Increased Incidence of Vestibular Disorders in Patients With SARS-CoV-2.

Objective: Determine the incidence of vestibular disorders in patients with SARS-CoV-2 compared to the control population. Study Design: Retrospective. Setting: Clinical data in the National COVID Cohort Collaborative database (N3C). Methods: Deidentified patient data from the National COVID Cohort Collaborative database (N3C) were queried based on variant peak prevalence (untyped, alpha, delta, omicron 21K, and omicron 23A) from covariants.org to retrospectively analyze the incidence of vestibular disorders in patients with SARS-CoV-2 compared to control population, consisting of patients without documented evidence of COVID infection during the same period. Results: Patients testing positive for COVID-19 were significantly more likely to have a vestibular disorder compared to the control population. Compared to control patients, the odds ratio of vestibular disorders was significantly elevated in patients with untyped (odds ratio [OR], 2.39; confidence intervals [CI], 2.29-2.50; P < 0.001), alpha (OR, 3.63; CI, 3.48-3.78; P < 0.001), delta (OR, 3.03; CI, 2.94-3.12; P < 0.001), omicron 21K variant (OR, 2.97; CI, 2.90-3.04; P < 0.001), and omicron 23A variant (OR, 8.80; CI, 8.35-9.27; P < 0.001). Conclusions: The incidence of vestibular disorders differed between COVID-19 variants and was significantly elevated in COVID-19-positive patients compared to the control population. These findings have implications for patient counseling and further research is needed to discern the long-term effects of these findings.

tranSMART: An Open Source Knowledge Management and High Content Data Analytics Platform.

The tranSMART knowledge management and high-content analysis platform is a flexible software framework featuring novel research capabilities. It enables analysis of integrated data for the purposes of hypothesis generation, hypothesis validation, and cohort discovery in translational research. tranSMART bridges the prolific world of basic science and clinical practice data at the point of care by merging multiple types of data from disparate sources into a common environment. The application supports data harmonization and integration with analytical pipelines. The application code was released into the open source community in January 2012, with 32 instances in operation. tranSMART's extensible data model and corresponding data integration processes, rapid data analysis features, and open source nature make it an indispensable tool in translational or clinical research.

Linking test ordering with order tracking: closing the loop in ambulatory care.

Test non-completion decreases quality of care and accounts for many diagnosis-related malpractice claims. Currently, clinicians using Partners' electronic Longitudinal Medical Record (LMR) can track results but lack a mechanism for tracking non-completed tests. This pilot intervention will study an "order tracking" functionality that flags newly-ordered tests and will lead to generation of written patient reminders if tests are not completed within pre-specified timeframes. If test completion rates improve, we will pursue development of a dedicated LMR application.

The Acute Respiratory Infection Quality Dashboard: a performance measurement reporting tool in an electronic health record.

Quality reporting tools, integrated with electronic health records, can help clinicians understand performance, manage populations, and improve quality. The Acute Respiratory Infection Quality Dashboard (ARI QD) for LMR users is a secure web report for performance measurement of an acute condition delivered through a central data warehouse and custom-built reporting tool. Pilot evaluation of the ARI QD indicates that clinicians prefer a quality report that combines not only structured data regarding diagnosis and antibiotic prescribing rates entered into EHRs but one that also shows billing data. The ARI QD has the potential to reduce inappropriate antibiotic prescribing for ARIs.

The coronary artery disease quality dashboard: a chronic care disease management tool in an electronic health record.

Quality reporting tools, integrated with ambulatory electronic health records (EHRs), may help clinicians understand performance, manage populations, and improve quality. The Coronary Artery Disease Quality Dash board (CAD QD) is a secure web report for performance measurement of a chronic care condition delivered through a central data warehouse and custom-built reporting tool. Pilot evaluation of the CAD Quality Dash board indicates that clinicians prefer a quality report that combines not only structured data from EHRs but one that facilitates actions to be taken on individual patients or on a population, i.e., for case management.

Report Central: quality reporting tool in an electronic health record.

Quality reporting tools, integrated with ambulatory electronic health records, can help clinicians and administrators understand performance, manage populations, and improve quality. Report Central is a secure web report delivery tool built on Crystal Reports XItrade mark and ASP.NET technologies. Pilot evaluation of Report Central indicates that clinicians prefer a quality reporting tool that is integrated with our home-grown EHR to support clinical workflow.