Citations

Background: Despite efforts to improve access to Medications for Opioid Use Disorder (MOUD), such as buprenorphine, the number of opioid overdoses in the United States continues to rise. In April 2021, the Department of Health and Human Services removed the mandatory training requirement to obtain a buprenorphine waiver; the goal was to encourage more providers to prescribe buprenorphine, thus improving access. Little is known about the attitudes on buprenorphine prescribing after this policy change. Objective: The primary objective was to assess attitudes among primary care providers toward the removal of the buprenorphine waiver training requirement. A secondary objective was to identify other barriers to prescribing buprenorphine. Methods: We conducted a survey between September 15 and October 13, 2021 to assess the overall beliefs on the effectiveness of MOUD and attitudes toward the removal of the waiver training, current knowledge of buprenorphine, current practice styles related to screening for and treating OUD, and attitudes toward prescribing buprenorphine in the future. This survey was sent to 890 Mayo Clinic primary care providers in 5 US states. Results: One hundred twenty-three respondents (13.8%) completed the survey; 35.8% respondents agreed that the removal of the waiver training was a positive step. These respondents expressed a greater familiarity with the different formulations, pharmacology, and titration of buprenorphine. This group was also more likely to prescribe (or continue to prescribe) buprenorphine in the future. Approximately one-third (34.4%) of respondents reported perceived institutional support in prescribing buprenorphine. This group expressed greater confidence in diagnosing OUD, had greater familiarity with the different formulations, pharmacology, and titration of buprenorphine, and was more likely to prescribe (or continue to prescribe) buprenorphine in the future. Respondents who have been in practice for 11 to 20 years since completion of training were most likely to refer all OUD patients to specialists. Conclusions: Results of our survey suggests that simply removing the mandatory waiver training requirement is insufficient in positively changing attitudes toward buprenorphine prescribing. A key barrier is the perceived lack of institutional support. Future studies investigating effective ways to provide such support may help improve providers’ willingness to prescribe buprenorphine.

Background: The COVID-19 pandemic has led to increased burnout and staff turnover for health care providers (HCPs). The purpose of this pilot study was to evaluate the safety and acceptability of a Stress Resilience Program (SRP) for reducing perceived stress and improving resilience among HCPs during a pandemic. Method: Of the 12 HCPs expressing interest in the study, 10 were enrolled in this study. Participants attended three in-person visits (consent/screen, baseline, and end-of-study). The SRP consisted of education related to resilience enhancement and a breathing device ( BreatherFit®) for combined respiratory muscle training (cRMT). Participants completed 4 weeks of cRMT and applied situational breathing strategies as needed. Outcomes measured were changes in stress (PSS-10), resilience (BRS), depression (PRIME-MD), and sleep (PSQI and Ōura Ring®). Findings: The majority of participants were male (60%) and White (60%) with an average age of 39.7 years. Changes from baseline to end-of-treatment indicated a positive trend with significant stress reduction (−3.2 ± 3.9, p = .028) and nonsignificant depression reduction (−0.5 ± 0.7, p = .05). Resilience was high at baseline and continued to stay high during the study with a nonsignificant increase at end-of-study (+0.07 ± 0.7, p = .77). No changes in overall sleep scores were noted. All participants agreed the study was worthwhile, 80% indicated they would repeat the experience, while 90% indicated they would recommend the study to others. Conclusion/Application to Practice: Because of its size and portability, SRP is an easily applicable and promising option for reducing stress among HCPs during a high-stress period, such as a pandemic. Larger studies are needed.

Objective: The purpose of this pilot study was to evaluate the safety and use of a nature-based virtual reality (VR) experience among health care providers (HCP) during a pandemic. Methods: Twenty-four frontline HCP participated in this crossover pilot where the viewing order of the experiences were randomized. All participants attended in-person consent, baseline, and end-of-study visits. The intervention consisted of viewing 2 nature-based scenes (“walk in the woods” and “forest of focus”) through 3-D VR and with computer 4K graphic imagery. Randomization took place with regards to the viewing order (VR vs 4K computer video, scene 1 and 2). Outcomes measured were safety, acceptability and changes in intensity of anxiety feelings, resilience, emotional distress, cognitive function, and self-efficacy. Results: Among the 26 HCP expressing interest in the study, 24 enrolled in this study. The majority were male (58.3%), white (66.7%) and of an average age of 46.3 ± 10.5 years (standard deviation (SD)). End of the study survey showed that almost all participants (96%) would participate in the study again and recommend it to others. Twenty-three of the 24 participants also felt relaxed after seeing the imagery. With respect to anxiety (as measured by the STAI Y1), the VR “walk in the woods” had the greatest reduction from pre to post (6.4 points, SD = 5.98) followed by VR “forest of focus” (5.8 points, SD = 9.29), computer screen “forest of focus” (5.0 points, SD = 8.89), and computer screen “walk in the woods” (4.1 points, SD = 6.22). All 4 sessions had a significant decrease in score from pre to post (P-values ≤.005), but there was no significant difference in the change from pre- to post-session between the 4 groups (P-value = .5835). Conclusion: The use of the VR among HCP has promise for reducing stress among health care providers during a high stress period, such as a pandemic but much larger studies are needed.

Background Glioblastoma multiforme (GBM) is among the most aggressive and lethal tumors, with a median survival of 12–15 months. Many patients use complementary and integrative medicine (CIM) therapies to supplement their cancer treatment. Objective To determine the prevalence of CIM use and identify the most frequently used types of CIM in a cohort of patients with GBM seen at a tertiary care medical center in the United States. Methods An anonymous survey was mailed through the US Postal Service from August 1, 2019, through February 21, 2020, to patients with GBM. Results A total of 346 surveys were mailed, and 146 responses (42%) were received. The median age of respondents was 61 years (range, 52–68 years), and 85 (58%) were male. Most patients had undergone surgery (90%), chemotherapy (96%), and radiotherapy (95%). The median time from diagnosis of GBM to survey participation was 18 months (range, 12–31 months). Most respondents (81%) used some form of CIM, most frequently meditation (22%), relaxation and other stress management techniques (19%), chiropractic therapy (16%), and acupuncture (12%). Compared with men, women more commonly meditated (32% vs 16%; P = .046) and practiced yoga (20% vs 6%; P = .04). We observed age-based differences, with younger patients more commonly meditating, practicing relaxation and stress management techniques, and receiving chiropractic therapy ( P < .05 for all). Conclusions Providers should encourage patients with GBM to discuss their interest in CIM therapies and guide them to evidence-based treatments that may help improve their quality of life.

AbstractBackgroundThe early phase of the coronavirus disease 2019 (COVID‐19) pandemic had a negative impact on the wellness of hospitalists and hospital medicine advanced practice providers (APPs). However, the burden of the pandemic has evolved and the change in hospitalist and hospital medicine APP wellness is unknown.ObjectiveTo evaluate the longitudinal trend in wellness of hospitalists and hospital medicine APPs during the COVID‐19 pandemic and guide wellness interventions.Design, Setting and ParticipantsBetween May 4, 2020, and June 6, 2021, we administered three surveys to Internal Medicine hospitalists (physicians) and hospital medicine APPs (nurse practitioners and physician assistants) at 16 Mayo Clinic hospitals in four U.S. states.MeasurementsWe evaluated the association of hospitalist and hospital medicine APP characteristics with PROMIS® measures of global wellbeing‐mental health, global wellbeing‐social activities and relationships, anxiety, social isolation, and emotional support, using logistic and linear regression models.ResultsThe response rates were 52.2% (n=154/295; May 2020), 37.1% (n=111/299; October 2020) and 35.5% (n=114/321; May 2021). In mixed models that included hospitalist and hospital medicine APP characteristics and survey period, APPs, compared with physicians, had lower odds of top global wellbeing‐social activities and relationships (adjusted odds ratio 0.42 [0.22–0.82]; p = .01), whereas survey period showed no association. The survey period showed an independent association with higher anxiety (May 2020 vs. others) and higher social isolation (October 2020 vs. others), whereas profession showed no association. Concern about contracting COVID‐19 at work was significantly associated with lower odds of top global wellbeing‐mental health and global wellbeing‐social activities and relationships, and with higher anxiety and social isolation. Hospitalist and hospital medicine APP characteristics showed no association with levels of emotional support.ConclusionsIn this longitudinal assessment of hospitalists and hospital medicine APPs, concern about contracting COVID‐19 at work remained a determinant of wellness. The trend for global wellbeing, anxiety, and social isolation may guide wellness interventions.

Objective: To evaluate the performance of an Electronic Health Record (EHR) integrated risk score for COVID-19 positive outpatients to predict 30-day risk of hospitalization. Patients and Methods: A retrospective observational study of 67 470 patients with COVID-19 confirmed by polymerase chain reaction (PCR) test between March 12, 2020 and February 8, 2021. Risk scores were calculated based on data in the chart at the time of the incident infection. Results: The Mayo Clinic COVID-19 risk score consisted of 13 components included age, sex, chronic lung disease, congenital heart disease, congestive heart failure, coronary artery disease, diabetes mellitus, end stage liver disease, end stage renal disease, hypertension, immune compromised, nursing home resident, and pregnant. Univariate analysis showed all components, except pregnancy, have significant ( P < .001) association with admission. The Mayo Clinic COVID-19 risk score showed a Receiver Operating Characteristic Area Under Curve (AUC) of 0.837 for the prediction of admission for this large cohort of COVID-19 positive patients. Conclusion: The Mayo Clinic COVID-19 risk score is a simple score that is easily integrated into the EHR with excellent predictive performance for severe COVID-19. It can be leveraged to stratify risk for severe COVID-19 at initial contact, when considering therapeutics or in the allocation of vaccine supply.

Objective: This study determined the incidence rates for obesity among adult patients ages 20 and older empaneled in primary care practice in Midwest United States to potentially identify an optimum timeframe for initiating intervention. Background: Primary care practice patients are likely to reflect underlying community trends in overweight and obesity; however, data on overweight and obesity in primary care patients is limited. While childhood incidence rates of obesity have been well reported, there is still a paucity of data on the incidence of obesity among adult population; literature has mainly focused on its prevalence. Methods: Medical record review of identified cohort with BMI data was conducted. Population was stratified by age and sex and overweight category was subdivided into tertiles. Results: Majority of 40 390 individuals who comprised the final population and had follow-up data, consisted of adults ages 40 to 69 years (47.5%), female (59.8%) of non-Hispanic ethnicity (95.9%) with 21 379 (52.8%) falling in weight category of overweight. Incidence of obesity was 7% at 1 year and 16% at 3 years follow-up. Highest percentages of individuals who became obese at 1 and 3 years were in age category of 40 to 69 years among men and 20 to 39 years among women. In Cox regression analysis, there was statistically significant association to developing obesity among all tertile groups in the overweight category. Age and particularly gender appeared to be modifying factors to likelihood of developing obesity. Conclusion: Study results suggest that while obesity incidence is higher among certain age groups in both genders, middle-aged women, and men in all tertiles of overweight category are at highest risk and may be the optimum population to target for weight loss interventions. Findings support the initiation of population-based interventions before onset of obesity.

Objectives: The purpose of the present study was to assess and describe the severity of symptoms reported by Covid-19 positive patients who vaped (smoked e-cigarettes) when compared to those who did not vape or smoke at the time of the diagnosis of Covid-19. Methods: Patients from this study are from a well-characterized patient cohort collected at Mayo Clinic between March 1, 2020 and February 28, 2021; with confirmed COVID-19 diagnosis defined as a positive result on reverse-transcriptase–polymerase-chain-reaction (RT-PCR) assays from nasopharyngeal swab specimens. Among the 1734 eligible patients, 289 patients reported current vaping. The cohort of vapers (N = 289) was age and gender matched to 1445 covid-19 positive patients who did not vape. The data analyzed included: date of birth, gender, ethnicity, race, marital status, as well as lifestyle history such as vaping and smoking and reported covid-19 symptoms experienced. Results: A logistic regression analysis was performed separately for each symptom using generalized estimating equations (GEE) with robust variance estimates in order to account for the 1:5 age, sex, and race matched set study design. Patients who vaped and developed Covid-19 infection were more likely to have chest pain or tightness (16% vs 10%, vapers vs non vapers, P = .005), chills (25% vs 19%, vapers vs non vapers, P = .0016), myalgia (39% vs 32%, vapers vs non vapers, P = .004), headaches (49% vs 41% vapers vs non vapers, P = .026), anosmia/dysgeusia (37% vs 30%, vapers vs non vapers, P = .009), nausea/vomiting/abdominal pain (16% vs 10%, vapers vs non vapers, P = .003), diarrhea (16% vs 10%, vapers vs non vapers, P = .004), and non-severe light-headedness (16% vs 9%, vapers vs non vapers, P < .001). Conclusion: Vapers experience higher frequency of covid-19 related symptoms when compared with age and gender matched non-vapers. Further work should examine the impact vaping has on post-covid symptom experience.

Objective: The purpose of this report is to describe the elements of a Covid-19 Care Clinic (CCC), patient demographics, and outcomes. Methods: Descriptive statistics were used to describe demographics, clinical characteristics, and outcomes. This report is based on 4934 unique patients seen in the CCC who provided research authorization within a 10-month period of time (April 1, 2020-January 31, 2021). The CCC infection control processes consisted of a rooming process that mitigated SARS-COV-2 transmission, preparing examination rooms, using PPE by staff, in room lab drawing, and escorting services to minimize the time in clinic. Results: Of the 4934 unique patients seen (age range newborn-102 years), 76.8% were tested for COVID-19. Of those tested, 11.8% were positive for SARS-CoV-2. Ninety-two percent of the patients with the reason for the visit documented had COVID-19 type symptoms. Cough, shortness of breath, and chest pain were the most common presenting symptom in those with COVID-19. At the time of the visit in the CCC, 5.8% of the patients were actively contagious. Thirty days after being seen in the CCC, 9.1% of the patients were seen in the emergency department (ED) and 0.2% died. During the 10-month period there were no known occupationally related COVID-19 infections. Conclusion: The COVID-19 Care Clinic provided face-to-face access for all ages with COVID-19 type symptoms. A minority of patients had COVID-19 who were seen in the clinic. The clinic provided an additional venue of care outside of the ED. The infectious control measures employed were highly effective in protecting the staff. Lessons learned allow for decentralization of COVID-19 symptom care to the primary care practices employing the infection control measures.