Suchergebnisse

Real-world evidence can provide answers on healthcare utilization and appropriateness, post-marketing drugs safety and comparative effectiveness, and cost-effectiveness profiles of healthcare pathways. Healthcare utilization databases, possibly integrated with drug and disease registries, electronic medical records, survey and cohort data (i.e. real-world data), allow to trace healthcare 'footprints' left from beneficiaries of National Health Service. Beaver is a research platform available on demand to Italian regions which we developed for computing indicators of healthcare utilization and clinical outcomes, as well as for generating evidence on effectiveness and cost-effectiveness profile. Two distinct solutions may be adopted. One, the so-called Beaver Light front-end allows to automatically compute health indicators of adherence to official guidelines. Two, the so-called Beaver Full front-end involves an eight-step procedure entirely driven by the study protocol. In order to fulfil the directives recently issued by the European Parliament and Council and the Italian Authority for the protection of individual data, the platform resides in each region's infrastructure, so limiting the free movement of electronic health data. Indeed, regional authorities should be responsible for data safety and for allowing data accessibility. The use of standardized and validated algorithms enables to obtain regional estimates that, being obtained by employing regional platforms containing data extracted with standardized procedure, may be compared and possibly summarized by using common meta-analytic techniques. In conclusion, the Beaver regional platform is a promising tool which may contribute to stimulate healthcare research in Italy.

The assessment of data quality and suitability plays an important role in improving the validity and generalisability of the results of studies based on secondary use of health databases. The availability of more and more updated and valid information on data quality and suitability provides data users and researchers an useful tool to optimize their activities. In this paper, we have summarized and synthesized the main aspects of Data Quality Assessment (DQA) applied in the field of secondary use of healthcare databases, with the aim of drawing attention to the critical aspects having to be considered and developed for improving the correct and effective use of secondary sources. Four developing features are identified: standardizing DQA methods, reporting DQA methods and results, synergy between data managers and data users, role of Institutions. Interdisciplinarity, multi-professionality and connection between government institutions, regulatory bodies, universities and the scientific community will provide the "toolbox" for i) developing standardized and shared DQA methods for health databases, ii) defining the best strategies for disseminating DQA information and results.

BACKGROUND: Research networks offer multidisciplinary expertise and promote information exchange between researchers across Europe. They are essential for the European Union's (EU) health information system as providers of health information and data. The aim of this mapping exercise was to identify and analyze EU research networks in terms of health data collection methods, quality assessment, availability and accessibility procedures. METHODS: A web-based search was performed to identify EU research networks that are not part of international organizations (e.g., WHO-Europe, OECD) and are involved in collection of data for health monitoring or health system performance assessment. General characteristics of the research networks (e.g., data sources, representativeness), quality assessment procedures, availability and accessibility of health data were collected through an ad hoc extraction form. RESULTS: Fifty-seven research networks, representative at national, international or regional level, were identified. In these networks, data are mainly collected through administrative sources, health surveys and cohort studies. Over 70% of networks provide information on quality assessment of their data collection procedures. Most networks share macrodata through articles and reports, while microdata are available from ten networks. A request for data access is required by 14 networks, of which three apply a financial charge. Few networks share data with other research networks (8/49) or specify the metadata-reporting standards used for data description (9/49). CONCLUSIONS: Improving health information and availability of high quality data is a priority in Europe. Research networks could play a major role in tackling health data and information inequalities by enhancing quality, availability, and accessibility of health data and data sharing across European networks. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13690-021-00766-2.

BACKGROUND: Health-related data are collected from a variety of sources for different purposes, including secondary use for population health monitoring (HM) and health system performance assessment (HSPA). Most of these data sources are not included in databases of international organizations (e.g., WHO, OECD, Eurostat), limiting their use for research activities and policy making. This study aims at identifying and describing collection methods, quality assessment procedures, availability and accessibility of health data across EU Member States (MS) for HM and HSPA. METHODS: A structured questionnaire was developed and administered through an online platform to partners of the InfAct consortium form EU MS to investigate data collections applied in HM and HSPA projects, as well as their methods and procedures. A descriptive analysis of the questionnaire results was performed. RESULTS: Information on 91 projects from 18 EU MS was collected. In these projects, data were mainly collected through administrative sources, population health interview or health examination surveys and from electronic medical records. Tools and methods used for data collection were mostly mandatory reports, self-administered questionnaires, or record linkage of various data sources. One-third of the projects shared data with EU research networks and less than one-third performed quality assessment of their data collection procedures using international standardized criteria. Macrodata were accessible via open access and reusable in 22 projects. Microdata were accessible upon specific request and reusable in 15 projects based on data usage licenses. Metadata was available for the majority of the projects, but followed reporting standards only in 29 projects. Overall, compliance to FAIR Data principles (Findable, Accessible, Interoperable, and Reusable) was not optimal across the EU projects. CONCLUSIONS: Data collection and exchange procedures differ across EU MS and research data are not always available, accessible, comparable or ...