Inferring patient transfer networks between healthcare facilities

Constructing accurate patient transfer networks between hospitals is critical for understanding the spread of healthcare associated infections through statistical and mathematical modeling, and for determining optimal screening and treatment strategies. The Healthcare Cost & Utilization Project (HCUP) State Inpatient Databases (SID) provide valuable information on patient transfers from publicly obtainable claims databases, yet often give an incomplete picture due to missingness of patient tracking identifiers. We designed a novel imputation algorithm that enabled us to estimate the true number of patient transfers between each pair of hospitals in a state over a specified time period and age group in the presence of these missing identifiers. We then validated the algorithm's performance through a series of simulation experiments using the HCUP SID, and finally tested the algorithm on multiple states' genuine data. Our proposed method significantly reduced the total mean squared error in predicting the true number of transfers amongst hospitals for all simulation experiments, and it also yielded epidemic simulations that more closely approximated those corresponding to the true patient transfer network.

COVID-19 Case Fatality and Alzheimer's Disease.

Previous studies have identified dementia as a risk factor for death from coronavirus disease 2019 (COVID-19). However, it is unclear whether Alzheimer's disease (AD) is an independent risk factor for COVID-19 case fatality rate. In a retrospective cohort study, we identified 387,841 COVID-19 patients through TriNetX. After adjusting for demographics and comorbidities, we found that AD patients had higher odds of dying from COVID-19 compared to patients without AD (Odds Ratio: 1.20, 95%confidence interval: 1.09-1.32, p < 0.001). Interestingly, we did not observe increased mortality from COVID-19 among patients with vascular dementia. These data are relevant to the evolving COVID-19 pandemic.

The Cardiovascular Effects of Treatment with Hydroxychloroquine and Azithromycin.

Hydroxychloroquine combined with azithromycin has been investigated for activity against coronavirus disease 2019 (COVID-19), but concerns about adverse cardiovascular (CV) effects have been raised. This study evaluated claims data to determine if risks for CV events were increased with hydroxychloroquine alone or combined with azithromycin. We identified data from 43,752 enrollees that qualified for analysis. The number of CV events increased by 25 (95% confidence interval [CI]: 8, 42, p=0.005) per 1000 people per year of treatment with hydroxychloroquine alone compared with pretreatment levels and by 201 (95% CI: 145, 256, p<0.001) events per 1000 people per year when individuals took hydroxychloroquine and azithromycin. These rates translate to an additional 0.34 (95% CI: 0.11, 0.58) CV events per 1000 patients placed on a 5-day treatment with hydroxychloroquine monotherapy and 2.75 (95% CI: 1.99, 3.51) per 1000 patients on a 5-day treatment with both hydroxychloroquine and azithromycin. The rate of adverse events increased with age following exposure to hydroxychloroquine alone and combined with azithromycin. For females aged 60 to 79 years prescribed hydroxychloroquine, the rate of adverse CV events was 0.92 per 1000 patients on 5 days of therapy, but it increased to 4.78 per 1000 patients when azithromycin was added. The rate of adverse CV events did not differ significantly from zero for patients 60 years of age or younger. These data suggest that hydroxychloroquine with or without azithromycin is likely safe in individuals under 60 years of age if they do not have additional CV risks. However, the combination of hydroxychloroquine and azithromycin should be used with extreme caution in older patients.