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Data Abstraction Jobs in Michigan (NOW HIRING)

Healthcare Support Staffing

HEDIS Specialist

Troy, MI · On-site

$35 - $40/hr

Under the direction of the HEDIS Program Manager, supports the annual HEDIS project management by coordinating the identification, collection and abstraction of medical records and other data in ...

Optech Us LLC

Java Developer

Auburn Hills, MI · On-site

$48.25 - $62.50/hr

... data storage & access techniques including abstraction layers, DAO's and RDBMS such as SQL Server Strong understanding and demonstrated use of design patterns Strong written & verbal communication ...

OptechUs

Java Developer

Auburn Hills, MI

$48.25 - $62.50/hr

... data storage & access techniques including abstraction layers, DAO's and RDBMS such as SQL Server Strong understanding and demonstrated use of design patterns Strong written & verbal communication ...

BCForward

HEDIS Patient Care Advocate

Auburn Hills, MI · On-site

$32 - $34/hr

Review provider performance data and identify opportunities for quality improvement. * Work with ... Experience with HEDIS review, chart abstraction, or HEDIS measures is highly relevant. Preferred ...

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All JobsData Abstraction JobsData Abstraction Jobs in Michigan

Data Abstraction information

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How much do data abstraction jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for data abstraction in Michigan is $22.08, according to ZipRecruiter salary data. Most workers in this role earn between $16.15 and $27.88 per hour, depending on experience, location, and employer.

What is data abstraction?

Data abstraction is the process of simplifying complex data by extracting relevant information and presenting it in a more manageable form. In many industries, especially healthcare, data abstractors review records and summarize key details into databases for analysis and reporting. This helps organizations make informed decisions by focusing on essential data points without unnecessary details. Data abstraction improves efficiency, accuracy, and data organization.

What are the key skills and qualifications needed to thrive as a data abstractor?

To thrive as a Data Abstractor, you need strong analytical skills, attention to detail, and a background in health information management or a related field, often supported by a relevant certification such as RHIT or RHIA. Familiarity with electronic health records (EHR) systems, data abstraction software, and coding standards like ICD-10 and CPT is typically required. Excellent organizational abilities, problem-solving skills, and clear communication help individuals excel in reviewing and extracting precise data from complex documents. These skills are crucial for ensuring data accuracy, supporting healthcare quality initiatives, and enabling effective decision-making.

What are some common challenges faced by data abstraction professionals, and how can they be addressed?

Data abstraction professionals often encounter challenges such as ensuring the accuracy and consistency of extracted data, navigating incomplete or ambiguous source documents, and staying updated with changing data standards. To address these issues, it's important to develop strong attention to detail, establish clear data abstraction protocols, and participate in regular training sessions. Collaborating closely with quality assurance teams and leveraging technology, such as data abstraction software, can also help maintain high standards and efficiency in the role.

What is the difference between Data Abstraction vs Data Analyst?

AspectData AbstractionData Analyst
Required CredentialsTypically a degree in computer science, information systems, or related fieldsUsually a degree in statistics, mathematics, or related fields
Work EnvironmentSoftware development teams, IT departments, data management projectsBusiness intelligence teams, marketing, finance, and operations departments
Employer & Industry UsageTech companies, software firms, data management organizationsCorporations across various industries, consulting firms, market research

Data Abstraction focuses on simplifying complex data structures in software development, while Data Analysts interpret data to support business decisions. Both roles require analytical skills but serve different purposes within data management and analysis.

How to become a data abstractor?

To become a data abstractor, typically you need a high school diploma or equivalent, strong attention to detail, and good organizational skills. Many employers prefer candidates with experience in healthcare, insurance, or related fields, and familiarity with electronic health records or data management tools. Certification programs are available to enhance skills and job prospects.

What do data abstractors do?

Data abstractors collect, review, and summarize information from various sources such as medical records, documents, or databases to create concise, standardized summaries. They often use specialized software and must ensure accuracy and confidentiality in their work, which is essential in fields like healthcare and research.

What are the most commonly searched types of Data Abstraction jobs in Michigan?

The most popular types of Data Abstraction jobs in Michigan are:

What are popular job titles related to Data Abstraction jobs in Michigan?

For Data Abstraction jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Data Abstraction jobs in Michigan look for?

The top searched job categories for Data Abstraction jobs in Michigan are:

What cities in Michigan are hiring for Data Abstraction jobs?

Cities in Michigan with the most Data Abstraction job openings:

Data Abstraction jobs near you
Infographic showing various Data Abstraction job openings in Michigan as of August 2026, with employment types broken down into 60% Full Time, 27% Part Time, and 13% Contract. Highlights an 73% In-person, and 27% Remote job distribution, with an average salary of $45,922 per year, or $22.1 per hour.

On-Call FIMR Case Abstractor

Western Michigan University

Kalamazoo, MI • On-site

$19.65 - $22.92/hr

Full-time

Posted 4 days ago

Western Michigan University rating

6.7

Company rating: 6.7 out of 10

Based on 30 frontline employees who took The Breakroom Quiz

492nd of 628 rated colleges and universities

Job description

Description
Case abstractions are an important part of Fetal Infant Mortality Reviews (FIMR). They provide vital information regarding maternal and infant medical conditions, treatment and outcomes, as well as social and public health services they receive. All cases reviewed by FIMR require abstraction of medical, social service, court and public health records and integration of this information into a narrative summary for review by the FIMR team. Kalamazoo FIMR reviews an average of 20 fetal and infant deaths a year.
The purpose of the case abstraction is to:
  • Gather information about parents' medical care and psychosocial issues before and during pregnancy.
  • Gather medical and psychosocial information about the events during the infant's life and around the time of death, including the results of death investigations conducted by other agencies such as the Medical Examiner, Child Protective Services and the Office of the Prosecuting Attorney.
  • To accurately summarize and convey this information so that it may be included within the FIMR case summary document.

Requirements
To perform this job successfully, an individual must be able to perform each duty satisfactorily. The requirements listed below are representative of the knowledge, skill, and/or ability required
EDUCATION AND/OR EXPERIENCE:
  • Three (3) years' experience in the medical field
  • Bachelor's degree
  • Valid driver's license

OTHER SKILLS AND ABILITIES:
  • Ability to organize a project calendar and the monthly case abstraction data collection requests and tasks.
  • Ability to navigate medical health information systems to locate relevant medical case data.
  • Ability to write a coherent, organized case summary following the FIMR case template.
  • Ability to accept and apply feedback.
  • Regular and predictable attendance is expected.
  • Demonstrates the ability to recognize priorities in the organization of workflow.
  • Able to perform duties independently, with a minimal need for direct supervision.

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