Business Systems Analyst Sr

Business Systems Analyst Senior

The University of Michigan Medical School (UMMS) and University of Michigan Medical Group (UMMG) are seeking a Business Systems Analyst Senior to serve as a high-impact, trusted advisor to leadership across UMMS, UMMG, and the clinical enterprise. Reporting to the Senior Director of Faculty Compensation, Compliance, and Analytics, you will own a broad portfolio of analytical workstreams that directly support Michigan Medicine's fiscal health and success across the tripartite mission.

Candidates for this position will be expected to quickly develop expertise for the primary data sources of faculty appointments, demographics, clinical productivity (wRVUs, grid utilization, visit lengths), clinical EMR data (e.g., CPT codes), productivity and compensation benchmarks, faculty effort, and clinical FTE (cFTE), among others. Candidates must have confidence working independently across complex data environments and in using a range of tools and coding languages (e.g., SQL, R, Python) to quickly expose root causes and offer novel solutions. Candidates must be creative, resilient, and curious. Faculty productivity drives the largest sources of revenue for Michigan Medicine. In this highly autonomous role, you will become the primary subject matter expert on faculty clinical productivity data.

Responsibilities

• Strategic Data Operations (75%)
• Program Ownership
  • Lead the day-to-day data operations for the faculty clinical productivity analytics program, managing the full lifecycle from requirements gathering to automated reporting.
  • Identify project timelines and dependencies, proactively provide limitations and key assumptions, and conduct data quality audits at every stage in each project
  • Lead annual maintenance and quality assurance processes
• Clinical FTE (cFTE) Leadership
  • Co-direct the data operations for the cFTE program, maintaining vendor relationships with QGenda and establishing best practice guidelines for departments
  • Actively engage the vendor to ensure alignment with the data model and data quality standards for the transformation of QGenda scheduling data into expected and actual session data
  • Via routine reporting, ensure that all departments/divisions are utilizing QGenda as minimally required for cFTE data to output as intended
  • Collaborate with the QGenda user community to develop best practice guidelines
  • Engage stakeholders to operationalize best practices
  • Oversee any HITS-related dependencies work as the lead UMMS and UMMG representative
  • Maintain data quality workbooks for each department/specialty to ensure minimum quality standards are being met
  • Engage and educate stakeholders on the cFTE data model, data definitions, and routine maintenance expectations
  • Serve as the first point of contact for troubleshooting errors and technical problems
  • Perform monthly and routine data quality audits
• Faculty Data Mart and Analytics
  • Co-lead the analytical and reporting components of the faculty data and reporting initiative
  • Identify reporting platform (e.g., Tableau)
  • Develop, seek feedback, iterate, and send to production a full suite of faculty data reports
  • Develop a routine data quality program to ensure that all reports are refreshed monthly/on the correct cadence, and do not break
  • Create stakeholder engagement strategies to ensure that the medical school and clinical enterprise community are aware of available faculty reporting
  • Co-lead engagement with stakeholders in Revenue Cycle, Ambulatory Analytics, Quality Analytics, among others, to identify opportunities to break down silos, integrate data sources, and ensure that stakeholders are utilizing validated sources of faculty data
• Advanced Dashboarding and Reporting
  • Under the direction of the Chief Physician Officer and the Senior Director of Compensation, Compliance, and Analytics, lead the development of a suite of faculty productivity, compensation, cost, and other financial analyses, metrics, and dashboards
  • Develop centralized metrics and reports that tie together the ways that all faculty-generated costs and revenues interconnect and interplay across the enterprise
  • Support the investigation and development of these novel analyses and metrics
  • Once vetted and finalized, develop stable reporting that can be cascaded, as directed, to other Michigan Medicine leaders
  • Co-lead faculty data quality management efforts
• Routine Data Quality
  • Ensure adherence to quality standards and facilitate improvement efforts.
  • Follow all appropriate data quality and security guidelines
  • Proactively engage stakeholders to ensure that only approved and maintained data sets, dashboards, and metrics are being used across the enterprise
• Technical Assistance & Ad Hoc Analytics (20%)
• Act as the lead analyst for clinical productivity inquiries from senior UMMS and UMMG executives
• Manage efforts on behalf of UMMS and UMMG to engage stakeholders from across Michigan Medicine to identify opportunities to increase the efficiency and accuracy of faculty data as it moves throughout the organization
• Work with other analysts, data managers, and business systems analysts to improve the use of faculty data, reports, and analytics
• Other Duties as Assigned (5%)
• Committee Engagement: Participate in committees focused on data governance, interpretation, and process improvements.
• Mentorship: Provide operational support and mentorship to other analysts within the medical school and clinical enterprise.

Required Qualifications

• Bachelor's Degree or equivalent professional experience in a quantitative field like Public Health, Business Intelligence, Computer Science, Informatics, Engineering, Biostatistics, Public Policy, Economics.
• Advanced skills in querying and transforming data directly from databases via SQL, R, Python, and Excel-get and transform, etc.
• Advanced skills in navigating data warehouse architecture and creating stable data tables, materialized views, and connected Excel workbooks
• Proven track record working autonomously in a fast-paced, quickly changing environment with multiple competing tasks and priorities
• Success working simultaneously with multiple stakeholders at both senior and lateral levels
• Proven track record of being able to tackle complex analytical and operational data problems
• Excellent verbal, written, and presentation skills

Desired Qualifications

• Master's Degree in a quantitative field like Public Health, Business Intelligence, Computer Science, Informatics, Engineering, Biostatistics, Public Policy, or Economics.
• Deep expertise and fluency in tools and languages such as SQL, R, Python, and Excel-get and transform, etc.
• Experience developing complex faculty data models and materialized views at an academic medical center, comprised of such data as faculty appointments, productivity, compensation, effort, and other related faculty data
• Experience working with and supporting a clinical FTE program
• High degree of fluency with faculty productivity and compensation benchmarks (e.g., AAMC, AMGA, MGMA, CPSC, etc.) and the manner in which they are structured by specialty, degree, rank, etc.

Why Join Michigan Medicine?

Michigan Medicine is one of the largest health care complexes in the world and has been the site of many groundbreaking medical and technological advancements since the opening of the U-M Medical School in 1850. Michigan Medicine is comprised of over 30,000 employees and our vision is to attract, inspire, and develop outstanding people in medicine, sciences, and healthcare to become one of the world's most distinguished academic health systems. In some way, great or small, every person here helps to advance this world-class institution. Work at Michigan Medicine and become a victor for the greater good.

What Benefits can you Look Forward to?

• Excellent medical, dental and vision coverage effective on your very first day
• 2:1 Match on retirement savings

Modes of Work

Positions that are eligible for hybrid or mobile/remote work mode are at the discretion of the hiring department. Work agreements are reviewed annually at a minimum and are subject to change at any time, and for any reason, throughout the