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Validation and validity of diagnoses in the General Practice Research Database: a systematic review.

Herrett E, Thomas SL, Schoonen WM, Smeeth L, Hall AJ - Br J Clin Pharmacol (2010)

Bottom Line: Details of validation methods and results were often incomplete.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.

View Article: PubMed Central - PubMed

Affiliation: Non-communicable Disease Epidemiology Unit, Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK. emily.herrett@lshtm.ac.uk

ABSTRACT

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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Measures of validity of categorical data. Sensitivity: A/(A+C); specificity: D/(B+D); positive predictive value: A/(A+B); negative predictive value: D/(C+D)
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fig02: Measures of validity of categorical data. Sensitivity: A/(A+C); specificity: D/(B+D); positive predictive value: A/(A+B); negative predictive value: D/(C+D)

Mentions: The most robust method of validation may be to request additional information from the GP, since this method uses information external to the database to verify disease status of individual cases. Most such validations were restricted to establishing the proportion of cases with specific diagnostic codes that were confirmed by medical record review or responses to questionnaires, thus providing an estimate of the PPV of that set of codes (Figure 2). Although a useful measure, PPV varies with disease prevalence, so use of historical validations may not be justified if disease incidence has changed over time.


Validation and validity of diagnoses in the General Practice Research Database: a systematic review.

Herrett E, Thomas SL, Schoonen WM, Smeeth L, Hall AJ - Br J Clin Pharmacol (2010)

Measures of validity of categorical data. Sensitivity: A/(A+C); specificity: D/(B+D); positive predictive value: A/(A+B); negative predictive value: D/(C+D)
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2805870&req=5

fig02: Measures of validity of categorical data. Sensitivity: A/(A+C); specificity: D/(B+D); positive predictive value: A/(A+B); negative predictive value: D/(C+D)
Mentions: The most robust method of validation may be to request additional information from the GP, since this method uses information external to the database to verify disease status of individual cases. Most such validations were restricted to establishing the proportion of cases with specific diagnostic codes that were confirmed by medical record review or responses to questionnaires, thus providing an estimate of the PPV of that set of codes (Figure 2). Although a useful measure, PPV varies with disease prevalence, so use of historical validations may not be justified if disease incidence has changed over time.

Bottom Line: Details of validation methods and results were often incomplete.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.

View Article: PubMed Central - PubMed

Affiliation: Non-communicable Disease Epidemiology Unit, Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK. emily.herrett@lshtm.ac.uk

ABSTRACT

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.

Show MeSH