COVID 19 Hotspots And Vulnerable Populations Identified By Area Deprivation Index Mapping

The authors used the Area Deprivation Index (ADI) to create an online tool for physicians and target outreach efforts to patients with greatest needs. COVID 19 pandemic is an opportunity for innovation to bridge the digital divide and the ADI is the first step in identifying patients most in need of practice supports.https://deepblue.lib.umich.edu/bitstream/2027.42/155341/1/Niharika2_COVID 19 hotspots and vulnerable populations-05062020.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155341/3/Figure 1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155341/4/Figure 2.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/155341/5/Figure 3.pdfDescription of Niharika2_COVID 19 hotspots and vulnerable populations-05062020.pdf : Main ArticleDescription of Figure 1.pdf : Figure 1Description of Figure 2.pdf : Figure 2Description of Figure 3.pdf : Figure

Community Awareness of HPV Screening and Vaccination in Odisha

Introduction. A number of new technologies including cervical cancer screening and vaccination have introduced new tools in the fight against cervical cancer. Methods. This study was set in Odisha, India, at the Acharya Harihar Regional Cancer Center and study research infrastructure at the Asian Institute of Public Health. IRB approvals were obtained and a research assistant recruited 286 women aged 18–49 years, who provided informed consent and completed a survey tool. Data were entered into EpiData software and statistical analysis was conducted. Results. 76.3% women participants were married, 45.5% had sexual debut at age 21 or greater, 60.5% used contraception, 12.2% reported having a Pap smear in the past, and 4.9% reported having prior genital warts. Most, 68.8% had never heard of HPV and 11.9% were aware that HPV is the main cause of cervical cancer. 82.9% women thought that vaccinations prevent disease, and 74.8% said they make the decision to vaccinate their children. Conclusion. The Odisha community demonstrated a low level of knowledge about cervical cancer prevention, accepted vaccinations in the prevention of disease and screening, and identified mothers/guardians as the key family contacts

Evaluation of PCMH Model Adoption on Teamwork and Impact on Patient Access and Safety

Purpose: Each of the participating patient-centered medical home (PCMH) received coaching and participated in learning collaborative for improving teamwork. The objective of the study was to assess the impact of trainings on patient-centered teamwork. Methods: The Teamwork Perception Questionnaire (TPQ) was administered once in spring 2014 and then in fall 2015. The TPQ consists of 35 questions across 5 domains: mutual support, situation monitoring, communication, team structure, and leadership. Based on our objective we compared the frequencies of strongly agree/agree by domain. The difference was tested using chi-square test. We compared the scores on each domain (strongly agree/agree = 1; maximum score = 7) via Wilcoxon rank sum test. Results: The response rate for this survey was n = 29 (80.6%) in spring 2014, and n = 31 (86.1%) in fall 2015. We found that the practice members significantly ( P < .05) strongly agreed/agreed more in fall 2015 than spring 2014 for characteristics—“staff relay relevant information in a timely manner” (64.5% vs 83.9%) and “staff follow a standardized method of sharing information when handing off patients” (67.7% vs 90.3%) under communication domain and for characteristic—“staff within my practice share information that enables timely decision making” (74.2% vs 90.3%). However, there was no statistical significant difference observed in the scores for the overall TPQ at the 2 time points. Conclusion: Despite the statistical insignificance, the observations in PCMHs across the spectrum of practices participating in the Maryland Multi-Payer Program demonstrated enhanced teamwork specifically in communication and in leadership. This we believe will continue to result in enhanced patient access to care and safety

Relations of Current and Past Cancer with Severe Outcomes among 104,590 Hospitalized COVID-19 Patients: The COVID EHR Cohort at the University of Wisconsin

BackgroundThere is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics.MethodsElectronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined.Results6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46-1.70] and 1.04 (95% CI, 0.96-1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53-0.90).ConclusionsCurrent cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types.ImpactThis study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3

Smoking Status, Nicotine Medication, Vaccination, and COVID-19 Hospital Outcomes: Findings from the COVID EHR Cohort at the University of Wisconsin (CEC-UW) Study.

IntroductionAvailable evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown.MethodsElectronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission.ResultsCurrent (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06-1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04-1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50-0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16-0.66) and former smokers (aOR, 0.47; 95% CI, 0.39-0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66-0.83) than never smokers (aOR, 0.87; 95% CI, 0.79-0.97).ConclusionsFormer but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers.ImplicationsPrior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects

Observed in–hospital mortality rates (Deaths/hospitalizations) and number of patients hospitalized per month for patient ethnicity subpopulations (March 2020 through September 2021).

Observed in–hospital mortality rates (Deaths/hospitalizations) and number of patients hospitalized per month for patient ethnicity subpopulations (March 2020 through September 2021).</p

Observed in–hospital mortality rates (Deaths/hospitalizations) and number of patients hospitalized per month for patient insurance status groups (March 2020 through September 2021).

Observed in–hospital mortality rates (Deaths/hospitalizations) and number of patients hospitalized per month for patient insurance status groups (March 2020 through September 2021).</p