Discontinuity of Stroke Care in a Black Urban Cohort: Insight from EHR Data.

This poster describes the findings from a study that attempts to characterize an underserved Black stroke cohort who are at risk for discontinuities of care using electronic health record (EHR). Preliminary analysis revealed that 90.1% of the patients were Black.

Survey of Potential Disparity Issues Among Minority Stroke Survivors in Central Brooklyn.

Medical data and information are ubiquitous due to internet availability. However, most people persist in using and trusting their healthcare professionals for health information. They are increasingly flooded with health information from diverse sources such as the internet, community-based organizations, and family or friends.

The Effect of Physicians' Acknowledgement of Clinical Decision Support Systems Generated Alerts on Patient Diabetes Management in a Primary Care Setting.

The purpose of the study is to evaluate whether clinician's acknowledgement and adherence to Clinical Best Practice Advisories (BPA) system's alerts improves the outcome of patients with chronic diabetes. We used deidentified clinical data of elderly (65 or older) diabetes patients with hemoglobin A1C (HbA1C) >= 6.5 that were extracted from the clinical database of a multi-specialty outpatient clinic that also provides primary care services.

Disparities in the Use of Intravenous t-PA among Ischemic Stroke Patients: Population-based Recent Temporal Trends.

Objective: To explore a 5-year comparison of disparities in intravenous t-PA (IV t-PA) use among acute ischemic stroke (AIS) patients based on race, gender, age, ethnic origin, hospital status, and geographic location.

Methods: We extracted patients' demographic information and hospital characteristics for 2010 and 2014 from the New York Statewide Planning and Research Cooperative System (SPARCS). We compared disparities in IV t-PA use among AIS patients in 2010 to that in 2014 to estimate temporal trends.

Evaluation of a Cyber Security System for Hospital Network.

Most of the cyber security systems use simulated data in evaluating their detection capabilities. The proposed cyber security system utilizes real hospital network connections. It uses a probabilistic data mining algorithm to detect anomalous events and takes appropriate response in real-time.