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      Recording of hospitalizations for acute exacerbations of COPD in UK electronic health care records

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          Abstract

          Background

          Accurate identification of hospitalizations for acute exacerbations of chronic obstructive pulmonary disease (AECOPD) within electronic health care records is important for research, public health, and to inform health care utilization and service provision. We aimed to develop a strategy to identify hospitalizations for AECOPD in secondary care data and to investigate the validity of strategies to identify hospitalizations for AECOPD in primary care data.

          Methods

          We identified patients with chronic obstructive pulmonary disease (COPD) in the Clinical Practice Research Datalink (CPRD) with linked Hospital Episodes Statistics (HES) data. We used discharge summaries for recent hospitalizations for AECOPD to develop a strategy to identify the recording of hospitalizations for AECOPD in HES. We then used the HES strategy as a reference standard to investigate the positive predictive value (PPV) and sensitivity of strategies for identifying AECOPD using general practice CPRD data. We tested two strategies: 1) codes for hospitalization for AECOPD and 2) a code for AECOPD other than hospitalization on the same day as a code for hospitalization due to unspecified reason.

          Results

          In total, 27,182 patients with COPD were included. Our strategy to identify hospitalizations for AECOPD in HES had a sensitivity of 87.5%. When compared with HES, using a code suggesting hospitalization for AECOPD in CPRD resulted in a PPV of 50.2% (95% confidence interval [CI] 48.5%–51.8%) and a sensitivity of 4.1% (95% CI 3.9%–4.3%). Using a code for AECOPD and a code for hospitalization due to unspecified reason resulted in a PPV of 43.3% (95% CI 42.3%–44.2%) and a sensitivity of 5.4% (95% CI 5.1%–5.7%).

          Conclusion

          Hospitalization for AECOPD can be identified with high sensitivity in the HES database. The PPV and sensitivity of strategies to identify hospitalizations for AECOPD in primary care data alone are very poor. Primary care data alone should not be used to identify hospitalizations for AECOPD. Instead, researchers should use data that are linked to data from secondary care.

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          Most cited references28

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          Data Resource Profile: Clinical Practice Research Datalink (CPRD)

          Emily Herrett, Arlene M. Gallagher, Krishnan Bhaskaran … (2015)
          The Clinical Practice Research Datalink (CPRD) is an ongoing primary care database of anonymised medical records from general practitioners, with coverage of over 11.3 million patients from 674 practices in the UK. With 4.4 million active (alive, currently registered) patients meeting quality criteria, approximately 6.9% of the UK population are included and patients are broadly representative of the UK general population in terms of age, sex and ethnicity. General practitioners are the gatekeepers of primary care and specialist referrals in the UK. The CPRD primary care database is therefore a rich source of health data for research, including data on demographics, symptoms, tests, diagnoses, therapies, health-related behaviours and referrals to secondary care. For over half of patients, linkage with datasets from secondary care, disease-specific cohorts and mortality records enhance the range of data available for research. The CPRD is very widely used internationally for epidemiological research and has been used to produce over 1000 research studies, published in peer-reviewed journals across a broad range of health outcomes. However, researchers must be aware of the complexity of routinely collected electronic health records, including ways to manage variable completeness, misclassification and development of disease definitions for research.
          Article 0 comments Cited 737 times – based on 0 reviews     Review now
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            Relationship between exacerbation frequency and lung function decline in chronic obstructive pulmonary disease.

            Meghan Donaldson, Jadwiga Wedzicha, A Bhowmik … (2002)
            Chronic obstructive pulmonary disease (COPD) is characterised by both an accelerated decline in lung function and periods of acute deterioration in symptoms termed exacerbations. The aim of this study was to investigate whether these are related. Over 4 years, peak expiratory flow (PEF) and symptoms were measured at home daily by 109 patients with COPD (81 men; median (IQR) age 68.1 (63-74) years; arterial oxygen tension (PaO(2)) 9.00 (8.3-9.5) kPa, forced expiratory volume in 1 second (FEV(1)) 1.00 (0.7-1.3) l, forced vital capacity (FVC) 2.51 (1.9-3.0) l); of these, 32 (29 men) recorded daily FEV(1). Exacerbations were identified from symptoms and the effect of frequent or infrequent exacerbations (> or < 2.92 per year) on lung function decline was examined using cross sectional, random effects models. The 109 patients experienced 757 exacerbations. Patients with frequent exacerbations had a significantly faster decline in FEV(1) and peak expiratory flow (PEF) of -40.1 ml/year (n=16) and -2.9 l/min/year (n=46) than infrequent exacerbators in whom FEV(1) changed by -32.1 ml/year (n=16) and PEF by -0.7 l/min/year (n=63). Frequent exacerbators also had a greater decline in FEV(1) if allowance was made for smoking status. Patients with frequent exacerbations were more often admitted to hospital with longer length of stay. Frequent exacerbations were a consistent feature within a patient, with their number positively correlated (between years 1 and 2, 2 and 3, 3 and 4). These results suggest that the frequency of exacerbations contributes to long term decline in lung function of patients with moderate to severe COPD.
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              Validation and validity of diagnoses in the General Practice Research Database: a systematic review

              Emily Herrett, Sara L Thomas, W Schoonen … (2010)
              AIMS To investigate the range of methods used to validate diagnoses in the General Practice Research Database (GPRD), to summarize findings and to assess the quality of these validations. METHODS A systematic literature review was performed by searching PubMed and Embase for publications using GPRD data published between 1987 and April 2008. Additional publications were identified from conference proceedings, back issues of relevant journals, bibliographies of retrieved publications and relevant websites. Publications that reported attempts to validate disease diagnoses recorded in the GPRD were included. RESULTS We identified 212 publications, often validating more than one diagnosis. In total, 357 validations investigating 183 different diagnoses met our inclusion criteria. Of these, 303 (85%) utilized data from outside the GPRD to validate diagnoses. The remainder utilized only data recorded in the database. The median proportion of cases with a confirmed diagnosis was 89% (range 24–100%). Details of validation methods and results were often incomplete. CONCLUSIONS A number of methods have been used to assess validity. Overall, estimates of validity were high. However, the quality of reporting of the validations was often inadequate to permit a clear interpretation. Not all methods provided a quantitative estimate of validity and most methods considered only the positive predictive value of a set of diagnostic codes in a highly selected group of cases. We make recommendations for methodology and reporting to strengthen further the use of the GPRD in research.
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                Author and article information

                Journal
                Journal ID (nlm-ta): Clin Epidemiol
                Journal ID (iso-abbrev): Clin Epidemiol
                Journal ID (publisher-id): Clinical Epidemiology
                Title: Clinical Epidemiology
                Publisher: Dove Medical Press
                ISSN (Electronic): 1179-1349
                Publication date Collection: 2016
                Publication date (Electronic): 21 November 2016
                Volume: 8
                Pages: 771-782
                Affiliations
                [1 ]Respiratory Epidemiology, Occupational Medicine and Public Health, National Heart and Lung Institute, Imperial College London, London, UK
                [2 ]Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
                [3 ]Respiratory Epidemiology, GlaxoSmithKline R&D, Uxbridge, London
                [4 ]Medical School
                [5 ]UCL Respiratory, University College London, London, UK
                Author notes
                Correspondence: Kieran J Rothnie, Respiratory Epidemiology, Occupational Medicine and Public Health, National Heart and Lung Institute, Emmanuel Kaye Building, 1b Manresa Road, Imperial College London, London SW3 6LR, UK, Tel +44 20 7594 8824, Email k.rothnie@ 123456imperial.ac.uk
                Article
                Publisher ID: clep-8-771
                DOI: 10.2147/CLEP.S117867
                PMC ID: 5123723
                PubMed ID: 27920578
                SO-VID: 4a2b3553-c67e-4803-aa49-dc15803d3588
                Copyright © © 2016 Rothnie et al. This work is published by Dove Medical Press Limited, and licensed under a Creative Commons Attribution License
                License:

                The full terms of the License are available at http://creativecommons.org/licenses/by/4.0/. The license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Categories
                Subject: Original Research

                ScienceOpen disciplines: Public health
                Keywords: validation,linked data,copd,hospitalization,cause-specific hospitalization
                Data availability:
                ScienceOpen disciplines: Public health
                Keywords: validation, linked data, copd, hospitalization, cause-specific hospitalization

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