Unraveling COVID-19: A Large-Scale Characterization of 4.5 Million COVID-19 Cases Using CHARYBDIS.

Purpose: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) Characterizing Health Associated Risks and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. Patients and Methods: We conducted a descriptive retrospective database study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11th June 2020 and are iteratively updated via GitHub. We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19, and 113,627 hospitalized with COVID-19 requiring intensive services. Results: We aggregated over 22,000 unique characteristics describing patients with COVID-19. All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts and are readily available online. Globally, we observed similarities in the USA and Europe: more women diagnosed than men but more men hospitalized than women, most diagnosed cases between 25 and 60 years of age versus most hospitalized cases between 60 and 80 years of age. South Korea differed with more women than men hospitalized. Common comorbidities included type 2 diabetes, hypertension, chronic kidney disease and heart disease. Common presenting symptoms were dyspnea, cough and fever. Symptom data availability was more common in hospitalized cohorts than diagnosed. Conclusion: We constructed a global, multi-centre view to describe trends in COVID-19 progression, management and evolution over time. By characterising baseline variability in patients and geography, our work provides critical context that may otherwise be misconstrued as data quality issues. This is important as we perform studies on adverse events of special interest in COVID-19 vaccine surveillance.

The OneFlorida Data Trust: a centralized, translational research data infrastructure of statewide scope.

The OneFlorida Data Trust is a centralized research patient data repository created and managed by the OneFlorida Clinical Research Consortium ("OneFlorida"). It comprises structured electronic health record (EHR), administrative claims, tumor registry, death, and other data on 17.2 million individuals who received healthcare in Florida between January 2012 and the present. Ten healthcare systems in Miami, Orlando, Tampa, Jacksonville, Tallahassee, Gainesville, and rural areas of Florida contribute EHR data, covering the major metropolitan regions in Florida. Deduplication of patients is accomplished via privacy-preserving entity resolution (precision 0.97-0.99, recall 0.75), thereby linking patients' EHR, claims, and death data. Another unique feature is the establishment of mother-baby relationships via Florida vital statistics data. Research usage has been significant, including major studies launched in the National Patient-Centered Clinical Research Network ("PCORnet"), where OneFlorida is 1 of 9 clinical research networks. The Data Trust's robust, centralized, statewide data are a valuable and relatively unique research resource.

Unraveling COVID-19: a large-scale characterization of 4.5 million COVID-19 cases using CHARYBDIS.

Background: Routinely collected real world data (RWD) have great utility in aiding the novel coronavirus disease (COVID-19) pandemic response [1,2]. Here we present the international Observational Health Data Sciences and Informatics (OHDSI) [3] Characterizing Health Associated Risks, and Your Baseline Disease In SARS-COV-2 (CHARYBDIS) framework for standardisation and analysis of COVID-19 RWD. Methods: We conducted a descriptive cohort study using a federated network of data partners in the United States, Europe (the Netherlands, Spain, the UK, Germany, France and Italy) and Asia (South Korea and China). The study protocol and analytical package were released on 11 th June 2020 and are iteratively updated via GitHub [4]. Findings: We identified three non-mutually exclusive cohorts of 4,537,153 individuals with a clinical COVID-19 diagnosis or positive test, 886,193 hospitalized with COVID-19 , and 113,627 hospitalized with COVID-19 requiring intensive services . All comorbidities, symptoms, medications, and outcomes are described by cohort in aggregate counts, and are available in an interactive website: https://data.ohdsi.org/Covid19CharacterizationCharybdis/. Interpretation: CHARYBDIS findings provide benchmarks that contribute to our understanding of COVID-19 progression, management and evolution over time. This can enable timely assessment of real-world outcomes of preventative and therapeutic options as they are introduced in clinical practice.

Spirometry use in Patients with Sickle Cell Disease with and without asthma and acute chest syndrome: A Multicenter Study.

A de-identified data repository of electronic medical record (EMR) data, i2b2 (Informatics for Integrating Biology and the Bedside), including 4 geographically diverse academic medical centers, was queried to determine the use of diagnostic spirometry testing in African American children and young adults 5-34 years old with sickle cell disease (SCD) with or without a documented history of asthma and/or acute chest syndrome (ACS). A total of 2,749 patients were identified with SCD, of these 577 had asthma and 409 had ACS. Cross-referencing the CPT code for diagnostic spirometry showed that for patients identified as having SCD, a history or ACS, and a diagnosis of asthma, only 31% across all 4 centers had spirometry. Having an asthma diagnosis was associated with ACS. Among SCD patients with asthma, the proportion with ACS for the four centers was 47%, 75%, 38%, and 36% respectively. The bivariate association between asthma and ACS for each Center was significant for each (p<.001). To summarize, only one third of patients with co-morbid SCD, ACS, and asthma received the spirometry procedure as recommended in evidence-based guidelines, suggesting limited testing for changes in pulmonary function. Future studies to determine barriers and facilitators to implementation of pulmonary testing in SCD are warranted.

Prognostic Value of Braden Activity Subscale for Mobility Status in Hospitalized Older Adults.

OBJECTIVE: To evaluate the predictive value of the Activity subscale of the Braden Scale for Predicting Pressure Sore Risk in assessing mobility impairment and recovery among hospitalized older adults. DESIGN: Retrospective cohort study. SETTING: UF Health Shands Hospital, University of Florida, Gainesville, Florida. PATIENTS: 19,769 older adults (≥65 years) hospitalized between January 2009 and April 2014. MEASUREMENTS: Incident mobility impairment and recovery were assessed with the Braden Activity subscale (BAS) score that nurses use to grade patients at every shift change (~3 times/d). Posthospital mortality rate and discharge disposition were used to assess the prognostic value of the BAS. RESULTS: Of the 10,717 study patients observed "walking frequently" at admission, 2218 (20.7%) developed incident mobility impairment. Of the other 9052 study patients, who were impaired at admission, 4734 (52.3%) recovered to a state of walking occasionally or frequently. Older adults who developed mobility impairment during hospitalization had an odds of death higher than that of those who remained mobile (odds ratio [OR], 1.23; 95% confidence interval [CI], 1.08- 1.39). This effect predominately occurred within the first 6 follow-up months. Older adults who recovered from mobility impairment had an odds of death lower than that of those who did not recover mobility in the hospital (OR, 0.54; 95% CI, 0.49-0.59). This effect was slightly stronger within the first 6 months after hospitalization. CONCLUSIONS: Nurses' BAS assessment of mobility status during hospitalization provides substantial prognostic value in hospitalized older adults. The BAS could be an efficient and valuable source of information about mobility status for targeting posthospital care of older adults. Journal of Hospital Medicine 2017;12:396-401.

In-Hospital Mobility Variations Across Primary Diagnoses Among Older Adults.

OBJECTIVES: To examine the relationship between primary diagnoses and mobility impairment and recovery among hospitalized older adults. DESIGN: Prospective cohort study. SETTING: UF Health Shands Hospital, an 852-bed level I trauma center located in Gainesville, Florida. PARTICIPANTS: A total of 18,551 older adults (≥65 years) with 29,148 hospitalizations between January 2009 and April 2014. MEASUREMENTS: Incident and discharge mobility impairment and recovery were assessed using the Braden activity subscale score that was recorded by the nursing staff at every shift change: approximately 3 times per day. Primary diagnosis ICD-9 codes were used as predictors and recategorized by using the Agency for Health Care Research and Quality Clinical Classification Software. RESULTS: Of the 15,498 hospital records in which the patient was initially observed to "walk frequently," 3186 (20.6%) developed incident mobility impairment (chair-fast or bedfast). Primary diagnoses with a surgical or invasive procedure were the most prevalent (77.2%) among the hospital observations with incident mobility impairment; otherwise, primary diagnoses without surgery were much more associated with discharge mobility impairment (59%). The highest incidence of mobility impairment occurred in patients with heart valve disorders and aortic and peripheral/visceral artery aneurysms (6.24 and 6.05 events per 30 person-days, respectively); septicemia showed the highest incidence rate for mobility limitation at discharge (0.94 events per 30 person-days). Mobility impairment was observed in 13,650 (46.8% of total) records at admission and 5930 (43.44%) were observed to recover to a state of walking occasionally or frequently. Osteoarthritis and cancer of gastrointestinal organs/peritoneum had the highest incidence rate for mobility recovery (7.68 and 5.63 events per 30 person-days respectively). CONCLUSIONS: Approximately 1 of 5 patients who were mobile at admission became significantly impaired during hospitalization. However, approximately half (43.4%) of patients observed to have mobility impairment at admission recovered during hospitalization. Conditions most associated with mobility impairment and recovery are varied, but older patients hospitalized for septicemia and cardiovascular diseases with surgery (heart valve disorders and aortic/peripheral/visceral artery aneurysms) appear to be at most risk for incident mobility impairment that did not recover at discharge.

Integrating "big data" into surgical practice.

'Big data' is the next frontier of medicine. We now have the ability to generate and analyze large quantities of healthcare data. Although interpreting and integrating this information into clinical practice poses many challenges, the potential benefits of personalized medicine are seemingly without limit.