Prevalence of antibiotic use: a comparison across various European health care data sources.

PURPOSE: There is widespread concern about increases in antibiotic use, but comparative data from different European countries on rates of use are lacking. This study was designed to measure and understand the variation in antibiotic utilization across five European countries. METHODS: Seven European healthcare databases with access to primary care data from Denmark, Germany, the Netherlands, Spain and the UK were used to measure and compare the point and 1-year-period prevalence of antibiotic use between 2004 and 2009. Descriptive analyses were stratified by gender, age and type of antibiotic. Separate analyses were performed to measure the most common underlying indications leading to the prescription of an antibiotic. RESULTS: The average yearly period prevalence of antibiotic use varied from 15 (Netherlands) to 30 (Spain) users per 100 patients. A higher prevalence of antibiotic use by female patients, the very young (0-9 years) and old (80+ years), was observed in all databases. The lowest point prevalence was recorded in June and September and ranged from 0.51 (Netherlands) to 1.47 (UK) per 100 patients per day. Twelve percent (Netherlands) to forty-nine (Spain) percent of all users were diagnosed with a respiratory tract infection, and the most common type of antibiotic prescribed were penicillin. CONCLUSION: Using identical methodology in seven EU databases to assess antibiotic use allowed us to compare drug usage patterns across Europe. Our results contribute quantitatively to the true understanding of similarities and differences in the use of antibiotic agents in different EU countries.

The Alignment of Real-World Evidence and Digital Health: Realising the Opportunity.

In the new era of healthcare digitalization, there is a golden opportunity in the overlap between digital health and Real-World Evidence (RWE). In this commentary, we define RWE and digital health and investigate their intersection. We describe the stages in the RWE value chain critical to the evidence generation process, how these stages change with new digital technologies and the opportunities and challenges that arise from how these stages evolve-including their application for stakeholders such as patients, physicians and regulators. We also discuss the current published guidelines and frameworks regarding digital health. We categorise these publications in terms of their clarity as "Extensive", "Intermediate" or "Basic" and according to whether they encompass all levels of digital health or are more focussed in their guidance. Finally, we provide recommendations to increase synergy between RWE and digital health.

Bridging the Gap Between RCTs and RWE Through Endpoint Selection.

This commentary is authored by several industry real-world evidence (RWE) experts, with support from IQVIA, as part of the 'RWE Leadership Forum': a group of Industry Leaders who have come together as non-competitive partners to understand and respond to RWD/E challenges and opportunities with a single expert voice. Here, the forum discusses the value in bridging the industry disconnect between RTCs and RWE, with a view to promoting the use of RWE in the RCT environment. RCT endpoints are explored along several axes including their clinical relevance and their measure of direct patient benefit, and then compared with their real-world counterparts to identify suitable paths, or gaps, for assimilating RWE endpoints into the RCT environment.

Strengthening pharma's contract with society: the value of trusted partnerships between pharma and healthcare facilitated by real-world data.

This White Paper is authored by 11 industry real-world evidence (RWE) experts, with support from IQVIA, as part of the 'RWE Leadership Forum': a group of industry leaders who come together as noncompetitive partners to understand and respond to internal or external RWD/E challenges and opportunities with a single expert voice. Herein we aim to clarify the rules of engagement between pharma and healthcare in order to establish trust-based partnerships, which will unlock unique value for society, including the medical community and the ultimate beneficiary, the patient.

Exploring methods for comparing the real-world effectiveness of treatments for osteoporosis: adjusted direct comparisons versus using patients as their own control.

Using Swedish and Dutch registry data for women initiating bisphosphonates, we evaluated two methods of comparing the real-world effectiveness of osteoporosis treatments that attempt to adjust for differences in patient baseline characteristics. Each method has advantages and disadvantages; both are potential complements to clinical trial analyses. PURPOSE: We evaluated methods of comparing the real-world effectiveness of osteoporosis treatments that attempt to adjust for both observed and unobserved confounding. METHODS: Swedish and Dutch registry data for women initiating zoledronate or oral bisphosphonates (OBPs; alendronate/risedronate) were used; the primary outcome was fracture. In adjusted direct comparisons (ADCs), regression and matching techniques were used to account for baseline differences in known risk factors for fracture (e.g., age, previous fracture, comorbidities). In an own-control analysis (OCA), for each treatment, fracture incidence in the first 90 days following treatment initiation (the baseline risk period) was compared with fracture incidence in the 1-year period starting 91 days after treatment initiation (the treatment exposure period). RESULTS: In total, 1196 and 149 women initiating zoledronate and 14,764 and 25,058 initiating OBPs were eligible in the Swedish and Dutch registries, respectively. Owing to the small Dutch zoledronate sample, only the Swedish data were used to compare fracture incidences between treatment groups. ADCs showed a numerically higher fracture incidence in the zoledronate than in the OBPs group (hazard ratio 1.09-1.21; not statistically significant, p > 0.05). For both treatment groups, OCA showed a higher fracture incidence in the baseline risk period than in the treatment exposure period, indicating a treatment effect. OCA showed a similar or greater effect in the zoledronate group compared with the OBPs group. CONCLUSIONS: ADC and OCA each possesses advantages and disadvantages. Combining both methods may provide an estimate of real-world treatment efficacy that could potentially complement clinical trial findings.