International Conference on Information Systems and Medicine. Volume 1

Portugal and Spain share one of Europe’s largest border regions, where healthcare accessibility remains a critical challenge. Despite the potential benefits of cross-border cooperation, healthcare planning has largely neglected shared access to specialized medical infrastructure, such as hemodynamic units. This study assesses spatial accessibility to these units for populations in the Portuguese-Spanish border region, particularly those at risk of acute myocardial infarctions. Using a Geographic Information Systems (GIS)-based three-step floating catchment area (3SFCA) method, we analyze healthcare resource distribution and identify disparities in service availability. The results highlight areas with limited access to emergency cardiac care, revealing crucial gaps in infrastructure. Findings suggest that strategic cross-border collaboration could enhance healthcare equity and reduce response times in life-threatening situations. This research provides valuable insights for policymakers, advocating for integrated planning efforts to optimize healthcare accessibility and improve patient outcomes in borderland regions.

A significant percentage of patients, according to recent studies, report persistent clinical manifestations of COVID-19 beyond the acute phase. These symptoms extend between four and twelve weeks from the initial clinical presentation. This clinical study details the case of a 50-year-old female patient with a history of hepatitis C who developed COVID-19 and subsequently experienced a series of symptoms indicative of Post-COVID-19 Syndrome (Long COVID). The presented symptoms included fever, general malaise, anorexia, vomiting, diarrhea, sore throat, dry cough, severe headache, mucosal dryness, skin fold, muscle weakness in the lower limbs, conjunctival injection, and sudden visual loss in the left eye. She showed initial improvement and was discharged from the hospital; however, she developed fever, ageusia, dyspnea, positional tachycardia, palpitations, and retrosternal pain. Subsequent examinations revealed pericarditis and subacuteinflammatory demyelinating polyneuropathy, demonstrating the diverse and prolonged clinical course associated with Long COVID. Treatment with colchicine and NSAIDs resulted in clinical improvement, highlighting the challenges in managing and potential therapeutic approaches for patients with persistent COVID-19 symptoms.

Stress is a critical problem due to its impact on emotional and physical health, presenting a demand for non-pharmacological interventions. Shinrin-yoku emerges as a practice based on connection with nature. The study aimed to assess the impact of sensory immersion tourism in natural environments on emotional balance and perceived stress reduction through the practice of Shinrin-yoku. A quantitative, exploratory methodology and an action research design were used. The intervention consisted of guided sessions that included slow walking, conscious breathing and observation of the natural environment. Three pre-post intervention instruments were used: the Perceived Stress Scale (PSS), the Positive and Negative Affect Scale (PANAS) and the Profile of Mood States (POMS). Pre-intervention findings revealed that participants experienced stressful situations that affected their emotional well-being. It was also noted that a considerable number experienced anxiety, nervousness and difficulty coping with daily obligations. Post-intervention results indicated a significant improvement in emotional well-being. According to the Profile of Mood States (POMS), emotional well-being improved significantly, with a predominance of positive states, while negative emotions decreased. In conclusion, Shinrin-yoku is an effective strategy for improving emotional health, reducing stress and strengthening psychological resilience.

Introduction Knowledge and attitudes of medical professionals and students towards artificial intelligence in the context of medical research remain poorly explored. Objective To determine the knowledge and attitudes about artificial intelligence in Cuban health professionals and students. Methods Cross-sectional descriptive study. A validated survey was used to gather data on demographics, AI resources, perceived knowledge, attitudes, confidence, and interest in AI policy. Ordinal regression was conducted to explore the influence of participant roles on attitudes and knowledge about AI. Results This study surveyed 728 Cuban health professionals and students, revealing a moderate level of AI knowledge, with significant differences between groups. Social networks were the primary source of AI information, Academics-Researchers also relied on academic journals and textbooks. Confidence in assessing AI outputs and mitigating clinical harms was moderate, but a majority (45.05%) believed AI could change their roles. Interest in reviewing or developing AI policies was high (39.97%). Undergraduate students expressed greater interest in learning about AI applications and confidence in understanding machine learning, while Academics-Researchers demonstrated strong attitudes towards AI and interest in policy development. A significant barrier to AI learning across groups was a lack of institutional support, though lack of time was also prevalent among undergraduate students. Conclusions Cuban health professionals and students demonstrate moderate AI knowledge, with significant differences between groups. Interest in AI and its potential impact on their roles is high, but barriers to adoption, like lack of institutional support and time, require attention.

To develop a questionnaire for Portuguese-speaking physiotherapists to collect data on their perceptions regarding the use of digital health technology and artificial intelligence in clinical practice. Design: A cross-sectional study utilizing an electronic survey. Setting: The study involved primary and secondary care physiotherapists across Portugal, Brazil, S. Tomé e Principe, Canada, Switzerland, and Angola. Participants: A total of 122 Portuguese-speaking physiotherapists treating musculoskeletal conditions were recruited. Of these, 97 completed the survey (completion rate: 80.3%). Participants were primarily female (72%), over 40 years of age (60.8%), with more than 20 years of clinical practice (37.1%). Interventions: Not applicable. Main outcome measures: The survey assessed the current utilization and acceptability of digital health technologies, including the frequency of use for various clinical tasks and the willingness to adopt new technologies. Results: Traditional methods such as face-to-face questioning (76%) and handwritten notes (42%) were predominantly used. Only 1–23% of physiotherapists used any digital health technology. Despite low current utilization, there was a high interest in digital technologies, particularly for tracking patient conditions (94.8%), inputting clinical progress notes (88.6%), and receiving imaging results (83.5%). Conclusions: The study highlights a significant interest among physiotherapists in adopting digital health technologies, despite current underutilization. Addressing barriers such as digital literacy and data security concerns could enhance the integration of these technologies, potentially improving musculoskeletal care delivery and patient outcomes.

Effective training in respiratory assessment and diagnosis is critical for physiotherapy students. Digital tools like chatbots offer interactive and personalized learning experiences, fostering clinical reasoning in safe and controlled environments. Objective: To develop and validate an AI-powered chatbot designed to simulate clinical scenarios, enabling students to practice respiratory assessment and diagnosis. Methods: The study will follow a four-phase process: Conceptualization, Identify reporting standards, chatbot development, pilot testing and validation, implementation and refinement, and finally dissemination and updates. Expected Outcomes: The chatbot is anticipated to enhance clinical reasoning, improve diagnostic accuracy, and increase student engagement in learning respiratory assessment. This project aims to establish a scalable model for integrating AI into physiotherapy education.

The Internet and social networking sites have developed considerably in recent years, but few studies have measured their impact on physiotherapy. Objective: To estimate the importance of the Internet and social networks in physiotherapy from the patient's point of view, their frequency of use, and the public's confidence in them. Methods: The measuring instrument is a questionnaire on the importance of the Internet and social networks from the patient's point of view. The questionnaire, which was distributed via social networks and in different public organizations, collected 347 responses on frequency of use, sites consulted and confidence in the internet from patients of all ages and genders. Results: 302 people (87.3%) use the Internet for health information. The most frequently consulted sites were government sites (57.8%), popularization sites (59.8%), scientific articles (35.8%) and social networks (32.8%). 312 patients (90%) had moderate or minimal confidence in the information. The study shows that 343 patients (98.8%) trust their healthcare professionals more than information found on the internet. 322 patients (92.8%) have never received a recommendation from their physiotherapist, while 260 (76.9%) would like to. Conclusion: The use of the Internet is very important and patients expect recommendations from their physiotherapist, as trust in the Internet is lower. The verification of information, its transmission and accessibility can be improved by modern means such as social networks or the use of organizations such as HON (Health On The Net).

This systematic review aimed to identify universities in Latin America that have implemented microcredentials in the training of dentists and analyze their impact on the employability of graduates. However, this study revealed a complete absence of eligible articles that met the inclusion criteria, highlighting a significant gap in the academic literature on this topic. Despite the increasing global recognition of microcredentials as effective tools to address specific skill gaps and enhance employability, no empirical studies have documented their application in the field of dentistry within the region. These findings emphasize the urgent need for future research investigating the feasibility, implementation, and outcomes of microcredentials in dental education. Such efforts could inform the development of frameworks to integrate microcredentials into traditional educational models, aligning educational outcomes with labor market demands. This study calls for initiatives that involve collaboration among academic institutions, policymakers, and industry stakeholders to promote the adoption of micro-credentials to strengthen employability and address emerging workforce challenges in dentistry.

Children are increasingly interacting with mobile devices from an early age, offering both challenges and opportunities for health education. Studies show that children aged 6–10 spend substantial time on these technologies, which can lead to poor postural habits and motor development issues associated with sedentary behavior. This study introduces PediaMouv, a mobile app designed to promote postural education and motor skills development for children aged 6–10. The app aims to leverage children’s affinity for technology, fostering healthier habits and behaviors through interactive, engaging content. PediaMouv was developed using a human-centered design approach by a multidisciplinary team of physiotherapists, educators, and developers. It integrates scientifically validated content with an intuitive interface, including posture correction guides, exercise libraries, and ergonomic advice. PediaMouv represents an innovative approach to integrating digital tools into pediatric health education. The pilot study will evaluate the app's usability, engagement, and preliminary impact, laying the groundwork for broader implementation.

Workplace safety remains a critical concern in Europe, with significant disparities in accident rates across countries. This study examines the impact of healthcare policies, workforce availability, and digital transformation on workplace accidents in Germany, Spain, France, and Italy. It explores how healthcare expenditure and regulatory enforcement influence accident rates in centralized versus decentralized healthcare systems. A quantitative analysis of workplace accident data, healthcare expenditure, and workforce distribution assesses correlations between healthcare investment and occupational safety. A SWOT analysis identifies key strengths and weaknesses in regulatory enforcement, funding, and digital adaptation. Findings indicate that Germany and France, with centralized and well-funded healthcare systems, report lower accident rates due to consistent safety regulations and higher healthcare investment. Conversely, Spain and Italy, characterized by decentralized healthcare models, experience higher accident rates due to underinvestment and regional disparities in regulatory enforcement. Gender disparities in workplace fatalities further highlight systemic safety gaps. Higher healthcare expenditure is associated with lower accident rates and improved workforce productivity, reinforcing the economic case for increased investment in occupational health. Digital transformation offers opportunities to enhance safety compliance, but Spain and Italy require further infrastructure investment and broader adoption of digital tools. The study underscores the importance of healthcare investment, robust safety regulations, and technological advancements in reducing workplace accidents. Policymakers should prioritize healthcare funding, workforce development, and digital innovation to enhance workplace safety. Future research should explore regional disparities and assess targeted safety interventions.

Introduction: Mandibular fractures in older adults range from 10.1 to 56%. These fractures often cause long-term disability and deformities, with social and psychological consequences. Health-related quality of life is becoming increasingly relevant in therapeutic decision-making, however, there are few studies that address that of older adults who have suffered FM. Objective: The aim of this article is to assess the quality of life of older adults with mandibular fracture treated at the “General Calixto García” Hospital between 2022 and 2023. Methodological Design: A descriptive prospective study was carried out with 17 patients aged over 60 years of both sexes with a mandibular fracture of traumatic aetiology who attended the Maxillofacial Surgery Service of “General Calixto García” Hospital between 2022 and 2023. Results: The mean age was 73.4 years. The females represented 71.4% of the low quality of life scores. The impairment of mandibular function was severe in 100% of patients with low quality of life. A tendency towards an increase in quality of life scores was observed after mandibular fracture treatment. The physical dimension was the most affected one before treatment. Conclusions: Low quality of life prevailed in patients older than 75 years and it was closely related to females. Patients who received open treatment had better quality of life. The quality of life improved as the impairment of mandibular function decreased.

If education is an inalienable right of children and adolescents with disabilities, obtaining a job is key to inclusion in adult life. The objective of this study was to analyze the psychological meanings that students from three health faculties in their final year have about the constructs “Adult”, “Adult Patient” and “Adult Patient with Autism Spectrum Disorder” in the city of Temuco, Chile. This was a cross-sectional, descriptive study, using qualitative methodology with the technique of natural semantic networks in group application. The results show that the word “adult” was defined by men in terms of Responsibility, Work and Maturity; while women defined it in terms of Maturity, Responsibility and Family. Both men and women associated the construct “Adult Patient” with concepts such as Diagnosis, Pathology and Pharmacology in different hierarchies, for women “Diagnosis” is the main one, while for men it is “Pathology”. Finally, the concept of “Adult Patient with Autism Spectrum Disorder” was defined by both sexes with concepts such as “Dependent”, “Dysregulation” and “Communication”; “Dependent” being the category with the greatest semantic weight for both sexes, while “Therapeutic Adaptation” and “Patient-Centered Approach” occupy the last positions in terms of their semantic weight.

This research analyses the development of an Arduino-based vital signs monitoring system, designed to improve comprehensive care in obstetric psychoprophylaxis in Ecuador. Advanced sensors such as the MLX90614 to measure body temperature, and the MAX30102 for heart rate and oxygen saturation, integrated with Arduino Uno, were implemented. The programming was carried out in Arduino IDE, using specific libraries for the management of real-time data, which are displayed on an LCD screen. During testing, the system proved to be reliable, obtaining data comparable to standard medical devices, with variations of <2%. The system was evaluated in real situations, such as psychoprophylaxis workshops, showing that it can capture variations in vital signs efficiently, providing early warnings in critical cases. In addition, its low cost and portability are highlighted, making it accessible in communities with limited resources. The potential findings of this technology are to become a key tool for primary health care in Ecuador, not only in psychoprophylaxis but also in other medical areas. The use of open technology such as Arduino allows the adaptation of the system to various local needs, promoting innovation in the health sector.

The analysis of contingency tables is fundamental in applied statistics to evaluate relationships between categorical variables. However, conventional methods such as Chi-square and Fisher’s exact test have limitations in tables with small sample sizes or low values, affecting statistical validity. This study proposes a linear scaling method, transforming contingency table values to an expanded range of 0–100 while maintaining original proportions. This technique enhances the sensitivity of statistical tests, allowing the detection of significant patterns that might be overlooked in smaller scales. The linear scaling was applied to simulated contingency tables reflecting clinical contexts, such as relationships between health problems and medications administered in ICUs. The original and scaled tables were analyzed using Chi-square and Fisher’s exact test, showing that scaling amplifies relative differences between cells, improving statistical interpretation. Additionally, simple correspondence analysis confirmed that structural relationships remain unchanged after scaling. The proposed method addresses challenges such as uncertainty and limited precision in diffuse data. With applications in various fields, including public health and economics, the linear scaling approach enables more robust and adaptable analysis, optimizing the use of complex data without compromising analytical validity.

Aging is a global phenomenon with multiple challenges for health systems, regarding the management of chronic diseases and comorbidities. This scenario leads to the use of different pharmacological groups, necessary for the control of diseases such as hypertension, diabetes, cardiovascular diseases, and neurodegenerative disorders. Is research work aimed to study the prevalence of the most used pharmacological groups in a group of elderly people integrated at the Senior University of Amares (Braga, Portugal) Portugal. The methodology used was quantitative. The group of elderly people integrated at the Senior University of Amares, also participants in a pilot program of health and therapeutic movement and physical exercise for active aging, the project FisioSeniorMoving, they responded to a diverse set of structured and oriented questions for the evaluation of clinical and pharmacological history, after written informed consent. In a group of 23 elderly people of both gender (masculine n = 13; female n = 10) with mean age of 76 years, the most used pharmacological groups are: sedatives n = 5 (21.7%); anxiolytics n = 10 (43.5%); antidepressants n = 1 (4.3%); anti-inflammatories non-steroidal (AINEs) n = 2 (8.7%); corticosteroids n = 1 (4.3%) and analgesics n = 1 (4.3%). It is noted that none of the elderly people are aware of taking anticonvulsants. Other significant pharmacological groups used by the elderly group include medication for control of diabetes mellitus n = 5 (21.7%); for control of hypercholesterolemia n = 11 (47.8%); hypertension arterial n = 16 (69.6%) and anticoagulants n = 3 (13.0%). We highlight the prevalence of use of anxiolytics, sedatives and antidepressants of 69.5%, in this group of the population. The analysis of the results also allows us to infer that 12 (52.2%) of the elderly use three or more different pharmacological groups per day, which may increase the risk of drug interactions. The results show that the pharmacological groups most used by the group participating in the study go against the control of the main diseases of today such as diabetes mellitus, hypertension, cardiovascular diseases, and in a very significant way to mental Health. Aging poses complex challenges to health management, especially regarding the use of pharmacological therapies.

Life expectancy for people aged 65 and over in Portugal has risen to 81.9 years, making it one of the highest cities in the European Union. As a result, the prevalence of frailty among older adults has increased. Frailty is a biological geriatric syndrome characterized by the decline in physiological reserves and resistance to stress factors leading to physical, mental, and emotional deficits. This condition is closely related to the perception of quality of life, which is a priority for public health. The aim of this cross-sectional descriptive observational study was to explore the relationship between frailty and quality of life in older adults. Involved 92 subjects (average age 76.0 ± 7.5) from the village of Amares in northern Portugal. Data were collected on socio-demographic characteristics, frailty, and quality of life. The statistical analysis was carried out using IBM®SPSS® Software, version 27 for descriptive and inductive statistics, considering statistically significant associations for p-value < 0.05. The results obtained, analyzed by age groups, revealed statistically significant correlations, mostly low negative and positive, between the domains of the SF-36 quality of life test and the Groningen Frailty Indicator. Moderate correlations were observed only in the areas of physical functioning, vitality, and mental health within the SF-36 and the Groningen Indicator. Assessing quality of life and frailty is essential for developing effective strategies to prevent and manage frailty, ultimately improving disease progression and treatment.

TECAR therapy is a form of non-invasive electrothermal therapy classified as deep thermotherapy and characterized by high-frequency electrical currents. Since heat influences muscle flexibility, TECAR therapy can influence hamstring flexibility. Objective: To compare the effects of Capacitive TECAR plus Resistive TECAR versus Bipolar form on hamstring flexibility and postural control in young university students. Methods: A study was conducted with 30 university students individuals, 5 males, and 25 females, with a mean age of 22.9 years. A questionnaire was applied, and three evaluations were performed before and after the intervention: 90–90 Straight Leg Raise (90-90 SLRT), Single Leg Hop Test (SLHT), and Star Excursion Balance Test (SEBT). Statistical analysis was performed using the IBM®SPSS® software, VERSION 25 for descriptive statistics, considering statistically significant associations for p-value < 0.05. Results: No statistically significant results were observed regarding the 90-90 SLRT or SLHT. However, concerning SEBT, minimal positive changes were found. Conclusion: A single 5-minute TECAR therapy session did not yield statistically significant improvements in hamstring flexibility, explosive strength, or semi-dynamic balance among healthy university students.

Introduction: This study introduces a practical-theoretical methodology to train left-handed dentistry students in using their non-dominant hand. This approach addresses training deficiencies that disregard biological factors like cerebral dominance, which result from abrupt changes in laterality and right-handed equipment designs, causing emotional and musculoskeletal challenges. Objective: To validate a practical-theoretical methodology designed to train left-handed dentistry students in using their non-dominant hand, enhancing their acquisition of essential practical skills. This methodology, validated through a Delphi method involving experts across three dimensions (brain dominance, pedagogy, and dentistry), demonstrated strong consensus (W = 0.750) after two rounds of refinement, indicating its potential for effective implementation. Methods: Technological development study in which 15 professionals selected through expert criteria participated, calculating their competence. The methodology was validated through the Delphi method, determining consensus with the Kendall W Test for a 5% significance level (p < 0.05). Results: Two rounds were conducted, gathering expert evaluations and modifying the methodology validation instrument based on suggestions. The methodology to train the non-dominant hand in the Dentistry career was conceived and validated according to the proposed objective. Conclusions: The experts considered the methodology valid, highly useful, and satisfactory, with the potential to gradually transform students’ laterality.

This study aims to identify and classify the essential digital competencies required for medical students and healthcare professionals to perform effectively in today’s digital healthcare environment. A systematic review was conducted following the Cochrane Handbook and PRISMA guidelines. The search targeted peer-reviewed publications from 2014 onwards in PubMed, Scopus, and Web of Science. Studies prior to 2014 were excluded to focus on competencies aligned with the rapid advancements in digital healthcare technologies over the past decade. Inclusion criteria focused on studies in English or Spanish exploring competencies such as digital literacy, telemedicine, and emerging technologies. Studies without empirical data, duplicates, and those unrelated to digital competencies were excluded. Thematic analysis, rather than pre-defined categories, guided the classification of competencies into five dimensions: general digital literacy, telemedicine, data management and digital privacy, communication in digital environments, and adaptation to emerging technologies like artificial intelligence and big data. From 652 records, 16 studies met the inclusion criteria. Core findings highlighted the importance of foundational skills like digital literacy and telemedicine, alongside the rising relevance of advanced technologies such as AI. Gaps in formal training and variability in competency levels were notable across contexts. The findings also emphasized the need for ethical and legal education to address challenges in privacy and security. Digital competencies are essential for integrating technology into healthcare education and practice. Training must include both foundational and advanced digital skills to align with evolving demands. Future research should examine the impact of these competencies on patient outcomes, explore strategies for integrating them into curricula, and address their implementation in resource-constrained settings.

Artificial intelligence (AI) has rapidly transformed healthcare, introducing advanced tools that optimize workflows, enhance diagnostic accuracy, and support clinical decision-making. While numerous studies have highlighted the potential benefits of AI in improving healthcare delivery, there remains a growing need to understand its impact on healthcare professionals’ job satisfaction and work quality. This study aimed to explore the positive and negative impacts of AI systems on the job quality and satisfaction of healthcare professionals, focusing on both individual well-being and organizational effectiveness. A systematic review was conducted following PRISMA guidelines, with searches performed in PubMed, Scopus, and Web of Science from 1997 to January 2025. The inclusion criteria encompassed empirical studies evaluating AI's impact on job satisfaction and work quality among healthcare professionals, without restrictions on study design. Articles focused solely on technical aspects of AI or unrelated to healthcare were excluded. Of 184 records initially identified, 9 studies met the eligibility criteria, representing a total of 1425 healthcare workers across diverse professions. Positive outcomes included improved diagnostic accuracy, reduced administrative burden, and enhanced work-life balance, particularly through workflow optimization and cognitive support. For instance, documentation time was reduced by up to 40% in complex cases. However, challenges such as deskilling risks, documentation errors, and interoperability issues were identified. Concerns regarding ethical implications, including privacy and data security, were also highlighted. AI systems demonstrate significant potential to enhance job satisfaction and work quality by alleviating administrative burdens and improving clinical decision-making. However, addressing challenges like training gaps, ethical concerns, and system interoperability is crucial for maximizing AI's benefits. Future research should prioritize the inclusion of diverse healthcare settings, particularly in resource-limited contexts, to ensure equitable and effective implementation.

The integration of artificial intelligence (AI) into healthcare is transforming the workforce, significantly affecting various professions. This systematic review aimed to identify the health professions most vulnerable to AI-driven automation and job replacement, focusing on roles with repetitive and predictable tasks. A comprehensive search was conducted across PubMed, Scopus, and Web of Science, applying inclusion criteria that targeted peer-reviewed studies evaluating the impact of AI on automation and workforce displacement in healthcare professions. A total of 56 studies were included, analyzed using a PRISMA approach. The findings revealed that radiology, nursing, pathology, and administrative roles are the most impacted due to their reliance on tasks highly amenable to AI automation, such as medical imaging analysis, patient monitoring, and data entry. However, professions requiring complex decision-making and critical thinking, such as surgery, showed lower vulnerability. Despite these risks, the review underscores that AI is unlikely to replace healthcare professionals entirely but will reshape roles, emphasizing the need for human oversight, empathy, and adaptability. To mitigate these challenges, healthcare systems must prioritize continuous education and workforce training to integrate AI as a complementary tool rather than a replacement. Policymakers and educational institutions should focus on ethical considerations, skill redefinition, and sustainable adaptation strategies for professionals in at-risk fields.

The paper presents the impact of emerging technologies, such as the Internet of Things (IoT) and cloud computing, on the healthcare sector. In the last decade, these innovations have enabled the interconnection of medical devices, the collection and analysis of real-time data, and the optimization of hospital resource management, improving both clinical and administrative processes. The findings highlight applications of IoT in hospitals, such as remote patient monitoring and healthcare service management. However, the implementation of these technologies faces significant challenges, including concerns about data security, system interoperability, and resistance to change by medical staff. The paper concludes that while the integration of IoT and cloud computing offers opportunities to improve healthcare, more research is crucial to address existing challenges. It is recommended to establish technology adoption frameworks, interoperability standards, and provide adequate training to staff. These actions are essential to maximize the benefits of these technologies in the health sector and ensure more efficient and safer medical care.

This research investigates the management of a Multiprofessional Unit in the hospital context, using the perspective of Design Management, with a focus on service optimization and data visualization. The objective was to map how the management activities of a Multiprofessional Team take place in the hospital context, with the support of Service Design and Design Management. Regarding the methodological procedures, this is an applied research with a qualitative approach and exploratory and descriptive objectives. The study conducted a Case Study with the Manager of a Multiprofessional Unit in a public hospital in Santa Catarina, Brazil, who coordinates 78 professionals. Using the Project Development Guidance Guide (GODP), a Design Management tool, the research involved data collection, analysis, and organization regarding the Manager’s role. The data collection resulted in the Manager’s Profile Description, Daily, Monthly, and Annual Routine Maps, Interaction Frequency with Other Departments, and the Stakeholders Map, providing a synthetic and graphical view of the Manager’s activities. A high variability of demands was observed, with a concentration of activities in the first half of each month and the second half of the year. Additionally, the research identified a high number of interactions between the Manager and all levels of the hospital's organizational structure. The mapping enabled a visualization of the context and an identification of the challenges faced by the Manager. The research intends to proceed with a diagnosis to identify the strengths and weaknesses of the unit.

This research explores the role of Occupational Therapists in the hospital context, utilizing the integration of Service Design and Design Management, both of which offer benefits in problem-solving and service optimization. The objective was to investigate the practice of Occupational Therapists in the hospital environment, considering the interaction between Service Design and Design Management. The research was conducted through a Case Study involving three Occupational Therapists from a public hospital in the state of Santa Catarina, Brazil, and an Integrative Literature Review, which included nine selected studies. It was structured with the support of the Design Management tool, the Project Development Guidance Guide (GODP), and Service Design tools, encompassing data collection, analysis, and organization regarding the practice of three Occupational Therapists in a public hospital in Santa Catarina. This process resulted in the development of the Therapists’ Profile, Routine Map, mapping of Involved People, and Stakeholder Map, facilitating a deeper understanding of the Therapists’ roles, profiles, and interactions. The integration of Design Management and Service Design proved to enhance the work of these Therapists in the hospital environment, aiding in the comprehension of hospital structures and occupational Therapy activities, while broadening the understanding of their professional practices.

In public health, unfavorable obstetric and neonatal outcomes pose a significant challenge due to their consequences for both mothers and newborns. These outcomes range from minor complications to severe conditions, such as preeclampsia, postpartum hemorrhage, and neonatal complications like low birth weight and respiratory distress. Understanding the factors leading to these unfavorable obstetric and neonatal outcomes is essential for proposing interventions and improving maternal and child health. Factors such as maternal age, marital status, and race are associated with higher risks in Brazil. In this study, the data is first divided into groups using K-means, then Apriori is applied to explore patterns in each cluster and identify factors associated with the health and well-being of newborns. The analysis was based on records from the Live Birth Information System (SINASC), aiming to identify key variables determining newborn health and well-being through the Apgar score. A total of 2,561,922 birth records were analyzed. The minimum metrics used as parameters for the Apriori algorithm were 25% support and 95% confidence, resulting in the generation of ten association rules.

The present study intends to explore different Deep Learning algorithms to identify dental implant brands, to assist in the rehabilitation process. Data Augmentation Techniques were implemented and explored, along with a VGG (Visual Geometry Group) style model, models implemented using Transfer Learning, and an approach from another academic study. A dataset was developed through contact with several dental clinics. Given the nature of the data that makes up the dataset, it was not possible to obtain a large amount of data, as well as an egalitarian distribution between classes. In view of the above, the Stratified k-fold cross-validation method was used during the training process to minimize potential problems. The model's performances were evaluated according to various statistical measures, during the training process and during the testing process. During the training process, the metrics used were entropy loss and accuracy. In the testing process, the models were evaluated for accuracy, recall, specificity and F1 Score. It is concluded that the best models are the model belonging to the academic study and the model in the VGG style, since both perform well at the level of the training process and at the level of the testing process.

Introduction: The incorporation of artificial intelligence (AI) into the supply management of sanitary requirements has managed to optimize a series of processes, such as the purchase of supplies, medicine, equipment, distribution management, inventory management, and prediction of demand, thus improving operational efficiency in the health sector. Objective: To identify AI applications in the supply management of health supplies and medical devices worldwide. Methodology: Systematic review, based on Moher’s [22] stages, of articles published between 2019 and 2024 in electronic databases such as PubMed, Web of Science, Scopus, and Scielo. AI applications are analysed according to the stages of the supply chain operations reference (SCOR) model. The articles are evaluated according to their methodological quality using the Mixed Methods Appraisal Tool (MMAT). Results: Eight relevant studies are selected that address the use of AI, machine learning (ML), deep learning (DL), the Internet of Things (IoT), and blockchain. AI and associated technologies are revealed to improve efficiency, traceability, and inventory management; optimize product delivery; and reduce risk. These advances are observed mainly in the planning, supplying, producing, and delivering stages of the SCOR model. Discussion: Although the implementation of AI in the medical supply chain has obvious benefits, challenges, such as the need to deepen the “return” stage, which is not sufficiently addressed in the studies reviewed, are identified in its application. Conclusions: The integration of AI in the supply chain of medical supplies facilitates more efficient and adaptable management, guaranteeing the continuity of supply and improving health sector operations. Future studies should focus on the “payback” stage and explore additional AI applications in this field.

In recent times, Family Health Units (USF) have achieved greater efficiency, accessibility, a better work environment, higher citizen satisfaction, and, overall, better quality. The reform has been a clear success in terms of professional engagement. However, there are still some weaknesses to address, and the continued success of USFs is closely dependent on the sustained interest from both government entities and healthcare professionals. This study focuses on the capacity building of staff and, mainly, the acquisition of skills within a family health unit. A quantitative and qualitative methodology employed, involving a focus group and a questionnaire survey, ensuring confidentiality and anonymity, and ensuring that the questions asked weren’t related to sensitive data. The staff of the USF were our target audience, with a sample of 17 people who attended the training and responded to the questionnaire. The results revealed a general need for training on teamwork and the analysis of information/communication provided. Working with multidisciplinary teams is increasingly important in healthcare structures.

Reading comprehension is a key skill that allows you to interpret, analyze and understand texts relevant for learning and personal development. However, many students face difficulties in extracting information, making inferences and relating ideas, which limits their academic and professional performance. The purpose of the research was to develop a reading brochure to improve reading comprehension in fifth-year basic general education students. A quasi-experimental design and the descriptive statistical method were applied with a comparative design with normality tests; To validate the idea to be defended, a questionnaire was applied to evaluate reading comprehension to 80 fifth-year children through individual and group reading workshops. The results showed that children have difficulty reading, so it was necessary to apply the reading booklet prepared with readings created by the children based on elements of the environment to improve reading skills. It is concluded that the reader brochure develops creativity and imagination in students, helping to raise creativity in the creation of real readings according to the contexts that allow the development of critical and creative thinking.

Healthcare organizations have undergone significant change, particularly in recent decades, leading to a significant increase in complexity. As a result, decision-making has become more challenging as healthcare managers have to deal with multiple interdependent factors (such as patient care, human resources, technology and infrastructure, financial and budget management, and regulatory compliance), often with incomplete or uncertain information. This paper aims to review studies on decision-making in healthcare management, linking these two concepts. Through a bibliometric analysis, this research identifies emerging trends in the field and ways to overcome difficulties in information management. Data were collected from the Scopus database (1140 documents) and analyzed using VOSviewer software. The study identifies two levels of decision-making, the clinical and the operational. The results show a sharp increase in research and highlight emerging trends related to artificial intelligence, machine learning and big data. These trends are transforming healthcare management, restructuring operations, improving decision-making, and ultimately improving patient care while reducing costs.

Huntington’s disease (HD) is a degenerative disease, it progressively deteriorates until reaching disability and complete dependence on a caregiver. The primary caregiver of a patient with HD requires training and support in this task. The caregiver needs education for the care of the sick by the family/caregiver, knowledge about the disease, form of transmission, management of symptoms, and knowledge about rights in the health and pension system. This article presents a digital educational platform (Cognoceme) for learning about managing household resources and care in the health system, which can be difficult for those suffering from rare diseases such as Huntington’s. Cognoceme, as a digital educational platform, can offer an accessible and effective solution to provide families with the knowledge and tools necessary to face the daily challenges of care. These platforms can play an essential role in training caregivers, optimizing the management of available resources, and promoting better integration of patients into the health system.