; 95% confidence interval (CI): 0.34–0.94) or mental health issues (OR = 0.54; 95% CI: 0.38–0.77). Respondents who received a video visit were significantly more likely than those who received a telephone visit to report preferences for using telehealth for education, care plan discussions, long-term health issues, and mental health. Discussion Patient preferences for telehealth services vary by services provided and respondent demographics. Experience with telehealth increases the likelihood for future use of these services.

Background: News articles, commentaries, and opinion articles have suggested that ongoing social distancing measures coupled with economic challenges during COVID-19 may worsen stress, affective state, and substance use across the globe. We sought to advance our understanding of the differences between individuals who change their substance use patterns during a public health crisis and those who do not. Methods: Cross-sectional survey of young adults (18–25 years of age) assessing respondent characteristics and vaping, tobacco, alcohol, and/or marijuana use. We calculated prevalence estimates, prevalence changes, and prevalence ratios with associated 95% confidence intervals and looked for differences with the chi-square test. Results: Of the total sample, 53.2% ( n = 542/1018) young adults reported vaping or using tobacco, alcohol, and/or marijuana. Among the 542 respondents reporting use, 34.3% reported a change in their use patterns. Among respondents reporting changes in substance use patterns during the pandemic ( n = 186), 68.8% reported an increase in alcohol use, 44.0% reported a decrease in vaping product use, and 47.3% reported a decrease in tobacco product use due to COVID-19. Substance use changed significantly for respondents with increasing degree of loneliness (continuous loneliness score: prevalence ratio = 1.12, 95% confidence interval = 1.01–1.25), anxiety (prevalence ratio = 1.45, 95% confidence interval = 1.14–1.85), and depression (prevalence ratio = 1.44, 95% confidence interval = 1.13–1.82). Conclusion: Self-reported substance use among young adults was observed to change during a pandemic, and the degree of loneliness appears to impact these changes. Innovative strategies are needed to address loneliness, anxiety, depression, and substance use during global health crises that impact social contact.

Objective: We surveyed patients who visited multiple outpatient specialty practices to understand what summary content was most helpful with the goal of optimizing meaningful outpatient clinical visit summary content. Materials and Methods: We constructed a survey instrument to measure delivery, use, and contents of clinical visit summaries. We surveyed patients who visited with at least 2 different outpatient medical specialties to understand preferences. Results: Most patients in our sample valued the summary information they received, and retained it as healthcare documentation (84%) and/or quick reference in supporting self-care (70%). Patients most commonly reported that information on results of completed tests (91%) and treatment plan instructions (89%) were very helpful. Additionally, patients expressed the importance of online access to clinical visit summary information. Discussion: Most patients used the clinical visit summary as healthcare documentation, and valued online availability of their summary information. Patients most often reported that information on results of recently completed tests and specific instructions on treatment plan were very helpful. Patients who sought further information after their visit most often looked to a provider and/or online. Conclusions: Patients valued clinical visit summary accessibility and as a reference tool to summarize care and provide next steps. Optimal clinical visit summaries might collate and integrate assessments and recommendations from multiple specialties into coherent care plans for patients.

AbstractBackgroundDespite malnutrition being associated with increased mortality and morbidity, there continues to be great difficulty in defining criteria and implementing widespread screening. Tools used to diagnose decreased fat‐free mass (FFM [sarcopenia]) should be easy to use, relatively inexpensive, and safe. Bioelectrical impedance analysis (BIA) has the potential to meet these criteria, but reliability across body mass index (BMI) classes is a concern.MethodsA total of 176 healthy ambulatory participants (aged 18–65 years) were recruited equally (n = 44) in 4 BMI categories: (1) 18.5–24.9, (2) 25.0–29.9, (3) 30–34.9, and (4) ≥35.0. Participants were fasting overnight and had S‐MFBIA (InBody 770) measurements the next morning, with DXA being performed subsequently within 30 minutes.ResultsThe measurement (mean ± SD) for FFM with DXA was 52.8 ± 11.0, and BIA was 53.6 ± 11.0. Delta (S‐MFBIA vs DXA) was 0.8 ± 2.2 (5% limits of agreement −3.5 to +5.2), and concordance correlation coefficient (CCC) was 0.98 (95% CI, 0.97–0.98). The measurements (mean ± SD) for PBF with DXA was 37.5 ± 10.6% and S‐MFBIA was 36.6 ± 11.3%. Delta (S‐MFBIA vs DXA) was −0.9 ± 2.6 (5% limits of agreement 6.0 to +4.2), and CCC was 0.97 (95% CI, 0.96–0.98). The CCC according to the 4 BMI groups for FFM and PBF was between 0.96–0.98 and 0.90–0.94, respectively.ConclusionsFFM and PBF measured by S‐MFBIA had good agreement with DXA across all BMI categories measured in the current study of ambulatory participants.