Data Analyst, Population Health Management

One Brooklyn Health•New York, NY

About The Position

Reporting to the SVP for Population and Community Health, this position works collaboratively across teams to develop and maintain data collection, measurement tools and databases to support data analysis in support of population health, community health and managed care initiatives. As part of the ongoing work of One Brooklyn Health to transform healthcare delivery in Central Brooklyn, the Population and Community Health team works to eliminate racial and gender health inequities rooted in historical and contemporary injustices, by improving health outcomes, addressing social drivers and using data for advocacy.

Requirements

Bachelor's Degree BA/BS in computer science, statistics, and/or public health or related field (required).
Fluent in MS Office, including MS Excel and MS PowerPoint.
Experience with EPIC Reporting.
Strong conceptual analytical and quantitative skills.
Strong data collection, manipulation, and analysis skills.
An informed perspective on embedding and applying a racial and gender justice lens in decision-making, planning and implementation.
Familiarity with SQL programming language concepts
Experience with health insurance claims structure and analytics, including GPRO/HEDIS Quality measures, risk adjustment methodologies, efficiency of care and utilization metrics.
Experience with large data sets, clinical quality measures, and claims analysis.
Experience with data sets typically found in a health plan environment, including claims data, care management and care planning data, provider network management data, etc.
Intermediate to Advanced level knowledge of Microsoft Office Suite including Excel, Word and PowerPoint.
Advanced skills in Excel and ease with data management concepts (i.e. MS Access, SQL).
Skill in oral and written communication and time management with ability to effectively present to and facilitate groups
Experience presenting technical data and information to non-technical users.
Working knowledge of finance, accounting, financial models, healthcare data, market and competitive analysis techniques
Interest in and active pursuit of opportunities to learn and grow, and ability to handle multiple demands, shifting priorities, crises, and rapid change.

Nice To Haves

Master's Degree Master’s in Business, Health Administration, Finance or other preferred.
5 years Minimum of five (5) to ten (10) years of experience working with data visualization software such as Tableau, Power BI, Qlik, etc. preferred.
3 years Minimum of three (3) to five (5) years of experience working with statistical programming languages such as R or Python (Preferred)
Knowledge of CMS, TJC and other applicable regulations.

Responsibilities

Designing and building population health data set processes for purposes such as modeling, production or mining.
Performing and interpreting population health data studies to learn more about new data sources or new uses for existing ones.
Develop reports, dashboards, scorecards, and other analytics results as necessary to support activities related to population health and other strategic goals.
Analyze, interpret and generate reports on performance related to overall outcomes, utilization, risk adjusted total costs of care, population health and care coordination.
Support the analysis of data from multiple sources, primarily claims files associated with value-based contracts.
Provide insight for informed decision-making and planning by identifying trends/patterns within complex data sets and visualizing and deploying the data to appropriately inform stakeholders.
Develop innovative recommendations to achieve successes related to population health management initiatives and impact quality and efficiency in the delivery model, resulting in a positive impact to clinical and financial outcomes.
Serve as subject matter expert to support the population health needs regarding claims data, value-based contracts, and quality data.
Develop and maintain quality control standards and data reconciliation techniques for internal and external reporting.
Create and maintain documentation relating to data management including training guides, report specifications, and data dictionaries.
Adhere to reporting deadlines for assigned reports.