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Background and aim: During the early stages of the COVID-19 pandemic, nationwide lockdowns caused disruption in the diets, physical activities, and lifestyles of patients with type 2 diabetes. Previous reports on the possible association between race/ethnicity, COVID-19, and mortality have shown that Hispanic/Latino patients with type 2 diabetes who are socioeconomically disadvantaged are disproportionately affected by this novel virus. The aim of this study was to explore stressors associated with changes in diabetes self-management behaviors. Our goal was to highlight the health disparities in these vulnerable racial/ethnic minority communities and underscore the need for effective interventions. Methods and participants: Participants were enrolled in part of a larger randomized controlled trial to compare diabetes telehealth management (DTM) with comprehensive outpatient management (COM) in terms of critical patient-centered outcomes among Hispanic/Latino patients with type 2 diabetes. We conducted a thematic analysis using patient notes collected from two research nurses between March 2020 and March 2021. Two authors read through the transcripts independently to identify overarching themes. Once the themes had been identified, both authors convened to compare themes and ensure that similar themes were identified within the transcripts. Any discrepancies were discussed by the larger study team until a consensus was reached. Results: Six themes emerged, each of which can be categorized as either a source or an outcome of stress. Sources of stress associated with the COVID-19 pandemic were (1) fear of contracting COVID-19, (2) disruptions from lockdowns, and (3) financial stressors (e.g., loss of income). Outcomes of COVID-19 stressors were (1) reduced diabetes management (e.g., reduced diabetes monitoring and physical activity), (2) suboptimal mental health outcomes (e.g., anxiety and depression), and (3) outcomes of financial stressors. Conclusion: The findings indicated that underserved Hispanic/Latino patients with type 2 diabetes encountered a number of stressors that led to the deterioration of diabetes self-management behaviors during the pandemic.
ABSTRACT
Anti-Black racism is a specific form of racism directed at Black people. In healthcare, there are poignant examples of anti-Black racism in the recruitment, selection, and retention stages of the job cycle. Research shows that anti-Black racism is associated with inequitable work outcomes and the under-representation of Black physicians. However, empirical findings are scattered with no organizing framework to consolidate these findings. To add to the literature, in this paper we present the attraction-selection-attrition (ASA) model (Schneider, 1987) as an organizing framework to discuss Black physicians' experiences with anti-Black racism and discrimination throughout their careers. We draw from previous literature to highlight specific experiences of Black physicians at each stage of the job cycle (i.e., attraction, selection, retention), and we offer considerations on how practitioners can mitigate anti-Black racism throughout the job cycle. In the wake of COVID-19 and highly publicized social justice movements, healthcare systems are seeking ways to increase the recruitment, selection, and retention of Black physicians to ensure health equity. We believe this guide will be valuable to practitioners, leaders, researchers, and program directions seeking to advance diversity, equity, and inclusion of Black physicians in their healthcare systems. We conclude by providing practical implications and directions for future research.
ABSTRACT
Though these changes may have facilitated healthcare access for some, they can be detrimental to patients unfamiliar with utilizing technology, which may be reflected in missed visit rates. [...]we aimed to identify the trends and factors associated with missed visits. On multivariate analysis, missed visits were 1% less likely for every one-year increase in age;more prevalent with non-White race, Medicaid and other public insurance, unemployment, single status, tobacco and illicit drug use, and non-English/Spanish speakers;and less prevalent for those in the 2 highest quartiles of median income (Table 1). Patient Characteristics Associated with Missed Visits Factor Missed (N = 3768) Completed (N = 43262) P-value Adjusted Odds Ratio for Missed Visits (95% CI) P-value Age in Years (Mean ± SD) 52.9 ± 17.8 56.6 ± 17.5 < 0.001 0.99 (0.98 - 0.99) for every one-year increase in age < 0.001 Age ≥ 65 Years 1098 (29.1%) 16260 (37.6%) < 0.001 Sex 0.46 Male 1456 (38.6%) 16459 (38%) Female 2312 (61.4%) 26804 (62%) Race < 0.001 White 2471 (65.7%) 33423 (77.3%) Reference Black 808 (21.5%) 5993 (13.9%) 1.42 (1.29 - 1.57) < 0.001 Hispanic 216 (5.7%) 1577 (3.6%) 1.34 (1.13 - 1.57) < 0.001 Others 268 (7.1%) 2220 (5.1%) 1.44 (1.25 - 1.66) < 0.001 Type of Insurance < 0.001 Private 1955 (53.3%) 26461 (62.4%) Reference Medicare 693 (18.9%) 8981 (21.2%) 1.05 (0.95 - 1.16) 0.29 Medicaid and other public 984 (26.8%) 6433 (15.2%) 1.35 (1.23 - 1.48) < 0.001 No insurance 35 (1%) 504 (1.2%) 1.04 (0.73 - 1.47) 0.81 Median Household Income by Zip Code (by quartile) < 0.001 Lowest 1304 (34.6%) 10321 (23.9%) Reference Second 1093 (29%) 10698 (24.7%) 1.02 (0.92 - 1.12) 0.64 Third 664 (17.6%) 11182 (25.8%) 0.64 (0.58 - 0.72) < 0.001 Highest 707 (18.8%) 11059 (25.6%) 0.71 (0.63 - 0.71) < 0.001 Employment Status < 0.001 Employed 1234 (23.8%) 16868 (39%) Reference Unemployed 1959 (52%) 16783 (38.8%) 1.45 (1.33 - 1.58) < 0.001 Retired 488 (13%) 8709 (20.2%) 0.99 (0.88 - 1.13) 0.99 Unknown 84 (2.2%) 852 (2%) 0.98 (0.73 - 1.30) 0.88 Marital Status < 0.001 Married 1565 (41.5%) 21463 (49.6%) Reference Single 2153 (57.1%) 21206 (49%) 1.09 (1.10 - 1.17) 0.023 Others 50 (1.3%) 593 (1.4%) 0.94 (0.68 - 1.29) 0.71 H/o Tobacco Use 756 (20.4%) 5903 (13.8%) < 0.001 1.23 (1.12 - 1.35) < 0.001 H/o Alcohol Use 1555 (43.2%) 18694 (45%) 0.074 H/o Illicit Drug Use 352 (9.7%) 2657 (6.4%) < 0.001 1.14 (1.01 - 1.29) 0.03 Primary Language < 0.001 English 3639 (96.6%) 42355 (97.9%) Reference Spanish 64 (1.7%) 413 (1%) 1.20 (0.89 - 1.63) 0.21 Other 64 (1.7%) 495 (1.1%) 1.37 (1.03 - 1.82) 0.028
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Patients with private insurance, the highest quartile of median household income, and education had increasing rates of colonoscopy (p< 0.001) in 2020 and 2021. The number of polyps and adenomas detected on screening colonoscopy has significantly increased in the post-pandemic lockdown period but that did not translate into excess advanced adenoma detection or CRC rates. Demographics, socioeconomic and clinical factors in each year’s study period Factor 2019 (N=7905) 2020 (N=6737) 2021 (N=8674) p-value Age (mean ± sd) 59.8 ± 8.6 59.6 ± 8.9 58.9 ± 9.3 < 0.001 Age >=65 2275 (28.8%) 1871 (27.8%) 2472 (28.5%) 0.38 Sex 0.97 Male 3648 (46.1%) 3107 (46.1%) 4014 (46.3%) Female 4257 (53.9%) 3630 (53.9%) 4660 (53.7%) Race < 0.001 Caucasians 6004 (76%) 4999 (74.2%) 6672 (76.9%) African Americans 1303 (16.5%) 1271 (18.9%) 1381 (15.9%) Others 598 (7.6%) 467 (6.9%) 621 (7.2%) Insurance type < 0.001 Medicare 1965 (24.9%) 1619 (24%) 1868 (21.5%) Medicaid and other public 435 (5.5%) 491 (7.3%) 541 (6.2%) Private 4662 (59%) 4061 (60.3%) 5641 (65%) No insurance 843 (10.7%) 566 (8.4%) 624 (7.2%) Education level (% high school grads in zip code) < 0.001 Q1< 88 1905 (22.8%) 1557 (24.1%) 1768 (21.3%) Q2 >=88 to < 92.5 1815 (24.3%) 1503 (23.3%) 1923 (23.1%) Q3 >= 92.5 to < 94 1714 (22.9%) 1549 (22.6%) 1942 (23.3%) Q4 >= 94 2237 (29.9%) 1935 (30%) 2686 (32.3%) Median household income < 0.001 Q1 < 43449 1647 (22%) 1544 (23.9%) 1715 (20.6%) Q2 >=43449 to < 55969 1837 (24.6%) 1532 (23.7%) 1964 (23.6%) Q3 >= 55969 to < 67917 1889 (25.3%) 1569 (24.3%) 2154 (25.9%) Q4 >= 67917 2098 (28.1%) 1809 (28%) 2486 (29.9%) Tobacco Use 699 (8.8%) 636 (9.4%) 827 (9.5%) 0.13 Alcohol use 5033 (63.7%) 4310 (64%) 5747 (66.3%) 0.001 Illicit drug use 259 (3.3%) 245 (3.6%) 326 (3.8%) 0.22 Preferred language 0.5 English 7732 (97.8%) 6613 (98.2%) 8489 (97.9%) Spanish 83(1%) 60 (0.9%) 81 (0.9%) Others 90 (1.1%) 64 (0.9%) 104 (1.2%) BMI 29.6 ± 6.4 29.8 ± 6.5 29.7 ± 6.5 0.52 Number of polyps < 0.001 0 4483 (56.7%) 3770 (56%) 4643 (53.5%) 1 2456 (31.1%) 2049 (30.4%) 2721 (31.4%) >=2 966 (12.2%) 918 (13.6%) 1310 (15.1%) Adenoma 1697 (21.5%) 1503 (22.3%) 2059 (23.7%) 0.002 Advanced Adenoma 361 (4.6%) 324 (4.8%) 382 (4.4%) 0.48 Cancer 12 (0.2%) 12 (0.2%) 9 (0.1%) 0.45
ABSTRACT
On multivariate analysis, age >65, male gender, Caucasian race, tobacco use, private insurance, and obesity were positive predictors of adenomas (p< 0.05 for all) (Table). Demographic, socioeconomic factors associated with adenoma detection on screening colonoscopy No Adenoma (N=18057) Adenoma (N=5259) p-value Adjusted OR (95% CI) p-value Age (mean ± sd) 59.1 ± 8.9 60.6 ± 9.0 < 0.001 NA Age >=65 4877 (27%) 1741 (33.1%) < 0.001 1.7 (1.6 - 1.7) < 0.001 Sex Male =1 7873 (43.6%) 2896 (55.1%) < 0.001 REF Female 10184 (56.4%) 2363 (44.9%) 0.65 (0.62 - 0.67) < 0.001 Race 0.003 Caucasians 13621 (75.4%) 4054 (77.1%) REF African Americans 3145 (17.4%) 810 (15.4%) 0.9 (0.85 - 0.96) 0.001 Others 1291 (7.1%) 395 (7.5%) 0.97 (0.89 - 1.05) 0.54 Insurance type < 0.001 Medicare 4033 (22.3%) 1419 (27%) 1.04 (0.98 - 1.09) 0.15 Medicaid and other public 1111 (6.2%) 356 (6.8%) 0.87 (0.8 - 0.94) 0.001 Private 11297 (62.6%) 3067 (58.3%) REF No insurance 1616 (8.9%) 417 (7.9%) 0.76 (0.71 - 0.82) < 0.001 Education level (% high school grads in zip code) 0.008 Q1< 88 3887 (22.6%) 1143 (22.7%) REF Q2 >=88 to < 92.5 3973 (23.1%) 1268 (25.1%) 1.01. (0.94 - 1.08) 0.79 Q3 >= 92.5 to < 94 3962 (23%) 1153 (22.9%) 0.99 (0.91 - 1.08) 0.82 Q4 >= 94 5380 (31.3%) 1478 (29.3%) 0.99 (0.9 - 1.09) 0.87 Median household income (Quartiles based on Zip code) 0.005 Q1 < 43449 3759 (21.9%) 1147 (22.7%) REF Q2 >=43449 to < 55969 4113 (23.9%) 1220 (24.2%) 0.96 (0.0.90-1.03) 0.37 Q3 >= 55969 to < 67917 4288 (24.9%) 1324 (26.3%) 1.08 (0.98 - 1.18) 0.09 Q4 >= 67917 5042 (29.3%) 1351 (26.8%) 1.0 (0.9 - 1.1) 0.99 Tobacco Use 1549 (8.6%) 613 (11.7%) < 0.001 1.41 (1.32 - 1.51) < 0.001 Alcohol use 11686 (64.7%) 3404 (64.7%) 0.99 NA Illicit drug use 622 (3.4%) 208 (4%) 0.079 NA Preferred language 0.3 NA English 17690 (98%) 5144 (97.8%) Spanish 176 (1%) 48 (0.9%) Others 191 (1.1%) 67 (1.3%) BMI 29.5 ± 6.5 30.3 ± 6.5 < 0.001 Obesity 7200 (40.3%) 2333 (44.8%) < 0.001 1.28 (1.23-1.33) < 0.001
ABSTRACT
Socioeconomic disparities adversely affected healthcare use during COVID-19 lockdown. However, trends in these disparities post lockdown are unknown. Therefore, our aim was to study temporal trends and factors associated with gastroenterology healthcare access and disparities during and after COVID-19 lockdown. This cohort study consisted of patients receiving outpatient care in the Cleveland Clinic gastroenterology department between March 2020 and June 2020 and corresponding time periods in 2019 and 2021. Patient demographics and socioeconomic factors were extracted and analyzed. There were 47,031 patients (mean age 56.3±17.6 years, 61.9% female and 76.4% white) included. Patients ≥65 years sought healthcare less frequently during and after the lockdown (40.1% vs 34.8% vs 35.2% in 2019, 2020, and 2021 respectively). Missed visits (4.2% vs 10% vs 10.4%), tobacco (11.4% vs 15.9% vs 16.1%), alcohol (38.6% vs 45.5% vs 50.9%), and illicit drug use (3.5% vs 5.8% vs 10.7%) have steadily increased during and after the lockdown compared with prepandemic levels. Factors associated with reduced telehealth use were black race (OR 0.89, 95% CI 0.81 to 0.99), Hispanic race (OR 0.63, 95% CI 0.51 to 0.77)), Medicaid/other public insurance (OR 0.87, 95% CI 0.79 to 0.95)), unemployed status (OR 0.85, 95% CI 0.79 to 0.92)), and non-English/Spanish speakers (OR 0.66, 95% CI 0.46 to 0.94)). In conclusion, socioeconomic and ethnic disparities persist in healthcare use even a year after the onset of the COVID-19 pandemic. There is an alarming increase in missed visits and substance abuse. Therefore, efforts should be targeted on improving healthcare access for these aforementioned vulnerable groups.
Subject(s)
COVID-19 , Gastroenterology , United States/epidemiology , Humans , Female , Adult , Middle Aged , Aged , Male , COVID-19/epidemiology , Pandemics , Cohort Studies , Communicable Disease Control , Healthcare DisparitiesABSTRACT
[...]developing and testing interventions takes time and requires substantial collaboration among organizations, researchers, and other key stakeholders (Bush et al., 2017). [...]for side effects of interventions to be recognized and reduced, there must be a comprehensive understanding of both the various factors that contribute to and create these side effects or adverse events, as well as the various factors that can contribute to an operative, multilevel response. Unlike traditional research processes, OBPR offers marginalized individuals a seat at the table, which is imperative especially in light of the recent social justice movements. Because the organization now has an invested and equitable role in the development of the intervention as well as the research process, funding will be sourced collaboratively from both the organization and researcher. [...]interventions can be tested and retested beyond a single project time frame, allowing for more flexibility to examine side effects and address them, making the research process cyclical and iterative (Collins et al., 2018).
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Telehealth has emerged as an evolving care management strategy that is playing an increasingly vital role, particularly with the onset of the coronavirus disease 2019 pandemic. A meta-analysis of 20 randomized controlled trials was conducted to test the effectiveness of home telemonitoring (HTM) in patients with type 2 diabetes in reducing A1C, blood pressure, and BMI over a median 180-day study duration. HTM was associated with a significant reduction in A1C by 0.42% (P = 0.0084). Although we found statistically significant changes in both systolic and diastolic blood pressure (-0.10 mmHg [P = 0.0041] and -0.07 mmHg [P = 0.044], respectively), we regard this as clinically nonsignificant in the context of HTM. Comparisons across different methods of transmitting vital signs suggest that patients logging into systems with moderate interaction with the technology platform had significantly higher reductions in A1C than those using fully automatic transmission methods or fully manual uploading methods. A1C did not vary significantly by study duration (from 84 days to 5 years). HTM has the potential to provide patients and their providers with timely, up-to-date information while simultaneously improving A1C.
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As communities of color are disproportionately affected by COVID-19, there is an urgent need for dissemination of timely and accurate information to community members. In this article, we describe a stakeholder approach for the implementation, evaluation, and lessons learned from COVID-19 Conversations, a program developed and delivered virtually by researchers and academics at Northwell Health. The goal of the program was to address the mental, physical, and psychosocial needs of community members. The program used Zoom/Facebook Live to deliver interactive discussions on topics ranging from health education on COVID-19 and mental health to resources for unmet social needs. This interprofessional, cross-sector collaboration highlights the importance of public health interventions aimed at reducing the spread of COVID-19 through easy online access and culturally relevant community education and outreach.