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Background Biological drugs have improved the management of immune-mediated inflammatory diseases (IMIDs) despite being associated with important safety issues such as immunogenicity, infections, and malignancies in real-world settings. Objective The aim of this study was to explore the potential of a large Italian multi-database distributed network for use in the postmarketing surveillance of biological drugs, including biosimilars, in patients with IMID. Methods A retrospective cohort study was conducted using 13 Italian regional claims databases during 2010–2019. A tailor-made R-based tool developed for distributed analysis of claims data using a study-specific common data model was customized for this study. We measured the yearly prevalence of biological drug users and the frequency of switches between originator and biosimilars for infliximab, etanercept, and adalimumab separately and stratified them by calendar year and region. We then calculated the cumulative number of users and person-years (PYs) of exposure to individual biological drugs approved for IMIDs. For a number of safety outcomes (e.g., severe acute respiratory syndrome coronavirus 2 [SARS-COV-2] infection), we conducted a sample power calculation to estimate the PYs of exposure required to investigate their association with individual biological drugs approved for IMIDs, considering different strengths of association. Results From a total underlying population of almost 50 million inhabitants from 13 Italian regions, we identified 143,602 (0.3%) biological drug users, with a cumulative exposure of 507,745 PYs during the entire follow-up. The mean age ± standard deviation of biological drug users was 49.3 ± 16.3, with a female-to-male ratio of 1.2. The age-adjusted yearly prevalence of biological drug users increased threefold from 0.7 per 1000 in 2010 to 2.1 per 1000 in 2019. Overall, we identified 40,996 users of biosimilars of tumor necrosis factor (TNF)-α inhibitors (i.e., etanercept, adalimumab, and infliximab) in the years 2015–2019. Of these, 46% (N = 18,845) switched at any time between originator and biosimilars or vice versa. To investigate a moderate association (incidence rate ratio 2) between biological drugs approved for IMIDs and safety events of interest, such as optic neuritis (lowest background incidence rate 10.4/100,000 PYs) or severe infection (highest background incidence rate 4312/100,000 PYs), a total of 43,311 PYs and 104 PYs of exposure to individual biological drugs, respectively, would be required. As such, using this network, of 15 individual biological drugs approved for IMIDs, the association with those adverse events could be investigated for four (27%) and 14 (93%), respectively. Conclusion The VALORE project multi-database network has access to data on more than 140,000 biological drug users (and > 0.5 million PYs) from 13 Italian regions during the years 2010–2019, which will be further expanded with the inclusion of data from other regions and more recent calendar years. Overall, the cumulated amount of person-time of exposure to biological drugs approved for IMIDs provides enough statistical power to investigate weak/moderate associations of almost all individual compounds and the most relevant safety outcomes. Moreover, this network may offer the opportunity to investigate the interchangeability of originator and biosimilars of several TNFα inhibitors in different therapeutic areas in real-world settings. Supplementary Information The online version contains supplementary material available at 10.1007/s40259-021-00498-3.

Background: In May 2020, the ACCESS (The vACCine covid-19 monitoring readinESS) project was launched to prepare real-world monitoring of COVID-19 vaccines. Within this project, this study aimed to generate background incidence rates of 41 adverse events of special interest (AESI) to contextualize potential safety signals detected following administration of COVID-19 vaccines. Methods: A dynamic cohort study was conducted using a distributed data network of 10 healthcare databases from 7 European countries (Italy, Spain, Denmark, The Netherlands, Germany, France and United Kingdom) over the period 2017 to 2020. A common protocol (EUPAS37273), common data model, and common analytics programs were applied for syntactic, semantic and analytical harmonization. Incidence rates (IR) for each AESI and each database were calculated by age and sex by dividing the number of incident cases by the total person-time at risk. Age-standardized rates were pooled using random effect models according to the provenance of the events. Findings: A total number of 63,456,074 individuals were included in the study, contributing to 211.7 million person-years. A clear age pattern was observed for most AESIs, rates also varied by provenance of disease diagnosis (primary care, specialist care). Thrombosis with thrombocytopenia rates were extremely low ranging from 0.06 to 4.53/100,000 person-years for cerebral venous sinus thrombosis (CVST) with thrombocytopenia (TP) and mixed venous and arterial thrombosis with TP, respectively. Interpretation: Given the nature of the AESIs and the setting (general practitioners or hospital-based databases or both), background rates from databases that show the highest level of completeness (primary care and specialist care) should be preferred, others can be used for sensitivity. The study was designed to ensure representativeness to the European population and generalizability of the background incidence rates. Funding: The project has received support from the European Medicines Agency under the Framework service contract nr EMA/2018/28/PE.

Background: Little is known about the comparative risk of death with atypical or conventional antipsychotics (APs) among persons with cardiovascular or cerebrovascular disease (CCD). Research design and methods: A cohort study was conducted using five Italian claims databases. New atypical AP users with CCD aged ≥65 (reference) were matched to new conventional AP users. Mortality per 100 person-years (PYs) and hazard ratios (HR), estimated using Cox models, were reported. Incidence and risk of death were estimated for persons having drug–drug interactions. Outcome occurrence was evaluated 180 days after AP initiation. Results: Overall 24,711 and 27,051 elderly new conventional and atypical AP users were identified. The mortality rate was 51.3 and 38.5 deaths per 100 PYs for conventional and atypical AP users. Mortality risk was 1.33 (95%CI: 1.27–1.39) for conventional APs. There was no increased mortality risk with single drug–drug interactions (DDIs) vs. no DDI. AP users with ≥1 DDI had a 29% higher mortality risk compared to no DDI in the first 90 days of treatment (HR: 1.29 (95% CI: 1.00–1.67)). Conclusions: Conventional APs had a higher risk of death than atypical APs among elderly persons with CCD. Having ≥1 DDI was associated with an increased risk of death.

BACKGROUND: acute myocardial infarction (AMI), ischemic heart diseases (IHDs) and stroke are serious cardiovascular diseases (CVDs) which may lead to hospitalizations, require periodical medical monitoring and life-long drugs use, thus having a high impact on public health and Healthcare Service expenditure. In this contest, Italian Healthcare Administrative Databases (HADs), which routinely collect patient-level information on healthcare services reimbursed by the National Healthcare service, are increasingly used for identification of these CVDs. ObjectiveS: to identify and describe all AMI, IHDs and stroke case-identification algorithms by means of Italian HADs, through the review of papers published in the past 10 years. Methods: this study is part of a project that systematically reviewed case-identification algorithms for 18 acute and chronic conditions by means of HADs in Italy. PubMed was searched for original articles, published between 2007 and 2017, in Italian or English. The search string consisted of a combination of free text and MeSH terms with a common part that focused on HADs and a disease-specific part. All identified papers were screened by two independent reviewers. Pertinent papers were classified according to the objective for which the algorithm had been used, and only articles that used algorithms for primary objectives (I disease occurrence; II population/cohort selection; III outcome identification) were considered for algorithm extraction. The HADs used (hospital discharge records, drug prescriptions, etc.), ICD-9 and ICD-10 codes, ATC classification of drugs, follow-back periods, and age ranges applied by the algorithms have been reported. Further information on specific objective(s), accuracy measures, sensitivity analyses and the contribution of each HAD, have also been recorded. Results: the search strategy has led to the identification of 611 papers for AMI,801 for IHDs and 791 for stroke. Among these,45,12 and 31 papers for AMI, IHDs and stroke respectively, were considered pertinent for inclusion in the systematic review. The majority of the works was published during 2014-2017. The setting of the studies was mainly regional for AMI and stroke, while the majority of IHD’s papers was based on a national multicenter context. By screening full texts, a total of 17,5 and 28 original algorithms for AMI, IHDs and stroke respectively, intended for the above-mentioned objectives, were found. Moreover, 3 original algorithms for STEMI, 3 for NSTEMI, 8 for ischemic stroke and 3 for hemorrhagic stroke were identified. The hospital discharge diagnosis database (HDD) was used in all algorithms. In only a few cases the co-payment exemption registry, drug prescription database, and mortality registry database were used as additional algorithm components. For the same event, there was always a difference of >1 code. External validation was performed in only one case for AMI and stroke identification. Conclusion: a remarkable heterogeneity, in terms of both data sources and codes used, was observed for algorithms aimed to identify AMI, IHDs and stroke in HADs. This was likely due to the paucity of validation studies. Administrative data sources other than HDD remain underutilized.

BACKGROUND: there has been a long-standing, consistent use worldwide of Healthcare Administrative Databases (HADs) for epidemiological purposes, especially to identify acute and chronic health conditions. These databases are able to reflect health-related conditions at a population level through disease-specific case-identification algorithms that combine information coded in multiple HADs. In Italy, in the past 10 years, HAD-based case-identification algorithms have experienced a constant increase, with a significant extension of the spectrum of identifiable diseases. Besides estimating incidence and/or prevalence of diseases, these algorithms have been used to enroll cohorts, monitor quality of care, assess the effect of environmental exposure, and identify health outcomes in analytic studies. Despite the rapid increase in the use of case-identification algorithms, information on their accuracy and misclassification rate is currently unavailable for most conditions. OBJECTIVES: to define a protocol to systematically review algorithms used in Italy in the past 10 years for the identification of several chronic and acute diseases, providing an accessible overview to future users in the Italian and international context. METHODS: PubMed will be searched for original research articles, published between 2007 and 2017, in Italian or English. The search string consists of a combination of free text and MeSH terms with a common part on HADs and a disease-specific part. All identified papers will be screened for eligibility by two independent reviewers. All articles that used/defined an algorithm for the identification of each disease of interest using Italian HADs will be included. Algorithms with exclusive use of death certificates, pathology register, general practitioner or pediatrician data will be excluded. Pertinent papers will be classified according to the objective for which the algorithm was used, and only articles that used algorithms with "primary objectives" (I disease occurrence; II population/cohort selection; III outcome identification) will be considered for algorithm extraction. The HADs used (hospital discharge records, drug prescriptions, etc.), ICD-9 and ICD-10 codes, ATC classification of drugs, follow-back periods, and age ranges applied by the algorithms will be collected. Further information on specific accuracy measures from external validations, sensitivity analyses, and the contribution of each source will be recorded. This protocol will be applied for 16 different systematic reviews concerning eighteen diseases (Hypothyroidism, Hyperthyroidism, Diabetes mellitus, Type 1 diabetes mellitus, Acute myocardial infarction, Ischemic heart disease, Stroke, Hypertension, Heart failure, Congenital heart anomalies, Parkinson's disease, Multiple sclerosis, Epilepsy, Chronic obstructive pulmonary disease, Asthma, Inflammatory bowel disease, Celiac disease, Chronic kidney failure). CONCLUSION: this protocol defines a standardized approach to extensively examine and compare all experiences of case identification algorithms in Italy, on the 18 abovementioned diseases. The methodology proposed may be applied to other systematic reviews concerning diseases not included in this project, as well as other settings, including international ones. Considering the increasing availability of healthcare data, developing standard criteria to describe and update characteristics of published algorithms would be of great use to enhance awareness in the choice of algorithms and provide a greater comparability of results.

Objective: The objective of this study was to investigate the relationship between adherence to statin therapy and the risk of exacerbation among elderly individuals affected by chronic obstructive pulmonary disease and cardiovascular disease. Methods: Using the healthcare utilisation databases of five Italian territorial units accounting for nearly 35% of the Italian population, we recruited a cohort of 6263 elderly persons (i.e. aged 65 years or older) with co-existing chronic obstructive pulmonary disease and cardiovascular disease who initiated statin therapy. Exposure was adherence to statins measured by the proportion of days of follow-up covered. Outcome was the first hospital admission for chronic obstructive pulmonary disease occurring in the period of observation. A proportional hazards model was used to estimate the hazard ratio and 95% confidence intervals for the exposure–outcome association, after adjusting for several covariates. A set of sensitivity analyses was performed to account for sources of systematic uncertainty. Results: During an average follow-up of about 4 years, 1307 cohort members experienced the outcome. Compared with patients with low adherence (proportion of days of follow-up covered ≤ 40%), those with intermediate (proportion of days of follow-up covered 41–80%) and high (proportion of days of follow-up covered > 80%) adherence exhibited a lower risk of exacerbation of 16% (95% confidence interval 3–27) and 23% (95% confidence interval 10–34). Conclusions: In a real-world setting, we observed evidence that adherence to statin therapy markedly reduced the risk of chronic obstructive pulmonary disease exacerbations in elderly patients with co-existing chronic obstructive pulmonary disease and cardiovascular disease. Given the limited and controversial evidence from trials, more randomised controlled trials are urgently needed to better examine the potential benefits of statins as adjunct therapy in chronic obstructive pulmonary disease.

Objectives To describe NSAID utilization for musculoskeletal conditions in a large cohort of Italian elderly with cerebro/cardiovascular disease, a population in which NSAIDs should be generally avoided due to the prothrombotic potential. Methods Administrative data from five Italian geographic areas were analyzed. Patients aged ≥ 65 with a cerebro/cardiovascular event recorded between 2008 and 2011 (cohort entry) were selected. Prescription NSAIDs reimbursed for musculoskeletal conditions and dispensed during 1 year follow-up were retrieved to describe (i) prevalence of use, (ii) average amount of defined daily doses of NSAIDs claimed by users per day of follow-up, and (iii) distribution of the received daily dose (RDD) among patients with ≥ 2 dispensings. Among new users, i.e., patients without NSAID dispensings during 2 years before cohort entry, the first dispensed NSAID molecule was observed. Results Overall, 511,989 patients were selected. Across the five geographic areas, prevalence of use ranged from 48 to 21% and average consumption ranged between 30 and 67 DDD/1000 users/day. Around 10% of patients in the overall cohort had a RDD > 1. Nimesulide (9.6%) and diclofenac (7.5%) had the highest prevalence of use. The most consumed NSAIDs were nimesulide and coxibs with 10.6 and 7.5 DDD/1000 users/day, respectively. Among new users recruited in 2011, 30% had diclofenac or a coxibs as the first prescription. Conclusions NSAID use was common in the study cohort, particularly in central-southern areas. In contrast with current recommendations, coxibs and diclofenac were among the most prescribed active principles, even in new users. Interventions to promote appropriateness of use are warranted. Electronic supplementary material The online version of this article (10.1007/s00228-018-2411-y) contains supplementary material, which is available to authorized users.

Switching between different erythropoiesis-stimulating agents (ESAs) during the first year of therapy is frequent (15–20%), much more so toward reference products than biosimilars. The objectives of this study were to investigate the frequency and identify the potential predictors of switching between biosimilar and originator ESAs during the first year of treatment in patients with chronic kidney disease (CKD), or chemotherapy-related anemia from six large Italian geographic areas in the years 2009–2015. A retrospective cohort study was conducted using six Italian regional claims databases (≥ 13 million inhabitants) during 2009–2015. Among incident epoetin users, the frequency of single, multiple, and backward switch during the first year of treatment was evaluated. Using frailty Cox models, potential predictors of first switch were identified. All analyses were stratified by the main indications for use. Among 102,240 incident epoetin users, 15,853 (15.5%) switched to another epoetin during the first year of therapy; only 18% of these switched to biosimilars. Single switch was more common (62.2% of the switchers) than multiple (23.5%) or backward switch (14.3%). In cancer, the cumulative number of transfusions and iron preparations dispensed, as well as hyperparathyroidism, were predictors of switching. In CKD, the cumulative number of transfusions, number of vitamin A/D preparations dispensed, and CKD severity increased the probability of switching. Switching between ESAs was frequent in both CKD and cancer patients. The number of cumulative transfusions and severity of disease seemed to affect the switch.

Introduction Real-world data on the comparative effectiveness and safety of switching among different epoetins (including originators and biosimilars) are limited. In light of current debate about interchangeability, prescribers, some patient groups and decision makers are calling for additional post-marketing evidence on the clinical effects of switching between originator and biosimilar epoetins in chronic kidney disease (CKD) patients. Objective The objective of this study was to evaluate the effectiveness and safety of switching versus non-switching and of switching from originator/biosimilar epoetin alpha (ESA α) to any other epoetin in CKD patients. Methods An observational, record-linkage, multi-database, retrospective cohort study was carried out in four Italian geographical areas. All subjects with at least one ESA α dispensing between 1 January 2009 and 31 December 2015 were retrieved. Switching was defined as any transition between originator/biosimilar ESA α to any other epoetin in a series of two consecutive prescriptions up to 2 years. Switchers were matched 1:1 with non-switchers by baseline propensity score and by duration of ESA α treatment. Switchers and non-switchers were followed up from switching date to a maximum of 1 year. Lack of effectiveness and safety of switching versus non-switching were evaluated through Cox regression models (hazard ratio [HR], 95% confidence interval [CI]). A direct comparison between the two switcher categories (switchers from originator/biosimilar ESA α to any other epoetin) was also performed. Results Overall, 14,400 incident users of ESA α for anaemia due to CKD (61.4% originator, 38.6% biosimilar) were available for analysis. During the follow-up, we found no differences on effectiveness (HR 1.02, 95% CI 0.79–1.31 originators; HR 1.16, 95% CI 0.75–1.79 biosimilars) and safety outcomes (HR 1.08, 95% CI 0.77–1.50 originators; HR 1.20, 95% CI 0.66–2.21 biosimilars) between switchers and non-switchers of ESA α. Cumulative probabilities of recording an adverse event, either in terms of lack of effectiveness or safety issue, were the same for two switching categories Conclusions In this large-scale Italian observational multi-database study, switching versus non-switching as well as switching from biosimilar/originator ESA α to any other epoetin in CKD patients is not associated with any effectiveness and safety outcomes. Electronic supplementary material The online version of this article (10.1007/s40264-019-00845-y) contains supplementary material, which is available to authorized users.

Background and Objectives: Antihypertensive treatment with calcium channel blockers (CCBs) is consolidated in clinical practice; however, different studies observed increased risks of acute events for short-acting CCBs. This study aimed to provide real-world evidence on risks of acute cardiovascular (CV) events, hospitalizations and mortality among users of different CCB classes in secondary CV prevention. Methods: Three case–control studies were nested in a cohort of Italian elderly hypertensive CV-compromised CCBs users. Cases were subjects with CV events (n = 25,204), all-cause hospitalizations (n = 19,237), or all-cause mortality (n = 17,996) during the follow-up. Up to four controls were matched for each case. Current or past exposition to CCBs at index date was defined based on molecule, formulation and daily doses of the last CCB delivery. The odds ratio (OR) and 95% confidence intervals (CI) were estimated using conditional logistic regression models. Results: Compared to past users, current CCB users had significant reductions in risks of CV events [OR 0.88 (95% CI: 0.84–0.91)], hospitalization [0.90 (0.88–0.93)] and mortality [0.48 (0.47–0.49)]. Current users of long-acting dihydropyridines (DHPs) had the lowest risk [OR 0.87 (0.84–0.90), 0.86 (0.83–0.90), 0.55 (0.54–0.56) for acute CV events, hospitalizations and mortality], whereas current users of short-acting CCBs had an increased risk of acute CV events [OR 1.77 (1.13–2.78) for short-acting DHPs; 1.19 (1.07–1.31) for short-acting non-DHPs] and hospitalizations [OR 1.84 (0.96–3.51) and 1.23 (1.08–1.42)]. Conclusions: The already-existing warning on short-acting CCBs should be potentiated, addressing clinicians towards the choice of long-acting formulations.

Background and Objective: Conflicting findings from studies evaluating the association between use of antidepressant drugs and mortality have been reported. We tested the hypothesis that better adherence to antidepressant therapy may reduce mortality. Methods: The cohort included 29,845 individuals aged ≥ 65 years from several Italian health units who were newly treated with antidepressant drugs after hospital discharge with a diagnosis for cardiovascular disease during 2008–2010. These individuals were observed from the first prescription until the end of data availability (i.e. 2012–2014, depending on the local database). During this period, information on (1) prescription of antidepressants and other medications and (2) death from any cause (outcome) was recorded. Proportional hazards models were fitted to estimate the association between better adherence to antidepressants (defined as proportion of days covered ≥ 75%) and outcome, by adjusting and stratifying for several covariates. Results: Patients with better adherence to antidepressants had a reduced mortality of 9% (95% CI 3–14). Patients who did not use other medicaments during follow-up had reduced mortality associated with better adherence to antidepressants of 21% (− 1–38), 14% (7–20), 20% (13–26) and 13% (7–19) for no users of antihypertensive agents, lipid-lowering agents, other cardiovascular drugs and antidiabetics, respectively. Conclusions: Better adherence to antidepressants is associated with reduced all-cause mortality, mainly in patients who did not use other pharmacological treatments. Behavioural changes to enhance adherence among the elderly with cardiovascular disease might offer important benefits in reducing their mortality.

Purpose In this proof-of-concept paper we describe the framework, process, and preliminary results of combining data from European electronic healthcare record (EHR) databases for large-scale monitoring of drug safety. Methods Aggregated demographic, clinical, and prescription data from eight databases in four countries (Denmark, Italy, Netherlands, the UK) were pooled using a distributed network approach by generation of common input data followed by local aggregation through custom-built software, Jerboa (c). Comparison of incidence rates of upper gastrointestinal bleeding (UGIB) and nonsteroidal anti-inflammatory drug (NSAID) utilization patterns were used to evaluate data harmonization and quality across databases. The known association of NSAIDs and UGIB was employed to demonstrate sensitivity of the system by comparing incidence rate ratios (IRRs) of UGIB during NSAID use to UGIB during all other person-time. Results The study population for this analysis comprised 19 647 445 individuals corresponding to 59 929 690 person-years of follow-up. 39 967 incident cases of UGIB were identified during the study period. Crude incidence rates varied between 38.8 and 109.5/100 000 person-years, depending on country and type of database, while age-standardized rates ranged from 25.1 to 65.4/100 000 person-years. NSAID use patterns were similar for databases within the same country but heterogeneous among different countries. A statistically significant age-and gender-adjusted association between use of any NSAID and increased risk for UGIB was confirmed in all databases, IRR from 2.0 (95%CI:1.7-2.2) to 4.3 (95%CI: 4.1-4.5). Conclusions Combining data from EHR databases of different countries to identify drug-adverse event associations is feasible and can set the stage for changing and enlarging the scale for drug safety monitoring. Copyright (C) 2010 John Wiley & Sons, Ltd.

Background For chronic conditions, disparities can take effect cumulatively at various times as the disease progresses, even when care is provided. The aim of this study was to quantify the prevalence of diabetes, congestive heart failure (CHF) and coronary heart disease (CHD) in adults by citizenship, and to compare the performance of primary care services in managing these chronic conditions, again by citizenship. Methods This is a population-based retrospective cohort study on 1,948,622 people aged 16 years or more residing in Italy. A multilevel regression model was applied to analyze adherence to care processes using explanatory variables at both patient and district level. Results The age-adjusted prevalence of diabetes was found higher among immigrants from high migratory pressure countries (HMPC) than among Italians, while the age-adjusted prevalence of CHD and CHF was higher for Italians than for HMPC immigrants or those from highly-developed countries (HDC). Our results indicate lower levels in all quality management indicators for citizens from HMPC than for Italians, for all the chronic conditions considered. Patients from HDC did not differ from Italian in their adherence to disease management schemes. Conclusion This study revealed a different prevalence of chronic diseases by citizenship, implying a different burden of primary care by citizenship. Our findings show that more effort is needed to guarantee migrant-sensitive primary health care.

Although studies show that interpersonal violence is associated with poorer mental health, few studies specify the conditions under which victimization can be more or less detrimental to psychological well-being. Building on previous research, the authors test whether the association between interpersonal violence and psychological distress is moderated by alcohol consumption. Our analysis of longitudinal data from the Welfare, Children, and Families project suggests that interpersonal violence is more strongly associated with psychological distress in the context of more frequent intoxication. Programs designed to treat the combination of victimization and heavy alcohol consumption may make unique contributions to the well-being of women.

The EU-ADR project aims to exploit different European electronic healthcare records (EHR) databases for drug safety signal detection. In this paper we report the preliminary results concerning the comparison of signal detection between EU-ADR network and two spontaneous reporting databases, the Food and Drug Administration and World Health Organization databases. EU-ADR data sources consist of eight databases in four countries (Denmark, Italy, Netherlands, and United Kingdom) that are virtually linked through distributed data network. A custom-built software (Jerboa©) elaborates harmonized input data that are produced locally and generates aggregated data which are then stored in a central repository. Those data are subsequently analyzed through different statistics (i.e. Longitudinal Gamma Poisson Shrinker). As potential signals, all the drugs that are associated to six events of interest (bullous eruptions - BE, acute renal failure - ARF, acute myocardial infarction - AMI, anaphylactic shock - AS, rhabdomyolysis - RHABD, and upper gastrointestinal bleeding - UGIB) have been detected via different data mining techniques in the two systems. Subsequently a comparison concerning the number of drugs that could be investigated and the potential signals detected for each event in the spontaneous reporting systems (SRSs) and EU-ADR network was made. SRSs could explore, as potential signals, a larger number of drugs for the six events, in comparison to EU-ADR (range: 630-3,393 vs. 87-856), particularly for those events commonly thought to be potentially drug-induced (i.e. BE: 3,393 vs. 228). The highest proportion of signals detected in SRSs was found for BE, ARF and AS, while for ARF, and UGIB in EU-ADR. In conclusion, it seems that EU-ADR longitudinal database network may complement traditional spontaneous reporting system for signal detection, especially for those adverse events that are frequent in general population and are not commonly thought to be drug-induced. The methodology for signal detection in EU-ADR is still under development and testing phase.

The overall objective of the EU-ADR project is the design, development, and validation of a computerised system that exploits data from electronic health records and biomedical databases for the early detection of adverse drug reactions. Eight different databases, containing health records of more than 30 million European citizens, are involved in the project. Unique queries cannot be performed across different databases because of their heterogeneity: Medical record and Claims databases, four different terminologies for coding diagnoses, and two languages for the information described in free text. The aim of our study was to provide database owners with a common basis for the construction of their queries. Using the UMLS, we provided a list of medical concepts, with their corresponding terms and codes in the four terminologies, which should be considered to retrieve the relevant information for the events of interest from the databases.

Background: An aging population means that chronic illnesses, such as diabetes, are becoming more prevalent and demands for care are rising. Members of primary care teams should organize and coordinate patient care with a view to improving quality of care and impartial adherence to evidence-based practices for all patients. The aims of the present study were: to ascertain the prevalence of diabetes in an Italian population, stratified by age, gender and citizenship; and to identify the rate of compliance with recommended guidelines for monitoring diabetes, to see whether disparities exist in the quality of diabetes patient management.Methods: A population-based analysis was performed on a dataset obtained by processing public health administration databases. The presence of diabetes and compliance with standards of care were estimated using appropriate algorithms. A multilevel logistic regression analysis was applied to assess factors affecting compliance with standards of care.Results: 1,948,622 Italians aged 16+ were included in the study. In this population, 105,987 subjects were identified as having diabetes on January 1st, 2009. The prevalence of diabetes was 5.43% (95% CI 5.33-5.54) overall, 5.87% (95% CI 5.82-5.92) among males, and 5.05% (95% CI 5.00-5.09) among females. HbA1c levels had been tested in 60.50% of our diabetic subjects, LDL cholesterol levels in 57.50%, and creatinine levels in 63.27%, but only 44.19% of the diabetic individuals had undergone a comprehensive assessment during one year of care. Statistical differences in diabetes care management emerged relating to gender, age, diagnostic latency period, comorbidity and citizenship.Conclusions: Process management indicators need to be used not only for the overall assessment of health care processes, but also to monitor disparities in the provision of health care.

Background: In 2020, during the COVID-19 pandemic, Italy implemented two national lockdowns aimed at reducing virus transmission. We assessed whether these lockdowns affected anti-seizure medication (ASM) use and epilepsy-related access to emergency departments (ED) in the general population. Methods: We performed a population-based study using the healthcare administrative database of Tuscany. We defined the weekly time series of prevalence and incidence of ASM, along with the incidence of epilepsy-related ED access from 1 January 2018 to 27 December 2020 in the general population. An interrupted time-series analysis was used to assess the effect of lockdowns on the observed outcomes. Results: Compared to pre-lockdown, we observed a relevant reduction of ASM incidence (0.65; 95% Confidence Intervals: 0.59–0.72) and ED access (0.72; 0.64–0.82), and a slight decrease of ASM prevalence (0.95; 0.94–0.96). During the post-lockdown the ASM incidence reported higher values compared to pre-lockdown, whereas ASM prevalence and ED access remained lower. Results also indicate a lower impact of the second lockdown for both ASM prevalence (0.97; 0.96–0.98) and incidence (0.89; 0.80–0.99). Conclusion: The lockdowns implemented during the COVID-19 outbreaks significantly affected ASM use and epilepsy-related ED access. The potential consequences of these phenomenon are still unknown, although an increased incidence of epilepsy-related symptoms after the first lockdown has been observed. These findings emphasize the need of ensuring continuous care of epileptic patients in stressful conditions such as the COVID-19 pandemic.

Background: The European post-authorisation study (EU PAS) register is a repository launched in 2010 by the European Medicines Agency (EMA). All EMA-requested PAS, commonly observational studies, must be recorded in this register. Multi-database studies (MDS) leveraging secondary data have become an important strategy to conduct PAS in recent years, as reflected by the type of studies registered in the EU PAS register. Objectives: To analyse and describe PAS in the EU PAS register, with focus on MDS. Methods: Studies in the EU PAS register from inception to 31st December 2018 were described concerning transparency, regulatory obligations, scope, study type (e.g., observational study, clinical trial, survey, systematic review/meta-analysis), study design, type of data collection and target population. MDS were defined as studies conducted through secondary use of >1 data source not linked at patient-level. Data extraction was carried out independently by 14 centres with expertise in pharmacoepidemiology, using publicly available information in the EU PAS register including study protocol, whenever available, using a standardised data collection form. For validation purposes, a second revision of key fields for a 15% random sample of studies was carried out by a different centre. The inter-rater reliability (IRR) was then calculated. Finally, to identify predictors of primary data collection-based studies/versus those based on secondary use of healthcare databases) or MDS (vs. non-MDS), odds ratios (OR) and 95% confidence intervals (CI) were calculated fitting univariate logistic regression models. Results: Overall, 1426 studies were identified. Clinical trials (N = 30; 2%), systematic reviews/meta-analyses (N = 16; 1%) and miscellaneous study designs (N = 46; 3%) were much less common than observational studies (N = 1227; 86%). The protocol was available for 63% (N = 360) of 572 observational studies requested by a competent authority. Overall, 36% (N = 446) of observational studies were based fully or partially on primary data collection. Of 757 observational studies based on secondary use of data alone, 282 (37%) were MDS. Drug utilisation was significantly more common as a study scope in MDS compared to non-MDS studies. The overall percentage agreement among collaborating centres that collected the data concerning study variables was highest for study type (93.5%) and lowest for type of secondary data (67.8%). Conclusions: Observational studies were the most common type of studies in the EU PAS register, but 30% used primary data, which is more resource-intensive. Almost half of observational studies using secondary data were MDS. Data recording in the EU PAS register may be improved further, including more widespread availability of study protocols to improve transparency.

Background The incretin-based medicines GLP1 analogues (GLP1a) and dipeptidyl peptidase-4 inhibitors (DPP4i) are hypoglycaemic agents licensed for the treatment of type 2 diabetes mellitus (T2DM). Although these drugs possess comparable efficacy and low risk of hypoglycaemia, differences in terms of route of administration (subcutaneous versus oral), effect on body weight and gastrointestinal tolerabily can impact their actual use in clinical practice. This study aimed to describe the real-world utilization of incretin-based medicines in the Italian clinical practice. Methods A multi-database, population-based, descriptive, cohort study was performed using administrative data collected between 2008 and 2014 from three Italian geographic areas. Subjects aged ≥18 were selected. New users were defined as those with ≥1 dispensing of GLP1a or DPP4i during the year of interest and none in the past. Trends of cumulative annual incidence of use in the general adult population were observed. New users of GLP1a or DPP4i were respectively described in terms of demographic characteristics and use of antidiabetic drugs during 1 year before and after the first incretin dispensing. Results The overall study population included 4,943,952 subjects. A total of 7357 new users of GLP1a and 41,907 of DPP4i were identified during the study period. Incidence of use increased between 2008 (0.2‰ for both GLP1a and DPP4i) and 2011 (GLP1a = 0.6‰; DPP4i = 2.5‰) and slightly decreased thereafter. In 2014, 61% of new GLP1a users received once-daily liraglutide while 52% of new DPP4i users received metformin/DPP4i in fixed-dose. The percentage of new DPP4i users older than 65 years of age increased from 30.9 to 62.6% during the study period. Around 12% of new users had not received any antidiabetic before starting an incretin. Conclusions During the study period, DPP4i rapidly became the most prescribed incretin-based medicine, particularly among older new user. The choice of the specific incretin-based medicine at first prescription appeared to be directed towards those with higher convenience of use (e.g. oral DPP4i rather than subcutaneous GLP1a, once-daily liraglutide rather than twice-daily exenatide). The non-negligibile use of incretin-based medicines as first-line pharmacotherapy for T2DM warrants further effectiveness and safety evaluations to better define their place in therapy. Electronic supplementary material The online version of this article (10.1186/s12902-019-0334-y) contains supplementary material, which is available to authorized users.

BACKGROUND AND OBJECTIVE: Cardiovascular (CV) diseases represent a major cause of death and severe medical condition worldwide. Different therapeutic options are available to control low-density lipoprotein cholesterol (LDL-C) level in order to prevent CV events. In recent years, two new drugs were approved for patients who are unable to reduce circulating LDL-C with the current therapies: evolocumab and alirocumab (proprotein convertase subtilisin/kexin type nine [PCSK9] inhibitors). This study was aimed to characterise patients who started treatment with PCSK9 inhibitors in the Tuscany region of Italy during the first year of public healthcare service reimbursement and to describe the pattern of PCSK9 inhibitor use in the first 6 months of treatment. METHODS: Patients on PCSK9 inhibitor treatment in Tuscany (3.7 million inhabitants) from 07/2017 to 06/2018 were selected from regional healthcare administrative databases. Concomitant use of lipid-lowering therapies (LLTs), adherence and persistence during the 6 months preceding the first PCSK9 inhibitor dispensing, as well as comorbidities since 1996, were described. In the first 6 months of PCSK9 inhibitor treatment, adherence, persistence and concomitant LLTs were assessed. RESULTS: There were 269 (176 evolocumab, 93 alirocumab) new users of PCSK9 inhibitors. Patients (mean age of 59.1 years) were mainly male (71.0%) in secondary prevention (70.2%) and affected by familial hypercholesterolaemia (53.5%). Sixty-six patients (24.5%) had diabetes mellitus and 12 (4.5%) chronic renal failure. In the 6 months prior to the first PCSK9 inhibitor administration, 61.3% of patients received at least one prescription of ezetimibe or high-intensity statins and 45.7% were persistent to these drugs. During follow-up, 79.9% of patients were adherent to PCSK9 inhibitor and 73.3% were persistent. CONCLUSIONS: During the first year of availability, the rate of prescription of PCSK9 inhibitors appears below expectations. Patients were mainly in secondary prevention and had been slightly persistent to previous LLTs. During follow-up, the PCSK9 inhibitor monotherapy showed high levels of adherence and persistence. This real-world study sets the stage for future longer-term investigations useful to improve our knowledge on the appropriateness, drug access and public healthcare sustainability of PCSK9 inhibitors.

Summary Analyses of healthcare data from 30 million individuals in three countries showed that current use of bisphosphonates may be associated with a small increased risk of cardiac valvulopathy (vs. those not exposed within the previous year), although confounding cannot be entirely ruled out. The observed tendency for decreased valvulopathy risk with cumulative duration of bisphosphonate use >6 months may even indicate a protective effect with prolonged use. Further studies are still needed to evaluate whether bisphosphonates increase or decrease the risk of valvulopathy. Introduction A signal of cardiac valve disorders with use of bisphosphonates was identified in the literature and EudraVigilance database, which contains reports of suspected adverse drug reactions from worldwide sources. The aim of this study was to evaluate the association using population-based healthcare data. Methods This was a case-control study among users of bisphosphonates and other drugs for osteoporosis in six healthcare databases covering over 30 million individuals in Italy, Netherlands and the UK from 1996 to 2012. Prescriptions/dispensations were used to assess drug exposure. Newly diagnosed cases of cardiac valvulopathy were identified via disease codes/free-text search. Controls were matched to each case by age, sex, database and index date. Adjusted odds ratios (ORs) were estimated using conditional logistic regression for the pooled data and meta-analysis of individual database risk estimates. Results A small but statistically significant association was found between exposure to bisphosphonates as a class and risk of valvulopathy. Overall risk was 18 % higher (95 % CI 12–23 %) in those currently exposed to any bisphosphonate (mainly alendronate and risedronate) vs. those not exposed within the previous year. Risk of valve regurgitation was 14 % higher (95 % CI 7–22 %). Decreased valvulopathy risk was observed with longer cumulative duration of bisphosphonate use, compared to use of less than 6 months. Meta-analyses of database-specific estimates confirmed results from pooled analyses. Conclusions The observed increased risks of cardiac valvulopathy with bisphosphonate use, although statistically significant, were quite small and unlikely to be clinically significant. Further studies are still needed to evaluate whether bisphosphonates increase or decrease the risk of valvulopathy and to investigate possible mechanisms for the association. Electronic supplementary material The online version of this article (doi:10.1007/s00198-015-3441-2) contains supplementary material, which is available to authorized users.

Background The Observational Medical Outcomes Partnership (OMOP) has just completed a large scale empirical evaluation of statistical methods and analysis choices for risks identification in longitudinal observational healthcare data. This experiment drew data from four large US health insurance claims databases and one US electronic health record (EHR) database, but it is unclear to what extend the findings of this study apply to other data sources. Objective To replicate the OMOP experiment in six European EHR databases. Research Design Six databases of the EU-ADR (Exploring and Understanding Adverse Drug Reactions) database network participated in this study: Aarhus (Denmark), ARS (Italy), HealthSearch (Italy), IPCI (the Netherlands), Pedianet (Italy), and Pharmo (the Netherlands). All methods in the OMOP experiment were applied to a collection of 165 positive and 234 negative control drug- outcome pairs across four outcomes: acute liver injury, acute myocardial infarction, acute kidney injury, and upper gastrointestinal bleeding. Area under the receiver operator characteristics curve (AUC) was computed per database and for a combination of all six databases using metaanalysis for random effects. We provide expected values of estimation error as well, based on negative controls. Results Similarly to the US experiment, high predictive accuracy was found (AUC[0.8) for some analyses. Selfcontrolled designs, such as self-controlled case series, IC temporal pattern discovery and self-controlled cohort achieved higher performance than other methods, both in terms of predictive accuracy and observed bias. Conclusions The major findings of the recent OMOP experiment were also observed in the European databases.

Objectives 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. Setting HSD is a database of primary care medical records. A panel of 12 GPs participated in this validation study. Participants 300 patients were sampled for each disease, except for HF, where 243 patients were assessed. Outcome measures The positive predictive value (PPV) was assessed for the presence/absence of each condition against the GP9s response to the questionnaire, and Cohen9s κ was calculated for agreement on the severity level. Results The PPV was 100% (99% to 100%) for T2DM and hypertension, 98% (96% to 100%) for IHD and 55% (49% to 61%) for HF. Cohen9s kappa for agreement on the severity level was 0.70 for T2DM and 0.69 for hypertension and IHD. Conclusions 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.

Aim Electronic healthcare record (EHR)-based surveillance systems are increasingly being developed to support early detection of safety signals. It is unknown what the power of such a system is for surveillance among children and adolescents. In this paper we provide estimates of the number and classes of drugs, and incidence rates (IRs) of events, that can be monitored in children and adolescents (0-18 years). Methods Data were obtained from seven population-based EHR databases in Denmark, Italy, and the Netherlands during the period 1996-2010. We estimated the number of drugs for which specific adverse events can be monitored as a function of actual drug use, minimally detectable relative risk (RR) and IRs for 10 events. Results The population comprised 4 838 146 individuals (25 575 132 person years (PYs)), who were prescribed 2170 drugs (1 610 631 PYs drug-exposure). Half of the total drug-exposure in PYs was covered by only 18 drugs (0.8%). For a relatively frequent event like upper gastrointestinal bleeding there were 39 drugs for which an association with a RR ≥4, if present, could be investigated. The corresponding number of drugs was eight for a rare event like anaphylactic shock. Conclusion Drug use in children is rare and shows little variation. The number of drugs with enough exposure to detect rare adverse events in children and adolescents within an EHR-based surveillance system such as EU-ADR is limited. Use of additional sources of paediatric drug exposure information and global collaboration are imperative in order to optimize EHR data for paediatric safety surveillance.

Background and Objective Spontaneous reporting systems (SRSs) remain the cornerstone of post-marketing drug safety surveillance despite their well-known limitations. Judicious use of other available data sources is essential to enable better detection, strengthening and validation of signals. In this study, we investigated the potential of electronic healthcare records (EHRs) to be used alongside an SRS as an independent system, with the aim of improving signal detection. Methods A signal detection strategy, focused on a limited set of adverse events deemed important in pharmacovigilance, was performed retrospectively in two data sources—(1) the Exploring and Understanding Adverse Drug Reactions (EU-ADR) database network and (2) the EudraVigilance database—using data between 2000 and 2010. Five events were considered for analysis: (1) acute myocardial infarction (AMI); (2) bullous eruption; (3) hip fracture; (4) acute pancreatitis; and (5) upper gastrointestinal bleeding (UGIB). Potential signals identified in each system were verified using the current published literature. The complementarity of the two systems to detect signals was expressed as the percentage of the unilaterally identified signals out of the total number of confirmed signals. As a proxy for the associated costs, the number of signals that needed to be reviewed to detect one true signal (number needed to detect [NND]) was calculated. The relationship between the background frequency of the events and the capability of each system to detect signals was also investigated. Results The contribution of each system to signal detection appeared to be correlated with the background incidence of the events, being directly proportional to the incidence in EU-ADR and inversely proportional in EudraVigilance. EudraVigilance was particularly valuable in identifying bullous eruption and acute pancreatitis (71 and 42 % of signals were correctly identified from the total pool of known associations, respectively), while EU-ADR was most useful in identifying hip fractures (60 %). Both systems contributed reasonably well to identification of signals related to UGIB (45 % in EudraVigilance, 40 % in EU-ADR) but only fairly for signals related to AMI (25 % in EU-ADR, 20 % in EudraVigilance). The costs associated with detection of signals were variable across events; however, it was often more costly to detect safety signals in EU-ADR than in EudraVigilance (median NNDs: 7 versus 5). Conclusion An EHR-based system may have additional value for signal detection, alongside already established systems, especially in the presence of adverse events with a high background incidence. While the SRS appeared to be more cost effective overall, for some events the costs associated with signal detection in the EHR might be justifiable. Electronic supplementary material The online version of this article (doi:10.1007/s40264-015-0341-5) contains supplementary material, which is available to authorized users.

A prospective pharmacovigilance signal detection study, comparing the real-world healthcare data (EU-ADR) and two spontaneous reporting system (SRS) databases, US FDA's Adverse Event Reporting System and WHO's Vigibase is reported. The study compared drug safety signals found in the EU-ADR and SRS databases. The potential for signal detection in the EU-ADR system was found to be dependent on frequency of the event and utilization of drugs in the general population. The EU-ADR system may have a greater potential for detecting signals for events occurring at higher frequency in general population and those that are commonly not considered as potentially a drug-induced event. Factors influencing various differences between the datasets are discussed along with potential limitations and applications to pharmacovigilance practice.

Background Data mining in spontaneous reporting databases has shown that drug-induced liver injury is infrequently reported in children. Objectives Our objectives were to (i) identify drugs potentially associated with acute liver injury (ALI) in children and adolescents using electronic healthcare record (EHR) data; and (ii) to evaluate the significance and novelty of these associations. Methods We identified potential cases of ALI during exposure to any prescribed/dispensed drug for individuals 1 and in the presence of at least three exposed cases of ALI. Potentially new signals were distinguished from already known associations concerning ALI (whether in adults and/or in the paediatric population) through manual review of published literature and drug product labels. Results The study population comprised 4,838,146 individuals aged < 18 years, who contributed an overall 25,575,132 person-years of follow-up. Within this population, we identified 1,015 potential cases of ALI. Overall, 20 positive drug-ALI associations were detected. The associations between ALI and domperidone, flunisolide and human insulin were considered as potentially new signals. Citalopram and cetirizine have been previously described as hepatotoxic in adults but not in children, while all remaining associations were already known in both adults and children. Conclusions Data mining of multiple EHR databases for signal detection confirmed known associations between ALI and several drugs, and identified some potentially new signals in children that require further investigation through formal epidemiologic studies. This study shows that EHRs may complement traditional spontaneous reporting systems for signal detection and strengthening.

Background & Aims: Concomitant use of nonsteroidal anti-inflammatory drugs (NSAIDs) and low-dose aspirin increases the risk of upper gastrointestinal bleeding (UGIB). Guidelines suggest avoiding certain drug combinations, yet little is known about the magnitude of their interactions. We estimated the risk of UGIB during concomitant use of nonselective (ns)NSAIDs, cyclooxygenase -2 selective inhibitors (COX-2 inhibitors), and low-dose aspirin with other drugs. Methods: We performed a case series analysis of data from 114,835 patients with UGIB (930,888 person-years of follow-up) identified from 7 population-based health care databases (approximately 20 million subjects). Each patient served as his or her own control. Drug exposure was determined based on prescriptions of nsNSAIDs, COX-2 inhibitors, or low-dose aspirin, alone and in combination with other drugs that affect the risk of UGIB. We measured relative risk (incidence rate ratio [IRR] during drug exposure vs nonexposure) and excess risk due to concomitant drug exposure (relative excess risk due to interaction [RERI]). Results: Monotherapy with nsNSAIDs increased the risk of diagnosis of UGIB (IRR, 4.3) to a greater extent than monotherapy with COX-2 inhibitors (IRR, 2.9) or low-dose aspirin (IRR, 3.1). Combination therapy generally increased the risk of UGIB; concomitant nsNSAID and corticosteroid therapies increased the IRR to the greatest extent (12.8) and also produced the greatest excess risk (RERI, 5.5). Concomitant use of nsNSAIDs and aldosterone antagonists produced an IRR for UGIB of 11.0 (RERI, 4.5). Excess risk from concomitant use of nsNSAIDs with selective serotonin reuptake inhibitors (SSRIs) was 1.6, whereas that from use of COX-2 inhibitors with SSRIs was 1.9 and that for use of low-dose aspirin with SSRIs was 0.5. Excess risk of concomitant use of nsNSAIDs with anticoagulants was 2.4, of COX-2 inhibitors with anticoagulants was 0.1, and of low-dose aspirin with anticoagulants was 1.9. Conclusions: Based on a case series analysis, concomitant use of nsNSAIDs, COX-2 inhibitors, or low-dose aspirin with SSRIs significantly increases the risk of UGIB. Concomitant use of nsNSAIDs or low-dose aspirin, but not COX-2 inhibitors, with corticosteroids, aldosterone antagonists, or anticoagulants produces significant excess risk of UGIB. © 2014 AGA Institute.

Background: Drug-related adverse events remain an important cause of morbidity and mortality and impose huge burden on healthcare costs. Routinely collected electronic healthcare data give a good snapshot of how drugs are being used in ‘real-world’ settings. Objective: To describe a strategy that identifies potentially drug-induced acute myocardial infarction (AMI) from a large international healthcare data network. Methods: Post-marketing safety surveillance was conducted in seven population-based healthcare databases in three countries (Denmark, Italy, and the Netherlands) using anonymised demographic, clinical, and prescription/dispensing data representing 21,171,291 individuals with 154,474,063 person-years of follow-up in the period 1996–2010. Primary care physicians’ medical records and administrative claims containing reimbursements for filled prescriptions, laboratory tests, and hospitalisations were evaluated using a three-tier triage system of detection, filtering, and substantiation that generated a list of drugs potentially associated with AMI. Outcome of interest was statistically significant increased risk of AMI during drug exposure that has not been previously described in current literature and is biologically plausible. Results: Overall, 163 drugs were identified to be associated with increased risk of AMI during preliminary screening. Of these, 124 drugs were eliminated after adjustment for possible bias and confounding. With subsequent application of criteria for novelty and biological plausibility, association with AMI remained for nine drugs (‘prime suspects’): azithromycin; erythromycin; roxithromycin; metoclopramide; cisapride; domperidone; betamethasone; fluconazole; and megestrol acetate. Limitations: Although global health status, co-morbidities, and time-invariant factors were adjusted for, residual confounding cannot be ruled out. Conclusion: A strategy to identify potentially drug-induced AMI from electronic healthcare data has been proposed that takes into account not only statistical association, but also public health relevance, novelty, and biological plausibility. Although this strategy needs to be further evaluated using other healthcare data sources, the list of ‘prime suspects’ makes a good starting point for further clinical, laboratory, and epidemiologic investigation. This research has been funded by the European Commission’s Seventh Framework Programme (FP7/2007–2013) under grant no. 215847–The EU-ADR Project.

OBJECTIVE: Data from electronic healthcare records (EHR) can be used to monitor drug safety, but in order to compare and pool data from different EHR databases, the extraction of potential adverse events must be harmonized. In this paper, we describe the procedure used for harmonizing the extraction from eight European EHR databases of five events of interest deemed to be important in pharmacovigilance: acute myocardial infarction (AMI); acute renal failure (ARF); anaphylactic shock (AS); bullous eruption (BE); and rhabdomyolysis (RHABD). DESIGN: The participating databases comprise general practitioners' medical records and claims for hospitalization and other healthcare services. Clinical information is collected using four different disease terminologies and free text in two different languages. The Unified Medical Language System was used to identify concepts and corresponding codes in each terminology. A common database model was used to share and pool data and verify the semantic basis of the event extraction queries. Feedback from the database holders was obtained at various stages to refine the extraction queries. MEASUREMENTS: Standardized and age specific incidence rates (IRs) were calculated to facilitate benchmarking and harmonization of event data extraction across the databases. This was an iterative process. RESULTS: The study population comprised overall 19 647 445 individuals with a follow-up of 59 929 690 person-years (PYs). Age adjusted IRs for the five events of interest across the databases were as follows: (1) AMI: 60-148/100 000 PYs; (2) ARF: 3-49/100 000 PYs; (3) AS: 2-12/100 000 PYs; (4) BE: 2-17/100 000 PYs; and (5) RHABD: 0.1-8/100 000 PYs. CONCLUSIONS: The iterative harmonization process enabled a more homogeneous identification of events across differently structured databases using different coding based algorithms. This workflow can facilitate transparent and reproducible event extractions and understanding of differences between databases.

Background Administrative databases are widely available and have been extensively used to provide estimates of chronic disease prevalence for the purpose of surveillance of both geographical and temporal trends. There are, however, other sources of data available, such as medical records from primary care and national surveys. In this paper we compare disease prevalence estimates obtained from these three different data sources. Methods Data from general practitioners (GP) and administrative transactions for health services were collected from five Italian regions (Veneto, Emilia Romagna, Tuscany, Marche and Sicily) belonging to all the three macroareas of the country (North, Center, South). Crude prevalence estimates were calculated by data source and region for diabetes, ischaemic heart disease, heart failure and chronic obstructive pulmonary disease (COPD). For diabetes and COPD, prevalence estimates were also obtained from a national health survey. When necessary, estimates were adjusted for completeness of data ascertainment. Results Crude prevalence estimates of diabetes in administrative databases (range: from 4.8% to 7.1%) were lower than corresponding GP (6.2%-8.5%) and survey-based estimates (5.1%-7.5%). Geographical trends were similar in the three sources and estimates based on treatment were the same, while estimates adjusted for completeness of ascertainment (6.1%-8.8%) were slightly higher. For ischaemic heart disease administrative and GP data sources were fairly consistent, with prevalence ranging from 3.7% to 4.7% and from 3.3% to 4.9%, respectively. In the case of heart failure administrative estimates were consistently higher than GPs’ estimates in all five regions, the highest difference being 1.4% vs 1.1%. For COPD the estimates from administrative data, ranging from 3.1% to 5.2%, fell into the confidence interval of the Survey estimates in four regions, but failed to detect the higher prevalence in the most Southern region (4.0% in administrative data vs 6.8% in survey data). The prevalence estimates for COPD from GP data were consistently higher than the corresponding estimates from the other two sources. Conclusion This study supports the use of data from Italian administrative databases to estimate geographic differences in population prevalence of ischaemic heart disease, treated diabetes, diabetes mellitus and heart failure. The algorithm for COPD used in this study requires further refinement.

BACKGROUND: Drug safety monitoring relies primarily on spontaneous reporting, but electronic health care record databases offer a possible alternative for the detection of adverse drug reactions (ADRs). OBJECTIVES: To evaluate the relative performance of different statistical methods for detecting drug-adverse event associations in electronic health care record data representing potential ADRs. RESEARCH DESIGN: Data from 7 databases across 3 countries in Europe comprising over 20 million subjects were used to compute the relative risk estimates for drug-event pairs using 10 different methods, including those developed for spontaneous reporting systems, cohort methods such as the longitudinal gamma poisson shrinker, and case-based methods such as case-control. The newly developed method "longitudinal evaluation of observational profiles of adverse events related to drugs" (LEOPARD) was used to remove associations likely caused by protopathic bias. Data from the different databases were combined by pooling of data, and by meta-analysis for random effects. A reference standard of known ADRs and negative controls was created to evaluate the performance of the method. MEASURES: The area under the curve of the receiver operator characteristic curve was calculated for each method, both with and without LEOPARD filtering. RESULTS: The highest area under the curve (0.83) was achieved by the combination of either longitudinal gamma poisson shrinker or case-control with LEOPARD filtering, but the performance between methods differed little. LEOPARD increased the overall performance, but flagged several known ADRs as caused by protopathic bias. CONCLUSIONS: Combinations of methods demonstrate good performance in distinguishing known ADRs from negative controls, and we assume that these could also be used to detect new drug safety signals.

The overall objective of the EU-ADR project is the design, development, and validation of a computerised system that exploits data from electronic health records and biomedical databases for the early detection of adverse drug reactions. Eight different databases, containing health records of more than 30 million European citizens, are involved in the project. Unique queries cannot be performed across different databases because of their heterogeneity: Medical record and Claims databases, four different terminologies for coding diagnoses, and two languages for the information described in free text. The aim of our study was to provide database owners with a common basis for the construction of their queries. Using the UMLS, we provided a list of medical concepts, with their corresponding terms and codes in the four terminologies, which should be considered to retrieve the relevant information for the events of interest from the databases.