The use of routinely collected computer data for research in primary care: opportunities and challenges

Lusignan, Simon de; Weel, Chris van

doi:10.1093/fampra/cmi106

Cited by 269 publications

(239 citation statements)

References 48 publications

Supporting

Mentioning

233

Contrasting

Unclassified

Order By: Relevance

“…Alongside the development of the risk score we have also developed a piece of software that enables integration of this score into routine clinical practice in primary care. Using this tool optimises the highquality data stored in general practices [23].…”

Section: Discussionmentioning

confidence: 99%

Implementation of the automated Leicester Practice Risk Score in two diabetes prevention trials provides a high yield of people with abnormal glucose tolerance

et al. 2012

View full text Add to dashboard Cite

Aims/hypothesis The Leicester Practice Risk Score (LPRS) is a tool for identifying those at high risk of either impaired glucose regulation (IGR), defined as impaired glucose tolerance and/or impaired fasting glucose, or type 2 diabetes from routine primary care data. The aim of this study was to determine the yield from the LPRS when applied in two diabetes prevention trials. Methods Let's Prevent Diabetes (LPD) and Walking Away from Diabetes (WAD) studies used the LPRS to identify people at risk of IGR or type 2 diabetes from 54 general practices. The top 10% at risk within each practice were invited for screening using a 75 g OGTT. The response rate to the invitation and the prevalence of IGR and/or type 2 diabetes in each study were calculated. Results Of those invited 19.2% (n 03,449) in LPD and 22.1% (n0833) in WAD attended. Of those screened for LPD 25.5% (95% CI 24.1, 27.0) had IGR and 4.5% (95% CI 3.8, 5.2) had type 2 diabetes, giving a prevalence of any abnormal glucose tolerance of 30.1% (95% CI 28.5, 31.6). Comparable rates were seen for the WAD study: IGR 26.5% (95% CI 23.5, 29.5), type 2 diabetes 3.0% (95% CI 1.8, 4.2) and IGR/type 2 diabetes 29.5% (95% CI 26.4, 32.6). Conclusions/interpretation Using the LPRS identifies a high yield of people with abnormal glucose tolerance, significantly higher than those seen in a population screening programme in the same locality. The LPRS is an inexpensive and simple way of targeting screening programmes at those with the highest risk.

show abstract

Section: Discussionmentioning

confidence: 99%

Implementation of the automated Leicester Practice Risk Score in two diabetes prevention trials provides a high yield of people with abnormal glucose tolerance

et al. 2012

View full text Add to dashboard Cite

show abstract

“…However, there are several disadvantages of using routinely collected data. 41 First, the older data used may have pre-dated the introduction of electronic record-keeping in many practices and therefore are more likely to be incomplete, and hence underestimate the number of females with GDM. This may also mean that some of the females identified may have had earlier GDM episodes that were not recorded.…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Diabetes screening after gestational diabetes in England: a quantitative retrospective cohort study

et al. 2013

Self Cite

View full text Add to dashboard Cite

show abstract

“…Non-invasive risk scores can use a number of approaches including being applied as a questionnaire to the individual being assessed (self assessment) or as a query to a general practice database where all those at high risk of having undiagnosed type 2 diabetes mellitus or IGR are identified using routinely collected data. Increasingly, high quality patient data are being stored electronically [7]. Optimising routinely collected data may have advantages over reliance on people to self-refer for testing and can be used to implement national screening programmes, such as the NHS Health Checks Programme in the UK [8].…”

Section: Introductionmentioning

confidence: 99%

Detection of impaired glucose regulation and/or type 2 diabetes mellitus, using primary care electronic data, in a multiethnic UK community setting

et al. 2012

View full text Add to dashboard Cite

Aims/hypothesis The aim of this study was to develop and validate a score for detecting the glycaemic categories of impaired glucose regulation (IGR) and type 2 diabetes using the WHO 2011 diagnostic criteria. Methods We used data from 6,390 individuals aged 40-75 years from a multiethnic population based screening study. We developed a logistic regression model for predicting IGR and type 2 diabetes (diagnosed using OGTT or HbA 1c ≥6.5% [48 mmol/mol]) from data which are routinely stored in primary care. We developed the score by summing the β coefficients. We externally validated the score using data from 3,225 participants aged 40-75 years screened as part of another study. Results The score includes age, ethnicity, sex, family history of diabetes, antihypertensive therapy and BMI. Fifty per cent of a population would need to be invited for testing to detect type 2 diabetes mellitus on OGTT with 80% sensitivity; this is slightly raised to 54% that need to be invited if using HbA 1c . Inviting the top 10% for testing, 9% of these would have type 2 diabetes mellitus using an OGTT (positive predictive value [PPV]

show abstract

The use of routinely collected computer data for research in primary care: opportunities and challenges

Cited by 269 publications

References 48 publications

Implementation of the automated Leicester Practice Risk Score in two diabetes prevention trials provides a high yield of people with abnormal glucose tolerance

Implementation of the automated Leicester Practice Risk Score in two diabetes prevention trials provides a high yield of people with abnormal glucose tolerance

Diabetes screening after gestational diabetes in England: a quantitative retrospective cohort study

Detection of impaired glucose regulation and/or type 2 diabetes mellitus, using primary care electronic data, in a multiethnic UK community setting

Contact Info

Product

Resources

About