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Appl Clin Inform ; 13(3): 612-620, 2022 05.
Article in English | MEDLINE | ID: covidwho-1890334


OBJECTIVE: During the coronavirus disease 2019 pandemic, as a safety-net organization with a substantial percentage of patients of color and with limited English proficiency (LEP), we were wary of furthering health disparities in our community. We analyzed gaps in telemedicine (telephone and video) delivery in our communities, quantified the effects of our tests of change, and began the process of accumulating evidence to create a road map for other organizations. METHODS: We leveraged Lean problem-solving strategies to identify modifiable gaps across multiple domains that could inhibit equity in telemedicine. We implemented tests of change across domains of community engagement, technology, education, and access. We observed the proportion of telemedicine encounters across races and languages between April and November, 2020. Regression analyses tested the impact of race and language on telemedicine controlling for age, gender, insurance, and time. RESULTS: Several rounds of changes and enhancements were associated with changes in telemedicine use of +5.5% (p < 0.0001) for Hispanic, +4.0% (p < 0.0001) for Spanish-speaking, -2.1% for Black (p < 0.05), and -4.4% for White patients (p < 0.001). African-American, Hispanic, and non-English-speaking patients had between 2.3 and 4.6 times the odds of preferring telephone to video encounters (p < 0.0001), with increases in preferences for video use over time (p < 0.05). CONCLUSION: Our roadmap to improve equitable delivery of telemedicine was associated with a significant improvement in telemedicine use among certain minority populations. Most populations of color used telephone more often than video. This preference changed over time and with equity-focused changes in telemedicine delivery.

COVID-19 , Telemedicine , COVID-19/epidemiology , Hispanic or Latino , Humans , Pandemics , Telephone
JAMIA Open ; 4(3): ooab055, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1526168


OBJECTIVE: Ensuring an efficient response to COVID-19 requires a degree of inter-system coordination and capacity management coupled with an accurate assessment of hospital utilization including length of stay (LOS). We aimed to establish optimal practices in inter-system data sharing and LOS modeling to support patient care and regional hospital operations. MATERIALS AND METHODS: We completed a retrospective observational study of patients admitted with COVID-19 followed by 12-week prospective validation, involving 36 hospitals covering the upper Midwest. We developed a method for sharing de-identified patient data across systems for analysis. From this, we compared 3 approaches, generalized linear model (GLM) and random forest (RF), and aggregated system level averages to identify features associated with LOS. We compared model performance by area under the ROC curve (AUROC). RESULTS: A total of 2068 patients were included and used for model derivation and 597 patients for validation. LOS overall had a median of 5.0 days and mean of 8.2 days. Consistent predictors of LOS included age, critical illness, oxygen requirement, weight loss, and nursing home admission. In the validation cohort, the RF model (AUROC 0.890) and GLM model (AUROC 0.864) achieved good to excellent prediction of LOS, but only marginally better than system averages in practice. CONCLUSION: Regional sharing of patient data allowed for effective prediction of LOS across systems; however, this only provided marginal improvement over hospital averages at the aggregate level. A federated approach of sharing aggregated system capacity and average LOS will likely allow for effective capacity management at the regional level.

Chem Biol Interact ; 341: 109449, 2021 May 25.
Article in English | MEDLINE | ID: covidwho-1157165


BACKGROUND: COVID-19, a severe global pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has emerged as one of the most threatening transmissible disease. As a great threat to global public health, the development of treatment options has become vital, and a rush to find a cure has mobilized researchers globally from all areas. SCOPE AND APPROACH: This review focuses on deciphering the potential of different secondary metabolites from medicinal plants as therapeutic options either as inhibitors of therapeutic targets of SARS-CoV-2 or as blockers of viral particles entry through host cell receptors. The use of medicinal plants containing specific phytomoieties could be seen in providing a safer and long-term solution for the population with lesser side effects. Key Findings and Conclusions: Considering the high cost and time-consuming drug discovery process, therapeutic repositioning of existing drugs was explored as treatment option in COVID-19, however several molecules have been retracted as therapeutics either due to no positive outcomes or the severe side effects. These effects call for exploring the alternate treatment options which are therapeutically effective as well as safe. Keeping this in mind, phytopharmaceuticals derived from medicinal plants could be explored as important resources in the development of COVID-19 treatment, as their role in the past for treatment of viral diseases like HIV, MERS-CoV, and influenza has been well reported. Considering this fact, different phytoconstituents such as flavonoids, alkaloids, tannins and glycosides etc. Possessing antiviral properties against coronaviruses and possessing potential against SARS-CoV-2 have been reviewed in the present work.

Antiviral Agents/pharmacology , COVID-19/drug therapy , Phytochemicals/pharmacology , Alkaloids/chemistry , Alkaloids/pharmacology , Anthraquinones/chemistry , Anthraquinones/pharmacology , Antiviral Agents/chemistry , Flavonoids/chemistry , Flavonoids/pharmacology , Humans , Oils, Volatile/chemistry , Oils, Volatile/pharmacology , Phytochemicals/chemistry , Plants, Medicinal/chemistry , Plants, Medicinal/metabolism , Saponins/chemistry , Saponins/pharmacology , Secondary Metabolism