Abstract
BackgroundClinical databases are increasingly used for health research; many of them capture information on common health indicators including height, weight, blood pressure, cholesterol level, smoking status, and alcohol consumption. However, these are often not recorded on a regular basis; missing data are ubiquitous. We described the recording of health indicators in UK primary care and evaluated key implications for handling missing data.MethodsWe examined the recording of health indicators in The Health Improvement Network (THIN) UK primary care database over time, by demographic variables (age and sex) and chronic diseases (diabetes, myocardial infarction, and stroke). Using weight as an example, we fitted linear and logistic regression models to examine the associations of weight measurements and the probability of having weight recorded with individuals’ demographic characteristics and chronic diseases.ResultsIn total, 6,345,851 individuals aged 18–99 years contributed data to THIN between 2000 and 2015. Women aged 18–65 years were more likely than men of the same age to have health indicators recorded; this gap narrowed after age 65. About 60–80% of individuals had their height, weight, blood pressure, smoking status, and alcohol consumption recorded during the first year of registration. In the years following registration, these proportions fell to 10%–40%. Individuals with chronic diseases were more likely to have health indicators recorded, particularly after the introduction of a General Practitioner incentive scheme. Individuals’ demographic characteristics and chronic diseases were associated with both observed weight measurements and missingness in weight.ConclusionMissing data in common health indicators will affect statistical analysis in health research studies. A single analysis of primary care data using the available information alone may be misleading. Multiple imputation of missing values accounting for demographic characteristics and disease status is recommended but should be considered and implemented carefully. Sensitivity analysis exploring alternative assumptions for missing data should also be evaluated.
Highlights
Clinical and administrative health databases, such as disease registers, health insurance claim databases, and primary care electronic health record databases, have long been recognized as rich data sources for health research
There are several primary care databases in the UK, such as The Health Improvement Network (THIN),[1,2] Clinical Practice Research Datalink,[3] and QRESEARCH,[4] which typically include several hundred geographically dispersed general practices with data collected since the early 1990s
6,345,851 individuals (3,070,711 [48%] men and 3,275,140 [52%] women) aged 18–99 years were registered with 642 general practices contributing data to THIN between January 1, 2000 and December 31, 2015
Summary
Clinical and administrative health databases, such as disease registers, health insurance claim databases, and primary care electronic health record databases, have long been recognized as rich data sources for health research. There are several primary care databases in the UK, such as The Health Improvement Network (THIN),[1,2] Clinical Practice Research Datalink,[3] and QRESEARCH,[4] which typically include several hundred geographically dispersed general practices with data collected since the early 1990s. Clinical databases are increasingly used for health research; many of them capture information on common health indicators including height, weight, blood pressure, cholesterol level, smoking status, and alcohol consumption. These are often not recorded on a regular basis; missing data are ubiquitous.
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