Monitoring sick leave data for early detection of influenza outbreaks.

BACKGROUND: Workplace absenteeism increases significantly during influenza epidemics. Sick leave records may facilitate more timely detection of influenza outbreaks, as trends in increased sick leave may precede alerts issued by sentinel surveillance systems by days or weeks. Sick leave data have not been comprehensively evaluated in comparison to traditional surveillance methods. The aim of this paper is to study the performance and the feasibility of using a detection system based on sick leave data to detect influenza outbreaks. METHODS: Sick leave records were extracted from private French health insurance data, covering on average 209,932 companies per year across a wide range of sizes and sectors. We used linear regression to estimate the weekly number of new sick leave spells between 2016 and 2017 in 12 French regions, adjusting for trend, seasonality and worker leaves on historical data from 2010 to 2015. Outbreaks were detected using a 95%-prediction interval. This method was compared to results from the French Sentinelles network, a gold-standard primary care surveillance system currently in place. RESULTS: Using sick leave data, we detected 92% of reported influenza outbreaks between 2016 and 2017, on average 5.88 weeks prior to outbreak peaks. Compared to the existing Sentinelles model, our method had high sensitivity (89%) and positive predictive value (86%), and detected outbreaks on average 2.5 weeks earlier. CONCLUSION: Sick leave surveillance could be a sensitive, specific and timely tool for detection of influenza outbreaks.

PRIORITIES FOR HEALTH ECONOMIC METHODOLOGICAL RESEARCH: RESULTS OF AN EXPERT CONSULTATION.

BACKGROUND: The importance of economic evaluation in decision making is growing with increasing budgetary pressures on health systems. Diverse economic evidence is available for a range of interventions across national contexts within Europe, but little attention has been given to identifying evidence gaps that, if filled, could contribute to more efficient allocation of resources. One objective of the Research Agenda for Health Economic Evaluation project is to determine the most important methodological evidence gaps for the ten highest burden conditions in the European Union (EU), and to suggest ways of filling these gaps. METHODS: The highest burden conditions in the EU by Disability Adjusted Life Years were determined using the Global Burden of Disease study. Clinical interventions were identified for each condition based on published guidelines, and economic evaluations indexed in MEDLINE were mapped to each intervention. A panel of public health and health economics experts discussed the evidence during a workshop and identified evidence gaps. RESULTS: The literature analysis contributed to identifying cross-cutting methodological and technical issues, which were considered by the expert panel to derive methodological research priorities. CONCLUSIONS: The panel suggests a research agenda for health economics which incorporates the use of real-world evidence in the assessment of new and existing interventions; increased understanding of cost-effectiveness according to patient characteristics beyond the "-omics" approach to inform both investment and disinvestment decisions; methods for assessment of complex interventions; improved cross-talk between economic evaluations from health and other sectors; early health technology assessment; and standardized, transferable approaches to economic modeling.

Cost-effectiveness of magnetic resonance imaging with a new contrast agent for the early diagnosis of Alzheimer's disease.

BACKGROUND: Used as contrast agents for brain magnetic resonance imaging (MRI), markers for beta-amyloid deposits might allow early diagnosis of Alzheimer's disease (AD). We evaluated the cost-effectiveness of such a diagnostic test, MRI+CLP (contrastophore-linker-pharmacophore), should it become clinically available. METHODOLOGY/PRINCIPAL FINDINGS: We compared the cost-effectiveness of MRI+CLP to that of standard diagnosis using currently available cognition tests and of standard MRI, and investigated the impact of a hypothetical treatment efficient in early AD. The primary analysis was based on the current French context for 70-year-old patients with Mild Cognitive Impairment (MCI). In alternative "screen and treat" scenarios, we analyzed the consequences of systematic screenings of over-60 individuals (either population-wide or restricted to the ApoE4 genotype population). We used a Markov model of AD progression; model parameters, as well as incurred costs and quality-of-life weights in France were taken from the literature. We performed univariate and probabilistic multivariate sensitivity analyses. The base-case preferred strategy was the standard MRI diagnosis strategy. In the primary analysis however, MRI+CLP could become the preferred strategy under a wide array of scenarios involving lower cost and/or higher sensitivity or specificity. By contrast, in the "screen and treat" analyses, the probability of MRI+CLP becoming the preferred strategy remained lower than 5%. CONCLUSIONS/SIGNIFICANCE: It is thought that anti-beta-amyloid compounds might halt the development of dementia in early stage patients. This study suggests that, even should such treatments become available, systematically screening the over-60 population for AD would only become cost-effective with highly specific tests able to diagnose early stages of the disease. However, offering a new diagnostic test based on beta-amyloid markers to elderly patients with MCI might prove cost-effective.