Ramar, Priya

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.

Introduction/Objectives: To describe health outcomes of older adults enrolled in the Mayo Clinic Care Transitions (MCCT) program before and during the COVID-19 pandemic compared to unenrolled patients. Methods: We conducted a retrospective cohort study of adults (age >60 years) in the MCCT program compared to a usual care control group from January 1, 2019, to September 20, 2022. The MCCT program involved a home, telephonic, or telemedicine visit by an advanced care provider. Outcomes were 30- and 180-day hospital readmissions, emergency department (ED) visit, and mortality. We performed a subgroup analysis after March 1, 2020 (during the pandemic). We analyzed data with Cox proportional hazards regression models and hazard ratios (HRs) with 95% CIs. Results: Of the 1,012 patients total, 354 were in the MCCT program and 658 were in the usual care group with a mean (SD) age of 81.1 (9.1) years overall. Thirty-day readmission was 16.9% (60 of 354) for MCCT patients and 14.7% (97 of 658) for usual care patients (HR, 1.24; 95% CI, 0.88-1.75). During the pandemic, the 30-day readmission rate was 15.1% (28 of 186) for MCCT patients and 14.9% (68 of 455) for usual care patients (HR, 1.20; 95% CI, 0.75-1.91). There was no difference between groups for 180-day hospitalization, 30- or 180-day ED visit, and 30- or 180-day mortality. Conclusions: Numerous factors involving patients, providers, and health care delivery systems during the pandemic most likely contributed to these findings.

Background Digital and mobile (mHealth) solutions are online or application-based services intended to support individuals with health needs. Despite evidence supporting the use of mHealth for patients with chronic pain, and the increasing desire of these types of solutions by both patients and providers, adoption of mHealth solutions remains limited. Implementation mapping can serve as a practical method to facilitate implementation and adoption of mHealth solutions within healthcare settings. Methods Implementation mapping was used to develop implementation strategies based on contextual determinants organized within the Consolidated Framework for Implementation Research (CFIR) for mHealth eLearning solutions across an integrated, multi-site healthcare system. We describe our experience identifying stakeholders, delineating implementation facilitators and barriers, defining implementation outcomes using RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework, outlining initial implementation strategies, and iterating on implementation strategies. Results A total of 30 implementation strategies were identified and implemented. Over the first year, primary and specialty care providers across all the clinical sites ( n = 70) placed 2559 orders for the mHealth solution. Most patients reported receiving the mHealth eLearning module (74%), and most patients felt that the tool improved their knowledge regarding their condition (82%) and their ability to provide self-care related to the condition (73%). Conclusion Practical applications of implementation science methods can help enable change within healthcare settings. Implementation mapping is an exercise that can engage stakeholders to facilitate the incorporation of new methods of care delivery, including mHealth solutions.

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.

Background and objectives Despite the dramatic increase in the provision of virtual nephrology care, only anecdotal reports of outcomes without comparators to usual care exist in the literature. This study aimed to provide objective determination of clinical noninferiority of hybrid (telenephrology plus face-to-face) versus standard (face-to-face) inpatient nephrology care. Design, setting, participants, & measurements This retrospective study compares objective outcomes in patients who received inpatient hybrid care versus standard nephrology care at two Mayo Clinic Health System community hospitals. Outcomes were then additionally compared with those patients receiving care at another Mayo Clinic Health System site where only standard care is available. Hospitalized adults who had nephrology consults from March 1, 2020 to February 28, 2021 were considered. Regression was used to assess 30-day mortality, length of hospitalization, readmissions, odds of being prescribed dialysis, and hospital transfers. Sensitivity analysis was performed using patients who had ≥50% of their care encounters via telenephrology. Structured surveys were used to understand the perspectives of non-nephrology hospital providers and telenephrologists. Results In total, 850 patients were included. Measured outcomes that included the number of hospital transfers (odds ratio, 1.19; 95% confidence interval, 0.37 to 3.82) and 30-day readmissions (odds ratio, 0.97; 95% confidence interval, 0.84 to 1.06), among others, did not differ significantly between controls and patients in the general cohort. Telenephrologists ( n =11) preferred video consults (82%) to phone for communication. More than half (64%) of telenephrologists spent less time on telenephrology compared with standard care. Non-nephrology hospital providers ( n =21) were very satisfied (48%) and satisfied (29%) with telenephrology response time and felt telenephrology was as safe as standard care (67%), while providing them enough information to make patient care decisions (76%). Conclusions Outcomes for in-hospital nephrology consults were not significantly different comparing hybrid care versus standard care. Non-nephrology hospital providers and telenephrologists had favorable opinions of telenephrology and most perceived it is as safe and effective as standard care. Podcast This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_04_11_CJN13441021.mp3

Abstract Background Bamlanivimab and casirivimab-imdevimab are authorized for treatment of mild to moderate coronavirus disease 2019 (COVID-19) in high-risk patients. We compared the outcomes of patients who received these therapies to identify factors associated with hospitalization and other clinical outcomes. Methods Adult patients who received monoclonal antibody from 19 November 2020 to 11 February 2021 were selected and divided into those who received bamlanivimab (n = 2747) and casirivimab-imdevimab (n = 849). The 28-day all-cause and COVID-19–related hospitalizations were compared between the groups. Results The population included 3596 patients; the median age was 62 years, and 50% were female. All had ≥1 medical comorbidity; 55% had multiple comorbidities. All-cause and COVID-19–related hospitalization rates at 28 days were 3.98% and 2.56%, respectively. After adjusting for medical comorbidities, there was no significant difference in all-cause and COVID-19–related hospitalization rates between bamlanivimab and casirivimab-imdevimab (adjusted hazard ratios [95% confidence interval], 1.4 [.9–2.2] and 1.6 [.8–2.7], respectively). Chronic kidney, respiratory and cardiovascular diseases, and immunocompromised status were associated with higher likelihood of hospitalization. Conclusions This observational study on the use of bamlanivimab and casirivimab-imdevimab in high-risk patients showed similarly low rates of hospitalization. The number and type of medical comorbidities are associated with hospitalizations after monoclonal antibody treatment.

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.

Background The clinical outcomes of patients who decline anti-spike monoclonal antibody therapies for coronavirus disease-2019 (COVID-19) is not known. Factors associated with the decision to accept or decline the offer for anti-spike monoclonal antibody therapies are not established. This study aimed to identify factors impacting the decision to consent for monoclonal antibody therapies and assess the differences in clinical outcomes of patients who accepted compared to those who declined these therapies. Methods This retrospective cohort study enrolled 2820 adult patients who were offered monoclonal antibody therapies, bamlanivimab and casirivimab-imdevimab, for COVID-19 at Mayo Clinic in the Midwest between 11/19/2020 and 12/31/2020. The primary endpoint is the decision to accept or decline monoclonal antibody treatment. Secondary endpoints were patient-level factors that could have impacted the decision to accept treatment (age, gender, race, ethnicity, primary language spoken, and medical comorbidities). The main clinical endpoint was hospitalization within 28 days of COVID-19 diagnosis. Results 59.1% (n = 1669) chose to accept monoclonal antibody therapy, and 40.9% (n = 1151) chose to decline the offer for treatment. Patients were more likely to accept treatment if they were non-Hispanic White, English speaking, identified a spouse or life partner, had a religious affiliation, and possessed more medical comorbidities. Overall, 28-day hospitalization rate was 2.6% (n = 72/2820) and was higher among those who declined (3.3%) than those who accepted monoclonal antibody therapy (2.0%; Rate Ratio = 0.62, 95% Confidence Interval, 0.39-0.98). Conclusions Despite having more comorbidities, patients who accepted monoclonal antibody treatments had a lower rate of hospitalization compared to patients who declined treatment. Several social and cultural factors were associated with the decision to decline therapy, including race, language, ethnicity, and lack of social support. These findings can inform public health efforts to reduce social disparities in the treatment of COVID-19 and increase utilization of monoclonal antibody therapies in high risk populations.

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.