Creating medical and drug code lists to identify cases in primary care databases
This paper demonstrates how compilation of medical and drug code lists for outcomes or exposures of interest for studies using primary care databases can be carried out efficiently using Stata. Use of Stata do-files to record and execute the commands provides good documentation and ease of replication of the procedure.
Available from: Geri Keane
- "All patients over the age of 18 with a Read code diagnosis for PDAC or BTC during the study period were included in the study. Read code lists of diagnostic terms for PDAC and BTC were developed using previously described methodology . Data from the first 6 months of registration were excluded to prevent the accidental inclusion of retrospective incident cases of PDAC or BTC. "
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The UK incidence of pancreatic ductal adenocarcinoma (PDAC) is approximately 9/100,000 population compared with 1–2/100,000 for biliary tract cancer (BTC). This study explores the incidence of these cancers over time and the influence of socio-demographic and geographic factors in a UK primary care cohort.
This study uses data from a large UK primary care database, The Health Improvement Network (THIN). All adult patients contributing data to THIN between January 2000 and December 2010 were included. Annual incidence rates were calculated, adjusted for age, gender, time period, deprivation score (Townsend quintile) and strategic health authority.
From 2000–2010, the annual incidence of PDAC increased by an average of 3% per year (95% CI 1.00–4.00%) and BTC by 4% (95% CI 2.00–6.00%). Incidence of both cancers increased steeply with age and was higher in men. BTC was associated with increasing deprivation (most deprived versus least deprived quintile (OR: 1.45 [95% CI: 1.17, 1.79.]).
The overall incidence of both cancers is low but increasing. Variations in incidence may reflect changes in coding practice or increased exposure to associated risk factors.
PLoS ONE 09/2014; 9(9):e108498. DOI:10.1371/journal.pone.0108498 · 3.23 Impact Factor
Available from: Irwin Nazareth
- "In UK primary care, diagnoses are recorded using Read codes, a hierarchical classification system that includes terms relating to signs and symptoms, diagnosis, procedures and investigations . Clinical diagnoses made by specialists and results from diagnostic tests are entered retrospectively in general practice. "
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ABSTRACT: ObjectiveTo explore whether there are gender differences in the number of GP recorded cases, the probability of survival and consulting pattern prior to diagnosis amongst patients with three non-sex-specific cancers.DesignCross sectional study.SettingUK primary care.Subjects12,189 patients aged 16 years or over diagnosed with colorectal cancer (CRC), 11,081 patients with lung cancer and 4,352 patients with malignant melanoma, with first record of cancer diagnosis during 1997–2006.Main outcome measuresCancer cases recorded in primary care; probability of survival following diagnosis; and number of GP contacts within the 24 months preceding diagnosis.ResultsFrom 1997–2006, overall rates of GP recorded CRC and lung cancer cases recorded were higher in men than in women, but rates of malignant melanoma were higher in women than in men. Gender differences in survival were small; 49% of men and 53% of women survived at least 5 years following CRC diagnosis; 9% of men and 12% of women with lung cancer, and 77% of men and 86% of women with malignant melanoma. The adjusted male to female relative hazard ratio of death in all patients was 1.20 (95%CI 1.13–1.30), 1.24 (95%CI 1.16–1.33) and 1.73 (95%CI 1.51–2.00) for CRC, lung cancer and malignant melanoma respectively. However, gender differences in the relative risk were much smaller amongst those who died during follow-up. For each cancer, there was little evidence of gender difference in the percentage who consulted and the number of GP contacts made within 24 months prior to diagnosis.ConclusionsThis study found that patterns of consulting prior to cancer diagnosis differed little between two genders, providing no support for the hypothesis that gender differences in survival are explained by gender differences in consultation for more serious illness, and suggests the need for a more critical view of gender and consultation.
PLoS ONE 07/2014; 9(7):e101562. DOI:10.1371/journal.pone.0101562 · 3.23 Impact Factor
Available from: N. Beloff
- "For example, there are over 200 codes for diabetes and 40 codes representing ‘abdominal pain’. Before carrying out an analysis using GP data the user must draw up code lists, that is, a comprehensive set of condition-specific medical or drug codes that can be used to search patient medical/clinical and prescription records.4 After constructing the code list, the user must develop a set of rules for extracting patients and events of interest and write queries to merge all the relevant tables and extract records for particular patients or events. "
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ABSTRACT: UK primary care databases, which contain diagnostic, demographic and prescribing information for millions of patients geographically representative of the UK, represent a significant resource for health services and clinical research. They can be used to identify patients with a specified disease or condition (phenotyping) and to investigate patterns of diagnosis and symptoms. Currently, extracting such information manually is time-consuming and requires considerable expertise. In order to exploit more fully the potential of these large and complex databases, our interdisciplinary team developed generic methods allowing access to different types of user.
Using the Clinical Practice Research Datalink database, we have developed an online user-focused system (TrialViz), which enables users interactively to select suitable medical general practices based on two criteria: suitability of the patient base for the intended study (phenotyping) and measures of data quality.
An end-to-end system, underpinned by an innovative search algorithm, allows the user to extract information in near real-time via an intuitive query interface and to explore this information using interactive visualization tools. A usability evaluation of this system produced positive results.
We present the challenges and results in the development of TrialViz and our plans for its extension for wider applications of clinical research.
Our fast search algorithms and simple query algorithms represent a significant advance for users of clinical research databases.
Journal of the American Medical Informatics Association 11/2013; 21(2). DOI:10.1136/amiajnl-2013-001847 · 3.50 Impact Factor
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