AHA Coding Clinic® for ICD-9 - 1989 Second Quarter
Data Quality
by Meryl Bloomrosen Director, Health Information Services Aspen Systems Corporation The important role of medical record coding in financial payment to health care providers cannot be disputed. Federal regulations, such as the implementation of the Medicare Prospective Payment System (PPS) in 1983, requiring hospitals to code using ICD-9-CM diagnosis and procedure codes, and continuing with the Catastrophic Coverage Act in 1988, requiring physicians to use ICD-9-CM diagnosis codes in order to receive reimbursement, are clear signals that coded data are vital to the fiscal solvency of providers. Such regulations have placed increasing pressures and responsibilities on the medical record...
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Article Overview
This article explains why data quality matters in medical record coding and abstracting and outlines a framework for internal controls within a health information department. It is geared toward coding professionals, HIM leaders, and administrators who manage coding workflows, education, productivity monitoring, and quality review processes. The discussion covers staffing qualifications, reference resources, continuing education, productivity measurement, formal policies and procedures, and retrospective quality studies in the context of hospital and physician coding requirements.
Why This Topic Matters
Reliable coded data affects reimbursement, operational reporting, quality review, and organizational planning. Understanding the broad elements of a data quality program helps departments support accurate, consistent, and timely coding practices.
Article Sections
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Personnel
Discusses staffing considerations for coding functions, including training, experience, and support for new coders.
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Resources
Covers the reference materials, current guidance sources, and administrative supports that help coders stay informed.
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Other references
Notes additional instructional and historical resources that can support coding work and answer questions.
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Education
Describes ongoing education approaches for coding staff and ways to keep them current on changing guidance.
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Productivity measures
Addresses ways to monitor coding volume, efficiency, and the relationship between productivity and quality.
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Formalized quality control procedures
Summarizes the need for written policies, standardized workflows, and coordination across departments.
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Retrospective data quality studies
Explains periodic review approaches used to evaluate coding performance and support improvement efforts.
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Conclusion
Provides a closing overview of the importance of credible, accurate coded data for internal and external uses.
What You Will Learn
- How internal data quality programs support coding and abstracting work
- What types of staff support and reference resources are important for coding departments
- Why ongoing education and productivity monitoring are part of data quality management
- How formal review processes and retrospective studies fit into coding quality programs
Who Should Read This
- Health information management professionals
- Medical coders
- Coding supervisors and managers
- Hospital administrators
- Quality assurance staff
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