Drug-Utilization, Healthcare Facilities Accesses and Costs of the First Generation of JAK Inhibitors in Rheumatoid Arthritis.

This study is aimed at describing tofacitinib and baricitinib users by characterizing their prescription and healthcare histories, drug and healthcare utilization patterns, and direct costs from a healthcare system perspective. This retrospective cohort study was performed using Tuscan administrative healthcare databases, which selected two groups of Janus kinase inhibitors (JAKi) incident users (index date) from 1st January 2018 to 31 December 2019 and from 1 January 2018 to 30 June 2019. We included patients ≥18 years old, at least 10 years of data, and six months of follow-up. In the first analysis, we describe mean time, standard deviation (SD), from the first-ever disease-modifying antirheumatic drug (DMARD) to the JAKi, and costs of healthcare facilities and drugs in the 5 years preceding the index date. In the second analysis, we assessed Emergency Department (ED) accesses and hospitalizations for any causes, visits, and costs in the follow-up. In the first analysis, 363 incident JAKi users were included (mean age 61.5, SD 13.6; females 80.7%, baricitinib 78.5%, tofacitinib 21.5%). The time to the first JAKi was 7.2 years (SD 3.3). The mean costs from the fifth to the second year before JAKi increased from 4325 € (0; 24,265) to 5259 € (0; 41,630) per patient/year, driven by hospitalizations. We included 221 incident JAKi users in the second analysis. We observed 109 ED accesses, 39 hospitalizations, and 64 visits. Injury and poisoning (18.3%) and skin (13.8%) caused ED accesses, and cardiovascular (69.2%) and musculoskeletal (64.1%) caused hospitalizations. The mean costs were 4819 € (607.5; 50,493) per patient, mostly due to JAKi. In conclusion, the JAKi introduction in therapy occurred in compliance with RA guidelines and the increase in costs observed could be due to a possible selective prescription.

ADVANCE: Towards near real-time monitoring of vaccination coverage, benefits and risks using European electronic health record databases.

BACKGROUND: The Accelerated Development of VAccine beNefit-risk Collaboration in Europe (ADVANCE) is a public-private partnership aiming to develop and test a system for rapid benefit-risk (B/R) monitoring of vaccines using European electronic health record (eHR) databases. This proof-of-concept study aimed to test the feasibility of near real-time (NRT) monitoring of vaccination coverage, benefits and risks based on multiple European eHR databases, using acellular pertussis vaccination in children aged <6 years as test case. METHODS: A qualitative feasibility assessment on NRT monitoring was carried out using a survey and face-to-face discussion with ADVANCE data partners. Subsequently, a dynamic cohort study was conducted containing two distinct observation periods: a first period to establish a baseline (Jan 2014 to Mar 2018) and a subsequent 3-month period to test the actual feasibility of weekly NRT monitoring, based on which data latencies were calculated. An interactive web-application was additionally developed to facilitate the visual monitoring of vaccination coverage, the vaccine preventable disease incidence rates (benefits) and the incidence rates of adverse events (risks). RESULTS: Nine databases from four countries (Denmark, Italy, Spain and UK) participated in the qualitative feasibility assessment. Of them, five databases took part in the dynamic cohort study, with 5 databases providing baseline data and 3 databases participating to the NRT monitoring, providing data extractions on an almost weekly basis. The median data latency (time between event date and data release date) was between 1 and 2 weeks except for the benefit and risk events in one of the databases (latency 16 weeks). CONCLUSION: Three European eHR databases successfully demonstrated the feasibility of providing data for weekly NRT monitoring, with short data latencies of 1-2 weeks for most events.

A Systematic Review of Case-Identification Algorithms Based on Italian Healthcare Administrative Databases for Three Relevant Diseases of the Cardiovascular System: Acute Myocardial Infarction, Ischemic Heart Disease, and Stroke.

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 patientlevel 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.