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medRxiv preprint Key PointsQuestion: What is the feasibility and effectiveness of physician telehealth services during a pandemic?Findings: In this cohort study of a COVID-19 telehealth hotline that included 10,112 callers and 4,213 physician telehealth visits, most patients (79%) were advised to self-isolate at home, 14% were found unlikely to have COVID-19, 4% dispositions (e.g. testing or office visit) and 3% were advised to immediately seek care emergency department. 83% of patients who were advised to stay home did not require in-person visits.Meaning: Physician-directed telehealth services conserve scarce resources and provide effective, equitable care during a pandemic without compromising patient safety.ABSTRACT Importance: Severe acute respiratory syndrome coronavirus (SARS-CoV-2) and the associated coronavirus disease of 2019 (COVID-19) have presented immense challenges for health care systems. Many regions have struggled to adapt to disruptions to health care practice and employ systems that effectively manage the demand for services.Objective: To examine the effectiveness of the first five weeks' of a 24/7 physician-staffed COVID-19 hotline.Design: Cohort study using electronic health records.Setting: A single large health care system in Northeast Ohio.Participants: During 5 weeks of operation, 10,112 patients called the hotline (callers) and were evaluated by a registered nurse (RN) using standardized protocols. Of these, 4,213 (42%) were referred for a physician telehealth visit (telehealth patients). The mean age of callers was 42 years. 67% were female, 51% white, and 46% were on Medicaid or uninsured.Intervention: Physician telehealth visits for COVID-19. Main Outcomes and Measures:We describe clinical diagnosis, patient characteristics (age, sex race/ethnicity, smoking status, insurance status), and visit disposition. We use logistic regression to evaluate associations between patient characteristics, visit disposition and subsequent emergency department use, hospitalization, and SARS-Cov-2 PCR testing. Results:Common caller concerns included cough, fever, and shortness of breath. Most telehealth patients (79%) were advised to self-isolate at home, 14% were determined to be unlikely to have COVID-19, 3% were advised to seek emergency care, and 4% had miscellaneous other dispositions. A total of 287 (7%) patients had a subsequent ED visit, and 44 (1%) were hospitalized with a COVID-19 diagnosis. Of the callers, 482 (5%) had a COVID-19 test reported with 69 (14%) testing positive. Among patients advised to stay at home, 83% had no further face-to-face visits. In multivariable results, only a physician recommendation to seek emergency care was associated with emergency room use (OR=4.73, 95%CI 1.37-16.39, p=.014). Only older age was associated with having a positive test result. Conclusions and Relevance:Robust, physician-directed telehealth services can meet a wide range of needs during the acute phase of a pandemic, conserving scarce resources such as personal protective equipment and testing sup...

To determine if the Area Deprivation Index (ADI) can serve as a predictor for patients from geographic regions of high socioeconomic distress as high risk for having no-shows to first-year newborn visits. MethodsWe assessed the no-show rate per patient from a large public safety-net hospital in Cleveland, Ohio, and the ADI of the census-designated tract for each patient's home geographic identifier (GEOID), aggregated into quintiles, and calculated differences in no-show-rates across census-designated tracts of different ADIs. ResultsA total of 2944 newborns from an approximate 18-month follow-up period between 2015-2017 were included. Large differences in no-shows per individual patient record (chi-square = 225, p = <0.001, df = 4) were found across quintiles of ADI. Heat-mapping indicated that census tracts with the highest ADIs and highest rates of no-show appointments encompass Cleveland's inner-city region. ConclusionThe ADI is demonstrated to identify communities at high risk of no-show newborn appointments. Mapping these communities and their socioeconomic distress levels represented by ADI and missed appointment rate for each community can provide future direction for interventions targeted towards these communities to reduce no-show rates and improve overall community infant health.