title: Automatic identification of type 2 diabetes, hypertension, ischaemic heart disease, heart failure and their levels of severity from Italian General Practitioners' electronic medical records: a validation study.
abstract: The Italian project MATRICE aimed to assess how well cases of type 2 diabetes (T2DM), hypertension, ischaemic heart disease (IHD) and heart failure (HF) and their levels of severity can be automatically extracted from the Health Search/CSD Longitudinal Patient Database (HSD). From the medical records of the general practitioners (GP) who volunteered to participate, cases were extracted by algorithms based on diagnosis codes, keywords, drug prescriptions and results of diagnostic tests. A random sample of identified cases was validated by interviewing their GPs.
  
  
  
  HSD is a database of primary care medical records. A panel of 12 GPs participated in this validation study.
  
  
  
  300 patients were sampled for each disease, except for HF, where 243 patients were assessed.
  
  
  
  The positive predictive value (PPV) was assessed for the presence/absence of each condition against the GP's response to the questionnaire, and Cohen's κ was calculated for agreement on the severity level.
  
  
  
  The PPV was 100% (99% to 100%) for T2DM and hypertension, 98% (96% to 100%) for IHD and 55% (49% to 61%) for HF. Cohen's kappa for agreement on the severity level was 0.70 for T2DM and 0.69 for hypertension and IHD.
  
  
  
  This study shows that individuals with T2DM, hypertension or IHD can be validly identified in HSD by automated identification algorithms. Automatic queries for levels of severity of the same diseases compare well with the corresponding clinical definitions, but some misclassification occurs. For HF, further research is needed to refine the current algorithm.
authors.affiliation: Agenzia regionale di sanità della Toscana, Osservatorio di epidemiologia, Florence, Italy.|Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands.
authors.forename: Rosa
authors.identifier: 0000-0002-6250-877X
authors.initials: R
authors.lastname: Gini
authors.affiliation: Department of Epidemiology Janssen Research & Development, Titusville, New Jersey, USA.|Observational Health Data Sciences and Informatics (OHDSI), New York, New York, USA.
authors.forename: Martijn J
authors.initials: MJ
authors.lastname: Schuemie
authors.affiliation: Health Search, Italian College of General Practitioners and Primary Care, Florence, Italy.
authors.forename: Giampiero
authors.initials: G
authors.lastname: Mazzaglia
authors.affiliation: Health Search, Italian College of General Practitioners and Primary Care, Florence, Italy.
authors.forename: Francesco
authors.initials: F
authors.lastname: Lapi
authors.affiliation: Agenzia regionale di sanità della Toscana, Osservatorio di epidemiologia, Florence, Italy.
authors.forename: Paolo
authors.initials: P
authors.lastname: Francesconi
authors.affiliation: Health Search, Italian College of General Practitioners and Primary Care, Florence, Italy.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Pasqua
authors.affiliation: Health Search, Italian College of General Practitioners and Primary Care, Florence, Italy.
authors.forename: Elisa
authors.initials: E
authors.lastname: Bianchini
authors.affiliation: Genomedics, Florence, Italy.
authors.forename: Carmelo
authors.initials: C
authors.lastname: Montalbano
authors.affiliation: Agenzia regionale di sanità della Toscana, Osservatorio di epidemiologia, Florence, Italy.
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Roberto
authors.affiliation: Agenzia regionale di sanità della Toscana, Osservatorio di epidemiologia, Florence, Italy.
authors.forename: Valentina
authors.initials: V
authors.lastname: Barletta
authors.affiliation: Genomedics, Florence, Italy.
authors.forename: Iacopo
authors.initials: I
authors.lastname: Cricelli
authors.affiliation: Italian College of General Practitioners and Primary Care, Florence, Italy.
authors.forename: Claudio
authors.initials: C
authors.lastname: Cricelli
authors.affiliation: Agenzia Nazionale per il Servizi Sanitari Regionali, Rome, Italy.
authors.forename: Giulia
authors.initials: G
authors.lastname: Dal Co
authors.affiliation: Agenzia Nazionale per il Servizi Sanitari Regionali, Rome, Italy.
authors.forename: Mariadonata
authors.initials: M
authors.lastname: Bellentani
authors.affiliation: Department of Medical Informatics, Erasmus Medical Center, Rotterdam, The Netherlands.
authors.forename: Miriam
authors.initials: M
authors.lastname: Sturkenboom
authors.affiliation: Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
authors.forename: Niek
authors.initials: N
authors.lastname: Klazinga
mesh_terms: D000465:Algorithms; D003924:Diabetes Mellitus, Type 2 / Q000175:diagnosis*; D057286:Electronic Health Records / Q000592:standards*; D006333:Heart Failure / Q000175:diagnosis*; D006801:Humans; D006973:Hypertension / Q000175:diagnosis*; D007558:Italy; D017202:Myocardial Ischemia / Q000175:diagnosis*; D011237:Predictive Value of Tests; D012720:Severity of Illness Index
keywords: DIABETES & ENDOCRINOLOGY; PRIMARY CARE; Validation study; electronic medical records