Three steps to data quality

Abstract

Background The quality of data in general practice clinical information systems varies enormously. This variability jeopardises the proposed national strategy for an integrated care records service and the capacity of primary care organisations to respond coherently to the demands of clinical governance and the proposed quality-based general practice contract. This is apparent in the difficulty in automating the audit process and in comparing aggregated data from different practices. In an attempt to provide data of adequate quality to support such operational needs, increasing emphasis is being placed on the standardisation of data recording. Objective To develop a conceptual framework to facilitate the recording of standardised data within primary care. Method A multiprofessional group of primary care members from the South Thames Research Network examined leading guidelines for best practice. Using the nominal group technique the group prioritised the information needs of primary care organisations for managing coronary heart disease according to current evidence. Results Information needs identified were prioritised and stratified into a functional framework. Conclusion It has been possible within the context of a primary care research network to produce a framework for standardising data collection. Motivation of front-line clinicians was achieved through the incorporation of their views into the synthesis of the dataset.

The languages of health in general practice electronic patient records: a Zipf’s law analysis

“…Clinical terminologies are required by electronic patient record systems to capture, process, use, transfer and share data in a standard form [4] by providing a mechanism to encode patient data in a structured and common language [5]. This standard language helps improve sharing and communication of information throughout the health system and beyond [6,7]. Codes assigned to patient encounters with the health system can be used for many purposes such as automated medical decision support, disease surveillance, payment and reimbursement of services rendered to the patients [8].…”

Problems with primary care data quality: osteoporosis as an exemplar

“…44 This is similar to our usual approach to implementing quality improvement, that is, to identify a subset of patients with the diagnosis or on treatment and then to examine key risk factors and associated co-morbidities. 45 However, the low rate of diagnostic recording, and the variation between practices in their choice of therapy, precluded us from doing this in this case. Further research is needed to explore the reasons for inter-practice variation in coding and whether there is an optimum size for a clinical terminology.…”

Identifying the optimal search strategy for coronary heart disease patients in primary care electronic patient record systems

“…17,18 Details of the methodology are provided elsewhere. 19 The group selected 55 essential pieces of information (independent variables). These were Read coded and stratified into four groups for modelling (Table 1).…”