Routinely-collected general practice data are complex, but with systematic processing can be used for quality improvement and research
ABSTRACT UK general practice is computerised, and quality targets based on computer data provide a further incentive to improve data quality. A National Programme for Information Technology is standardising the technical infrastructure and removing some of the barriers to data aggregation. Routinely collected data is an underused resource, yet little has been written about the wide range of factors that need to be taken into account if we are to infer meaning from general practice data.
To report the complexity of general practice computer data and factors that need to be taken into account in its processing and interpretation.
We run clinically focused programmes that provide clinically relevant feedback to clinicians, and overview statistics to localities and researchers. However, to take account of the complexity of these data we have carefully devised a system of process stages and process controls to maintain referential integrity, and improve data quality and error reduction. These are integrated into our design and processing stages. Our systems document the query, reference code set and create unique patient ID. The design stage is followed by appraisal of: data entry issues, how concepts might be represented in clinical systems, coding ambiguities, using surrogates where needed, validation and pilot-ing. The subsequent processing of data includes extraction, migration and integration of data from different sources, cleaning, processing and analysis.
Results are presented to illustrate issues with the population denominator, data entry problems, identification of people with unmet needs, and how routine data can be used for real-world testing of pharmaceuticals.
Routinely collected primary care data could contribute more to the process of health improvement; however, those working with these data need to understand fully the complexity of the context within which data entry takes place.
- SourceAvailable from: Simon De Lusignan[Show abstract] [Hide abstract]
ABSTRACT: UK primary care is highly computerized; initially led by enthusiastic general practitioners who developed their own systems. This preceded the development of a National Health Service information strategy and an ambitious National Programme for IT. A 4-element model is proposed to explain the development of information technology: (1) individual clinician choice; (2) integration into the clinical task--usually an office visit; (3) technological developments; and (4) organizational factors. All 4 elements of this model have been tilted in favor of the utilization of information technology; lessons from the United Kingdom may help other health systems looking to implement information technology systems in primary care.The Journal of ambulatory care management 01/2008; 31(3):201-10. DOI:10.1097/01.JAC.0000324664.88131.d2
- [Show abstract] [Hide abstract]
ABSTRACT: The success in achieving treatment goals for cardiovascular risk factors in primary care is largely unknown. Therefore, the goals of this study were (i) to assess whether routinely collected practice data can be used to evaluate treatment in primary care, (ii) to compare current treatment with goals of published guidelines, and (iii) to calculate future risk for cardiovascular events using these real-life data. In 110 physician offices in Germany, data from the patient management systems of all patients seen between January 1998 and June 2005 were extracted and analysed (715 644) with current guidelines used for reference. Of those patents, 284 096 (40% of all patients analysed) had one of the following diseases: 157 101 (55% of 284 096) had hypertension, 83 005 (29%) diabetes, 64 205 (23%) coronary artery disease (CAD), 174 787 (62%) hyperlipidaemia, and 136 360 (48%) had more than one of the listed diagnoses. During the last visit, treatment goals were achieved for total and LDL cholesterol in 9 and 29%, respectively, for blood pressure in 28%, and for HbA1c in 36%. Low achievement of treatment goals was also seen in patients with CAD or diabetes. Using the Framingham risk model and the SCORE Deutschland risk charts, 20 and 22% of patients had a high 10-year risk for a primary cardiovascular event and a fatal cardiovascular event, respectively. Achieving treatment goals for all risk factors would significantly reduce the number of high-risk patients. (i) Routinely collected practice data can be used to evaluate quality of care; (ii) 40% of patients in primary care have cardiovascular disease or diabetes; (iii) even in high-risk patients, the majority does not achieve treatment goals; and (iv) achieving the treatment goals would reduce the proportion of high-risk patients from 20 to <5%.European Heart Journal 12/2007; 28(24):3051-8. DOI:10.1093/eurheartj/ehm520 · 14.72 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: In Norway there is a shortage of valid health activity statistics from the primary care out-of-hours services and the pre-hospital emergency health care system. There is little systematic information available because data registration is lacking or is only recorded periodically, and definitions of variables are not consistent. A representative sample of Norwegian municipalities and out-of-hours districts was contracted to establish a sentinel network, "The Watchtowers", and procedures were developed for collecting continuous data from out-of-hours services. All contacts, either per telephone or direct attendance, are recorded during day and night. The variables are registered in a computer program developed by the National Centre for Emergency Primary Health Care, and sent by email in Excel-file format to the Centre on a monthly basis. The selection process yielded a group of 18 municipalities, with a fair degree of representativeness for Norwegian municipalities as a whole. The sample has 212,921 inhabitants, which constitutes 4.6% of the total Norwegian population. During a pilot period lasting three months the Watchtowers recorded all individual contacts. The procedures for registration, submitting and checking data worked satisfactorily. There was little data missing, and during the last three months of 2006 a total of 23,346 contacts were registered. We have been able to establish a sentinel network with a fair degree of representativeness for Norwegian out-of-hours districts and municipalities. The data collected reflect national activities from casualty clinics in Norway. Such data are useful for both research and system improvements.BMC Health Services Research 02/2008; 8:62. DOI:10.1186/1472-6963-8-62 · 1.66 Impact Factor