What is the abdomen? Rationalising clinical and anatomical perspectives using formal semantics.

The meaning of the term 'abdomen' has become increasingly ambiguous, as it has to satisfy the contemporary requirements of natural language discourse, literature, gross and radiological anatomy and its role in ontologies supporting electronic records and data modelling. It is critical that there is an agreed understanding of the semantics of the abdominopelvic cavity, its component volumes including the abdomen proper, true and false pelvic cavities, and its boundaries and regional contents. The expression of part-whole (meronymic) relationships is essential for inferences to be drawn by computer algorithms, but unless these are rigorously reviewed and tested incorrect assumptions are drawn. The SNOMED CT terminology descriptions and hierarchy of anatomical concepts relating to the trunk were scrutinised for ambiguity and sub-optimal relationships using a panel of reference sources. Any identified errors were corrected and the impact of any changes reviewed iteratively by evaluating their effect on dependant hierarchies (modelled with the associated anatomical concepts). Anatomical concepts are generally structured according to a traditional gross standpoint, but in clinical practice covert complex regional notions are frequently used and during the evaluation process a new viewpoint relating to projectional (transmissive) or emissive radiological perspective was identified. The subtle but important differences in the boundaries, volumes and contents of these distinctive perspectives of the 'abdomen' are presented. Three significant complex variants have been identified which relate to the most common uses of the word 'abdomen'. The merits and disadvantages of using 'abdomen' as common synonym to more than one concept (polysemy) are briefly discussed and the solution adopted by SNOMED International described. The review of existing ontologies and academic literature confirmed the frequent varied use of the word 'abdomen', which raises concerns when derived data are increasingly being used remotely from the point of clinical contact, potentially leading to incorrect inferences. The documented regional truncal volumes from an anatomical regional, segmental and cross-sectional perspective have been integrated into a logical and comprehensive model suitable for computer processing. The robust modelling of meronymic hierarchies has to be rigorous to avoid systematic errors and it is thus timely that a proposed standard description of these subtly related volumes and structures is made available for discussion and comment.

A methodology for the functional comparison of coding schemes in primary care.

There has been massive investment in the development of clinical terminologies for use in electronic patient records. However, there has been little published evidence for the added value for primary care that implementation of such a terminology would offer. This paper outlines a methodology that has been used to compare two existing coding schemes (Read codes 5 byte set and Clinical Terms Version 3-CTV3) and demonstrates their relative performance using a certainty-agreement diagram. In the study described, CTV3 offers improved accuracy and consistency with improved usability. The potential advantages of the recently released terminology, SNOMED Clinical Terms, are briefly considered in this context.

Randomised crossover trial comparing the performance of Clinical Terms Version 3 and Read Codes 5 byte set coding schemes in general practice.

OBJECTIVE: To determine whether Clinical Terms Version 3 provides greater accuracy and consistency in coding electronic patient records than the Read Codes 5 byte set. DESIGN: Randomised crossover trial. Clinicians coded patient records using both schemes after being randomised in pairs to use one scheme before the other. SETTING: 10 general practices in urban, suburban, and rural environments in Norfolk. PARTICIPANTS: 10 general practitioners. SOURCE OF DATA: Concepts were collected from records of 100 patient encounters. MAIN OUTCOME MEASURES: Percentage of coded choices ranked as being exact representations of the original terms; percentage of cases where coding choice of paired general practitioners was identical; length of time taken to find a code. RESULTS: A total of 995 unique concepts were collected. Exact matches were more common with Clinical Terms (70% (95% confidence interval 67% to 73%)) than with Read Codes (50% (47% to 53%)) (P < 0.001), and this difference was significant for each of the 10 participants individually. The pooled proportion with exact and identical matches by paired participants was greater for Clinical Terms (0.58 (0.55 to 0.61)) than Read Codes (0.36 (0.33 to 0.39)) (P < 0.001). The time taken to code with Clinical Terms (30 seconds per term) was not significantly longer than that for Read Codes. CONCLUSIONS: Clinical Terms Version 3 performed significantly better than Read Codes 5 byte set in capturing the meaning of concepts. These findings suggest that improved coding accuracy in primary care electronic patient records can be achieved with the use of such a clinical terminology.

Info-tsunami: surviving the storm with data quality probes.

As a result of the rapid expansion of electronically available clinical knowledge, clinicians are faced with potential information overload (info-tsunami). The use of data quality probes (DQPs) in primary care can encourage clinicians' awareness of, and improvement in, data quality entry over time. DQPs can also highlight areas of potential error or omission as well as good practice, which can impact directly upon the quality of patient care. In this paper, five specific conditions have been subjected to the use of a series of DQPs over a five-year period in order to assess and measure the performance of different initiatives on the quality of data capture and patient care.

Data quality probes-exploiting and improving the quality of electronic patient record data and patient care.

Increasing reliance is being placed on electronic medical records to support clinical care and achieve improved quality standards. In order for clinical information systems (CIS) to deliver excellence the data within it needs to be complete, consistent and accurate. This capture of data is critical but forms only part of the procedure in delivering quality health care during the clinician-patient encounter. A number of processes are involved in this encounter, each of which has to be performed flawlessly to deliver a perfect outcome. This paper outlines a method of assessing the quality of these processes involved in healthcare provision and data quality within a CIS. It proposes the principle of Data Quality Probes (DQP) to assess the performance of the whole encounter system. The main feature of this is the generation of a query which clinical knowledge predicts should not retrieve any cases in a system performing flawlessly. Any cases retrieved (which fail the DQP) indicate an error in either data quality or clinical judgment. This approach is applied practically within the paradigm of a UK family practice testing the hypothesis that a series DQPs can provide a valuable method for monitoring both the data accuracy of a CIS and the provision of quality patient care.