Purpose: The COVID-19 pandemic has intensified the demand and use of healthcare resources, prompting the search for efficient solutions under budgetary constraints. In this context, the increasing use of artificial intelligence and telemedicine has emerged as a key strategy to optimize healthcare delivery and resources. Consequently, chatbots have emerged as innovative tools in various healthcare fields, such as mental health and patient monitoring, offering therapeutic conversations and early interventions. This systematic review aims to explore the current state of chatbots in the healthcare sector, meticulously evaluating their effectiveness, practical applications, and potential benefits. Methods: This systematic review was conducted following PRISMA guidelines, utilizing three databases, including PubMed, Web of Science, and Scopus, to identify relevant studies on the use and cost of chatbots in health over the past 5 years. Results: Several articles were identified through the database search ( n = 31). The chatbot interventions were categorized by similar types. The reviewed articles highlight the diverse applications of chatbot interventions in healthcare, including mental health support, medical information, appointment management, health education, lifestyle changes, and COVID-19 management, demonstrating significant potential across these areas. Conclusion: Furthermore, there are challenges regarding the implementation of chatbots, compatibility with other systems, and ethical considerations that may arise in different healthcare settings. Addressing these issues will be essential to maximize the benefits of chatbots, mitigate risks, and ensure equitable access to these health innovations.

The increase in the proportion of elderly people in developed societies has several consequences, such as the rise in demand for long-term care (LTC). Due to cost, inequalities may arise and punish low-income households. Our objective is to examine socioeconomic inequalities in LTC utilization in Europe. We use the last wave from the Survey of Health, Aging, and Retirement in Europe SHARE (Munich Center for the Economics of Ageing, Munich, Germany), dated 2017, to analyze the impact of socioeconomic status (SES) on LTC. For this purpose, we construct logistic models and control for socioeconomic/household characteristics, health status, and region. Then, concentration indices are calculated to assess the distribution of LTC. Moreover, we also analyze horizontal inequity by using the indirect need-standardization process. We use two measures of SES (household net total income and household net wealth) to obtain robust results. Our findings demonstrate that informal care is concentrated among low-SES households, whereas formal care is concentrated in high-SES households. The results for horizontal concentration indices show a pro-rich distribution in both formal and informal LTC. We add new empirical evidence by showing the dawning of deep social inequalities in LTC utilization. Policymakers should implement policies focused on people who need care to tackle socioeconomic inequalities in LTC.

Prostate cancer has huge health and societal impacts, and there is no clear consensus on the most effective and efficient treatment strategy for this disease, particularly for localized prostate cancer. We have reviewed the scientific literature describing the economic burden and cost-effectiveness of different treatment strategies for localized prostate cancer in OECD countries. We initially identified 315 articles, studying 13 of them in depth (those that met the inclusion criteria), comparing the social perspectives of cost, time period, geographical area, and severity. The economic burden arising from prostate cancer due to losses in productivity and increased caregiver load is noticeable, but clinical decision-making is carried out with more subjective variability than would be advisable. The direct cost of the intervention was the main driver for the treatment of less severe cases of prostate cancer, whereas for more severe cases, the most important determinant was the loss in productivity. Newer, more affordable radiotherapy strategies may play a crucial role in the future treatment of early prostate cancer. The interpretation of our results depends on conducting thorough sensitivity analyses. This approach may help better understand parameter uncertainty and the methodological choices discussed in health economics studies. Future results of ongoing clinical trials that are considering genetic characteristics in assessing treatment response of patients with localized prostate cancer may shed new light on important clinical and pharmacoeconomic decisions.

Tools to predict surges in cases and hospitalizations during the COVID-19 pandemic may help guide public health decisions. Low cycle threshold (CT) counts may indicate greater SARS-CoV-2 concentrations in the respiratory tract, and thereby may be used as a surrogate marker of enhanced viral transmission. Several population studies have found an association between the oscillations in the mean CT over time and the evolution of the pandemic. For the first time, we applied temporal series analysis (Granger-type causality) to validate the CT counts as an epidemiological marker of forthcoming pandemic waves using samples and analyzing cases and hospital admissions during the third pandemic wave (October 2020 to May 2021) in Madrid. A total of 22,906 SARS-CoV-2 RT-PCR-positive nasopharyngeal swabs were evaluated; the mean CT value was 27.4 (SD: 2.1) (22.2% below 20 cycles). During this period, 422,110 cases and 36,727 hospital admissions were also recorded. A temporal association was found between the CT counts and the cases of COVID-19 with a lag of 9–10 days (p ≤ 0.01) and hospital admissions by COVID-19 (p < 0.04) with a lag of 2–6 days. According to a validated method to prove associations between variables that change over time, the short-term evolution of average CT counts in the population may forecast the evolution of the COVID-19 pandemic.

Introducción: La crisis sanitaria generada por la COVID-19 tuvo importantes repercusiones a todos los niveles y supuso diversos retos educativos, siendo el más relevante la suspensión de clases presenciales. El objetivo principal de este trabajo es analizar la implantación y futura consolidación postCOVID-19 del blended learning. Método: Entre los nuevos métodos docentes se encuentran las clases online, la organización de webinars impartidos por expertos del ámbito económico y empresarial, seminarios impartidos por los propios alumnos, el fomento de debate en foros y chats a través de Moodle. Resultados: Algunos puntos positivos para el alumnado son los siguientes: mejora global de los resultados, mayor profundización en los conocimientos adquiridos, mejora de la capacidad de debate y aprendizaje activo y cooperativo, creación de redes de networking que permiten la colaboración entre alumnos y agentes externos al ámbito universitario. No obstante, se detectan desigualdades en el acceso a la tecnología y problemas de incompatibilidad de horarios y tareas. Discusión: Los resultados muestran una mejora de los resultados académicos y satisfacción generalizada. Como reto fundamental queda la consolidación de estos métodos teniendo en cuenta que en ocasiones suponen un trabajo extra para el alumnado y la desigualdad en el acceso a la tecnología.