THIN

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Type declaration dctypes:Dataset
Title The Health Imrovement Network
Description The Health Improvement Network (THIN) database represents a collaboration between two companies; In Practice Systems (INPS) - who developed Vision software used by general practitioners (GPs) in the UK to manage patient data, and IMS Health who then provide access to the data for use in medical research. THIN data are collected during routine practice and regularly delivered to THIN. Since THIN data collection began in 2003, over 500 Vision practices have joined the scheme. Research studies for publication conducted using THIN data are approved by a nationally accredited ethics committee which has also approved the data collection scheme. The UCL Research Departments Primary Care & Population Health (PCPH) and Infection & Public Health (IPH) have acquired a full license to THIN for the purposes of conducting large-scale epidemiological, clinical and health care utilisation studies. THIN data currently contains the electronic medical records of 11.1 million patients (3.7 million active patients) equivalent to 75.6 million patient years of data collected from 562 general practices in the UK, covering 6.2% of the UK population. All data are fully anonymised, processed and validated by CSD Medical Research UK. THIN is a database of anonymized electronic health records (EHR) of more than 10 million patients from more than 530 primary care practices in the UK. It is not a claims database and is most commonly used in research on epidemiology, drug safety, health economics, outcomes, and drug utilization. Their patient data is representative of the UK based on gender, age, most major diseases, and geographic location. Unique to this database is the inclusion of anonymized free text comments accompanying patient records. THIN is the database of information collected exclusively from Vision software used in primary care offices. This differentiates it from CPRD, which is a database of National Health Service data. THIN contains mainly outpatient data and inpatient data only for patients already in THIN (eg: their primary care provider uses the Vision software). THIN is a large database with over 400 variables; however, not all fields are mandatory to be entered. Patients receive a unique patient ID and THIN captures when a patient registers and “deregisters” with the database, but it is unknown if patients who move in and out of the EHR receive a new patient ID or not. The database contains over 10 million records and has the ability to go back and collect extra information from patients, physicians, and research sites.
Publisher http://www.ucl.ac.uk/
HTML page https://www.ucl.ac.uk/pcph/research-groups-themes/thin-pub/database
Alternative titles THIN
References https://www.ucl.ac.uk/pcph/research-groups-themes/thin-pub/database
Preferred prefix THIN
Version linking THIN v0
Publications using this dataset https://www.ucl.ac.uk/pcph/research-groups-themes/thin-pub/publications, https://www.ncbi.nlm.nih.gov/pubmed/?term=%22THIN+Database%22%5Btiab%5D+OR+%22Health+Improvement+Network%22%5Btiab%5D
Publication number 532
Patient type Primary Care Practice
Geographic area United Kingdom
Method entities in publications Linear Regression, Bootstrap, Poisson Regression, Logistic Regression, Cox Regression, Proportional Hazards, Survival Analysis, Cox Proportional Hazards, Chi-squared Test, Logistic Regression Model, Fishers Exact Test, T Test, Proportional Hazards Regression, Paired T-test, Regression Model, Wilcoxon, Kaplan-Meier Survival, T-test, Chi-square Test, Chi-square, Cox Model, KaplanMeier Survival Analysis, Log Rank Test, Propensity Score Analysis, Inverse Probability Weighting, Chisquare Test, Chi-squared, Wilcoxon Rank Sum Test, Wald Test, Multivariable Cox Proportional Hazards, ANOVA, Hazard Model, Chisquared, Linear Regression Model, McNemars Test, Wilcoxon Rank-sum Test, CochranArmitage Test For Trend, Propensity Score Matching, Kolmogorov-Smirnov, Chi Square Test, Log-rank Test, F Ratio, Analysis Of Variance, Kruskal Wallis, Wilcoxon Ranksum Test, Kaplan-Meier Survival Curve, Chi Square, Schoenfeld Test, KruskalWallis Test, Logrank Test, Fisher Exact Test, MannWhitney U Test, McNemar Test, Mann Whitney, Chi2, Nearest Neighbour, Association Rule Mining, Chisquare, Complete Linkage, KaplanMeier Survival Curve, KolmogorovSmirnov, K-nearest Neighbor, Support Vector Machine, KaplanMeier Survival, MannWhitney, Apriori, Mann-Whitney U Test, Mann-Whitney, Backward Stepwise Logistic Regression, Kruskal-Wallis, Mann-Whitney U-test, Ttest, KNN, F Test, KruskalWallis, Kolmogorov - Smirnov, Mann- Whitney U Test, Decision Tree Model, Boosting, Pattern Discovery Method, Fisher's Exact Test, Principal Component Analysis, Bayesian Method, Schoenfeld Residuals Test, F-test, Chi Squared Test, Deep Learning, RIPPER, Linear Discriminant Analysis, Wilcoxon Signed Rank Test, Chi Squared
Top methods in publications Logistic Regression (37.33%), Cox Regression (26.04%), Chi-Squared Test (23.27%), Poisson Regression (12.44%), Regression Model (9.91%), Inverse Probability Weighting (8.99%), Linear Regression (8.53%), T-Test (8.06%), Survival Analysis (6.91%), Propensity Score Matching (6.68%)
Availability Proprietary. Available upon request.
Publication-based Popularity Index 84.6
Facts about "THIN"
AvailabilityProprietary. Available upon request. +
Cito:citesAsDataSourcehttps://www.ucl.ac.uk/pcph/research-groups-themes/thin-pub/publications + and https://www.ncbi.nlm.nih.gov/pubmed/?term="THIN+Database"[tiab+OR+"Health+Improvement+Network"[tiab]] +
Dct:alternativeTHIN +
Dct:descriptionThe Health Improvement Network (THIN) data
The Health Improvement Network (THIN) database represents a collaboration between two companies; In Practice Systems (INPS) - who developed Vision software used by general practitioners (GPs) in the UK to manage patient data, and IMS Health who then provide access to the data for use in medical research. THIN data are collected during routine practice and regularly delivered to THIN. Since THIN data collection began in 2003, over 500 Vision practices have joined the scheme. Research studies for publication conducted using THIN data are approved by a nationally accredited ethics committee which has also approved the data collection scheme. The UCL Research Departments Primary Care & Population Health (PCPH) and Infection & Public Health (IPH) have acquired a full license to THIN for the purposes of conducting large-scale epidemiological, clinical and health care utilisation studies. THIN data currently contains the electronic medical records of 11.1 million patients (3.7 million active patients) equivalent to 75.6 million patient years of data collected from 562 general practices in the UK, covering 6.2% of the UK population. All data are fully anonymised, processed and validated by CSD Medical Research UK. THIN is a database of anonymized electronic health records (EHR) of more than 10 million patients from more than 530 primary care practices in the UK. It is not a claims database and is most commonly used in research on epidemiology, drug safety, health economics, outcomes, and drug utilization. Their patient data is representative of the UK based on gender, age, most major diseases, and geographic location. Unique to this database is the inclusion of anonymized free text comments accompanying patient records. THIN is the database of information collected exclusively from Vision software used in primary care offices. This differentiates it from CPRD, which is a database of National Health Service data. THIN contains mainly outpatient data and inpatient data only for patients already in THIN (eg: their primary care provider uses the Vision software). THIN is a large database with over 400 variables; however, not all fields are mandatory to be entered. Patients receive a unique patient ID and THIN captures when a patient registers and “deregisters” with the database, but it is unknown if patients who move in and out of the EHR receive a new patient ID or not. The database contains over 10 million records and has the ability to go back and collect extra information from patients, physicians, and research sites.
patients, physicians, and research sites. +
Dct:publisherhttp://www.ucl.ac.uk/ +
Dct:referenceshttps://www.ucl.ac.uk/pcph/research-groups-themes/thin-pub/database +
Dct:titleThe Health Imrovement Network +
Foaf:pagehttps://www.ucl.ac.uk/pcph/research-groups-themes/thin-pub/database +
Geographic areaUnited Kingdom +
Idot:preferredPrefixTHIN +
Methods in publicationsLinear Regression +, Bootstrap +, Poisson Regression +, Logistic Regression +, Cox Regression +, Proportional Hazards +, Survival Analysis +, Cox Proportional Hazards +, Chi-squared Test +, Logistic Regression Model +, Fishers Exact Test +, T Test +, Proportional Hazards Regression +, Paired T-test +, Regression Model +, Wilcoxon +, Kaplan-Meier Survival +, T-test +, Chi-square Test +, Chi-square +, Cox Model +, KaplanMeier Survival Analysis +, Log Rank Test +, Propensity Score Analysis +, Inverse Probability Weighting +, Chisquare Test +, Chi-squared +, Wilcoxon Rank Sum Test +, Wald Test +, Multivariable Cox Proportional Hazards +, ANOVA +, Hazard Model +, Chisquared +, Linear Regression Model +, McNemars Test +, Wilcoxon Rank-sum Test +, CochranArmitage Test For Trend +, Propensity Score Matching +, Kolmogorov-Smirnov +, Chi Square Test +, Log-rank Test +, F Ratio +, Analysis Of Variance +, Kruskal Wallis +, Wilcoxon Ranksum Test +, Kaplan-Meier Survival Curve +, Chi Square +, Schoenfeld Test +, KruskalWallis Test +, Logrank Test +, Fisher Exact Test +, MannWhitney U Test +, McNemar Test +, Mann Whitney +, Chi2 +, Nearest Neighbour +, Association Rule Mining +, Chisquare +, Complete Linkage +, KaplanMeier Survival Curve +, KolmogorovSmirnov +, K-nearest Neighbor +, Support Vector Machine +, KaplanMeier Survival +, MannWhitney +, Apriori +, Mann-Whitney U Test +, Mann-Whitney +, Backward Stepwise Logistic Regression +, Kruskal-Wallis +, Mann-Whitney U-test +, Ttest +, KNN +, F Test +, KruskalWallis +, Kolmogorov - Smirnov +, Mann- Whitney U Test +, Decision Tree Model +, Boosting +, Pattern Discovery Method +, Fisher's Exact Test +, Principal Component Analysis +, Bayesian Method +, Schoenfeld Residuals Test +, F-test +, Chi Squared Test +, Deep Learning +, RIPPER +, Linear Discriminant Analysis +, Wilcoxon Signed Rank Test + and Chi Squared +
PPI84.6 +
Patient typePrimary Care Practice +
Pav:hasCurrentVersionTHIN v0 +
Publication number532 +
Rdf:typedctypes:Dataset +
Top methods in publicationsLogistic Regression (37.33%), Cox Regressi
Logistic Regression (37.33%), Cox Regression (26.04%), Chi-Squared Test (23.27%), Poisson Regression (12.44%), Regression Model (9.91%), Inverse Probability Weighting (8.99%), Linear Regression (8.53%), T-Test (8.06%), Survival Analysis (6.91%), Propensity Score Matching (6.68%)
(6.91%), Propensity Score Matching (6.68%) +