COVID-19 Among American Indian and Alaska Native Persons - 23 States, January 31-July 3, 2020.

Although non-Hispanic American Indian and Alaska Native (AI/AN) persons account for 0.7% of the U.S. population,* a recent analysis reported that 1.3% of coronavirus disease 2019 (COVID-19) cases reported to CDC with known race and ethnicity were among AI/AN persons (1). To assess the impact of COVID-19 among the AI/AN population, reports of laboratory-confirmed COVID-19 cases during January 22†-July 3, 2020 were analyzed. The analysis was limited to 23 states§ with >70% complete race/ethnicity information and five or more laboratory-confirmed COVID-19 cases among both AI/AN persons (alone or in combination with other races and ethnicities) and non-Hispanic white (white) persons. Among 424,899 COVID-19 cases reported by these states, 340,059 (80%) had complete race/ethnicity information; among these 340,059 cases, 9,072 (2.7%) occurred among AI/AN persons, and 138,960 (40.9%) among white persons. Among 340,059 cases with complete patient race/ethnicity data, the cumulative incidence among AI/AN persons in these 23 states was 594 per 100,000 AI/AN population (95% confidence interval [CI] = 203-1,740), compared with 169 per 100,000 white population (95% CI = 137-209) (rate ratio [RR] = 3.5; 95% CI = 1.2-10.1). AI/AN persons with COVID-19 were younger (median age = 40 years; interquartile range [IQR] = 26-56 years) than were white persons (median age = 51 years; IQR = 32-67 years). More complete case report data and timely, culturally responsive, and evidence-based public health efforts that leverage the strengths of AI/AN communities are needed to decrease COVID-19 transmission and improve patient outcomes.

The Association Between Resiliency Factors and Suicide Indicators Among American Indian/Alaska Native Middle School Students in New Mexico: A Strength-Based Analysis.

OBJECTIVE: Suicide is a leading cause of death among American Indian/Alaska Native (AI/AN) young people aged 10-19 years in the United States, but data collection and reporting in this population are lacking. We examined results of an oversample project in New Mexico to determine the association between resiliency factors and suicide-related behaviors among AI/AN middle school students. METHODS: We conducted analyses using data from the 2019 New Mexico Youth Risk and Resiliency Survey for students in grades 6 through 8. An oversampling method was used to increase the sample size of AI/AN students. We used logistic regression to determine the association between resiliency factors and suicide indicators among AI/AN students, stratified by sex. RESULTS: Among female AI/AN students, community support had the strongest protective effect against having seriously thought about suicide (adjusted odds ratio [aOR] = 0.23; 95% CI, 0.14-0.38), while family support was significantly associated with the lowest odds of having made a suicide plan (aOR = 0.15; 95% CI, 0.08-0.28) and having attempted suicide (aOR = 0.21; 95% CI, 0.13-0.34) (P < .001 for all). Among male AI/AN students, school support had the strongest protective effect against all 3 outcomes: seriously thought about suicide (aOR = 0.34; 95% CI, 0.19-0.62; P < .001), having made a suicide plan (aOR = 0.19; 95% CI, 0.09-0.39; P < .001), and having attempted suicide (aOR = 0.27; 95% CI, 0.12-0.65; P = .003). CONCLUSIONS: Oversampling AI/AN young people can help accurately quantify and understand health risk behaviors and strengths of this population, leading to improved health and wellness. Family, community, and school-based support should be considered in interventions geared toward suicide prevention among AI/AN young people.

Predictors and Barriers to Faculty Scholarly Activity in United States Urology Residency Programs.

OBJECTIVE: To determine factors and barriers associated with scholarly activity among faculty members at urology residency programs in the United States. METHODS: An online survey was sent to all 134 urology residency program directors. The survey assessed program characteristics including size, location and definition of scholarly activity. It assessed available support for and barriers to resident scholarly activity, faculty participation in scholarly activity and mentorship of residents. Linear regression analysis was used. RESULTS: We had a 40% response rate (N = 40). Faculty attitudes toward conducting scholarly activity (P < .001) and lack of a research curriculum (P = .05) were barriers to the outcome 'participation in scholarly activity'. Faculty attitudes toward conducting scholarly activity was also a barrier to the outcomes 'mentorship of residents' (P = .004) and 'publication of at least 1 paper' (P = .004). Available statistician was positively associated with the outcomes 'publications' (P = .062) and 'presentations' (P = .032). A minimum requirement of a local presentation (P=0.04) and chairman support (P = .015) were positively associated with the outcome 'presentation at a conference.' CONCLUSION: Training residents in research matters for the resident, the institution and future generations of surgeon scientists. Higher levels of faculty scholarly activity were associated with a minimum requirement for residents to submit a manuscript for publication, strong chairman support for resident research, and the availability of a statistician. A common barrier to faculty scholarly activity, publications, and resident mentorship was faculty attitudes toward resident scholarly activity. Urology residency programs seeking to prioritize scholarly activity among faculty should consider these factors.

Association of Electronic Health Record Design and Use Factors With Clinician Stress and Burnout.

Importance: Many believe a major cause of the epidemic of clinician burnout is poorly designed electronic health records (EHRs). Objectives: To determine which EHR design and use factors are associated with clinician stress and burnout and to identify other sources that contribute to this problem. Design, Setting, and Participants: This survey study of 282 ambulatory primary care and subspecialty clinicians from 3 institutions measured stress and burnout, opinions on EHR design and use factors, and helpful coping strategies. Linear and logistic regressions were used to estimate associations of work conditions with stress on a continuous scale and burnout as a binary outcome from an ordered categorical scale. The survey was conducted between August 2016 and July 2017, with data analyzed from January 2019 to May 2019. Main Outcomes and Measures: Clinician stress and burnout as measured with validated questions, the EHR design and use factors identified by clinicians as most associated with stress and burnout, and measures of clinician working conditions. Results: Of 640 clinicians, 282 (44.1%) responded. Of these, 241 (85.5%) were physicians, 160 (56.7%) were women, and 193 (68.4%) worked in primary care. The most prevalent concerns about EHR design and use were excessive data entry requirements (245 [86.9%]), long cut-and-pasted notes (212 [75.2%]), inaccessibility of information from multiple institutions (206 [73.1%]), notes geared toward billing (206 [73.1%]), interference with work-life balance (178 [63.1%]), and problems with posture (144 [51.1%]) and pain (134 [47.5%]) attributed to the use of EHRs. Overall, EHR design and use factors accounted for 12.5% of variance in measures of stress and 6.8% of variance in measures of burnout. Work conditions, including EHR use and design factors, accounted for 58.1% of variance in stress; key work conditions were office atmospheres (ß̂ = 1.26; P < .001), control of workload (for optimal control: ß̂ = -7.86; P < .001), and physical symptoms attributed to EHR use (ß̂ = 1.29; P < .001). Work conditions accounted for 36.2% of variance in burnout, where challenges included chaos (adjusted odds ratio, 1.39; 95% CI, 1.10-1.75; P = .006) and physical symptoms perceived to be from EHR use (adjusted odds ratio, 2.01; 95% CI, 1.48-2.74; P < .001). Coping strategies were associated with only 2.4% of the variability in stress and 1.7% of the variability in burnout. Conclusions and Relevance: Although EHR design and use factors are associated with clinician stress and burnout, other challenges, such as chaotic clinic atmospheres and workload control, explain considerably more of the variance in these adverse clinician outcomes.