Structuring and coding in health care records: a qualitative analysis using diabetes as a case study.

Area of Science:

• Health Informatics
• Diabetes Management
• Electronic Health Records

Background:

• Diabetes mellitus poses a growing global health burden.
• Electronic health records (EHRs) are crucial for information sharing and patient self-management.
• Effective structuring and coding of EHR data are essential for maximizing benefits.

Purpose of the Study:

• To investigate the structuring and coding of adult diabetes records in the UK National Health Service (NHS).
• To explore stakeholder perceptions of current practices in diabetes EHR documentation.
• To identify barriers and facilitators for optimal EHR data utilization.

Main Methods:

• Qualitative, theoretically informed case study approach.
• Data collection through semi-structured interviews (n=22), on-site observations (n=4), systems demonstrations, and documentary analysis.
• Focus on family practice and hospital settings in England.

Main Results:

• Stakeholders recognized significant benefits of structured, coded diabetes data for secondary uses (research, audit, public health) and potential clinical gains.
• Marked disparities in data structuring and coding levels were observed between family practices (high) and hospitals (lower).
• Limited evidence of structured/coded data being used to improve inter-setting information sharing.

Conclusions:

• High levels of data structuring and coding in diabetes EHRs hold untapped potential for improved healthcare.
• Hospitals require enhanced health information technology infrastructure and systems use to align with family practices.
• Learning from successful UK developments can optimize EHR data exploitation for diabetes care.