Dataset Information

Can primary care data be used to monitor regional smoking prevalence? An analysis of The Health Improvement Network primary care data.

ABSTRACT:

Background

Accurate and timely regional data on smoking trends allow tobacco control interventions to be targeted at the areas most in need and facilitate the evaluation of such interventions. Electronic primary care databases have the potential to provide a valuable source of such data due to their size, continuity and the availability of socio-demographic data. UK electronic primary care data on smoking prevalence from The Health Improvement Network (THIN) have previously been validated at the national level, but may be less representative at the regional level due to reduced sample sizes. We investigated whether this database provides valid regional data and whether it can be used to compare smoking prevalence in different UK regions.

Methods

Annual estimates of smoking prevalence by government office region (GOR) from THIN were compared with estimates of smoking prevalence from the General Lifestyle Survey (GLF) from 2000 to 2008.

Results

For all regions, THIN prevalence data were generally found to be highly comparable with GLF data from 2006 onwards.

Conclusions

THIN primary care data could be used to monitor regional smoking prevalence and highlight regional differences in smoking in the UK.

SUBMITTER: Langley TE

PROVIDER: S-EPMC3198710 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Can primary care data be used to monitor regional smoking prevalence? An analysis of The Health Improvement Network primary care data.

Langley Tessa E TE Szatkowski Lisa C LC Wythe Stephen S Lewis Sarah A SA

BMC public health 20111007

<h4>Background</h4>Accurate and timely regional data on smoking trends allow tobacco control interventions to be targeted at the areas most in need and facilitate the evaluation of such interventions. Electronic primary care databases have the potential to provide a valuable source of such data due to their size, continuity and the availability of socio-demographic data. UK electronic primary care data on smoking prevalence from The Health Improvement Network (THIN) have previously been validate ...[more]

PMID: 21981754

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Project description:BackgroundMonitoring how the incidence of influenza infections changes over time is important for quantifying the transmission dynamics and clinical severity of influenza. Infection incidence is difficult to measure directly, and hence, other quantities which are more amenable to surveillance are used to monitor trends in infection levels, with the implicit assumption that they correlate with infection incidence.MethodsHere, we demonstrate, through mathematical reasoning using fundamental mathematical principles, the relationship between the incidence of influenza infections and three commonly reported surveillance indicators: (1) the rate per unit time of influenza-like illness reported through sentinel healthcare sites, (2) the rate per unit time of laboratory-confirmed influenza infections and (3) the proportion of laboratory tests positive for influenza ('test-positive proportion').ResultsOur analysis suggests that none of these ubiquitously reported surveillance indicators are a reliable tool for monitoring influenza incidence. In particular, we highlight how these surveillance indicators can be heavily biassed by the following: the dynamics of circulating pathogens (other than influenza) with similar symptom profiles, changes in testing rates and differences in infection rates, symptom rates and healthcare-seeking behaviour between age-groups and through time. We make six practical recommendations to improve the monitoring of influenza infection incidence. The implementation of our recommendations would enable the construction of more interpretable surveillance indicator(s) for influenza from which underlying patterns of infection incidence could be readily monitored.ConclusionsThe implementation of all (or a subset) of our recommendations would greatly improve understanding of the transmission dynamics, infection burden and clinical severity of influenza, improving our ability to respond effectively to seasonal epidemics and future pandemics.

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Dataset Information

Can primary care data be used to monitor regional smoking prevalence? An analysis of The Health Improvement Network primary care data.

Background

Methods

Results

Conclusions

Publications

Can primary care data be used to monitor regional smoking prevalence? An analysis of The Health Improvement Network primary care data.

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