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The RedETS horizon scanning (HS) program in Spain is focused on identifying non-pharmaceutical emerging health technologies. HS is organized in three steps: (i) identification using different sources (PubMed, the biomedical press, and others); (ii) screening performed by the HS Working Group and clinicians; and (iii) prioritization using the PriTec tool. This study aimed to evaluate the accuracy of RedETS HS in identifying disruptive emerging technologies for our health system.
Methods
Data from brief files and full reports related to the identified emerging technologies were collected. Full health technology assessment (HTA) reports were also reviewed. The period of analysis was from 2016 to 2023. The information collected included the name, type, category, and indication of the emerging technology and the source of identification. An ad hoc Excel spreadsheet was designed to collect the information. The analysis consisted of a description of the variables and an assessment of concordance between the emerging technologies identified and those with full HTA reports.
Results
There were 338 emerging technologies identified. These technologies were mainly therapeutic (52.1%) or diagnostic (25.7%). In addition, about 45 percent were medical devices and 15.7 percent were in vitro diagnostic tests; imaging comprised 7.4 percent. Most of the emerging technologies were identified through the biomedical press (22.2%), PubMed (23.6%) and industry (20.3%). In a preliminary analysis of these main sources, 31 percent of the technologies identified by HS had full HTA reports, with all of these being identified three years before the HTA.
Conclusions
HS systems might help identify the most relevant technologies for healthcare systems, enabling them to be more ready to incorporate the new technologies. Therefore, HS must be able to detect emerging technologies that will have an impact on the health system. Periodic evaluation of the accuracy of HS programs will improve their impact in the HTA process.
Data are scarce regarding hospital infection control committees and compliance with infection prevention and control (IPC) recommendations in Brazil, a country of continental dimensions. We assessed the main characteristics of infection control committees (ICCs) on healthcare-associated infections (HAIs) in Brazilian hospitals.
Methods:
This cross-sectional study was conducted in ICCs of public and private hospitals distributed across all Brazilian regions. Data were collected directly from the ICC staff by completing an online questionnaire and during on-site visits through face-to-face interviews.
Results:
In total, 53 Brazilian hospitals were evaluated from October 2019 to December 2020. All hospitals had implemented the IPC core components in their programs. All centers had protocols for the prevention and control of ventilator-associated pneumonia as well as bloodstream, surgical site, and catheter-associated urinary tract infections. Most hospitals (80%) had no budget specifically allocated to the IPC program; 34% of the laundry staff had received specific IPC training; and only 7.5% of hospitals reported occupational infections in healthcare workers.
Conclusions:
In this sample, most ICCs complied with the minimum requirements for IPC programs. The main limitation regarding ICCs was the lack of financial support. The findings of this survey support the development of strategic plans to improve IPCs in Brazilian hospitals.
The purpose of this study was to analyse the reliability and validity of a semi-quantitative FFQ to assess food group consumption in South American children and adolescents.
Design:
The SAYCARE (South American Youth/Child cARdiovascular and Environmental) study is an observational, multicentre, feasibility study performed in a sample of 3- to 18-year-old children and adolescents attending private and public schools from six South American countries. Participants answered the FFQ twice with a two-week interval and three 24-h dietary recalls. Intraclass and Spearman’s correlations, weighted Cohen’s kappa (κw), percentage of agreement and energy-adjusted Pearson’s correlation coefficients were calculated.
Setting:
Seven cities in South America (Buenos Aires, Lima, Medelin, Montevideo, Santiago, Sao Paulo and Teresina).
Subjects:
A sample of 200 children and 244 adolescents for reliability analyses and 252 children and 244 adolescents for validity analyses were included.
Results:
Depending on the food group, for children and adolescents, reliability analyses resulted in Spearman’s coefficients from 0·47 to 0·73, intraclass correlation coefficients from 0·66 to 0·99, κw coefficients from 0·35 to 0·63, and percentage of agreement between 72·75 and 83·52 %. In the same way, validity analyses resulted in Spearman’s coefficients from 0·17 to 0·37, energy-adjusted Pearson’s coefficients from 0·17 to 0·61, κw coefficients from 0·09 to 0·24, and percentages of agreement between 45·79 and 67·06 %.
Conclusion:
The SAYCARE FFQ achieved reasonable reliability and slight-moderate validity for almost all food groups intakes. Accordingly, it can be used for the purpose of ranking the intake of individuals within a population.
Ontologies are frequently used in the context of software and technology engineering. These can be grouped into two main categories, depending on whether they are used to describe the knowledge of a domain (domain ontologies) or whether they are used as software artifacts in software development processes. This paper presents some experiences and lessons learnt from the effective use of an ontology for Software Measurement, called software measurement ontology (SMO). The SMO was developed some years ago as a result of a thorough analysis of the software measurement domain. Its use as a domain ontology is presented first, a description of how the SMO can serve as a conceptual basis for comparing international standards related to software measurement. Second, the paper describes several examples of the applications of SMO as a software artifact. In particular, we show how the SMO can be instantiated to define a data quality model for Web portals, and also how it can be used to define a Domain-Specific Language (DSL) for measuring software entities. These examples show the significant role that ontologies can play as software artifacts in the realm of model-driven engineering and domain-specific modeling.
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