The utility of the general practice research database to examine selected congenital heart defects: a validation study

Wurst, Keele; Ephross, Sara A.; Loehr, James P.; Clark, Douglas W.; Guess, Harry A.

doi:10.1002/pds.1431

Cited by 30 publications

(40 citation statements)

References 21 publications

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“…A handful of studies have used free text to verify clinical conditions in combination with codes; a few of them have used free text to identify cases4 5 while the majority have used free text to verify and validate coded information 3 6–9. However, with the exception of the study by Wurst et al ,7 most studies have little or no detail on the process of selection and review of the free text that was used.…”

Section: Discussionmentioning

confidence: 99%

Using free text information to explore how and when GPs code a diagnosis of ovarian cancer: an observational study using primary care records of patients with ovarian cancer

et al. 2011

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BackgroundPrimary care databases provide a unique resource for healthcare research, but most researchers currently use only the Read codes for their studies, ignoring information in the free text, which is much harder to access.ObjectivesTo investigate how much information on ovarian cancer diagnosis is ‘hidden’ in the free text and the time lag between a diagnosis being described in the text or in a hospital letter and the patient being given a Read code for that diagnosis.DesignAnonymised free text records from the General Practice Research Database of 344 women with a Read code indicating ovarian cancer between 1 June 2002 and 31 May 2007 were used to compare the date at which the diagnosis was first coded with the date at which the diagnosis was recorded in the free text. Free text relating to a diagnosis was identified (a) from the date of coded diagnosis and (b) by searching for words relating to the ovary.Results90% of cases had information relating to their ovary in the free text. 45% had text indicating a definite diagnosis of ovarian cancer. 22% had text confirming a diagnosis before the coded date; 10% over 4 weeks previously. Four patients did not have ovarian cancer and 10% had only ambiguous or suspected diagnoses associated with the ovarian cancer code.ConclusionsThere was a vast amount of extra information relating to diagnoses in the free text. Although in most cases text confirmed the coded diagnosis, it also showed that in some cases GPs do not code a definite diagnosis on the date that it is confirmed. For diseases which rely on hospital consultants for diagnosis, free text (particularly letters) is invaluable for accurate dating of diagnosis and referrals and also for identifying misclassified cases.

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Section: Discussionmentioning

confidence: 99%

Using free text information to explore how and when GPs code a diagnosis of ovarian cancer: an observational study using primary care records of patients with ovarian cancer

et al. 2011

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“…Studies in this review reported high PPVs over 90% for the recording of anorexia, bulimia, 16 cataract, 17 congenital heart defects (including ventricular septal defects, tetralogy of Fallot, and coarctation of the aorta), 18 inflammatory bowel disease, 19 cerebrovascular disease, diabetes, respiratory tract infection, 19 Paget's disease, 20 hip fracture, 21 upper gastrointestinal bleeding, 22 non-affective and non-organic psychosis, 23 venous leg ulcer, 24 and pressure ulcer. 32 and cardiac arrhythmia, 33 were not as accurately recorded, with reported PPVs lower than 80%.…”

Section: Papers Validating a Diagnosis Or Patient Characteristicmentioning

confidence: 99%

Validity of diagnostic coding within the General Practice Research Database: a systematic review

2010

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The UK-based General Practice Research Database (GPRD) is a valuable source of longitudinal primary care records and is increasingly used for epidemiological research. AimTo conduct a systematic review of the literature on accuracy and completeness of diagnostic coding in the GPRD. Design of studySystematic review. MethodSix 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. ResultsA 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. ConclusionMost 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. Keywordsdatabase management systems; meta-analysis; sensitivity and specificity; and systematic review.

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“…The benefit of using primary care databases is that they provide prospective and systematic collection of clinically verified data that can be comprehensive for studying a variety of important outcomes. 13 The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) is one example of a primary care database. It is an electronic medical records (EMR)-based information system for chronic disease surveillance that has been functioning since April 2008.…”

mentioning

confidence: 99%

Validation of the Diagnostic Algorithms for 5 Chronic Conditions in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN): A Kingston Practice-based Research Network (PBRN) Report

Kadhim-Saleh

Green

Williamson

et al. 2013

The Journal of the American Board of Family Medicine

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Objective: The objective of this study was to assess the validity of electronic medical records-based diagnostic algorithms for 5 chronic conditions.Methods: A retrospective validation study using primary chart abstraction. A standardized abstraction form was developed to ascertain diagnoses of diabetes, hypertension, osteoarthritis, chronic obstructive pulmonary disease, and depression. Information about billing, laboratory tests, notes, specialist and hospital reports, and physiologic data was collected. An age-stratified random sample of 350 patient charts was selected from Kingston, Ontario, Canada. Approximately 90% of those charts were allocated to people aged >60 years.Results: Three hundred thirteen patient records were included in the study. Patients' mean age was 68 years and 52% were women. High interrater reliability was indicated by 92% complete agreement and a statistic of 89.3%. The sensitivities of algorithms were 100% (diabetes), 83% (hypertension), 45% (osteoarthritis), 41% (chronic obstructive pulmonary disease), and 39% (depression). The lowest specificity was 97%, for depression. The positive predictive value ranged from 79% (depression) to 100%, and the negative predictive value ranged from 68% (osteoarthritis) to 100%. Chronic diseases constitute a major burden of illness in Canada and around the world. Recent estimates suggest that 46% of adult Canadians suffer from one or more of 7 common chronic diseases. 1Of these conditions, 6 million Canadians are affected with hypertension, 2 2 million with diabetes, 3 1.2 million with major depression, 4 Ͼ750,000adults with chronic obstructive pulmonary disease (COPD), 5 and 3 million with osteoarthritis. 6Currently available information on chronic diseases at the national level is derived from databases such as hospital discharge summaries, disease-specific registries, and population health surveys. These sources have significant limitations, such as the inability to capture data on conditions that do not lead to hospitalizations and the unreliability of self-reported surveys.7 A large validation study of the Discharge At the Canadian provincial level, billing for physician services may provide a source of data, but it is limited in the depth of information because administrative data are created for financial management rather than research purposes.10 When compared against a clinical research database, administrative data had only 20% agreement. 11Primary care databases constitute another source of data on chronic conditions. For instance, people with one or more chronic conditions accounted for 51% of family physician encounters, 12 suggesting that comprehensive clinical records collected by primary care physicians could be a rich resource for researchers and policymakers. The benefit of using primary care databases is that they provide prospective and systematic collection of clinically verified data that can be comprehensive for studying a variety of important outcomes. 13The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) is one...

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The utility of the general practice research database to examine selected congenital heart defects: a validation study

Cited by 30 publications

References 21 publications

Using free text information to explore how and when GPs code a diagnosis of ovarian cancer: an observational study using primary care records of patients with ovarian cancer

Using free text information to explore how and when GPs code a diagnosis of ovarian cancer: an observational study using primary care records of patients with ovarian cancer

Validity of diagnostic coding within the General Practice Research Database: a systematic review

Validation of the Diagnostic Algorithms for 5 Chronic Conditions in the Canadian Primary Care Sentinel Surveillance Network (CPCSSN): A Kingston Practice-based Research Network (PBRN) Report

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