Telehealth and Medicare Type 2 Diabetes Care Outcomes: Evidence From Louisiana.

BACKGROUND: At the onset of the COVID-19 pandemic, the Centers for Medicare and Medicaid Services broadened access to telehealth. This provided an opportunity to test whether diabetes, a risk factor for COVID-19 severity, can be managed with telehealth services. OBJECTIVE: The objective of this study was to examine the impacts of telehealth on diabetes control. RESEARCH DESIGN: A doubly robust estimator combined a propensity score-weighting strategy with regression controls for baseline characteristics using electronic medical records data to compare outcomes in patients with and without telehealth care. Matching on preperiod trajectories in outpatient visits and weighting by odds were used to ensure comparability between comparators. SUBJECTS: Medicare patients with type 2 diabetes in Louisiana between March 2018 and February 2021 (9530 patients with a COVID-19 era telehealth visit and 20,666 patients without one). MEASURES: Primary outcomes were glycemic levels and control [ie, hemoglobin A1c (HbA1c) under 7%]. Secondary outcomes included alternative HbA1c measures, emergency department visits, and inpatient admissions. RESULTS: Telehealth was associated with lower pandemic era mean A1c values [estimate=-0.080%, 95% confidence interval (CI): -0.111% to -0.048%], which translated to an increased likelihood of having HbA1c in control (estimate=0.013; 95% CI: 0.002-0.024; P<0.023). Hispanic telehealth users had relatively higher COVID-19 era HbA1c levels (estimate=0.125; 95% CI: 0.044-0.205; P<0.003). Telehealth was not associated with differences in the likelihood of having an emergency department visits (estimate=-0.003; 95% CI: -0.011 to 0.004; P<0.351) but was associated with more the likelihood of having an inpatient admission (estimate=0.024; 95% CI: 0.018-0.031; P<0.001). CONCLUSION: Telehealth use among Medicare patients with type 2 diabetes in Louisiana stemming from the COVID-19 pandemic was associated with relatively improved glycemic control.

COVID-19 bacteremic co-infection is a major risk factor for mortality, ICU admission, and mechanical ventilation.

BACKGROUND: Recent single-center reports have suggested that community-acquired bacteremic co-infection in the context of Coronavirus disease 2019 (COVID-19) may be an important driver of mortality; however, these reports have not been validated with a multicenter, demographically diverse, cohort study with data spanning the pandemic. METHODS: In this multicenter, retrospective cohort study, inpatient encounters were assessed for COVID-19 with community-acquired bacteremic co-infection using 48-h post-admission blood cultures and grouped by: (1) confirmed co-infection [recovery of bacterial pathogen], (2) suspected co-infection [negative culture with ≥ 2 antimicrobials administered], and (3) no evidence of co-infection [no culture]. The primary outcomes were in-hospital mortality, ICU admission, and mechanical ventilation. COVID-19 bacterial co-infection risk factors and impact on primary outcomes were determined using multivariate logistic regressions and expressed as adjusted odds ratios with 95% confidence intervals (Cohort, OR 95% CI, Wald test p value). RESULTS: The studied cohorts included 13,781 COVID-19 inpatient encounters from 2020 to 2022 in the University of Alabama at Birmingham (UAB, n = 4075) and Ochsner Louisiana State University Health-Shreveport (OLHS, n = 9706) cohorts with confirmed (2.5%), suspected (46%), or no community-acquired bacterial co-infection (51.5%) and a comparison cohort consisting of 99,170 inpatient encounters from 2010 to 2019 (UAB pre-COVID-19 pandemic cohort). Significantly increased likelihood of COVID-19 bacterial co-infection was observed in patients with elevated ≥ 15 neutrophil-to-lymphocyte ratio (UAB: 1.95 [1.21-3.07]; OLHS: 3.65 [2.66-5.05], p < 0.001 for both) within 48-h of hospital admission. Bacterial co-infection was found to confer the greatest increased risk for in-hospital mortality (UAB: 3.07 [2.42-5.46]; OLHS: 4.05 [2.29-6.97], p < 0.001 for both), ICU admission (UAB: 4.47 [2.87-7.09], OLHS: 2.65 [2.00-3.48], p < 0.001 for both), and mechanical ventilation (UAB: 3.84 [2.21-6.12]; OLHS: 2.75 [1.87-3.92], p < 0.001 for both) across both cohorts, as compared to other risk factors for severe disease. Observed mortality in COVID-19 bacterial co-infection (24%) dramatically exceeds the mortality rate associated with community-acquired bacteremia in pre-COVID-19 pandemic inpatients (5.9%) and was consistent across alpha, delta, and omicron SARS-CoV-2 variants. CONCLUSIONS: Elevated neutrophil-to-lymphocyte ratio is a prognostic indicator of COVID-19 bacterial co-infection within 48-h of admission. Community-acquired bacterial co-infection, as defined by blood culture-positive results, confers greater increased risk of in-hospital mortality, ICU admission, and mechanical ventilation than previously described risk factors (advanced age, select comorbidities, male sex) for COVID-19 mortality, and is independent of SARS-CoV-2 variant.

Synergies between centralized and federated approaches to data quality: a report from the national COVID cohort collaborative.

OBJECTIVE: In response to COVID-19, the informatics community united to aggregate as much clinical data as possible to characterize this new disease and reduce its impact through collaborative analytics. The National COVID Cohort Collaborative (N3C) is now the largest publicly available HIPAA limited dataset in US history with over 6.4 million patients and is a testament to a partnership of over 100 organizations. MATERIALS AND METHODS: We developed a pipeline for ingesting, harmonizing, and centralizing data from 56 contributing data partners using 4 federated Common Data Models. N3C data quality (DQ) review involves both automated and manual procedures. In the process, several DQ heuristics were discovered in our centralized context, both within the pipeline and during downstream project-based analysis. Feedback to the sites led to many local and centralized DQ improvements. RESULTS: Beyond well-recognized DQ findings, we discovered 15 heuristics relating to source Common Data Model conformance, demographics, COVID tests, conditions, encounters, measurements, observations, coding completeness, and fitness for use. Of 56 sites, 37 sites (66%) demonstrated issues through these heuristics. These 37 sites demonstrated improvement after receiving feedback. DISCUSSION: We encountered site-to-site differences in DQ which would have been challenging to discover using federated checks alone. We have demonstrated that centralized DQ benchmarking reveals unique opportunities for DQ improvement that will support improved research analytics locally and in aggregate. CONCLUSION: By combining rapid, continual assessment of DQ with a large volume of multisite data, it is possible to support more nuanced scientific questions with the scale and rigor that they require.

The Association Between Neighborhood Social Vulnerability and COVID-19 Testing, Positivity, and Incidence in Alabama and Louisiana.

Racial/ethnic and socioeconomic disparities in COVID-19 burden have been widely reported. Using data from the state health departments of Alabama and Louisiana aggregated to residential Census tracts, we assessed the relationship between social vulnerability and COVID-19 testing rates, test positivity, and incidence. Data were cumulative for the period of February 27, 2020 to October 7, 2020. We estimated the association of the 2018 Social Vulnerability Index (SVI) overall score and theme scores with COVID-19 tests, test positivity, and cases using multivariable negative binomial regressions. We adjusted for rurality with 2010 Rural-Urban Commuting Area codes. Regional effects were modeled as fixed effects of counties/parishes and state health department regions. The analytical sample included 1160 Alabama and 1105 Louisiana Census tracts. In both states, overall social vulnerability and vulnerability themes were significantly associated with increased COVID-19 case rates (RR 1.57, 95% CI 1.45-1.70 for Alabama; RR 1.36, 95% CI 1.26-1.46 for Louisiana). There was increased COVID-19 testing with higher overall vulnerability in Louisiana (RR 1.26, 95% CI 1.14-1.38), but not in Alabama (RR 0.95, 95% CI 0.89-1.02). Consequently, test positivity in Alabama was significantly associated with social vulnerability (RR 1.66, 95% CI 1.57-1.75), whereas no such relationship was observed in Louisiana (RR 1.05, 95% CI 0.98-1.12). Social vulnerability is a risk factor for COVID-19 infection, particularly among racial/ethnic minorities and those in disadvantaged housing conditions without transportation. Increased testing targeted to vulnerable communities may contribute to reduction in test positivity and overall COVID-19 disparities.

The importance of anosmia, ageusia and age in community presentation of symptomatic and asymptomatic SARS-CoV-2 infection in Louisiana, USA; a cross-sectional prevalence study.

OBJECTIVE: While many seroprevalence studies of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been performed, few are demographically representative. This investigation focused on defining the nature and frequency of symptomatic and asymptomatic SARS-CoV-2 infection in a representative, cross-sectional sample of communities in Louisiana, USA. METHODS: A sample of 4778 adults from New Orleans and Baton Rouge, Louisiana were given a survey of symptoms and co-morbidities, nasopharyngeal swab to test for active infection (PCR), and blood draw to test for past infection (IgG). Odds ratios, cluster analysis, quantification of virus and antibody, and linear modelling were used to understand whether certain symptoms were associated with a positive test, how symptoms grouped together, whether virus or antibody varied by symptom status, and whether being symptomatic was different across the age span. RESULTS: Reported anosmia/ageusia was strongly associated with a positive test; 40.6% (93/229) tested positive versus 4.8% (218/4549) positivity in those who did not report anosmia/ageusia (OR 13.6, 95% CI 10.1-18.3). Of the people who tested positive, 47.3% (147/311) were completely asymptomatic. Symptom presentation clustered into three groups; low/no symptoms (0.4 ± 0.9, mean ± SD), highly symptomatic (7.5 ± 1.9) or moderately symptomatic (4.0 ± 1.5). Quantity of virus was lower in the asymptomatic versus symptomatic group (cycle number 23.3 ± 8.3 versus 17.3 ± 9.0; p < 0.001). Modelling the probability of symptoms showed changes with age; the highest probability of reporting symptoms was 64.6% (95% CI 50.4-76.5) at age 29 years, which decreased to a probability of 49.3% (95% CI 36.6-62.0) at age 60 years and only 25.1% (95% CI 5.0-68.1) at age 80 years. CONCLUSION: Anosmia/ageusia can be used to differentiate SARS-CoV-2 infection from other illnesses, and, given the high ratio of asymptomatic individuals, contact tracing should include those without symptoms. Regular testing in congregant settings of those over age 60 years may help mitigate asymptomatic spread.

Seroprevalence of SARS-CoV-2 and Infection Fatality Ratio, Orleans and Jefferson Parishes, Louisiana, USA, May 2020.

Using a novel recruitment method and paired molecular and antibody testing for severe acute respiratory syndrome coronavirus 2 infection, we determined seroprevalence in a racially diverse municipality in Louisiana, USA. Infections were highly variable by ZIP code and differed by race/ethnicity. Overall census-weighted seroprevalence was 6.9%, and the calculated infection fatality ratio was 1.63%.

Racial and Workplace Disparities in Seroprevalence of SARS-CoV-2, Baton Rouge, Louisiana, USA.

By using paired molecular and antibody testing for severe acute respiratory syndrome coronavirus 2 infection, we determined point prevalence and seroprevalence in Louisiana, USA, during the second phase of reopening. Infections were highly variable by race and ethnicity, work environment, and ZIP code. Census-weighted seroprevalence was 3.6%, and point prevalence was 3.0%.

Locally Informed Modeling to Predict Hospital and Intensive Care Unit Capacity During the COVID-19 Epidemic.

Background: In the early phases of the 2019 novel coronavirus (COVID-19) pandemic, health system leaders faced the urgent task of translating the unknown into forecasting models for hospital capacity. Our study objective was to demonstrate the application of a practical, locally informed model to estimate the hospital capacity needed even though the community COVID-19 caseload was unknown. Methods: We developed a susceptible-infected-recovered (SIR) model that was adopted from the University of Pennsylvania COVID-19 Hospital Impact Model for Epidemics and employed at 8 hospitals within Ochsner Health, the largest integrated delivery system in Louisiana, between March 16 and April 15, 2020. Intensive care unit (ICU) admissions of cases in the New Orleans area were used to estimate the community case load when testing was delayed. Results: Initially, the observed ICU census trended near R0=2.0, whereas the ventilator census trended between R0=2.0 and 3.0. After implementing social distancing, both the ICU and ventilator capacity trended toward R0=1.3, while non-ICU medical/surgical beds trended toward R0=1.5. The model accurately predicted peak ICU (n=250) and hospital bed (n=487) usage by April 6, 2020. In response to model trends, Ochsner added 130 ICU beds across its hospitals by opening a new ICU and converting operating rooms and parts of emergency departments to ICU beds. Conclusion: When disease testing is limited or results are delayed, ICU admissions data can inform SIR models of the rate of spread of COVID-19 in a community. Our model used various R0 plots to demonstrate an array of scenarios to guide planning for hospital and political leaders.

Hospitalization and Mortality among Black Patients and White Patients with Covid-19.

BACKGROUND: Many reports on coronavirus disease 2019 (Covid-19) have highlighted age- and sex-related differences in health outcomes. More information is needed about racial and ethnic differences in outcomes from Covid-19. METHODS: In this retrospective cohort study, we analyzed data from patients seen within an integrated-delivery health system (Ochsner Health) in Louisiana between March 1 and April 11, 2020, who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, the virus that causes Covid-19) on qualitative polymerase-chain-reaction assay. The Ochsner Health population is 31% black non-Hispanic and 65% white non-Hispanic. The primary outcomes were hospitalization and in-hospital death. RESULTS: A total of 3626 patients tested positive, of whom 145 were excluded (84 had missing data on race or ethnic group, 9 were Hispanic, and 52 were Asian or of another race or ethnic group). Of the 3481 Covid-19-positive patients included in our analyses, 60.0% were female, 70.4% were black non-Hispanic, and 29.6% were white non-Hispanic. Black patients had higher prevalences of obesity, diabetes, hypertension, and chronic kidney disease than white patients. A total of 39.7% of Covid-19-positive patients (1382 patients) were hospitalized, 76.9% of whom were black. In multivariable analyses, black race, increasing age, a higher score on the Charlson Comorbidity Index (indicating a greater burden of illness), public insurance (Medicare or Medicaid), residence in a low-income area, and obesity were associated with increased odds of hospital admission. Among the 326 patients who died from Covid-19, 70.6% were black. In adjusted time-to-event analyses, variables that were associated with higher in-hospital mortality were increasing age and presentation with an elevated respiratory rate; elevated levels of venous lactate, creatinine, or procalcitonin; or low platelet or lymphocyte counts. However, black race was not independently associated with higher mortality (hazard ratio for death vs. white race, 0.89; 95% confidence interval, 0.68 to 1.17). CONCLUSIONS: In a large cohort in Louisiana, 76.9% of the patients who were hospitalized with Covid-19 and 70.6% of those who died were black, whereas blacks comprise only 31% of the Ochsner Health population. Black race was not associated with higher in-hospital mortality than white race, after adjustment for differences in sociodemographic and clinical characteristics on admission.