The internal validation of weight and weight change coding using weight measurement data within the UK primary care Electronic Health Record

References

• BhaskaranKDouglasIForbesHdos-Santos-SilvaILeonDASmeethLBody-mass index and risk of 22 specific cancers: a population-based cohort study of 5·24 million UK adultsThe Lancet20143849945755765
   PubMed Web of Science ®Google Scholar
• di AngelantonioEBhupathirajuSNWormserDBody-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continentsThe Lancet201638810046776786
   PubMed Web of Science ®Google Scholar
• WongCJInvoluntary weight lossMed Clin North Am201498362564324758965
   PubMed Web of Science ®Google Scholar
• Hippisley-CoxJCouplandCBrindlePDevelopment and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort studyBMJ2017357j2099
   PubMed Web of Science ®Google Scholar
• Hippisley-CoxJCouplandCBrindlePDevelopment and validation of QRISK3 risk prediction algorithms to estimate future risk of cardiovascular disease: prospective cohort studyBMJ2017357j209928536104
   PubMed Web of Science ®Google Scholar
• KharraziHChangHYHeinsSEWeinerJPGudzuneKAAssessing the impact of body mass index information on the performance of risk adjustment models in predicting health care costs and utilizationMed Care201856121042105030339574
   PubMed Web of Science ®Google Scholar
• Usher-SmithJAHarshfieldASaundersCLExternal validation of risk prediction models for incident colorectal cancer using UK BiobankBr J Cancer2018118575075929381683
   PubMed Web of Science ®Google Scholar
• HerrettEGallagherAMBhaskaranKData resource profile: clinical practice research datalink (CPRD)Int J Epidemiol201544382783626050254
   PubMed Web of Science ®Google Scholar
• KontopantelisEParisiRSpringateDAReevesDLongitudinal multiple imputation approaches for body mass index or other variables with very low individual-level variability: the mibmi command in StataBMC Res Notes20171014128086961
   PubMedGoogle Scholar
• NicholsonBDHamiltonWO’SullivanJAveyardPHobbsFRWeight loss as a predictor of cancer in primary care: a systematic review and meta-analysisBr J Gen Pract201868670e311e32229632004
   PubMed Web of Science ®Google Scholar
• VerberneLDMNielenMMJLeemrijseCJVerheijRAFrieleRDRecording of weight in electronic health records: an observational study in general practiceBMC Fam Pract201819117430447691
   PubMed Web of Science ®Google Scholar
• HamiltonWLancashireRSharpDPetersTJChengKKMarshallTThe risk of colorectal cancer with symptoms at different ages and between the sexes: a case-control studyBMC Medicine2009711719374736
   PubMed Web of Science ®Google Scholar
• MurtaughMAGibsonBSReddDZeng-TreitlerQRegular expression-based learning to extract bodyweight values from clinical notesJ Biomed Inform20155418619025746391
   PubMed Web of Science ®Google Scholar
• NichollsSGLanganSMBenchimolEIRoutinely collected data: the importance of high-quality diagnostic coding to researchCMAJ201718933E1054E105528827435
   PubMed Web of Science ®Google Scholar
• van WalravenCAustinPAdministrative database research has unique characteristics that can risk biased resultsJ Clin Epidemiol201265212613122075111
   PubMed Web of Science ®Google Scholar
• PriceSJStapleySAShephardEBarracloughKHamiltonWTIs omission of free text records a possible source of data loss and bias in clinical practice research datalink studies? A case-control studyBMJ Open201665e011664
   Web of Science ®Google Scholar
• BradleySHLawrenceNRCarderPUsing primary care data for health research in England – an overviewFuture Hospital Journal201853207212
   Google Scholar
• CiminoJJReview paper: coding systems in health careMethods Inf Med1996354–52732849019091
   PubMed Web of Science ®Google Scholar
• BensonTThe history of the read codes: the inaugural James read memorial lecture 2011Inform Prim Care201119317318222688227
   PubMedGoogle Scholar
• WatsonJNicholsonBDHamiltonWPriceSIdentifying clinical features in primary care electronic health record studies: methods for codelist developmentBMJ Open2017711e019637
   Web of Science ®Google Scholar
• SpringateDAKontopantelisEAshcroftDMClinicalCodes: an online clinical codes Repository to improve the validity and reproducibility of research using electronic medical recordsPLoS One201496e9982524941260
   PubMed Web of Science ®Google Scholar
• WilliamsRKontopantelisEBuchanIPeekNClinical code set engineering for reusing EHR data for research: a reviewJ Biomed Inform20177011328442434
   PubMed Web of Science ®Google Scholar
• BenchimolEISmeethLGuttmannAThe reporting of studies conducted using observational Routinely-collected health data (record) statementPLoS Med20151210e100188526440803
   PubMed Web of Science ®Google Scholar
• EhrensteinVPetersenISmeethLHelping everyone do better: a call for validation studies of routinely recorded health data. Clin Epidemiol20168495127110139
   PubMed Web of Science ®Google Scholar
• KhanNFHarrisonSERosePWValidity of diagnostic coding within the general practice Research database: a systematic reviewBr J Gen Pract201060572e128e13620202356
   PubMed Web of Science ®Google Scholar
• ThomasKHDaviesNMetcalfeCWindmeijerFMartinRMGunnellDValidation of suicide and self-harm records in the clinical practice research datalinkBr J Clin Pharmacol201376114515723216533
   PubMed Web of Science ®Google Scholar
• ThomasSLEdwardsCJSmeethLCooperCHallAJHow accurate are diagnoses for rheumatoid arthritis and juvenile idiopathic arthritis in the general practice Research Database?Arthritis Rheum20085991314132118759262
   PubMed Web of Science ®Google Scholar
• HerrettEThomasSLSchoonenWMSmeethLHallAJValidation and validity of diagnoses in the general practice research database: a systematic reviewBr J Clin Pharmacol201069141420078607
   PubMed Web of Science ®Google Scholar
• NissenFQuintJKWilkinsonSMüllerovaHSmeethLDouglasIJValidation of asthma recording in electronic health records: a systematic reviewClin Epidemiol2017964365629238227
   PubMed Web of Science ®Google Scholar
• HermanussenMDanker-HopfeHWeberGWBody weight and the shape of the natural distribution of weight, in very large samples of German, Austrian and Norwegian conscriptsInt J Obes Relat Metab Disord200125101550155311673780
   PubMed Web of Science ®Google Scholar
• AltmanDPractical Statistics for Medical ResearchLondonChapman and Hall/CRC1990
   Google Scholar
• NicholsonBDAveyardPHobbsFDRWeight loss as a predictor of cancer and serious disease in primary care: an ISAC-approved CPRD protocol for a retrospective cohort study using routinely collected primary care data from the UKDiagnostic and Prognostic Research2018211
   Google Scholar
• HamiltonWLancashireRSharpDPetersTJChengKMarshallTThe risk of colorectal cancer with symptoms at different ages and between the sexes: a case-control studyBMC Med2009711719374736
   PubMed Web of Science ®Google Scholar
• BhaskaranKForbesHJDouglasILeonDASmeethLRepresentativeness and optimal use of body mass index (BMI) in the UK Clinical Practice Research Datalink (CPRD)BMJ Open201339e003389
   Web of Science ®Google Scholar
• NHS Digital [website on the Internet]Health Survey for England – England’s changing health since the 1990s - Weight Trends2018 Available from: http://healthsurvey.hscic.gov.uk/data-visualisation/data-visualisation/explore-the-trends/weight.aspxAccessed August 28, 2018
   Google Scholar
• GaspariniAAbramsKRBarrettJKMixed effects models for health-care longitudinal data with an informative visiting process: a Monte Carlo simulation studyarXiv2018180800419v1
   Google Scholar
• KharraziHAnzaldiLJHernandezLThe value of unstructured electronic health record data in geriatric syndrome case identificationJournal of the American Geriatrics Society20186681499150729972595
   PubMed Web of Science ®Google Scholar
• SperrinMPetherickEBadrickEInformative observation in health data: association of past level and trend with time to next measurementStud Health Technol Inform201723526126528423794
   PubMedGoogle Scholar
• WallaceJISchwartzRSEpidemiology of weight loss in humans with special reference to wasting in the elderlyInt J Cardiol2002851152112163206
   PubMed Web of Science ®Google Scholar
• TateARDungeySGlewSBeloffNWilliamsRWilliamsTQuality of recording of diabetes in the UK: how does the GP’s method of coding clinical data affect incidence estimates? cross-sectional study using the CPRD databaseBMJ Open201771e012905
   Web of Science ®Google Scholar
• Suspected Cancer: Recognition and Referral [webpage on the Internet]National Institute for Health and Care Excellence2015 Available from: https://www.nice.org.uk/guidance/ng12Accessed August 28, 2018
   Google Scholar
• GaddeyHLHolderKUnintentional weight loss in older adultsAm Fam Physician201489971872224784334
   PubMed Web of Science ®Google Scholar
• McminnJSteelCBowmanAInvestigation and management of unintentional weight loss in older adultsBMJ20113421d173221447571
   PubMed Web of Science ®Google Scholar