Use of and Satisfaction with Telemedicine Services during the Pandemic. Findings from the COVID-19 Snapshot Monitoring in Germany (COSMO)

Our aim was to investigate to what extent physician visits were replaced by telemedicine services because of the COVID-19 pandemic and the satisfaction with such telemedicine services. Cross-sectional data from the “COVID-19 Snapshot Monitoring in Germany” (COSMO, wave 49 from 11 to 12 August 2021 with n = 967). The average age was 44.9 years (SD: 15.6 years, ranging from 18 to 74 years) and 50.8% were female. Indiviuals were asked whether any physician visit was replaced by a telemedicine service (e.g., video consultation) since March 2020 because of the pandemic (yes, once; yes, several times; yes, always; no, not replaced; no, there was no need to see a doctor). Additionally, individuals who gave positive responses (i.e., yes, once; yes, several times; yes, always) were asked how satisfied they were with the corresponding telemedicine services (from 1 = very dissatisfied to 7 = very satisfied). While 55.4% of the respondents reported no need to see a doctor and 31.3% of the respondents did not replace physician visits by telemedicine services, about 13.3% of the respondents did replace physician visits by telemedicine services (4.8%: yes, once; 6.4%: yes, several times; 2.1%: yes, always). Among the individuals who used such services, the average satisfaction was moderately high (4.7, SD: 2.0). Additionally, several correlates of the replacing telemedicine service use were identified (e.g., perceived severity of a COVID-19 infection). In conclusion, about one out of seven individuals replaced physician visits by telemedicine services during the pandemic. For example, knowledge about the correlates of satisfaction with such services might be of importance to increase the quality of such services.

Effect of Nudge-Based Intervention on Adherence to Physician Visit Recommendations and Early Health Outcomes among Individuals Identified with Chronic Kidney Disease in Screens

BackgroundAlthough CKD screening programs have been provided in many settings, little is known as to how we can effectively translate those screening programs into improved health.MethodsWe conducted a randomized clinical trial on national health screening for CKD in Japan between April 2018 and March 2019. A total of 4011 participants in CKD screening programs aged 40–63 years were randomly assigned to two interventions or the control, with a ratio of 2:2:1, respectively: (1) the nudge-based letter that contained a message on the basis of behavioral economics, (2) the clinical letter including general information about CKD risks, and (3) the control (informed only of the screening results). The main outcome was adherence to a recommended physician visit within 6 months of the intervention. The secondary outcomes were eGFR, proteinuria, and BP 1 year after the intervention.ResultsCompared with the control group, the probability of undergoing a recommended physician visit was higher among participants who received the nudge-based letter (19.7% for the intervention group versus 15.8% for the control; difference, +3.9 percentage points [pp]; 95% CI, +0.8 to +7.0; P=0.02) and the clinical letter (19.7% versus 15.8%; difference, +3.9 pp; 95% CI, +0.8 to +7.0; P=0.02). We found no evidence that interventions were associated with improved early health outcomes.ConclusionsThe behavioral economics intervention tested in this large RCT had limited effect on changing behavior or improving health outcomes. Although the approach has promise, this study demonstrates the challenge of developing behavioral interventions that improve the effectiveness of CKD screening programs.Clinical Trial registry name and registration number: University Hospital Medical Information Network Clinical Trial Registry, UMIN000035230

Effects of physician visit frequency for Parkinson’s disease treatment on mortality, hospitalization, and costs: a retrospective cohort study

Background The number of patients with Parkinson’s disease among older adults is rapidly increasing. Such patients mostly take medication and require regular physician visits. However, the effect of physician visit frequency for the treatment for Parkinson’s disease has not been evaluated. This study aimed to evaluate the impact of physician visit frequency for Parkinson’s disease treatment on mortality, healthcare days, and healthcare and long-term care costs among older adults. Methods This study employed a retrospective cohort design utilizing claims data from the Fukuoka Prefecture Wide-Area Association of Latter-Stage Elderly Healthcare Insurance and Long-Term Care Insurance. Patients aged ≥75 years who were newly diagnosed with Parkinson’s disease in 2014 were included in this study, following the onset of Parkinson’s disease to March 31, 2019. We calculated the restricted mean survival time to evaluate mortality, focusing on the frequency of physician visits for Parkinson’s disease treatment. Inpatient days, outpatient days, and healthcare and long-term care costs per month were calculated using a generalized linear model. Results There were 2224 participants, with 46.5% mortality among those with a higher frequency of physician visits and 56.4% among those with a lower frequency of physician visits. A higher frequency of physician visits was associated with a significant increase in survival time (1.57 months at 24 months and 5.00 months at 60 months) after the onset of Parkinson’s disease and a decrease in inpatient days and healthcare costs compared to a lower frequency of physician visits. Conclusions A higher frequency of physician visits was significantly associated with longer survival time, fewer inpatient days, and lower healthcare costs. Caregivers should support patients with Parkinson’s disease to visit physicians regularly for their treatment.

Epidemiology Unknown: Developing an Approach to Identify Potential Smoldering Multiple Myeloma Cases

Background Smoldering Multiple Myeloma (SMM) is an asymptomatic clonal plasma cell disorder that identifies patients at risk for progression to Multiple Myeloma (MM). The standard of care for SMM has traditionally been observation, but some cancer centers are now treating high-risk SMM before progression to MM. The diagnostic criteria for SMM have also changed in recent years, and current estimates of SMM are derived from large MM databases and observations from tertiary centers. The goal of this study was to develop an approach for identifying SMM cases in a large integrated healthcare delivery system to better characterize the epidemiology of SMM in community-based populations. Methods This retrospective, observational study was conducted in Kaiser Permanente Northern California (KPNC) using KPNC SEER-based Cancer Registry data and information from the electronic health record (EHR). Potential SMM cases from 1/1/2010 to 12/31/2018 were identified using three approaches: Group 1 - identified via the KPNC Cancer Registry based on indicators of 'asymptomatic myeloma', 'evolving myeloma', and 'smoldering myeloma'; Group 2 - identified via the KPNC Cancer Registry as MM cases who had a physician visit note containing the word 'smoldering' but did not begin treatment within 1 year of diagnosis; Group 3 - identified via the KPNC Cancer Registry as MM cases who had a physician visit note containing the word 'smoldering' but did begin treatment within 1 year of diagnosis. Chart review was performed for these potential SMM cases (Groups 1-3) to document initial bone marrow biopsy results (bone marrow plasma cell percentage, BMPC) and skeletal findings (presence or absence of lytic bone lesions) around the time of biopsy. When BMPC was reported as a range, the highest value was captured. Patient demographics (age, sex and race/ethnicity) were obtained from the EHR. Bivariate analyses were performed using the chi-squared test and the Wilcoxon-Mann-Whitney nonparametric test. For binomial comparisons by mode of potential SMM case identification, Groups 1 and 2 were combined and compared to Group 3. Results A total of 471 potential SMM cases were identified, including 178 (37.8%) via Group 1, 35 (7.4%) via Group 2, and 258 (54.8%) via Group 3 (Figure). The median age was 71 years (interquartile range, IQR 62-78) and 40.0% were female. The racial/ethnic distribution included 57.1% White, 17.6% Black, 10.8% Hispanic, 13.6% Asian, and 0.9% other/unknown race. There were no significant differences across groups (Group 1+2 vs Group 3) with respect to age (p=0.07), sex (p=0.85), or race/ethnicity (p=0.81). There were 442 (93.8%) who underwent bone marrow biopsy. Among those with BMPC data, the median BMPC for Group 1 was 20.0% (IQR 10.0%-28.0%); for Group 2 was 25.0% (IQR 12.5%-50.0%), for Group 3 was 28.0% (IQR 15.0%-50.0%) (p<0.001 comparing Groups 1+2, combined median 20.0%, IQR 10.0%-30.0%, vs Group 3, 28.0%, IQR 15.0%-50.0%). The proportion with BMPC ≥60% was 4%, 13%, and 22% for Groups 1, 2, and 3, respectively (Figure). There were 413 (87.7%) who had skeletal imaging (n=405, 86.0% with available results) within 6 months of diagnosis. Of those with imaging results available to view, n=68 were found to have lytic lesions; 7.6% among Group 1, 6.9% among Group 2, 24.9% among Group 3 (p<0.001 comparing Groups 1+2, 7.5%, vs Group 3, 24.9%). Discussion This study used a multifaceted approach to identify potential SMM cases from a large real-world clinical population in an integrated health system. We used an approach similar to prior SMM epidemiological studies and also included those with physician visit notes specifically containing the word 'smoldering' within the text. The vast majority of our cohort had BMPC between 10 and 60%, but those who received treatment within 1 year had greater BMPC and a higher proportion of lytic lesions. This suggests those who received treatment, Group 3, may have actually had a MM diagnosis, and physician visit notes containing the word 'smoldering' may have been intended to communicate something other than a SMM diagnosis. Further analyses will determine the effectiveness of each approach by confirming SMM cases according to the International Myeloma Working Group diagnostic criteria with incorporation of laboratory data and additional clinical findings. Among confirmed cases of SMM, the rate of progression to MM and the severity of end-organ damage at time of progression will be assessed. Figure 1 Figure 1. Disclosures Lo: Novartis: Research Funding; Bristol-Myers-Squibb: Research Funding; CSL-Bering: Research Funding.

Head to head randomized trial of two decision aids for prostate cancer

Background While many studies have tested the impact of a decision aid (DA) compared to not receiving any DA, far fewer have tested how different types of DAs affect key outcomes such as treatment choice, patient–provider communication, or decision process/satisfaction. This study tested the impact of a complex medical oriented DA compared to a more simplistic decision aid designed to encourage shared decision making in men with clinically localized prostate cancer. Methods 1028 men at 4 VA hospitals were recruited after a scheduled prostate biopsy. Participants completed baseline measures and were randomized to receive either a simple or complex DA. Participants were men with clinically localized cancer (N = 285) by biopsy and who completed a baseline survey. Survey measures: baseline (biopsy); immediately prior to seeing the physician for biopsy results (pre- encounter); one week following the physician visit (post-encounter). Outcome measures included treatment preference and treatment received, knowledge, preference for shared decision making, decision making process, and patients’ use and satisfaction with the DA. Results Participants who received the simple DA had greater interest in shared decision making after reading the DA (p = 0.03), found the DA more helpful (p’s < 0.01) and were more likely to be considering watchful waiting (p = 0.03) compared to those receiving the complex DA at Time 2. While these differences were present before patients saw their urologists, there was no difference between groups in the treatment patients received. Conclusions The simple DA led to increased desire for shared decision making and for less aggressive treatment. However, these differences disappeared following the physician visit, which appeared to change patients’ treatment preferences. Trial registration This trial was pre-registered prior to recruitment of participants.

Factors Associated With Clinical Recovery After Concussion in Youth Ice Hockey Players

Background: The identification of factors associated with clinical recovery in youth after sports-related concussion could improve prognostication regarding return to play (RTP). Purpose: To assess factors associated with clinical recovery after concussion in youth ice hockey players. Study Design: Cohort study; Level of evidence, 2. Methods: Participants were part of a larger longitudinal cohort study (the Safe to Play study; N = 3353). Included were 376 ice hockey players (age range, 11-17 years) from teams in Calgary and Edmonton, Canada, with 425 physician-diagnosed ice hockey–related concussions over 5 seasons (2013-2018). Any player with a suspected concussion was referred to a sports medicine physician for diagnosis, and a Sport Concussion Assessment Tool (SCAT) form was completed. Time to clinical recovery was based on time between concussion and physician clearance to RTP. Two accelerated failure time models were used to estimate days to RTP clearance: model 1 considered symptom severity according to the SCAT3/SCAT5 symptom evaluation score (range, 0-132 points), and model 2 considered responses to individual symptom evaluation items (eg, headache, neck pain, dizziness) of none/mild (0-2 points) versus moderate/severe (3-6 points). Other covariates were time to physician first visit (≤7 and >7 days), age group (11-12, 13-14, and 15-17 years), sex, league type (body checking and no body checking), tandem stance (modified Balance Error Scoring System result ≥4 errors out of 10), and number of previous concussions (0, 1, 2, and ≥3). Results: The complete case analysis (including players without missing covariates) included 329 players (366 diagnosed concussions). The median time to clinical recovery was 18 days. In model 1, longer time to first physician visit (>7 days) (time ratio [TR], 1.637 [95% confidence interval (CI), 1.331-1.996]) and greater symptom severity (TR, 1.016 [95% CI, 1.012-1.020]) were significant predictors of longer clinical recovery. In model 2, longer time to first physician visit (TR, 1.698 [95% CI, 1.399-2.062]), headache (moderate/severe) (TR, 1.319 [95% CI, 1.110-1.568]), and poorer tandem stance (TR, 1.249 [95% CI, 1.052-1.484]) were significant predictors of longer clinical recovery. Conclusion: Medical clearance to RTP was longer for players with >7 days to physician assessment, poorer tandem stance, greater symptom severity, and moderate/severe headache at first visit.

Wait times in the management of non–small cell lung carcinoma before, during and after regionalization of lung cancer care: a high-resolution analysis

Background: Timeliness can have a substantial effect on treatment outcomes, prognosis and quality of life for patients with lung cancer. We sought to evaluate changes in wait times for patients with non–small cell lung carcinoma (NSCLC) and to identify bottlenecks in cancer care. Methods: We included patients who received treatment with curative intent or palliative treatment for NSCLC, diagnosed through mediastinal staging by a thoracic surgeon. Data were collected from 3 cohorts over 3 time periods: before the regionalization of lung cancer care (2005–2007, C1), immediately postregionalization (2011–2013, C2) and 5 years after regionalization (2016–2017, C3). Total wait time and delays along treatment pathways were compared across cohorts using multivariate Cox proportionality models. Results: Our total sample size was 299 patients. Overall, there was no significant difference in total wait time among the 3 cohorts. However, wait time from symptom onset to first physician visit significantly increased in C3 compared with C2 (hazard ratio [HR] 0.41, p < 0.01) and C1 (HR 0.43, p < 0.01). Time from first physician visit to computed tomography (CT) scan significantly decreased in C3 compared with C2 (HR 1.54, p < 0.01). Time from abnormal CT scan to first surgeon visit also significantly decreased in C2 (HR 1.43, p < 0.01) and C3 (HR 4.47, p < 0.01) compared with C1, and between C3 and C2 (HR 2.67, p < 0.01). In contrast, time from first surgeon visit to completion of staging significantly increased in C2 (HR 0.36, p < 0.01) and C3 (HR 0.24, p < 0.01) compared with C1, as well as between C3 and C2 (HR 0.60, p < 0.01). Time to first treatment after completion of staging was significantly shorter for C3 than C1 (HR 1.58, p < 0.01). Conclusion: Trends toward a reduction in wait time are evident 5 years after the regionalization of lung cancer care, primarily led by shorter wait times for CT scans and thoracic surgeon consults. However, wait times can further be reduced by addressing delays in staging completion and patient and provider education to identify the early signs of NSCLC.

Evaluation of Patient Flow and Waiting Time for the First Physician Visit in an Overcrowded Emergency Department

Background: The velocity of providing services in health centers is crucial to reduce mortality and adverse outcomes. Objectives: The present study aimed at determining the waiting time from entering the emergency department (ED) up to physician visiting based on congestion in the triple shift at Shahid Mohammadi Hospital in Bandar Abbas, Iran. Methods: The current cross-sectional, analytical study was conducted in 2019 on 1285 subjects selected from three shifts. The data collection tools included demographic data and standard triage forms, as well as a timetable with a stopwatch. The time between patient arrival and physician visit was recorded. SPSS software version 21 was employed to analyze the data. Results: The highest percentage of patients, 65.1% (n = 837), was non-traumatic, 38.98% (n = 501) referred during the evening shift, and 47.54% (n = 611) were related to the triage level 3. The maximum average waiting time from the beginning to the end of the triage was 4.46, and up to the physician, the visit was 12.8 minutes. Waiting time from entering ED up to physician first visit in terms of gender, refer to ED, and cause of referral statistically divulged a significant difference (P < 0.05). Estimation of the maximum congestion in the department was from 16:00 to 20:00, which showed a significant difference with other day times (P < 0.05). Conclusions: The average waiting time for patients was higher than the global standard. The interventions based on the maximum congestion in ED can be effective in reducing patient waiting time.