Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized With COVID-19 in the New York City Area.

Importance: There is limited information describing the presenting characteristics and outcomes of US patients requiring hospitalization for coronavirus disease 2019 (COVID-19). Objective: To describe the clinical characteristics and outcomes of patients with COVID-19 hospitalized in a US health care system. Design, Setting, and Participants: Case series of patients with COVID-19 admitted to 12 hospitals in New York City, Long Island, and Westchester County, New York, within the Northwell Health system. The study included all sequentially hospitalized patients between March 1, 2020, and April 4, 2020, inclusive of these dates. Exposures: Confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by positive result on polymerase chain reaction testing of a nasopharyngeal sample among patients requiring admission. Main Outcomes and Measures: Clinical outcomes during hospitalization, such as invasive mechanical ventilation, kidney replacement therapy, and death. Demographics, baseline comorbidities, presenting vital signs, and test results were also collected. Results: A total of 5700 patients were included (median age, 63 years [interquartile range {IQR}, 52-75; range, 0-107 years]; 39.7% female). The most common comorbidities were hypertension (3026; 56.6%), obesity (1737; 41.7%), and diabetes (1808; 33.8%). At triage, 30.7% of patients were febrile, 17.3% had a respiratory rate greater than 24 breaths/min, and 27.8% received supplemental oxygen. The rate of respiratory virus co-infection was 2.1%. Outcomes were assessed for 2634 patients who were discharged or had died at the study end point. During hospitalization, 373 patients (14.2%) (median age, 68 years [IQR, 56-78]; 33.5% female) were treated in the intensive care unit care, 320 (12.2%) received invasive mechanical ventilation, 81 (3.2%) were treated with kidney replacement therapy, and 553 (21%) died. As of April 4, 2020, for patients requiring mechanical ventilation (n = 1151, 20.2%), 38 (3.3%) were discharged alive, 282 (24.5%) died, and 831 (72.2%) remained in hospital. The median postdischarge follow-up time was 4.4 days (IQR, 2.2-9.3). A total of 45 patients (2.2%) were readmitted during the study period. The median time to readmission was 3 days (IQR, 1.0-4.5) for readmitted patients. Among the 3066 patients who remained hospitalized at the final study follow-up date (median age, 65 years [IQR, 54-75]), the median follow-up at time of censoring was 4.5 days (IQR, 2.4-8.1). Conclusions and Relevance: This case series provides characteristics and early outcomes of sequentially hospitalized patients with confirmed COVID-19 in the New York City area.

Designing a Clinical Data Warehouse Architecture to Support Quality Improvement Initiatives.

Clinical data warehouses, initially directed towards clinical research or financial analyses, are evolving to support quality improvement efforts, and must now address the quality improvement life cycle. In addition, data that are needed for quality improvement often do not reside in a single database, requiring easier methods to query data across multiple disparate sources. We created a virtual data warehouse at NewYork Presbyterian Hospital that allowed us to bring together data from several source systems throughout the organization. We also created a framework to match the maturity of a data request in the quality improvement life cycle to proper tools needed for each request. As projects progress in the Define, Measure, Analyze, Improve, Control stages of quality improvement, there is a proper matching of resources the data needs at each step. We describe the analysis and design creating a robust model for applying clinical data warehousing to quality improvement.

A competency-based curriculum to acculturate biomedical informatics students to the practice of medicine.

Biomedical informatics students who choose to study clinical information systems may not have significant clinical experience. A course was designed to "acculturate" these students to the practice of medicine through case-based presentations that span three competency areas: biomedicine, clinical workflow and practice, and applications in clinical informatics.

Architectural design of a data warehouse to support operational and analytical queries across disparate clinical databases.

As the clinical data warehouse of the New York Presbyterian Hospital has evolved innovative methods of integrating new data sources and providing more effective and efficient data reporting and analysis need to be explored. We designed and implemented a new clinical data warehouse architecture to handle the integration of disparate clinical databases in the institution. By examining the way downstream systems are populated and streamlining the way data is stored we create a virtual clinical data warehouse that is adaptable to future needs of the organization.