RESUMO
In accordance with the cognitive orientation contemplated in the resolution of complex problems posed in public decision-making using decision support systems and social networks, this work studies the possibility of identifying the state of mind of society through the state of mind of network leaders. Using sentiment and emotion analysis as research techniques and Twitter as a representative social network, the study corpus considers tweets and retweets in Spanish about COVID-19 in the period from February 27, 2020 to December 31, 2021. As cognitive orientation claims, the proposed techniques will allow us to extract the arguments that support the different positions and decisions from the analysis of the tweets issued exclusively by social leaders. In the case study considered, the COVID-19 vaccination process in Spain, the reduction in the number of tweets' authors (more than 8,000) to the network leaders (just 8) was greater than 99 %; and the subsequent reduction in the number of associated tweets was greater than 88 % from the 18,193 tweets in society to the 2,145 tweets of the eight social leaders. The impressive degree of information compression achieved may be useful to establish new directions of social mood analysis applied to healthcare and business management.
RESUMO
RATIONALE, AIMS AND OBJECTIVES: Disparities in haemodialysis outcomes among centres have been well-documented. Besides, attempts to assess haemodialysis results have been based on non-comprehensive methodologies. This study aimed to develop a comprehensive methodology for assessing haemodialysis centres, based on the value of health care. The value of health care is defined as the patient benefit from a specific medical intervention per monetary unit invested (Value = Patient Benefit/Cost). This study assessed the value of health care and ranked different haemodialysis centres. METHOD: A nephrology quality management group identified the criteria for the assessment. An expert group composed of stakeholders (patients, clinicians and managers) agreed on the weighting of each variable, considering values and preferences. Multi-criteria methodology was used to analyse the data. Four criteria and their weights were identified: evidence-based clinical performance measures = 43 points; yearly mortality = 27 points; patient satisfaction = 13 points; and health-related quality of life = 17 points (100-point scale). Evidence-based clinical performance measures included five sub-criteria, with respective weights, including: dialysis adequacy; haemoglobin concentration; mineral and bone disorders; type of vascular access; and hospitalization rate. The patient benefit was determined from co-morbidity-adjusted results and corresponding weights. The cost of each centre was calculated as the average amount expended per patient per year. RESULTS: The study was conducted in five centres (1-5). After adjusting for co-morbidity, value of health care was calculated, and the centres were ranked. A multi-way sensitivity analysis that considered different weights (10-60% changes) and costs (changes of 10% in direct and 30% in allocated costs) showed that the methodology was robust. The rankings: 4-5-3-2-1 and 4-3-5-2-1 were observed in 62.21% and 21.55%, respectively, of simulations, when weights were varied by 60%. CONCLUSIONS: Value assessments may integrate divergent stakeholder perceptions, create a context for improvement and aid in policy-making decisions.
