Methodological issues for the economic evaluation of health interventions: a concise state of the art

This paper presents a preliminary report of the Italian Society of Medical Statistics and Clinical Epidemiology (SISMEC) working group called SiPrEMAS (Evidence Synthesis and Decision Modelling in Health) collating some topics addressed throughout the first two years of collaboration. It contains a rapid overview of the principal methods used for the economic evaluation of health interventions. Special focus is given to the process of assembling and pooling the available evidence, modeling methods, the analysis of uncertainty (structural and on parameters), cost analysis and cost consequences analysis. This paper intends to stimulate the discussion among different professionals involved in the decision making process at national level, trying to (re)bridge the gap between decision makers and researchers

Production, efficiency and corruption in Italian Serie A : a DEA analysis

This paper uses data from Italian Serie A football to analyse the technical efficiency of Italian football clubs , utilising a panel dataset comprising season aggregated match statistics over ten seasons from 2000/01 to 2009/10 inclusive . While there has been considerable research on production and efficiency in most of the major European football leagues , corresponding evidence relating to Serie A is limited. T his paper addresses this imbalance , e stimating a production function for the league and the relative efficiency of 36 teams , taking into consideration the impact of the Calciopoli corruption scan dal in 2006 . To achieve this , Da ta Envelopment Analysis (DEA) models ha ve been used to calculate the frontiers of efficient production. The results highlight how playing style has changed in response to the corruption scandal , emphasizing the importance of attacking play in Serie A

Prevalence of gastroschisis at birth: Retrospective study

[No abstract available

Public reporting on individual hospitals’ quality: the risk of misinformation

Obiettivo: benché con sempre maggiore frequenza i mass media riportino informazioni sulla qualità dei servizi, spesso con l’esplicito intento di individuare i «migliori», la comunicazione di questi temi avviene attraverso modalità che o sono troppo semplicistiche nel loro sforzo di confrontare le performance cliniche dei singoli centri, o ricorrono a indicatori di qualità inadeguati. In tale senso, queste informazioni possono facilmente portare a interpretazioni errate. Questo lavoro considera due esempi concreti per evidenziare il problema. Metodi: sono stati utilizzati due casi recenti di comunicazione attraverso i mass media delle performance cliniche di centri cardiochirurgici: i risultati dello studio BPAC «Esiti a breve termine di interventi di by-pass coronarico nelle cardiochirurgie italiane», coordinato dall’ISS, e la pubblicazione sulla rivista Panorama di quelle che erano definite come le migliori cardiochirurgie italiane sulla base di un indice di reputazione. Risultati: il primo dei casi citati evidenzia i problemi della rappresentazione delle performance con semplici league tables. Con un metodo basato su Markov Chain Monte Carlo si evince che il ricorso alle classifiche, pur basate su un corretto indicatore di esito, è un esercizio potenzialmente fuorviante. Nel secondo caso, si dimostra l’inaffidabilità di un indice reputazionale utilizzato come indicatore della qualità dei servizi. Conclusione: le modalità con cui si comunica al pubblico la qualità dei servizi sono ancora largamente inadeguate e quindi potenzialmente fuorvianti nell’indirizzare le scelte dei cittadini

A systematic review of the economic impact of rapid diagnostic tests for dengue.

BACKGROUND: Dengue fever is rapidly expanding geographically, with about half of the world's population now at risk. Among the various diagnostic options, rapid diagnostic tests (RDTs) are convenient and prompt, but limited in terms of accuracy and availability. METHODS: A systematic review was conducted of published data on the use of RDTs for dengue with respect to their economic impact. The search was conducted with combinations of key search terms, including "((Dengue[Title]) AND cost/economic)" and "rapid diagnostic test/assay (or point-of-care)". Articles with insufficient report on cost/economic aspect of dengue RDTs, usually on comparison of different RDTs or assessment of novel rapid diagnostic tools, were excluded. This review has been registered in the PROSPERO International prospective register of systematic reviews (registry #: CRD42015017775). RESULTS: Eleven articles were found through advanced search on Pubmed. From Embase and Web of Science, two and 14 articles were obtained, respectively. After removal of duplicate items, title screening was done on 21 published works and 12 titles, including 2 meeting abstracts, were selected for abstract review. For full-text review, by two independent reviewers, 5 articles and 1 meeting abstract were selected. Among these, the abstract was referring to the same study results as one of the articles. After full text review, two studies (two articles and one abstract) were found to report on cost-wise or economic benefits of dengue RDTs and were selected for data extraction. One study found satisfactory performance of IgM-based Panbio RDT, concluding that it would be cost-effective in endemic settings. The second study was a modeling analysis and showed that a dengue RDT would not be advantageous in terms of cost and effectiveness compared to current practice of antibiotics prescription for acute febrile illness. CONCLUSIONS: Despite growing use of RDTs in research and clinical settings, there were limited data to demonstrate an economic impact. The available two studies reached different conclusions on the cost-effectiveness of dengue RDTs, although only one of the two studies reported outcomes from cost-effectiveness analysis of dengue and the other was considering febrile illness more generally. Evidence of such an impact would require further quantitative economic studies

Bayesian Meta-Analysis of Health State Utility Values: A Tutorial with a Practical Application in Heart Failure.

Researchers incorporate health state utility values as inputs to inform economic models. However, for a particular health state or condition, multiple utility values derived from different studies typically exist and a single study is often insufficient to represent the best available source of utility needed to inform policy decisions. The purpose of this paper is to provide an introductory guidance for conducting Bayesian meta-analysis of health state utility values to generate a single parameter input for economic evaluation, using R. The tutorial is illustrated using data from a systematic review of health state utilities of patients with heart failure, with 21 studies that reported utilities measured using the EuroQol-5D (EQ-5D). Explanations, key considerations and suggested readings are provided for each step of the tutorial, adhering to a clear workflow for conducting Bayesian meta-analysis: (1) setting-up the data; (2) employing methods to impute missing standard deviations; (3) defining the priors; (4) fitting the model; (5) diagnosing model convergence; (6) interpreting the results; and (7) performing sensitivity analyses. The posterior distributions for the pooled effect size (i.e. mean health state utility) and between-study heterogeneity are discussed and interpreted in light of the data, priors and models used. We hope that this tutorial will foster interest in Bayesian methods and their applications in the meta-analysis of utilities

A study on serum calcium and phosphate in dialysis patients via a mixed effects latent markov model with two outcomes.

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Prevalence of human papillomavirus in head and neck cancers in European populations: a meta-analysis.

BACKGROUND: Infection with human papillomavirus (HPV) is necessary for the development of cervical carcinoma. By contrast, the role of HPV in the pathogenesis of other malignancies, such as head and neck cancers, is less well characterised. This study aimed to address key information gaps by conducting a systematic review and meta-analysis of the prevalence of HPV infection in head and neck cancers, focusing on data for European populations. METHODS: MEDLINE, Embase and grey literature sources were systematically searched for primary studies that were published in English between July 2002 and July 2012, and which reported on the prevalence of HPV infection in head and neck cancers in European populations. Studies on non-European populations, those not published in English, and those assessing patients co-infected with human immunodeficiency virus were excluded. Eligible studies were combined in a meta-analysis. In addition, the potential statistical association between the head and neck cancers and certain HPV types was investigated. RESULTS: Thirty-nine publications met the inclusion criteria. The prevalence of HPV of any type in 3,649 patients with head and neck cancers was 40.0% (95% confidence interval, 34.6% to 45.5%), and was highest in tonsillar cancer (66.4%) and lowest in pharyngeal (15.3%) and tongue (25.7%) cancers. There were no statistically significant associations between the HPV types analysed and the geographical setting, type of sample analysed or type of primer used to analyse samples in head and neck cancers. CONCLUSIONS: The prevalence of HPV infection in European patients with head and neck cancers is high but varies between the different anatomical sites of these malignancies. There appears to be no association between HPV type and geographical setting, type of samples analysed or type of primer used to analyse samples in such cancers

How well do discrete choice experiments predict health choices? A systematic review and meta-analysis of external validity.

Discrete choice experiments (DCEs) are economic tools that elicit the stated preferences of respondents. Because of their increasing importance in informing the design of health products and services, it is critical to understand the extent to which DCEs give reliable predictions outside of the experimental context. We systematically reviewed the literature of published DCE studies comparing predictions to choices made in reality; we extracted individual-level data to estimate a bivariate mixed-effects model of pooled sensitivity and specificity. Eight studies met the inclusion criteria, and six of these gave sufficient data for inclusion in a meta-analysis. Pooled sensitivity and specificity estimates were 88% (95% CI 81, 92%) and 34% (95% CI 23, 46%), respectively, and the area under the SROC curve (AUC) was 0.60 (95% CI 0.55, 0.64). Results indicate that DCEs can produce reasonable predictions of health-related behaviors. There is a great need for future research on the external validity of DCEs, particularly empirical studies assessing predicted and revealed preferences of a representative sample of participants