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Position Summary:

The Health Data Analyst will join a dynamic and collaborative team of data analysts, clinicians, epidemiologists, and information technology (IT) professionals. The analyst manages, analyzes, interprets, presents and visualizes clinical, public health, financial and operational data from a variety of data sources in order to improve healthcare and public health activities at the university. This position collaborates across campus with clinical, analytic, IT and public health professionals to improve health care and public health at the University of Michigan.

Responsibilities*

The primary duties are data extraction, cleaning, analysis, visualization, reporting and communication using the electronic medical record and various health databases and data warehouses as data sources.

Data Management, Analysis, and Reporting (90%)

Extract data from medical records and other data sources (including but not limited to Wolverine Wellness, Michigan Housing, DPSS, Office of the Registrar). Ensure workflow integrity by using secure connections at all opportunities.

Design and implement health-related surveys using tools such as Qualtrics.

Respond to data inquiries from health and wellness leadership, UHC clinicians and counselors, and others in the health and wellness portfolio.

Create, manipulate and monitor dashboards and reports (using software such as Tableau and Excel) to ensure timely and accurate information. The target audiences for these may include UHC clinicians and counselors, health and wellness leadership, and external stakeholders such as the county health department.

Link data from a variety of data systems (including medical records, student records, and other health-related data systems) based on a key identifier.

Identify and analyze trends in data using graphics and statistical testing.

Conduct data cleaning activities to include reconciliation of multiple and sometimes conflicting data sources, periodic review of dashboards and reports for accuracy; manual review of medical records to resolve data concerns and ensure accurate information and data integrity.

Perform statistical analyses, including basic descriptive statistics, and more advanced univariate and multivariate analyses, using software such as R or SAS.

Prepare reports at regular intervals for various stakeholders including health and wellness, student life and university leadership, and state and local health departments.

Design, develop, and regularly update data visualizations, such as static graphs and dynamic dashboards, to communicate information to key decision makers.

Maintain privacy and confidentiality of all information in line with HIPAA and FERPA guidelines.

Other duties as assigned.

Partnership and Collaboration (10%)

Collaborate with UHC managers, Wolverine Wellness health promotion specialists, and public health and data professionals.

Liaise with partners in Environment, Health & Safety, School of Public Health, Michigan Medicine, local health departments, the Office of the Registrar, Student Life Tech Services, ITS, HITS, and other campus partners.

Integrate feedback/other requested components into dashboards and reports.

Required Qualifications*:

Bachelor's degree in a related field

2 years of experience in a healthcare or public health setting where a significant component of the work was data analysis and interpretation, including statistical analysis

Desired Qualifications*:

Master's degree in epidemiology or biostatistics or a related field

Knowledge of Epic/MiChart; experience using Epic Clarity, Caboodle, and reporting Workbench

Experience with data warehousing and business intelligence tools such as Clarity (Clarity certification highly desired)

Experience using programming languages such as SQL and Python

Advanced experience with software tools such as Microsoft Office, OneDrive, SharePoint, etc.

Experience managing and linking large data sets

Ability to write clear and concise analytical summaries of methodologies and statistical results

Working knowledge of public health and epidemiologic concepts

Advanced experience with statistical analysis (using tools such as SAS, SPSS, R)

Advanced experience with data visualization methods and programs (R, Tableau, etc.)

Knowledge of informed consent and confidentiality

Experience with quality and process improvement

Familiarity with application program interfaces (APIs) and automated data pulls and processing

Experience with survey methodologies and online survey tools