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Health technology assessment (HTA) of optoelectronic biosensors for oncology by analytic hierarchy process (AHP) and Likert scale
BACKGROUND: The multicriteria decision method (MCDM) aims to find conflicts among alternatives by comparing and evaluating them according to various criteria to reach the best compromise solution. The evaluation of a new health technology is extremely important in the health sciences field. The aim...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6612208/ https://www.ncbi.nlm.nih.gov/pubmed/31277572 http://dx.doi.org/10.1186/s12874-019-0775-z |
Sumario: | BACKGROUND: The multicriteria decision method (MCDM) aims to find conflicts among alternatives by comparing and evaluating them according to various criteria to reach the best compromise solution. The evaluation of a new health technology is extremely important in the health sciences field. The aim of this work is to evaluate a new health technology to assay thyroglobulin in patients with differentiated thyroid cancer to improve its service from an organizational point of view, by planning new and appropriate training activities, ensuring proper use of resources and satisfying the needs of different users. METHODS: The evaluation was performed using two methodologies: the analytic hierarchy process (AHP) and the Likert scale. The AHP is a multicriteria decision approach that assigns a weight to each evaluation criterion according to the decision maker’s pairwise comparisons of the criteria. The Likert scale is a psychometric scale employed to study the degree of user satisfaction by measuring opinions. RESULTS: Results show the need of particularly improving clinical efficiency, effectiveness, and return on sales (ROS) related to the technology; technological safety, human resources and other parameters do not need to be improved because of the high satisfaction results of the users. CONCLUSIONS: The application of both methods provided the necessary information to improve the quality of the service, allowing the decision maker to identify the most valuable service features and to improve these to ensure user satisfaction and to identify possible service improvements. |
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