University of Michigan Health System
Research Informatics Specialist
University of Michigan Health System, Ann Arbor, Michigan, us, 48113
How to Apply
A cover letter is required for consideration for this position and should be attached as the first page of your resume. The cover letter should address your specific interest in the position and outline skills and experience that directly relate to this position.
Job Summary The Research Informatics Specialist (RIS) will play a vital role in supporting clinical trials and research initiatives by developing and validating clinical phenotypes (i.e., patient or clinical care attributes derived from multiple EHR data sources using an algorithmic approach with a coding framework), as well as ensuring the quality and accuracy of EHR-derived data within the MPOG registry. This position is well-suited for candidates with a strong clinical background who can offer valuable insights from patient care settings and possess familiarity with diverse healthcare systems. MPOG utilizes computed EHR phenotypes to identify cases and ascertain clinical practice patterns and outcomes for research and quality improvement efforts. The RIS will leverage their clinical experience to specify, develop, and validate (through clinical review) both new and existing EHR phenotypes, ensuring outputs are accurate and meaningful in research contexts. As new data types are incorporated into the MPOG registry, the RIS will also provide guidance on mapping, defining, storing, and organizing clinical data to support future analyses. Success in this role requires bridging clinical expertise with informatics, applying knowledge of patient care and medical terminology to effectively organize and leverage data for a wide range of research projects.
The RIS will also engage in scholarly activities, such as (i) conducting comprehensive literature reviews to inform research study design, (ii) performing post-hoc research data cleaning, to ensure rigorous analysis and (iii) investigation of research data processes, including peer reviewed medical literature. The selected candidate will collaborate with multidisciplinary teams on various research initiatives, contributing clinical and informatics expertise to advance scientific understanding in perioperative care. Furthermore, there will be opportunities to co-author peer-reviewed manuscripts, offering valuable experience in academic publishing and enhancing the candidates professional profile within the medical and research communities.
Responsibilities Clinical Trial & Data Support
Collaborate with investigators and research facilitators to ensure trial-relevant data elements are accurately captured, validated, and represented in the MPOG registry
Identify data gaps in the current registry and develop plans to acquire and clean data from multiple sources (EHR, administrative records, anesthesia information management systems) to facilitate research projects
Translate SQL code for phenotypes into plain-text specifications that are easily understood by both researchers and clinicians, working collaboratively with software developers to ensure accuracy,
Participate in protocol feasibility reviews and study design discussions with clinical and research teams
Build strong relationships with software developers and clinicians to assess and address data needs
Clearly communicate and present resource requirements to MPOG Director(s) to ensure the success of clinical trials and research projects
Support team members in understanding strengths and weaknesses of clinical care documentation practices for accurate interpretation of database query results
Literature Reviews & Scientific Writing
Conduct comprehensive literature reviews to inform research design, data analysis strategies, and the development of clinical phenotypes
Contribute to the writing, editing, and organization of peer-reviewed manuscripts and abstracts, serving as a co-author on publications
Assist in the preparation of grant applications and other scholarly communications
Critically evaluate scientific publications and summarize key findings relevant to perioperative outcomes and clinical informatics
Identify research gaps, propose new research questions, and help inform protocol development
Research Data Cleaning and Quality Inspection
Perform post-hoc reviews of data subsequently collected for research projects, to characterize remaining gaps in EHR phenotype data quality that may lead to either (i) continued refinement of the EHR phenotype coding, or (ii) communication with statisticians to modify the study design (e.g. new inclusion/exclusion criteria, techniques for handling missing data, sensitivity analyses using modified EHR phenotype definitions, etc.)
Create data visualizations (e.g. histograms, scatterplots, run charts) to identify potential gaps and biases in EHR data quality specific to a single institution or date range during the study period
Required Qualifications
A graduate degree in a clinical healthcare-related field (e.g., CRNA, MBBS, MD, DO) with experience in perioperative patient care as a provider
Five or more years of experience working with large-scale electronic health record datasets
Strong knowledge of real-world healthcare data (EHR, procedures, claims) and its application in clinical research and QI initiatives.
Proficient in data analysis tools (Microsoft Excel, Tableau, Power BI, or another interactive data visualization platform)
Advanced proficiency in Microsoft Office Suite, especially Excel, Access, and PowerPoint, and Teams
Proven ability to manage multiple projects and teams concurrently, ensuring timely delivery and high-quality outcomes.
Strong organizational and time-management skills, with the ability to adapt to changing priorities and deadlines.
Excellent verbal, written, and presentation skills, capable of conveying complex data findings to both technical and non-technical audiences.
Desired Qualifications
Familiarity with database structures and Microsoft SQL, as well as familiarity with clinical coding systems such as ICD-10, CPT, and LOINC
Hands‑on experience supporting clinical trials, research protocols, or multicenter research studies
Previous experience critically reviewing and co‑authoring peer‑reviewed manuscripts
Work Locations Arbor Lakes, B1F2, Suite 2200, 4251 Plymouth Rd., Ann Arbor, MI 48105
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 course of employment.
Background Screening Michigan Medicine conducts background screening and pre‑employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third‑party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Pre‑employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U‑M campuses.
Application Deadline Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.
U‑M EEO Statement The University of Michigan is an equal employment opportunity employer.
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Job Summary The Research Informatics Specialist (RIS) will play a vital role in supporting clinical trials and research initiatives by developing and validating clinical phenotypes (i.e., patient or clinical care attributes derived from multiple EHR data sources using an algorithmic approach with a coding framework), as well as ensuring the quality and accuracy of EHR-derived data within the MPOG registry. This position is well-suited for candidates with a strong clinical background who can offer valuable insights from patient care settings and possess familiarity with diverse healthcare systems. MPOG utilizes computed EHR phenotypes to identify cases and ascertain clinical practice patterns and outcomes for research and quality improvement efforts. The RIS will leverage their clinical experience to specify, develop, and validate (through clinical review) both new and existing EHR phenotypes, ensuring outputs are accurate and meaningful in research contexts. As new data types are incorporated into the MPOG registry, the RIS will also provide guidance on mapping, defining, storing, and organizing clinical data to support future analyses. Success in this role requires bridging clinical expertise with informatics, applying knowledge of patient care and medical terminology to effectively organize and leverage data for a wide range of research projects.
The RIS will also engage in scholarly activities, such as (i) conducting comprehensive literature reviews to inform research study design, (ii) performing post-hoc research data cleaning, to ensure rigorous analysis and (iii) investigation of research data processes, including peer reviewed medical literature. The selected candidate will collaborate with multidisciplinary teams on various research initiatives, contributing clinical and informatics expertise to advance scientific understanding in perioperative care. Furthermore, there will be opportunities to co-author peer-reviewed manuscripts, offering valuable experience in academic publishing and enhancing the candidates professional profile within the medical and research communities.
Responsibilities Clinical Trial & Data Support
Collaborate with investigators and research facilitators to ensure trial-relevant data elements are accurately captured, validated, and represented in the MPOG registry
Identify data gaps in the current registry and develop plans to acquire and clean data from multiple sources (EHR, administrative records, anesthesia information management systems) to facilitate research projects
Translate SQL code for phenotypes into plain-text specifications that are easily understood by both researchers and clinicians, working collaboratively with software developers to ensure accuracy,
Participate in protocol feasibility reviews and study design discussions with clinical and research teams
Build strong relationships with software developers and clinicians to assess and address data needs
Clearly communicate and present resource requirements to MPOG Director(s) to ensure the success of clinical trials and research projects
Support team members in understanding strengths and weaknesses of clinical care documentation practices for accurate interpretation of database query results
Literature Reviews & Scientific Writing
Conduct comprehensive literature reviews to inform research design, data analysis strategies, and the development of clinical phenotypes
Contribute to the writing, editing, and organization of peer-reviewed manuscripts and abstracts, serving as a co-author on publications
Assist in the preparation of grant applications and other scholarly communications
Critically evaluate scientific publications and summarize key findings relevant to perioperative outcomes and clinical informatics
Identify research gaps, propose new research questions, and help inform protocol development
Research Data Cleaning and Quality Inspection
Perform post-hoc reviews of data subsequently collected for research projects, to characterize remaining gaps in EHR phenotype data quality that may lead to either (i) continued refinement of the EHR phenotype coding, or (ii) communication with statisticians to modify the study design (e.g. new inclusion/exclusion criteria, techniques for handling missing data, sensitivity analyses using modified EHR phenotype definitions, etc.)
Create data visualizations (e.g. histograms, scatterplots, run charts) to identify potential gaps and biases in EHR data quality specific to a single institution or date range during the study period
Required Qualifications
A graduate degree in a clinical healthcare-related field (e.g., CRNA, MBBS, MD, DO) with experience in perioperative patient care as a provider
Five or more years of experience working with large-scale electronic health record datasets
Strong knowledge of real-world healthcare data (EHR, procedures, claims) and its application in clinical research and QI initiatives.
Proficient in data analysis tools (Microsoft Excel, Tableau, Power BI, or another interactive data visualization platform)
Advanced proficiency in Microsoft Office Suite, especially Excel, Access, and PowerPoint, and Teams
Proven ability to manage multiple projects and teams concurrently, ensuring timely delivery and high-quality outcomes.
Strong organizational and time-management skills, with the ability to adapt to changing priorities and deadlines.
Excellent verbal, written, and presentation skills, capable of conveying complex data findings to both technical and non-technical audiences.
Desired Qualifications
Familiarity with database structures and Microsoft SQL, as well as familiarity with clinical coding systems such as ICD-10, CPT, and LOINC
Hands‑on experience supporting clinical trials, research protocols, or multicenter research studies
Previous experience critically reviewing and co‑authoring peer‑reviewed manuscripts
Work Locations Arbor Lakes, B1F2, Suite 2200, 4251 Plymouth Rd., Ann Arbor, MI 48105
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 course of employment.
Background Screening Michigan Medicine conducts background screening and pre‑employment drug testing on job candidates upon acceptance of a contingent job offer and may use a third‑party administrator to conduct background screenings. Background screenings are performed in compliance with the Fair Credit Report Act. Pre‑employment drug testing applies to all selected candidates, including new or additional faculty and staff appointments, as well as transfers from other U‑M campuses.
Application Deadline Job openings are posted for a minimum of seven calendar days. The review and selection process may begin as early as the eighth day after posting. This opening may be removed from posting boards and filled anytime after the minimum posting period has ended.
U‑M EEO Statement The University of Michigan is an equal employment opportunity employer.
#J-18808-Ljbffr