Out-of-pocket prescription drug costs for adults with cardiovascular risk factors under Amazon's direct-to-consumer pharmacy service.

BACKGROUND: US adults often overpay for generic prescription medications, which can lead to medication nonadherence that negatively impacts cardiovascular outcomes. As a result, new direct-to-consumer online medication services are growing in popularity nationwide. Amazon recently launched a $5/month direct-to-consumer medication subscription service (Amazon RxPass), but it is unclear how many US adults could save on out-of-pocket drug costs by using this new service. OBJECTIVES: To estimate out-of-pocket savings on generic prescription medications achievable through Amazon's new direct-to-consumer subscription medication service for adults with cardiovascular risk factors and/or conditions. METHODS: Cross-sectional study of adults 18-64 years in the 2019 Medical Expenditure Panel Survey. RESULTS: Of the 25,280,517 (SE ± 934,809) adults aged 18-64 years with cardiovascular risk factors or conditions who were prescribed at least 1 medication available in the Amazon RxPass formulary, only 6.4% (1,624,587 [SE ± 68,571]) would achieve savings. Among those achieving savings, the estimated average out-of-pocket savings would be $140 (SE ± $15.8) per person per year, amounting to a total savings of $228,093,570 (SE ± $26,117,241). In multivariable regression models, lack of insurance coverage (adjusted odds ratio [OR] 3.5, 95%CI 1.9-6.5) and being prescribed a greater number of RxPass-eligible medications (2-3 medications versus 1 medication: OR 5.6, 95%CI 3.0-10.3; 4+ medications: OR 21.8, 95%CI 10.7-44.3) were each associated with a higher likelihood of achieving out-of-pocket savings from RxPass. CONCLUSIONS: Changes to the pricing structure of Amazon's direct-to-consumer medication service are needed to expand out-of-pocket savings on generic medications to a larger segment of the working-age adults with cardiovascular risk factors and/or diseases.

Cardiovascular Health, Lifestyle Factors, and Social Determinants in Asian Subpopulations in the United States.

Asian Americans are often aggregated in national public health surveillance efforts, which may conceal important differences in the health status of subgroups that are included in this highly diverse population. Little is known about how cardiovascular health varies across Asian subpopulations and the extent to which lifestyle and social risk factors contribute to any observed differences. This national study used data from the National Health Interview Survey to evaluate the burden of cardiovascular risk factors (hypertension, hyperlipidemia, diabetes mellitus) and cardiovascular diseases (heart attack, coronary heart disease, angina, stroke) across Asian groups (Chinese, Asian Indian, Filipino, Other Asian), and determine whether differences are related to lifestyle factors and/or social determinants of health. The weighted study population included 13,592,178 Asian adults. Filipino adults were more likely to have hypertension than Chinese adults (29.4% vs 15.4%; adjusted odds ratio [OR] 2.40, 95% confidence interval [1.91 to 3.02]), as were Asian Indians (15.7%; OR 1.59 [1.25 to 2.02]). These patterns were similar for hyperlipidemia and diabetes mellitus. For cardiovascular diseases, Filipino adults were significantly more likely to have coronary heart disease (4.2% vs 1.9%; OR 2.19 [1.32 to 3.56]), heart attack (2.6% vs 0.9%; OR 2.79 [1.44 to 5.41]), angina (1.8% vs 0.9%; OR 2.15 [1.06 to 4.32]), and stroke (2.1% vs 0.8%; OR 2.54 [1.42 to 4.55]) compared with Chinese adults, whereas there were no differences compared with Asian Indian adults. Adjustments for lifestyle factors and social determinants completely attenuated differences in coronary heart disease, heart attack, and angina among subpopulations. In conclusion, these findings demonstrate that cardiovascular risk factors and diseases vary significantly across Asian subpopulations, with Filipino adults experiencing the highest burden and Chinese adults the lowest, and that differences in cardiovascular disease are largely attenuated after adjustment for lifestyle and social determinants.

Changes in Health Care Access and Preventive Health Screenings by Race and Ethnicity.

Importance: The COVID-19 pandemic led to unprecedented disruptions in health care. Little is known about whether health care access and preventive health screenings among US adults have recovered to prepandemic levels, and how patterns varied by race and ethnicity. Objective: To evaluate health care access and preventive health screenings among eligible US adults in 2021 and 2022 compared with prepandemic year 2019, overall and by race and ethnicity. Design, Setting, and Participants: This cross-sectional study used data from US adults aged 18 years or older who participated in the National Health Interview Survey in 2021 and 2022. Survey weights provided by the National Health Interview Survey were used to generate nationally representative estimates. Data were analyzed from May 23 to November 13, 2023. Main Outcomes and Measures: Measures of health care access included the proportion of adults with a usual place for care, those with a wellness visit, and those who delayed or did not receive medical care due to cost within the past year. Preventive health screening measures included eligible adults who received blood pressure, cholesterol, or blood glucose screening within the past year (2021), as well as colorectal, cervical, breast, and prostate cancer screenings based on US Preventive Services Task Force guidelines. Results: The unweighted study population included 89 130 US adults. The weighted population included 51.6% females; 16.8% Hispanic, 5.9% non-Hispanic Asian (hereafter, Asian), 11.8% non-Hispanic Black (hereafter, Black), 62.8% non-Hispanic White (hereafter, White) individuals; and 2.9% individuals of other races and ethnicities (including American Indian, Alaska Native, Native Hawaiian or other Pacific Islander, or multiracial). After adjusting for age and sex, having a usual place for health care did not differ among adults in 2021 or 2022 vs 2019 (adjusted rate ratio [ARR] for each year, 1.00; 95% CI, 0.99-1.01). However, fewer participants had wellness visits in 2022 compared with 2019 (ARR, 0.98; 95% CI, 0.97-0.99), with the most pronounced decline among Asian adults (ARR, 0.95; 95% CI, 0.92-0.98). In addition, adults were less likely to delay medical care (ARR, 0.79; 95% CI, 0.73-0.87) or to not receive care (ARR, 0.76; 95% CI, 0.69-0.83) due to cost in 2022 vs 2019. Preventive health screenings in 2021 remained below 2019 levels (blood pressure: ARR, 0.95 [95% CI, 0.94-0.96]; blood glucose: ARR, 0.95 [95% CI, 0.93-0.96]; and cholesterol: ARR, 0.93 [95% CI, 0.92-0.94]). Eligible adults were also significantly less likely to receive colorectal cancer screening (ARR, 0.88; 95% CI, 0.81-0.94), cervical cancer screening (ARR, 0.86; 95% CI, 0.83-0.89), breast cancer screening (ARR, 0.93; 95% CI, 0.90-0.97), and prostate cancer screening (ARR, 0.86 [0.78-0.94]) in 2021 vs 2019. Asian adults experienced the largest relative decreases across most preventive screenings, while Black and Hispanic adults experienced large declines in colorectal cancer screening (ARR, 0.78; 95% CI, 0.67-0.91) and breast cancer screening (ARR, 0.83; 95% CI, 0.75-0.91), respectively. Differences in preventive screening rates across years persisted after additional adjustment for socioeconomic factors (income, employment status, and insurance coverage). Conclusions and Relevance: Results of this cohort study suggest that, in the US, wellness visits and preventive health screenings have not returned to prepandemic levels. These findings support the need for public health efforts to increase the use of preventive health screenings among eligible US adults.

Cardiovascular hospitalizations and mortality among adults aged 25-64 years in the USA.

BACKGROUND AND AIMS: Declines in cardiovascular mortality have stagnated in the USA since 2011. There is growing concern that these patterns reflect worsening cardiovascular health in younger adults. However, little is known about how the burden of acute cardiovascular hospitalizations and mortality has changed in this population. Changes in cardiovascular hospitalizations and mortality among adults aged 25-64 years were evaluated, overall and by community-level income. METHODS: Using the National Inpatient Sample, age-standardized annual hospitalization and in-hospital mortality rates for acute myocardial infarction (AMI), heart failure, and ischaemic stroke were determined among adults aged 25-64 years. Quasi-Poisson and quasi-binominal regression models were fitted to compare outcomes between individuals residing in low- and higher-income communities. RESULTS: Between 2008 and 2019, age-standardized hospitalization rates for AMI increased among younger adults from 155.0 (95% confidence interval: 154.6, 155.4) per 100 000 to 160.7 (160.3, 161.1) per 100 000 (absolute change +5.7 [5.0, 6.3], P < .001). Heart failure hospitalizations also increased (165.3 [164.8, 165.7] to 225.3 [224.8, 225.8], absolute change +60.0 (59.3, 60.6), P < .001), as ischaemic stroke hospitalizations (76.3 [76.1, 76.7] to 108.1 [107.8, 108.5], absolute change +31.7 (31.2, 32.2), P < .001). Across all conditions, hospitalizations rates were significantly higher among younger adults residing in low-income compared with higher-income communities, and disparities did not narrow between groups. In-hospital mortality decreased for all conditions over the study period. CONCLUSIONS: There was an alarming increase in cardiovascular hospitalizations among younger adults in the USA from 2008 to 2019, and disparities between those residing in low- and higher-income communities did not narrow.

Neighborhood Environmental Burden and Cardiovascular Health in the US.

Importance: Cardiovascular disease is the leading cause of death in the US. However, little is known about the association between cumulative environmental burden and cardiovascular health across US neighborhoods. Objective: To evaluate the association of neighborhood-level environmental burden with prevalence of cardiovascular risk factors and diseases, overall and by levels of social vulnerability. Design, Settings, and Participants: This was a national cross-sectional study of 71 659 US Census tracts. Environmental burden (EBI) and social vulnerability indices from the US Centers for Disease Control and Prevention (CDC) and Agency for Toxic Substances and Disease Registry were linked to the 2020 CDC PLACES data set. Data were analyzed from March to October 2023. Exposures: The EBI, a measure of cumulative environmental burden encompassing 5 domains (air pollution, hazardous or toxic sites, built environment, transportation infrastructure, and water pollution). Main Outcomes and Measures: Neighborhood-level prevalence of cardiovascular risk factors (hypertension, diabetes, and obesity) and cardiovascular diseases (coronary heart disease and stroke). Results: Across the US, neighborhoods with the highest environmental burden (top EBI quartile) were more likely than those with the lowest environmental burden (bottom EBI quartile) to be urban (16 626 [92.7%] vs 13 414 [75.4%]), in the Midwest (5191 [28.9%] vs 2782 [15.6%]), have greater median (IQR) social vulnerability scores (0.64 [0.36-0.85] vs 0.42 [0.20-0.65]), and have higher proportions of adults in racial or ethnic minority groups (median [IQR], 34% [12-73] vs 12% [5-30]). After adjustment, neighborhoods with the highest environmental burden had significantly higher rates of cardiovascular risk factors than those with the lowest burden, including hypertension (mean [SD], 32.83% [7.99] vs 32.14% [6.99]; adjusted difference, 0.84%; 95% CI, 0.71-0.98), diabetes (mean [SD], 12.19% [4.33] vs 10.68% [3.27]; adjusted difference, 0.62%; 95% CI, 0.53-0.70), and obesity (mean [SD], 33.57% [7.62] vs 30.86% [6.15]; adjusted difference, 0.77%; 95% CI, 0.60-0.94). Similarly, neighborhoods with the highest environmental burden had significantly higher rates of coronary heart disease (mean [SD], 6.66% [2.15] vs 6.82% [2.41]; adjusted difference, 0.28%; 95% CI, 0.22-0.33) and stroke (mean [SD], 3.65% [1.47] vs 3.31% [1.12]; adjusted difference, 0.19%; 95% CI, 0.15-0.22). Results were consistent after matching highest and lowest environmentally burdened neighborhoods geospatially and based on other covariates. The associations between environmental burden quartiles and cardiovascular risk factors and diseases were most pronounced among socially vulnerable neighborhoods. Conclusions and Relevance: In this cross-sectional study of US neighborhoods, cumulative environmental burden was associated with higher rates of cardiovascular risk factors and diseases, although absolute differences were small. The strongest associations were observed in socially vulnerable neighborhoods. Whether initiatives that address poor environmental conditions will improve cardiovascular health requires additional prospective investigations.

Cardiovascular Health of Middle-Aged U.S. Adults by Income Level, 1999 to March 2020 : A Serial Cross-Sectional Study.

BACKGROUND: Although cardiovascular mortality has increased among middle-aged U.S. adults since 2011, how the burden of cardiovascular risk factors has changed for this population by income level over the past 2 decades is unknown. OBJECTIVE: To evaluate trends in the prevalence, treatment, and control of cardiovascular risk factors among low-income and higher-income middle-aged adults and how social determinants contribute to recent associations between income and cardiovascular health. DESIGN: Serial cross-sectional study. SETTING: NHANES (National Health and Nutrition Examination Survey), 1999 to March 2020. PARTICIPANTS: Middle-aged adults (aged 40 to 64 years). MEASUREMENTS: Age-standardized prevalence of hypertension, diabetes, hyperlipidemia, obesity, and cigarette use; treatment rates for hypertension, diabetes, and hyperlipidemia; and rates of blood pressure, glycemic, and cholesterol control. RESULTS: The study population included 20 761 middle-aged adults. The prevalence of hypertension, diabetes, and cigarette use was consistently higher among low-income adults between 1999 and March 2020. Low-income adults had an increase in hypertension over the study period (37.2% [95% CI, 33.5% to 40.9%] to 44.7% [CI, 39.8% to 49.5%]) but no changes in diabetes or obesity. In contrast, higher-income adults did not have a change in hypertension but had increases in diabetes (7.8% [CI, 5.0% to 10.6%] to 14.9% [CI, 12.4% to 17.3%]) and obesity (33.0% [CI, 26.7% to 39.4%] to 44.0% [CI, 40.2% to 47.7%]). Cigarette use was high and stagnant among low-income adults (33.2% [CI, 28.4% to 38.0%] to 33.9% [CI, 29.6% to 38.3%]) but decreased among their higher-income counterparts (18.6% [CI, 13.5% to 23.7%] to 11.5% [CI, 8.7% to 14.3%]). Treatment and control rates for hypertension were unchanged in both groups (>80%), whereas diabetes treatment rates improved only among the higher-income group (58.4% [CI, 44.4% to 72.5%] to 77.4% [CI, 67.6% to 87.1%]). Income-based disparities in hypertension, diabetes, and cigarette use persisted in more recent years even after adjustment for insurance coverage, health care access, and food insecurity. LIMITATION: Sample size limitations could preclude detection of small changes in treatment and control rates. CONCLUSION: Over 2 decades in the United States, hypertension increased in low-income middle-aged adults, whereas diabetes and obesity increased in their higher-income counterparts. Income-based disparities in hypertension, diabetes, and smoking persisted even after adjustment for other social determinants of health. PRIMARY FUNDING SOURCE: National Institutes of Health.

Health Care Access and Cardiovascular Risk Factor Management Among Working-Age US Adults During the Pandemic.

BACKGROUND: Low-income working-age US adults disproportionately experienced health care disruptions at the onset of the coronavirus disease 2019 pandemic. Little is known about how health care access and cardiovascular risk factor management changed as the pandemic went on or if patterns differed by state Medicaid expansion status. METHODS: Cross-sectional data from the behavioral risk factor surveillance system were used to compare self-reported measures of health care access and cardiovascular risk factor management among US adults aged 18 to 64 years in 2021 (pandemic) to 2019 (prepandemic) using multivariable Poisson regression models. We assessed differential changes between low-income (<138% federal poverty level) and high-income (>400% federal poverty level) working-age adults by including an interaction term for income group and year. We then evaluated changes among low-income adults in Medicaid expansion versus nonexpansion states using a similar approach. RESULTS: The unweighted study population included 80 767 low-income and 184 136 high-income adults. Low-income adults experienced improvements in insurance coverage (relative risk [RR], 1.10 [95% CI, 1.08-1.12]), access to a provider (RR, 1.12 [95% CI, 1.09-1.14]), and ability to afford care (RR, 1.07 [95% CI, 1.05-1.09]) in 2021 compared with 2019. While these measures also improved for high-income adults, gains in coverage and ability to afford care were more pronounced among low-income adults. However, routine visits (RR, 0.96 [95% CI, 0.94-0.98]) and cholesterol testing (RR, 0.93 [95% CI, 0.91-0.96]) decreased for low-income adults, while diabetes screening (RR, 1.01 [95% CI, 0.95-1.08]) remained stable. Treatment for hypertension (RR, 1.05 [95% CI, 1.02-1.08]) increased, and diabetes-focused visits and insulin use remained stable. These patterns were similar for high-income adults. Across most outcomes, there were no differential changes between low-income adults residing in Medicaid expansion versus nonexpansion states. CONCLUSIONS: In this national study of working-age adults in the United States, measures of health care access improved for low- and high-income adults in 2021. However, routine outpatient visits and cardiovascular risk factor screening did not return to prepandemic levels, while risk factor treatment remained stable. As many coronavirus disease-era safety net policies come to an end, targeted strategies are needed to protect health care access and improve cardiovascular risk factor screening for working-age adults.

Prevalence and characteristics of long COVID in elderly patients: An observational cohort study of over 2 million adults in the US.

BACKGROUND: Incidence of long COVID in the elderly is difficult to estimate and can be underreported. While long COVID is sometimes considered a novel disease, many viral or bacterial infections have been known to cause prolonged illnesses. We postulate that some influenza patients might develop residual symptoms that would satisfy the diagnostic criteria for long COVID, a condition we call "long Flu." In this study, we estimate the incidence of long COVID and long Flu among Medicare patients using the World Health Organization (WHO) consensus definition. We compare the incidence, symptomatology, and healthcare utilization between long COVID and long Flu patients. METHODS AND FINDINGS: This is a cohort study of Medicare (the US federal health insurance program) beneficiaries over 65. ICD-10-CM codes were used to capture COVID-19, influenza, and residual symptoms. Long COVID was identified by (a) the designated long COVID code B94.8 (code-based definition), or (b) any of 11 symptoms identified in the WHO definition (symptom-based definition), from 1 to 3 months post-infection. A symptom would be excluded if it occurred in the year prior to infection. Long Flu was identified in influenza patients from the combined 2018 and 2019 Flu seasons by the same symptom-based definition for long COVID. Long COVID and long Flu were compared in 4 outcome measures: (a) hospitalization (any cause); (b) hospitalization (for long COVID symptom); (c) emergency department (ED) visit (for long COVID symptom); and (d) number of outpatient encounters (for long COVID symptom), adjusted for age, sex, race, region, Medicare-Medicaid dual eligibility status, prior-year hospitalization, and chronic comorbidities. Among 2,071,532 COVID-19 patients diagnosed between April 2020 and June 2021, symptom-based definition identified long COVID in 16.6% (246,154/1,479,183) and 29.2% (61,631/210,765) of outpatients and inpatients, respectively. The designated code gave much lower estimates (outpatients 0.49% (7,213/1,479,183), inpatients 2.6% (5,521/210,765)). Among 933,877 influenza patients, 17.0% (138,951/817,336) of outpatients and 24.6% (18,824/76,390) of inpatients fit the long Flu definition. Long COVID patients had higher incidence of dyspnea, fatigue, palpitations, loss of taste/smell, and neurocognitive symptoms compared to long Flu. Long COVID outpatients were more likely to have any-cause hospitalization (31.9% (74,854/234,688) versus 26.8% (33,140/123,736), odds ratio 1.06 (95% CI 1.05 to 1.08, p < 0.001)), and more outpatient visits than long Flu outpatients (mean 2.9(SD 3.4) versus 2.5(SD 2.7) visits, incidence rate ratio 1.09 (95% CI 1.08 to 1.10, p < 0.001)). There were less ED visits in long COVID patients, probably because of reduction in ED usage during the pandemic. The main limitation of our study is that the diagnosis of long COVID in is not independently verified. CONCLUSIONS: Relying on specific long COVID diagnostic codes results in significant underreporting. We observed that about 30% of hospitalized COVID-19 patients developed long COVID. In a similar proportion of patients, long COVID-like symptoms (long Flu) can be observed after influenza, but there are notable differences in symptomatology between long COVID and long Flu. The impact of long COVID on healthcare utilization is higher than long Flu.

Mis-mappings between a producer's quantitative test codes and LOINC codes and an algorithm for correcting them.

OBJECTIVES: To access the accuracy of the Logical Observation Identifiers Names and Codes (LOINC) mapping to local laboratory test codes that is crucial to data integration across time and healthcare systems. MATERIALS AND METHODS: We used software tools and manual reviews to estimate the rate of LOINC mapping errors among 179 million mapped test results from 2 DataMarts in PCORnet. We separately reported unweighted and weighted mapping error rates, overall and by parts of the LOINC term. RESULTS: Of included 179 537 986 mapped results for 3029 quantitative tests, 95.4% were mapped correctly implying an 4.6% mapping error rate. Error rates were less than 5% for the more common tests with at least 100 000 mapped test results. Mapping errors varied across different LOINC classes. Error rates in chemistry and hematology classes, which together accounted for 92.0% of the mapped test results, were 0.4% and 7.5%, respectively. About 50% of mapping errors were due to errors in the property part of the LOINC name. DISCUSSIONS: Mapping errors could be detected automatically through inconsistencies in (1) qualifiers of the analyte, (2) specimen type, (3) property, and (4) method. Among quantitative test results, which are the large majority of reported tests, application of automatic error detection and correction algorithm could reduce the mapping errors further. CONCLUSIONS: Overall, the mapping error rate within the PCORnet data was 4.6%. This is nontrivial but less than other published error rates of 20%-40%. Such error rate decreased substantially to 0.1% after the application of automatic detection and correction algorithm.

Social Determinants of Health Influence Future Health Care Costs in the Medicaid Cohort of the District of Columbia Study.

Policy Points Social determinants of health are an important predictor of future health care costs. Medicaid must partner with other sectors to address the underlying causes of its beneficiaries' poor health and high health care spending. CONTEXT: Social determinants of health are an important predictor of future health care costs but little is known about their impact on Medicaid spending. This study analyzes the role of social determinants of health (SDH) in predicting future health care costs for adult Medicaid beneficiaries with similar past morbidity burdens and past costs. METHODS: We enrolled into a prospective cohort study 8,892 adult Medicaid beneficiaries who presented for treatment at an emergency department or clinic affiliated with two hospitals in Washington, DC, between September 2017 and December 31, 2018. We used SDH information measured at enrollment to categorize our participants into four social risk classes of increasing severity. We used Medicaid claims for a 2-year period; 12 months pre- and post-study enrollment to measure past and future morbidity burden according to the Adjusted Clinical Groups system. We also used the Medicaid claims data to characterize total annual Medicaid costs one year prior to and one year after study enrollment. RESULTS: The 8,892 participants were primarily female (66%) and Black (91%). For persons with similar past morbidity burdens and past costs (p < 0.01), the future morbidity burden was significantly higher in the upper two social risk classes (1.15 and 2.04, respectively) compared with the lowest one. Mean future health care spending was significantly higher in the upper social risk classes compared with the lowest one ($2,713, $11,010, and $17,710, respectively) and remained significantly higher for the two highest social risk classes ($1,426 and $3,581, respectively), given past morbidity burden and past costs (p < 0.01). When we controlled for future morbidity burden (measured concurrently with future costs), social risk class was no longer a significant predictor of future health care costs. CONCLUSIONS: SDH are statistically significant predictors of future morbidity burden and future costs controlling for past morbidity burden and past costs. Further research is needed to determine whether current payment systems adequately account for differences in the care needs of highly medically and socially complex patients.

Effect of common maintenance drugs on the risk and severity of COVID-19 in elderly patients.

BACKGROUND: Maintenance drugs are used to treat chronic conditions. Several classes of maintenance drugs have attracted attention because of their potential to affect susceptibility to and severity of COVID-19. METHODS: Using claims data on 20% random sample of Part D Medicare enrollees from April to December 2020, we identified patients diagnosed with COVID-19. Using a nested case-control design, non-COVID-19 controls were identified by 1:5 matching on age, race, sex, dual-eligibility status, and geographical region. We identified usage of angiotensin-converting enzyme inhibitors (ACEI), angiotensin-receptor blockers (ARB), statins, warfarin, direct factor Xa inhibitors, P2Y12 inhibitors, famotidine and hydroxychloroquine based on Medicare prescription claims data. Using extended Cox regression models with time-varying propensity score adjustment we examined the independent effect of each study drug on contracting COVID-19. For severity of COVID-19, we performed extended Cox regressions on all COVID-19 patients, using COVID-19-related hospitalization and all-cause mortality as outcomes. Covariates included gender, age, race, geographic region, low-income indicator, and co-morbidities. To compensate for indication bias related to the use of hydroxychloroquine for the prophylaxis or treatment of COVID-19, we censored patients who only started on hydroxychloroquine in 2020. RESULTS: Up to December 2020, our sample contained 374,229 Medicare patients over 65 who were diagnosed with COVID-19. Among the COVID-19 patients, 278,912 (74.6%) were on at least one study drug. The three most common study drugs among COVID-19 patients were statins 187,374 (50.1%), ACEI 97,843 (26.2%) and ARB 83,290 (22.3%). For all three outcomes (diagnosis, hospitalization and death), current users of ACEI, ARB, statins, warfarin, direct factor Xa inhibitors and P2Y12 inhibitors were associated with reduced risks, compared to never users. Famotidine did not show consistent significant effects. Hydroxychloroquine did not show significant effects after censoring of recent starters. CONCLUSION: Maintenance use of ACEI, ARB, warfarin, statins, direct factor Xa inhibitors and P2Y12 inhibitors was associated with reduction in risk of acquiring COVID-19 and dying from it.

A review of thromboembolic events in hospitalized COVID-19 patients.

CONTEXT: A higher incidence of thromboembolic disorders in COVID-19 has been reported by many clinicians worldwide. OBJECTIVE, DESIGN AND DATA SOURCES: Selected studies found in PubMed that reported thromboembolic events were included for meta-analysis using weighted fixed and random effects. Data from 19 articles on cohort studies in patients diagnosed with COVID-19 and thromboembolic events, including thrombosis and embolism were included in this review. RESULTS: The likelihood for developing thromboembolic disorders in hospitalized COVID-19 patients was 0.28 (95% CI 0.21-0.36). CONCLUSION: This study further validates the increased risk of VTE in COVID-19 patients when compared to healthy, non-hospitalized people, and hospitalized patients. These findings will be useful to researchers and medical practitioners caring for COVID-19 patients.

A Review of Thromboembolic Events in Hospitalized COVID-19 Patients.

Context: A higher incidence of thromboembolic disorders in COVID-19 has been reported by many clinicians worldwide. Objective, Design and Data Sources: Selected studies found in PubMed that reported thromboembolic events were included for meta-analysis using weighted fixed and random effects. Data from 19 articles on cohort studies in patients diagnosed with COVID-19 and thromboembolic events, including thrombosis and embolism were included in this review. Results: The likelihood for developing thromboembolic disorders in hospitalized COVID-19 patients was 0.28 (95% CI 0.21â€"0.36). Conclusion: This study further validates the increased risk of VTE in COVID-19 patients when compared to healthy, non-hospitalized people, and hospitalized patients. These findings will be useful to researchers and medical practitioners caring for COVID-19 patients.

The Influence of Social Determinants of Health on Emergency Departments Visits in a Medicaid Sample.

STUDY OBJECTIVE: We evaluate the relationship between social determinants of health and emergency department (ED) visits in the Medicaid Cohort of the District of Columbia. METHODS: We conducted a retrospective cohort analysis of 8,943 adult Medicaid beneficiaries who completed a social determinants of health survey at study enrollment. We merged the social determinants of health data with participants' Medicaid claims data for up to 24 months before enrollment. Using latent class analysis, we grouped our participants into 4 distinct social risk classes based on similar responses to the social determinants of health questions. We classified ED visits as primary care treatable or ED care needed, using the Minnesota algorithm. We calculated the adjusted log relative primary care treatable and ED care needed visit rates among the social risk classes by using generalized linear mixed-effects models. RESULTS: The majority (71%) of the 49,111 ED visits made by the 8,943 participants were ED care needed. The adjusted log relative rate of both primary care treatable and ED care needed visit rates increased with each higher (worse) social risk class compared with the lowest class. Participants in the highest social risk class (ie, unemployed and many social risks) had a log relative primary care treatable and ED care needed rate of 39% (range 28% to 50%) and 29% (range 21% to 38%), respectively, adjusted for age, sex, and illness severity. CONCLUSION: There is a strong relationship between social determinants of health and ED utilization in this Medicaid sample that is worth investigating in other Medicaid samples and patient populations.

Latent Class Analysis to Represent Social Determinant of Health Risk Groups in the Medicaid Cohort of the District of Columbia.

OBJECTIVE: To develop distinct social risk profiles based on social determinants of health (SDH) information and to determine whether these social risk groups varied in terms of health, health care utilization, and costs. METHODS: We prospectively enrolled 8943 beneficiaries insured by the District of Columbia Medicaid program between September 2017 and December 2018. Participants completed a SDH survey and we obtained their Medicaid claims data for a 2-year period before study enrollment. We used latent class analysis (LCA) to identify distinct social risk profiles based on their SDH responses. We assessed the relationship among different SDH as well as the relationship among the social risk classes and health, health care use and costs. RESULTS: The majority of SDH were moderately to strongly correlated with one another. LCA yielded 4 distinct social risk groups. Group 1 reported the least social risks with the most employed. Group 2 was distinguished by financial strain and housing instability with fewer employed. Group 3 were mostly unemployed with limited car and internet access. Group 4 had the most social risks and most unemployed. The social risk groups demonstrated meaningful differences in health, acute care utilization, and health care costs with group 1 having the best health outcomes and group 4 the worst (P<0.05). CONCLUSIONS: LCA is a practical method of aggregating correlated SDH data into a finite number of distinct social risk groups. Understanding the constellation of social challenges that patients face is critical when attempting to address their social needs and improve health outcomes.

Targeted Screening for HIV Pre-Exposure Prophylaxis Eligibility in Two Emergency Departments in Washington, DC.

Pre-exposure prophylaxis (PrEP) is an effective method to prevent HIV acquisition in high-risk individuals. This cross-sectional survey study estimated the proportion of patients who were PrEP eligible among a targeted sample of emergency department (ED) patients with chief complaints indicative of HIV risk. Research assistants screened a convenience sample of adult patients who presented to two hospital EDs in Washington, DC, during a 6-month period with genitourinary, substance use, or intentional injury-related complaints. Patients with these complaints who reported being sexually active within the past 6 months and HIV negative completed a computer-assisted survey that included questions on sexual practices and partners, substance use, and attitudes and knowledge about PrEP. We used the Centers for Disease Control and Prevention (CDC) clinical guidelines to determine whether PrEP use was indicated. We report differences in PrEP eligibility by demographic characteristics, knowledge, and attitudes. Of the 410 participants, the majority were black (85%), and heterosexual females (72%). PrEP use was indicated in 20% (N = 84), most commonly because of condomless sex with a person of unknown HIV status (82%) and/or a sexually transmitted infection (STI) diagnosis (41%). One-third (34%) of participants had heard of PrEP. Overall, 36% of the sample (N = 148) wanted to learn more about PrEP while in the ED. The percentage who wanted to learn more about PrEP was higher among PrEP-eligible patients (52%) compared with PrEP-ineligible patients (32%). Using CDC criteria, targeted screening identified that a substantial proportion of ED patients are PrEP eligible based on their self-reported behaviors.

A method for prioritizing risk groups for early SARS-CoV-2 Vaccination, By the Numbers.

Background: Given the limited supply of two COVID-19 vaccines, it will be important to choose which risk groups to prioritize for vaccination in order to get the most health benefits from that supply. Method: In order to help decide how to get the maximum health yield from this limited supply, we implemented a logistic regression model to predict COVID-19 death risk by age, race, and sex and did the same to predict COVID-19 case risk. Results: Our predictive model ranked all demographic groups by COVID-19 death risk. It was highly concentrated in some demographic groups, e.g. 85+ year old Black, Non-Hispanic patients suffered 1,953 deaths per 100,000. If we vaccinated the 17 demographic groups at highest COVID-19 death ranked by our logistic model, it would require only 3.7% of the vaccine supply needed to vaccinate all the United States, and yet prevent 47% of COVID-19 deaths. Nursing home residents had a higher COVID-19 death risk at 5,200 deaths/100,000, more than our highest demographic risk group. Risk of prison residents and health care workers (HCW) were lower than that of our demographic groups with the highest risks.We saw much less concentration of COVID-19 case risk in any demographic groups compared to the high concentration of COVID-19 death in some such groups. We should prioritize vaccinations with the goal of reducing deaths, not cases, while the vaccine supply is low. Conclusion: SARS-CoV-2 vaccines protect against severe COVID-19 infection and thus against COVID-19 death per vaccine studies. Allocating at least some of the early vaccine supplies to high risk demographic groups could maximize lives saved. Our model, and the risk estimate it produced, could help states define their vaccine allocation rules.

Characteristics and Severity of Disease among 100 Cases of Imported Malaria Seen at a U.S. University Hospital, 2000-2017.

Malaria acquired in endemic areas poses a substantial risk to travelers arriving in or returning to the United States. Timely diagnosis and recognition of severe illness are crucial; however, many U.S.-based clinicians lack familiarity with this disease. We conducted a retrospective review of 100 cases of malaria in adults seen at a single urban university hospital during 2000-2017. Descriptive and analytical statistics were calculated, including logistic regression modeling case severity. Most of the patients presented with Plasmodium falciparum (76%), most commonly after travel from sub-Saharan Africa (94%). Prior malaria experience was common (50%), but adherence to a prophylactic regimen was exceedingly rare (4%). Twenty-one patients had severe malaria, including 10 with cerebral malaria. Severity was predicted by high parasitemia, bandemia, hypoglycemia, and hypotension at the time of presentation. In 24 patients, the initial treatment regimen was changed, usually because of the appearance of clinical deterioration or drug toxicity. One patient required intravenous artesunate. All patients survived, although one suffered fetal loss. Among 30 patients initially evaluated at other institutions, 43% had been treated for an alternative diagnosis. The most common reasons for transfer of patients to our hospital were inadequate facilities and lack of expertise with malaria. There needs to be increased awareness among U.S.-based travelers and clinicians regarding malaria as a potentially lethal condition, emphasizing the use of appropriate prophylaxis. Our simple model of disease severity could serve frontline physicians when deciding which patients should be admitted to the intensive care unit or transferred for higher level care.