Call for consistent coding in diabetes mellitus using the Royal College of General Practitioners and NHS pragmatic classification of diabetes

Journal of Innovation in Health Informatics

Norah Hassan Sadek¹  Aumran Tahir²  Helen McDonald³  Pete Horsfield⁴  Terry Desombre⁵  Kamlesh Khunti⁶  Simon de Lusignan⁷  Khaled Sadek⁸ 

[1] Academic Foundation Programme Doctor;Clinical Research Fellow;Doctoral Student, School of Hygiene and Tropical Medicine, London, UK;General Practitioner, Primary Care Information Services (PRIMIS), University of Nottingham, UK;Professor of Healthcare Management, Department of Health Care Management and Policy, University of Surrey, Guildford, UK;Professor of Primary Care Diabetes and Vascular Medicine, Department of Health Sciences, University of Leicester, Leicester, UK;Professor of Primary Care and Clinical Informatics, Department of Health Care Management and Policy, University of Surrey, Guildford, UK;Research Registrar, Department of Health Care Management and Policy, University of Surrey, Guildford, UK;

关键词: data quality;    diabetes mellitus;    medical records systems computerised;    records as topic;    vocabulary controlled;    medical informatics;   

DOI  :  10.14236/jhi.v20i2.31

来源: DOAJ

【 摘 要 】

Background The prevalence of diabetes is increasing with growing levels of obesity and an aging population. New practical guidelines for diabetes provide an applicable classification. Inconsistent coding of diabetes hampers the use of computerised disease registers for quality improvement, and limits the monitoring of disease trends.

Objective To develop a consensus set of codes that should be used when recording diabetes diagnostic data.

Methods The consensus approach was hierarchical, with a preference for diagnostic/disorder codes, to define each type of diabetes and non-diabetic hyperglycaemia, which were listed as being completely, partially or not readily mapped to available codes. The practical classification divides diabetes into type 1 (T1DM), type 2 (T2DM), genetic, other, unclassified and non-diabetic fasting hyperglycaemia. We mapped the classification to Read version 2, Clinical Terms version 3 and SNOMED CT.

Results T1DMand T2DM were completely mapped to appropriate codes. However, in other areas only partial mapping is possible. Genetics is a fast-moving field and there were considerable gaps in the available labels for genetic conditions; what the classification calls ‘other’ the coding system labels ‘secondary’ diabetes. The biggest gap was the lack of a code for diabetes where the type of diabetes was uncertain. Notwithstanding these limitations we were able to develop a consensus list.

Conclusions It is a challenge to develop codes that readily map to contemporary clinical concepts. However, clinicians should adopt the standard recommended codes; and audit the quality of their existing records.

【 授权许可】

Unknown