PHARMACOEPIDEMIOLOGY AND PRESCRIPTION Ascertainment of acute liver injury in two European primary care databases A. Ruigómez & R. Brauer & L. A. García Rodríguez & C. Huerta & G. Requena & M. Gil & Francisco de Abajo & G. Downey & A. Bate & M. Feudjo Tepie & M. de Groot & R. Schlienger & R. Reynolds & O. Klungel Received: 4 February 2014 /Accepted: 16 July 2014 /Published online: 29 July 2014 # Springer-Verlag Berlin Heidelberg 2014 Abstract Purpose The purpose of this study was to ascertain acute liver injury (ALI) in primary care databases using different com- puter algorithms. The aim of this investigation was to study and compare the incidence of ALI in different primary care databases and using different definitions of ALI. Methods The Clinical Practice Research Datalink (CPRD) in UK and the Spanish “Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria” (BIFAP) were used. Both are primary care databases from which we selected individuals of all ages registered between January 2004 and December 2009. We developed two case definitions of idio- pathic ALI using computer algorithms: (i) restrictive defini- tion (definite cases) and (ii) broad definition (definite and probable cases). Patients presenting prior liver conditions were excluded. Manual review of potential cases was performed to confirm diagnosis, in a sample in CPRD (21 %) and all potential cases in BIFAP. Incidence rates of ALI by age, sex and calendar year were calculated. Results In BIFAP, all cases considered definite after manual review had been detected with the computer algorithm as potential cases, and none came from the non-cases group. The restrictive definition of ALI had a low sensitivity but a very high specificity (95 % in BIFAP) and showed higher rates of agreement between computer search and manual review compared to the broad definition. Higher incidence rates of definite ALI in 2008 were observed in BIFAP (3.01 (95 % confidence interval (CI) 2.13–4.25) per 100,000 person-years than CPRD (1.35 (95 % CI 1.03–1.78)). Conclusions This study shows that it is feasible to identify ALI cases if restrictive selection criteria are used and the possibility to review additional information to rule out This work has not been published or presented in any way before. Electronic supplementary material The online version of this article (doi:10.1007/s00228-014-1721-y) contains supplementary material, which is available to authorized users. A. Ruigómez (*) : L. A. G. Rodríguez Centro Español de Investigación Farmacoepidemiologica (CEIFE), Almirante 28, 2°, 28004 Madrid, Spain e-mail: aruigomez@ceife.es R. Brauer Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK C. Huerta : G. Requena : M. Gil : F. de Abajo Division of Pharmacoepidemiology and Pharmacovigilance, Medicines for Human Use Department, Agencia Española de Medicamentos y Productos Sanitarios (AEMPS), Madrid, Spain F. de Abajo Pharmacology Section, Department of Biomedical Sciences II, University of Alcalá, Madrid, Spain R. Brauer : G. Downey : M. F. Tepie Amgen NV, London, UK A. Bate Epidemiology, Pfizer Ltd, Walton Oaks, Dorking Road, Tadworth, UK M. de Groot : O. Klungel Division of Pharmacoepidemiology & Clinical Pharmacology, Faculty of Science, Utrecht University, Utrecht, The Netherlands R. Schlienger Novartis Pharma AG, Basel, Switzerland R. Reynolds Epidemiology, Pfizer Research & Development, New York, NY, USA Eur J Clin Pharmacol (2014) 70:1227–1235 DOI 10.1007/s00228-014-1721-y