Computing disease incidence, prevalence and comorbidity from electronic medical records

[1]  L. Baker,et al.  Increased risk of incident chronic medical conditions in infertile men: analysis of United States claims data. , 2016, Fertility and sterility.

[2]  Laura L. Pullum,et al.  Discovering Multi-Scale Co-Occurrence Patterns of Asthma and Influenza with Oak Ridge Bio-Surveillance Toolkit , 2015, Front. Public Health.

[3]  S. Vigod,et al.  Validation of a Population-Based Algorithm to Detect Chronic Psychotic Illness , 2015, Canadian journal of psychiatry. Revue canadienne de psychiatrie.

[4]  I. Gold,et al.  A Bayesian Approach to Latent Class Modeling for Estimating the Prevalence of Schizophrenia Using Administrative Databases , 2015, Front. Psychiatry.

[5]  Stephen Jones,et al.  Assessment of administrative claims data for public health reporting of Salmonella in Tennessee , 2015, J. Am. Medical Informatics Assoc..

[6]  A. Vanasse,et al.  Improving the selection of true incident cases of low back pain by screening retrospective administrative data , 2014, European journal of pain.

[7]  Shuang Wang,et al.  Hidden in plain sight: bias towards sick patients when sampling patients with sufficient electronic health record data for research , 2014, BMC Medical Informatics and Decision Making.

[8]  F. R. Rosendaal,et al.  Direct comparison of first-contact versus longitudinal register-based case finding in the same population: early evidence that the incidence of schizophrenia may be three times higher than commonly reported , 2014, Psychological Medicine.

[9]  M. Hernán,et al.  Commentary: A structural approach to Berkson's fallacy and a guide to a history of opinions about it. , 2014, International journal of epidemiology.

[10]  Kelly J. Cowan,et al.  Estimating Wisconsin asthma prevalence using clinical electronic health records and public health data. , 2014, American journal of public health.

[11]  Chunhua Weng,et al.  Sick Patients Have More Data: The Non-Random Completeness of Electronic Health Records , 2013, AMIA.

[12]  Doheon Lee,et al.  Inferring disease association using clinical factors in a combinatorial manner and their use in drug repositioning , 2013, Bioinform..

[13]  E. Rahme,et al.  Observation Period Effects on Estimation of Systemic Lupus Erythematosus Incidence and Prevalence in Quebec , 2013, The Journal of Rheumatology.

[14]  George Hripcsak,et al.  Caveats for the use of operational electronic health record data in comparative effectiveness research. , 2013, Medical care.

[15]  M. Nivison,et al.  Diagnosing comorbidity in psychiatric hospital: challenging the validity of administrative registers , 2013, BMC Psychiatry.

[16]  R. Nielsen,et al.  Changes in the diagnosed incidence of early onset schizophrenia over four decades , 2012, Acta psychiatrica Scandinavica.

[17]  K. Anderson Health service registry data in psychiatric epidemiology: challenges for definition and interpretation , 2012, Acta psychiatrica Scandinavica.

[18]  S. Brunak,et al.  Mining electronic health records: towards better research applications and clinical care , 2012, Nature Reviews Genetics.

[19]  William R. Buckingham,et al.  Estimating Wisconsin Asthma Prevalence Using Clinical Electronic Health Records And Public Health Data , 2012, ATS 2012.

[20]  M. Fleury,et al.  Treatment prevalence and incidence of schizophrenia in Quebec using a population health services perspective: different algorithms, different estimates , 2012, Social Psychiatry and Psychiatric Epidemiology.

[21]  Hendriek C Boshuizen,et al.  Longitudinal administrative data can be used to examine multimorbidity, provided false discoveries are controlled for. , 2011, Journal of clinical epidemiology.

[22]  P. van Baal,et al.  Co-occurrence of diabetes, myocardial infarction, stroke, and cancer: quantifying age patterns in the Dutch population using health survey data , 2011, Population health metrics.

[23]  Søren Brunak,et al.  Using Electronic Patient Records to Discover Disease Correlations and Stratify Patient Cohorts , 2011, PLoS Comput. Biol..

[24]  Marc-André Blanchette,et al.  Controlling asthma during pregnancy prevents asthma in children: a Berkson fallacy? , 2010, European Respiratory Journal.

[25]  J. Roy,et al.  Estimation of age‐specific incidence rates from cross‐sectional survey data , 2010, Statistics in medicine.

[26]  R. de Graaf,et al.  Berkson's bias and the mood dimensions of bipolar disorder , 2009, International journal of methods in psychiatric research.

[27]  R. Gènova-Maleras,et al.  Epidemiological usefulness of population-based electronic clinical records in primary care: estimation of the prevalence of chronic diseases. , 2009, Family practice.

[28]  A. Carpentier,et al.  Optimal strategy to identify incidence of diagnostic of diabetes using administrative data , 2009, BMC medical research methodology.

[29]  Gabriel Coll de Tuero,et al.  A selection-bias free method to estimate the prevalence of hypertension from an administrative primary health care database in the Girona Health Region, Spain , 2009, Comput. Methods Programs Biomed..

[30]  V. Addona,et al.  On the incidence–prevalence relation and length‐biased sampling , 2008, 0808.1226.

[31]  Jim Todd,et al.  Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation , 2008, PLoS medicine.

[32]  T. Stukel,et al.  How many people have had a myocardial infarction? Prevalence estimated using historical hospital data , 2007, BMC public health.

[33]  A. Rzhetsky,et al.  Probing genetic overlap among complex human phenotypes , 2007, Proceedings of the National Academy of Sciences.

[34]  George Hripcsak,et al.  A statistical methodology for analyzing co-occurrence data from a large sample , 2007, J. Biomed. Informatics.

[35]  C. D. de Vries,et al.  Systemic lupus erythematosus prevalence in the U.K.: methodological issues when using the General Practice Research Database to estimate frequency of chronic relapsing‐remitting disease , 2007, Pharmacoepidemiology and drug safety.

[36]  L. Svenson,et al.  Estimating osteoarthritis incidence from population-based administrative health care databases. , 2007, Annals of epidemiology.

[37]  W. Bilker,et al.  The relationship between time since registration and measured incidence rates in the General Practice Research Database , 2005, Pharmacoepidemiology and drug safety.

[38]  M. Ward Estimating rare disease prevalence from administrative hospitalization databases. , 2005, Epidemiology.

[39]  L. Iezzoni,et al.  Do Variations in Disease Prevalence Limit the Usefulness of Population-Based Hospitalization Rates for Studying Variations in Hospital Admissions? , 2005, Medical care.

[40]  Oernulv Oedegaard M. D. The incidence of mental diseases as measured by census investigations versus admission statistics , 2005, The Psychiatric Quarterly.

[41]  J. Kragstrup,et al.  Estimating incidence and prevalence of episodes of care in general practice , 2004, Scandinavian journal of primary health care.

[42]  B. Modan,et al.  The limitations of using hospital controls in cancer etiology – one more example for Berkson's bias , 2002, European Journal of Epidemiology.

[43]  C. Holman,et al.  Improved methods for estimating incidence from linked hospital morbidity data. , 2003, International journal of epidemiology.

[44]  E. Goldner,et al.  Using administrative data to analyze the prevalence and distribution of schizophrenic disorders. , 2003, Psychiatric services.

[45]  L. Iezzoni,et al.  Comparing the importance of disease rate versus practice style variations in explaining differences in small area hospitalization rates for two respiratory conditions , 2003, Statistics in medicine.

[46]  M. McBean,et al.  Administrative data for public health surveillance and planning. , 2001, Annual review of public health.

[47]  T. Sørensen,et al.  The effect of recurrent events on register-based estimates of level and trends in incidence of acute myocardial infarction. , 1999, Journal of clinical epidemiology.

[48]  J. Hallas,et al.  The Waiting Time Distribution as a Graphical Approach to Epidemiologic Measures of Drug Utilization , 1997, Epidemiology.

[49]  M. Goldacre,et al.  Crohn's disease and ulcerative colitis in England and the Oxford record linkage study area: a profile of hospitalized morbidity. , 1995, International journal of epidemiology.

[50]  M. Mclean,et al.  Incidence of Guillain‐Barre Syndrome in Ontario and Quebec, 1983–1989, Using Hospital Service Databases , 1994, Epidemiology.

[51]  M. Goldacre,et al.  Estimating incidence and prevalence of treated psychiatric disorders from routine statistics: the example of schizophrenia in Oxfordshire. , 1994, Journal of epidemiology and community health.

[52]  R. Bland,et al.  Psychiatric Comorbidity and Treatment Seeking: Sources of Selection Bias in the Study of Clinical Populations , 1993, The Journal of nervous and mental disease.

[53]  E. Strömgren Changes in the Incidence of Schizophrenia? , 1987, British Journal of Psychiatry.

[54]  E. Stromgren Changes in the incidence of schizophrenia , 1987 .

[55]  N. Snyder,et al.  The Berkson Bias in Action , 1979, The Yale journal of biology and medicine.

[56]  D. Sackett,et al.  An empirical demonstration of Berkson's bias. , 1978, Journal of chronic diseases.

[57]  O. Oedegaard The incidence of mental diseases as measured by census investigations versus admission statistics , 1952, The Psychiatric quarterly.

[58]  J BERKSON,et al.  Limitations of the application of fourfold table analysis to hospital data. , 1946, Biometrics.