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Anna Ponjoan,1–3 Josep Garre-Olmo,3 Jordi Blanch,1 Ester Fages,1,4Lia Alves-Cabratosa,1 Ruth Martí-Lluch,1–3 Marc Comas-Cufí,1 Dídac Parramon,1,4María García-Gil,1 Rafel Ramos1,51Vascular Health Research Group (ISV-Girona), Jordi Gol Institute for Primary Care Research (IDIAPJGol), Barcelona, Catalonia, Spain; 2Universitat Autònoma de Barcelona, Bellaterra, Catalonia, Spain; 3Girona Biomedical Research Institute (IDIBGI), Girona, Catalonia, Spain; 4Primary Care Services, Catalan Health Institute (ICS), Girona, Catalonia, Spain; 5Department of Medical Sciences, School of Medicine, Campus Salut, University of Girona, Girona, Catalonia, SpainBackground: Electronic health records (EHR) from primary care are emerging in Alzheimer’s disease (AD) research, but their accuracy is a concern. We aimed to validate AD diagnoses from primary care using additional information provided by general practitioners (GPs), and a register of dementias.Patients and methods: This retrospective observational study obtained data from the System for the Development of Research in Primary Care (SIDIAP). Three algorithms combined International Statistical Classification of Diseases (ICD-10) and Anatomical Therapeutic Chemical codes to identify AD cases in SIDIAP. GPs evaluated dementia diagnoses by means of an online survey. We linked data from the Register of Dementias of Girona and from SIDIAP. We estimated the positive predictive value (PPV) and sensitivity and provided results stratified by age, sex and severity.Results: Using survey data from the GPs, PPV of AD diagnosis was 89.8% (95% CI: 84.7–94.9). Using the dataset linkage, PPV was 74.8 (95% CI: 73.1–76.4) for algorithm A1 (AD diagnoses), and 72.3 (95% CI: 70.7–73.9) for algorithm A3 (diagnosed or treated patients without previous conditions); sensitivity was 71.4 (95% CI: 69.6–73.0)and 83.3 (95% CI: 81.8–84.6) for algorithmsA1 (AD diagnoses) and A3, respectively.Stratified results did not differ by age, but PPV and sensitivity estimates decreased amongst men and severe patients, respectively.Conclusions: PPV estimates differed depending on the gold standard. The development of algorithms integrating diagnoses and treatment of dementia improved the AD case ascertainment. PPV and sensitivity estimates were high and indicated that AD codes recorded in a large primary care database were sufficiently accurate for research purposes.Keywords: dementia, family physician, survey, algorithm, data accuracy, real-world data, validation, electronic medical records

Anna Ponjoan,1–3 Josep Garre-Olmo,2 Jordi Blanch,1 Ester Fages,1 Lia Alves-Cabratosa,1 Ruth Martí-Lluch,1–3 Marc Comas-Cufí,1 Dídac Parramon,1,4 María Garcia-Gil,1 Rafel Ramos1,5 1Vascular Health Research Group (ISV-Girona), Jordi Gol Institute for Primary Care Research (IDIAPJGol), Barcelona, Catalonia, Spain; 2Girona Biomedical Research Institute (IDIBGI), Girona, Catalonia, Spain; 3Santa Clara Primary Care Health Center, Catalan Health Institute, Girona, Catalonia, Spain; 4Autonomous University of Barcelona, Bellaterra (Cerdanyola del Vallès), Catalonia, Spain; 5Department of Medical Sciences, School of Medicine, Campus Salut, University of Girona, Girona, Catalonia, Spain Purpose: Updated estimates of incidence and prevalence of dementia are crucial to ensure adequate public health policy. However, most of the epidemiological studies in the population in Spain were conducted before 2010. This study assessed the validity of dementia diagnoses recorded in electronic health records contained in a large primary-care database to determine if they could be used for research purposes. Then, to update the epidemiology of dementia in Catalonia (Spain), we estimated crude and standardized prevalence and incidence rates of dementia in Catalonia in 2016. Methods: The System for the Development of Research in Primary Care (SIDIAP) database contains anonymized information for >80% of the Catalan population. Validity of dementia codes in SIDIAP was assessed in patients at least 40 years old by asking general practitioners for additional evidence to support the diagnosis. Crude and standardized incidence and prevalence (95% CI) in people aged ≥65 years were estimated assuming a Poisson distribution. Results: The positive predictive value of dementia diagnoses recorded in SIDIAP was estimated as 91.0% (95% CI 87.5%–94.5%). Age- and sex-standardized incidence and prevalence of dementia were 8.6/1,000 person-years (95% CI 8.0–9.3) and 5.1% (95% CI 4.5%–5.7%), respectively. Conclusion: SIDIAP contains valid dementia records. We observed incidence and prevalence estimations similar to recent face-to-face studies conducted in Spain and higher than studies using electronic health data from other European populations. Keywords: family physician, accuracy, quality, positive predictive value, electronic medical record, real-world data