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      • Record: found
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      Temporal trends in use of tests in UK primary care, 2000-15: retrospective analysis of 250 million tests

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          Abstract

          Objectives

          To assess the temporal change in test use in UK primary care and to identify tests with the greatest increase in use.

          Design

          Retrospective cohort study.

          Setting

          UK primary care.

          Participants

          All patients registered to UK General Practices in the Clinical Practice Research Datalink, 2000/1 to 2015/16.

          Main outcome measures

          Temporal trends in test use, and crude and age and sex standardised rates of total test use and of 44 specific tests.

          Results

          262 974 099 tests were analysed over 71 436 331 person years. Age and sex adjusted use increased by 8.5% annually (95% confidence interval 7.6% to 9.4%); from 14 869 tests per 10 000 person years in 2000/1 to 49 267 in 2015/16, a 3.3-fold increase. Patients in 2015/16 had on average five tests per year, compared with 1.5 in 2000/1. Test use also increased statistically significantly across all age groups, in both sexes, across all test types (laboratory, imaging, and miscellaneous), and 40 of the 44 tests that were studied specifically.

          Conclusion

          Total test use has increased markedly over time, in both sexes, and across all age groups, test types (laboratory, imaging, and miscellaneous) and for 40 of 44 tests specifically studied. Of the patients who underwent at least one test annually, the proportion who had more than one test increased significantly over time.

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          Most cited references26

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          Prevalence and outcomes of diabetes, hypertension and cardiovascular disease in COPD.

          D Mannino, D. Thorn, A Swensen … (2008)
          Chronic obstructive pulmonary disease (COPD) is associated with important chronic comorbid diseases, including cardiovascular disease, diabetes and hypertension. The present study analysed data from 20,296 subjects aged > or =45 yrs at baseline in the Atherosclerosis Risk in Communities Study (ARIC) and the Cardiovascular Health Study (CHS). The sample was stratified based on baseline lung function data, according to modified Global Initiative for Obstructive Lung Disease (GOLD) criteria. Comorbid disease at baseline and death and hospitalisations over a 5-yr follow-up were then searched for. Lung function impairment was found to be associated with more comorbid disease. In logistic regression models adjusting for age, sex, race, smoking, body mass index and education, subjects with GOLD stage 3 or 4 COPD had a higher prevalence of diabetes (odds ratio (OR) 1.5, 95% confidence interval (CI) 1.1-1.9), hypertension (OR 1.6, 95% CI 1.3-1.9) and cardiovascular disease (OR 2.4, 95% CI 1.9-3.0). Comorbid disease was associated with a higher risk of hospitalisation and mortality that was worse in people with impaired lung function. Lung function impairment is associated with a higher risk of comorbid disease, which contributes to a higher risk of adverse outcomes of mortality and hospitalisations.
          Article 0 comments Cited 355 times – based on 0 reviews     Review now
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            Validity of diagnostic coding within the General Practice Research Database: a systematic review.

            Nada F. Khan, Sian Harrison, Peter W Rose (2010)
            The UK-based General Practice Research Database (GPRD) is a valuable source of longitudinal primary care records and is increasingly used for epidemiological research. To conduct a systematic review of the literature on accuracy and completeness of diagnostic coding in the GPRD. Systematic review. Six electronic databases were searched using search terms relating to the GPRD, in association with terms synonymous with validity, accuracy, concordance, and recording. A positive predictive value was calculated for each diagnosis that considered a comparison with a gold standard. Studies were also considered that compared the GPRD with other databases and national statistics. A total of 49 papers are included in this review. Forty papers conducted validation of a clinical diagnosis in the GPRD. When assessed against a gold standard (validation using GP questionnaire, primary care medical records, or hospital correspondence), most of the diagnoses were accurately recorded in the patient electronic record. Acute conditions were not as well recorded, with positive predictive values lower than 50%. Twelve papers compared prevalence or consultation rates in the GPRD against other primary care databases or national statistics. Generally, there was good agreement between disease prevalence and consultation rates between the GPRD and other datasets; however, rates of diabetes and musculoskeletal conditions were underestimated in the GPRD. Most of the diagnoses coded in the GPRD are well recorded. Researchers using the GPRD may want to consider how well the disease of interest is recorded before planning research, and consider how to optimise the identification of clinical events.
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              Recent advances in the utility and use of the General Practice Research Database as an example of a UK Primary Care Data resource.

              Tim Williams, Tjeerd Van Staa, Shivani Puri … (2012)
              Since its inception in the mid-1980s, the General Practice Research Database (GPRD) has undergone many changes but remains the largest validated and most utilised primary care database in the UK. Its use in pharmacoepidemiology stretches back many years with now over 800 original research papers. Administered by the Medicines and Healthcare products Regulatory Agency since 2001, the last 5 years have seen a rebuild of the database processing system enhancing access to the data, and a concomitant push towards broadening the applications of the database. New methodologies including real-world harm-benefit assessment, pharmacogenetic studies and pragmatic randomised controlled trials within the database are being implemented. A substantive and unique linkage program (using a trusted third party) has enabled access to secondary care data and disease-specific registry data as well as socio-economic data and death registration data. The utility of anonymised free text accessed in a safe and appropriate manner is being explored using simple and more complex techniques such as natural language processing.
              Article 0 comments Cited 144 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                Jack W O’Sullivan:
                ORCID: http://orcid.org/0000-0003-3629-2546
                Role: clinical researcher
                Sarah Stevens: Role: statistician
                F D Richard Hobbs: Role: professor of primary care health sciences
                Chris Salisbury: Role: professor of primary health care
                Paul Little: Role: professor of primary care research
                Ben Goldacre: Role: senior clinical research fellow
                Clare Bankhead: Role: associate professor of primary care
                Jeffrey K Aronson: Role: clinical pharmacologist
                Rafael Perera: Role: professor of medical statistics
                Carl Heneghan: Role: professor of evidence-based medicine
                Journal
                Journal ID (nlm-ta): BMJ
                Journal ID (iso-abbrev): BMJ
                Journal ID (publisher-id): BMJ-UK
                Journal ID (hwp): bmj
                Title: The BMJ
                Publisher: BMJ Publishing Group Ltd.
                ISSN (Print): 0959-8138
                ISSN (Electronic): 1756-1833
                Publication date Collection: 2018
                Publication date (Electronic): 28 November 2018
                Volume: 363
                Electronic Location Identifier: k4666
                Affiliations
                [1 ]Centre for Evidence-Based Medicine, Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford OX2 6GG, UK
                [2 ]Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK
                [3 ]Center for Inherited Cardiovascular Disease, Stanford University, Stanford, CA, USA
                [4 ]Meta-Research Innovation Center at Stanford (METRICS), Stanford University, Stanford, CA, USA
                [5 ]Centre for Academic Primary Care, Department of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
                [6 ]Primary Care and Population Sciences, University of Southampton, Southampton, UK
                Author notes
                Correspondence to: J W O’Sullivan jack.osullivan@ 123456phc.ox.ac.uk (or @drjackosullivan on Twitter)
                Author information
                http://orcid.org/0000-0003-3629-2546
                Article
                Publisher ID: osuj044789
                DOI: 10.1136/bmj.k4666
                PMC ID: 6260131
                PubMed ID: 30487169
                SO-VID: a0ba9416-f90f-4ab8-a264-551e150fa0a2
                Copyright © Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions
                License:

                This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/.

                History
                Date accepted : 29 October 2018
                Categories
                Subject: Research

                ScienceOpen disciplines: Medicine
                Data availability:
                ScienceOpen disciplines: Medicine

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