Managed care COVID-19 outcomes in a population health program.

OBJECTIVES: To determine (1) factors linked to hospitalizations among managed care patients (MCPs), (2) outcome improvement with use of outpatient off-label treatment, and (3) outcome comparison between MCPs and a mirror group. STUDY DESIGN: Retrospective cohort study comparing MCPs with an age- and gender-matched mirror group in Florida from April 1, 2020, to May 31, 2020. METHODS: A total of 38,193 MCPs in a Florida primary care group were monitored for COVID-19 incidence, hospitalization, and mortality. The highest-risk patients were managed by the medical group's COVID-19 Task Force. As part of a population health program, the COVID-19 Task Force contacted patients, conducted medical encounters, and tracked data including comorbidities and medical outcomes. The MCPs enrolled in the medical group were compared with a mirror group from the state of Florida. RESULTS: The mean (SD) age among the MCPs was 67.9 (15.2) years, and 60% were female. Older age and hypertension were the most important factors in predicting COVID-19. Obesity, chronic kidney disease (CKD), and congestive heart failure (CHF) were linked to higher rates of hospitalizations. Patients prescribed off-label outpatient medications had 73% lower likelihood of hospitalization (P < .05). Compared with the mirror group, MCPs had 60% lower COVID-19 mortality (P < .05). CONCLUSIONS: MCPs have risk factors similar to the general population for COVID-19 incidence and progression, including older age, hypertension, obesity, CHF, and CKD. Outpatient treatment with off-label medicines decreased hospitalizations. A comprehensive population health program decreased COVID-19 mortality.

Current Understanding of COVID-19 Clinical Course and Investigational Treatments.

Importance: Currently, there is no unified framework linking disease progression to established viral levels, clinical tests, inflammatory markers, and investigational treatment options. Objective: It may take many weeks or months to establish a standard treatment approach. Given the growing morbidity and mortality with respect to COVID-19, this systemic review presents a treatment approach based on a thorough review of scholarly articles and clinical reports. Our focus is on staged progression, clinical algorithms, and individualized treatment. Evidence Review: We followed the protocol for a quality review article proposed by Heyn et al. (1). A literature search was conducted to find all relevant studies related to COVID-19. The search was conducted between April 1, 2020, and April 13, 2020, using the following electronic databases: PubMed (1809 to present); Google Scholar (1900 to present); MEDLINE (1946 to present), CINAHL (1937 to present); and Embase (1980 to present). The keywords used included COVID-19, 2019-nCov, SARS-CoV-2, SARS-CoV, and MERS-CoV, with terms such as efficacy, seroconversion, microbiology, pathophysiology, viral levels, inflammation, survivability, and treatment and pharmacology. No language restriction was placed on the search. Reference lists were manually scanned for additional studies. Findings: Of the articles found in the literature search, 70 were selected for inclusion in this study (67 cited in the body of the manuscript and 3 additional unique references in the Figures). The articles represent work from China, Japan, Taiwan, Vietnam, Rwanda, Israel, France, the United Kingdom, the Netherlands, Canada, and the United States. Most of the articles were cohort or case studies, but we also drew upon other information, including guidelines from hospitals and clinics instructing their staff on procedures to follow. In addition, we based some decisions on data collected by organizations such as the CDC, FDA, IHME, IDSA, and Worldometer. None of the case studies or cohort studies used a large number of participants. The largest group of participants numbered <500 and some case studies had fewer than 30 patients. However, the review of the literature revealed the need for individualized treatment protocols due to the variability of patient clinical presentation and survivability. A number of factors appear to influence mortality: the stage at which the patient first presented for care, pre-existing health conditions, age, and the viral load the patient carried. Conclusion and Relevance: COVID-19 can be divided into three distinct stages, beginning at the time of infection (Stage I), sometimes progressing to pulmonary involvement (Stage II, with or without hypoxemia), and less frequently to systemic inflammation (Stage III). In addition to modeling the stages of disease progression along with diagnostic testing, we have also created a treatment algorithm that considers age, comorbidities, clinical presentation, and disease progression to suggest drug classes or treatment modalities. This paper presents the first evidence-based recommendations for individualized treatment for COVID-19.