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

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: T1DM and T2DM were completely mapped to appropriate codes. However, in other areas only partial mapping is possible. Genetics is a fastmoving 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.

Identifying and establishing consensus on the most important safety features of GP computer systems: e-Delphi study.

Our objective was to identify and establish consensus on the most important safety features of GP computer systems, with a particular emphasis on medicines management. We used a two-round electronic Delphi survey, completed by a 21-member multidisciplinary expert panel, all from the UK. The main outcome measure was percentage agreement of the panel members on the importance of the presence of a number of different safety features (presented as clinical statements) on GP computer systems. We found 90% or greater agreement on the importance of 32 (58%) statements. These statements, indicating issues considered to be of considerable importance (rated as important or very important), related to: computerised alerts; the need to avoid spurious alerts; making it difficult to override critical alerts; having audit trails of such overrides; support for safe repeat prescribing; effective computer-user interface; importance of call and recall management; and the need to be able to run safety reports. The high level of agreement among the expert panel members indicates clear themes and priorities that need to be addressed in any further improvement of safety features in primary care computing systems.

Generating information from electronic patient records in general practice: a description of clinical care and gender inequalities in coronary heart disease using data from over two million patient records.

OBJECTIVES: To describe the epidemiology of coronary heart disease (CHD) in England and the activity of primary healthcare teams in managing patients with CHD, and also to demonstrate the utility of computerised patient records in providing access to epidemiological data and data reflecting healthcare activity. DESIGN: A descriptive survey of CHD and related clinical data, recorded using computerised clinical records, entered by primary healthcare teams. Aspects reported include prevalence of CHD, together with additional data reflecting clinical monitoring activity, therapeutic interventions and comorbidity in patients affected by CHD. SETTING: 317 general practices in 23 English primary care trusts (PCTs). DATA ACQUISITION: MIQUEST was used to interrogate 2 252 274 computerised patient records. Data were extracted in the form of sex and age aggregated counts of patients meeting a range of extraction criteria. RESULTS: The observed crude prevalence of CHD is 40.3 per 1000 (males 46.6, females 34.2). A variety of findings are presented relating to the treatment, monitoring and comorbidities of CHD. Significant and systematic gender inequalities are demonstrated to exist in the monitoring and treatment of CHD. CONCLUSIONS: Extraction of data from computerised patient records is a valuable and practicable method of generating information to inform clinicians and National Health Service (NHS) organisations. Systematic gender disparities exist in the care delivered to patients with CHD.