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Biomedical subjects

Pushpa Kumarapeli

Publications and source records attributed to Pushpa Kumarapeli.

3 recordsLinked to original sources
PubMed2006

A study of cardiovascular risk in overweight and obese people in England.

OBJECTIVES: To report current levels of obesity and associated cardiac risk using routinely collected primary care computer data. METHODS: 67 practices took part in an educational intervention to improve computer data quality and care in cardiovascular disease. Data were extracted from 435,102 general practice computer records. 64.3% (229,108/362,861) of people age 15 y and older had a body mass index (BMI) recording or a valid height and weight record that enabled BMI to be derived. Data about cardiovascular disease and risk factors were also extracted. The prevalence of disease and the control of risk factors in the overweight and obese population were compared with those of normal body weight. RESULTS: 56.8% of men and 69.3% of women aged over 15 y had a BMI record. 22% of men and 32.3% of women aged 15 to 24 y were overweight or obese; rising each decade to a peak of 65.6% of men and 57.5% of women aged 55 to 64 y. Thereafter, the proportion who were overweight or obese declined. The prevalence of ischaemic heart disease, diabetes mellitus and hypertension rose with increasing levels of obesity; their prevalence in those who are moderately obese was between two and three times that of the general population. Systolic and diastolic blood pressure, blood glucose even in non-diabetics, cholesterol and triglycerides were all elevated in the overweight and obese population. CONCLUSION: Based on the recorded data over half of men and nearly half of women are overweight or obese. They have increased cardiovascular risk, which is not adequately controlled by current practice.

Adolescent↗
PubMed2006

Routinely-collected general practice data are complex, but with systematic processing can be used for quality improvement and research.

BACKGROUND: 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. OBJECTIVE: To report the complexity of general practice computer data and factors that need to be taken into account in its processing and interpretation. METHOD: 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: 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. CONCLUSIONS: 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.

Ambulatory Care Information Systems↗