Clinical Data Analyst Int

Location

• Hybrid position. Travel into office is occasionally required ranging from once a week to once a month, subject to business needs.
• Department Details: While the focus will start on ambulatory analytics, the work that our team focuses on is driven by the strategic initiatives of the organization. This means that the role will have multi-disciplinary components, expansion opportunities, exposure to multiple analytics platforms and leadership exposure.
• Purpose: The Clinical Data Analyst Intermediate designs, analyzes and presents analytical solutions to multidisciplinary teams including but not limited to physicians, administrators and organizational leaders, summarizing population characteristics and outcomes to support data-based decision making throughout the organization to improve elements such as patient care, clinical outcomes and operational throughput. Reporting specifications to be provided by requesting audience, and subsequently discussed within interdepartmental team meetings. Various clinical and administrative systems will be used as the data sources, including but not limited to Epic, Cerner and Medipac. Final aggregation and presentation will be completed through various software packages, including SQL Developer, Qlik and Cognos. The Clinical Data Analyst, Intermediate must ensure reporting logic is accurate and sound by comparing analytical output to data within the source systems, as well as through cross validation to base reports under the direction of the Expert Clinical Data Analyst. The Clinical Data Analyst, Intermediate must be able to work both independently as well as in a team setting. Responsibilities:
• Perform clinical analyses in a team oriented atmosphere and review the analytical outcomes to both clinical and non-clinical audiences
• Identify trends in outcomes, utilization, medical quality and other areas.
• Stay abreast on new solutions relevant to the department through various webinars and intermittent conferences requiring brief travel
• Maintain high level of accuracy and timeliness.
• Identify current /future data challenges, develop meaningful recommendations and provide timely updates on issues encountered.
• Meet deadlines and turnaround times set by department (these deadlines and turnaround times will, at times, require the employee to work until the project is completed, meaning extended daily work hours, extended work weeks, or both).