Objectives: To explore and test methods for the operation of a national Early Warning System (EWS) in Denmark and to support decision making by the Danish Centre for Evaluation and Health Technology Assessment on this issue.
Methods: On the basis of literature reviews, information from members of EuroScan, and supported by clinical experts and stakeholders, existing methods were adapted and new methods were developed as part of a feasibility study.
Results: Approximately 200 technologies in 30 specialties were identified on the basis of information by EuroScan. A new instrument was developed to distinguish between important and unimportant technologies (filtering). Clinical experts in six specialties applied the instrument to sixty-two technologies in their respective fields, of which nine (15%) were judged potentially important for the Danish health care system. For priority setting, adapting a Dutch instrument to the Danish context was discussed. In principle, the instrument was acceptable, but several changes were proposed, for example, relating to the decentralized structure of the Danish health care system. For early assessment, the format and methods applied by SBU and Canadian Coordinating Office for Health Technology Assessment (CCOHTA) were compared and applied to pharmaceuticals (glitazones in treatment of type 2 diabetes mellitus) and a procedure (embolization of uterine fibromas). Given the main target group of the Danish EWS, local decision makers, the CCOHTA format was preferred.
Conclusions: The findings of the study have laid the foundation for an EWS using appropriate methods adapted to local circumstances. On the basis of the findings, a decision was made to start an EWS.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1017/s0266462304001163 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Machine Learning-Based predictive model for adolescent metabolic syndrome: Utilizing data from NHANES 2007-2016.
Sci Rep
January 2025
Department of Anesthesiology and Surgical Intensive Care Unit, Kunming Children's Hospital, Kunming, Yunnan, China.
Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hypertension, and insulin resistance, increasing risks of cardiovascular disease and mental health problems. Early detection and intervention are crucial but often hindered by complex diagnostic requirements. This study aims to develop a predictive model using NHANES data, excluding biochemical indicators, to provide a simple, cost-effective tool for large-scale, non-medical screening and early prevention of adolescent MetS.
View Article and Find Full Text PDFPopulation-Level SARS-CoV-2 RT-PCR Cycle Threshold Values and Their Relationships with COVID-19 Transmission and Outcome Metrics: A Time Series Analysis Across Pandemic Years.
Viruses
January 2025
Antiguo Hospital Civil de Guadalajara, "Fray Antonio Alcalde", Guadalajara 44280, Mexico.
This study investigates the relationship between SARS-CoV-2 RT-PCR cycle threshold (Ct) values and key COVID-19 transmission and outcome metrics across five years of the pandemic in Jalisco, Mexico. Utilizing a comprehensive time-series analysis, we evaluated weekly median Ct values as proxies for viral load and their temporal associations with positivity rates, reproduction numbers (Rt), hospitalizations, and mortality. Cross-correlation and lagged regression analyses revealed significant lead-lag relationships, with declining Ct values consistently preceding surges in positivity rates and hospitalizations, particularly during the early phases of the pandemic.
View Article and Find Full Text PDFDevelopment of a Luciferase Immunosorbent Assay for Detecting Crimean-Congo Hemorrhagic Fever Virus IgG Antibodies Based on Nucleoprotein.
Viruses
December 2024
Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou 510515, China.
Crimean-Congo hemorrhagic fever (CCHF) is a serious tick-borne disease with a wide geographical distribution. Classified as a level 4 biosecurity risk pathogen, CCHF can be transmitted cross-species due to its aerosol infectivity and ability to cause severe hemorrhagic fever outbreaks with high morbidity and mortality. However, current methods for detecting anti-CCHFV antibodies are limited.
View Article and Find Full Text PDFResearch on Fire Detection of Cotton Picker Based on Improved Algorithm.
Sensors (Basel)
January 2025
College of Mechanical and Electrical Engineering, Xinjiang Agricultural University, Urumqi 830052, China.
According to the physical characteristics of cotton and the work characteristics of cotton pickers in the field, during the picking process, there is a risk of cotton combustion. The cotton picker working environment is complex, cotton ignition can be hidden, and fire is difficult to detect. Therefore, in this study, we designed an improved algorithm for multi-sensor data fusion; built a cotton picker fire detection system by using infrared temperature sensors, CO sensors, and the upper computer; and proposed a BP neural network model based on improved mutation operator hybrid gray wolf optimizer and particle swarm optimization (MGWO-PSO) algorithm based on the BP neural network model.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!