Incidence of post-acute COVID-19 symptoms across healthcare settings in seven countries: an international retrospective cohort study using routinely-collected data.

Background: The World Health Organisation (WHO) has identified a range of symptomatic manifestations to aid in the clinical diagnosis of post-COVID conditions, herein referred to as post-acute COVID-19 symptoms. We conducted an international network cohort study to estimate the burden of these symptoms in North American, European, and Asian populations.

Methods: A federated analysis was conducted including 10 databases from the United Kingdom, Netherlands, Norway, Estonia, Spain, France, South Korea, and the United States, between September 1st 2020 and latest data availability (which varied from December 31st 2021 to February 28th 2023), covering primary and secondary care, nationwide registries, and claims data, all mapped to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM).

Developing an interpretable machine learning model for predicting COVID-19 patients deteriorating prior to intensive care unit admission using laboratory markers.

Coronavirus disease (COVID-19) remains a significant global health challenge, prompting a transition from emergency response to comprehensive management strategies. Furthermore, the emergence of new variants of concern, such as BA.2.

A Smart Digital Health Platform to Enable Monitoring of Quality of Life and Frailty in Older Patients with Cancer: A Mixed-Methods, Feasibility Study Protocol.

Objectives: LifeChamps is an EU Horizon 2020 project that aims to create a digital platform to enable monitoring of health-related quality of life and frailty in patients with cancer over the age of 65. Our primary objective is to assess feasibility, usability, acceptability, fidelity, adherence, and safety parameters when implementing LifeChamps in routine cancer care. Secondary objectives involve evaluating preliminary signals of efficacy and cost-effectiveness indicators.

Analytical exploratory tool for healthcare professionals to monitor cancer patients' progress.

Introduction: Cancer is a primary public concern in the European continent. Due to the large case numbers and survival rates, a significant population is living with cancer needs. Consequently, health professionals must deal with complex treatment decision-making processes.

Machine learning model from a Spanish cohort for prediction of SARS-COV-2 mortality risk and critical patients.

Patients affected by SARS-COV-2 have collapsed healthcare systems around the world. Consequently, different challenges arise regarding the prediction of hospital needs, optimization of resources, diagnostic triage tools and patient evolution, as well as tools that allow us to analyze which are the factors that determine the severity of patients. Currently, it is widely accepted that one of the problems since the pandemic appeared was to detect (i) who patients were about to need Intensive Care Unit (ICU) and (ii) who ones were about not overcome the disease.

Artificial Intelligence for Hospital Health Care: Application Cases and Answers to Challenges in European Hospitals.

The development and implementation of artificial intelligence (AI) applications in health care contexts is a concurrent research and management question. Especially for hospitals, the expectations regarding improved efficiency and effectiveness by the introduction of novel AI applications are huge. However, experiences with real-life AI use cases are still scarce.

Predicting morbidity by local similarities in multi-scale patient trajectories.

Patient Trajectories (PTs) are a method of representing the temporal evolution of patients. They can include information from different sources and be used in socio-medical or clinical domains. PTs have generally been used to generate and study the most common trajectories in, for instance, the development of a disease.

Design of 1-year mortality forecast at hospital admission: A machine learning approach.

Palliative care is referred to a set of programs for patients that suffer life-limiting illnesses. These programs aim to maximize the quality of life (QoL) for the last stage of life. They are currently based on clinical evaluation of the risk of 1-year mortality.

Machine Learning-Based Identification of Obesity from Positive and Unlabelled Electronic Health Records.

Introduction: Prevalence of overweight and obesity are increas- ing in the last decades, and with them, diseases and health conditions such as diabetes, hypertension or cardiovascular diseases. However, hos- pital databases usually do not record such conditions in adults, neither anthropomorfic measures that facilitate their identification.

Methods: We implemented a machine learning method based on PU (Positive and Unlabelled) Learning to identify obese patients without a diagnose code of obesity in the health records.

A Web-Based Telemanagement System for Patients With Complex Inflammatory Bowel Disease: Protocol for a Randomized Controlled Clinical Trial.

Background: Telemedicine has been successfully used to provide inflammatory bowel disease (IBD) patients with health care services remotely via the implementation of information and communications technology, which uses safe and feasible apps that have been well accepted by patients in remission. However, the design of telemedicine apps in this setting involves difficulties that hinder the adherence of patients to the follow-up plans and the efficacy of these systems to improve disease activity and quality of life.

Objective: This study aimed to evaluate the development of a Web platform, Telemonitoring of Crohn Disease and Ulcerative Colitis (TECCU), for remote monitoring of patients with complex IBD and the design of a clinical trial involving IBD patients who received standard care (G_Control), nurse-assisted telephone care (G_NT), or care based on distance monitoring (G_TECCU).

A Web-Based Telemanagement System for Improving Disease Activity and Quality of Life in Patients With Complex Inflammatory Bowel Disease: Pilot Randomized Controlled Trial.

Background: The reported efficacy of telemedicine in patients with inflammatory bowel disease (IBD) is inconsistent among studies, and data for complex IBD are lacking.

Objective: We aimed to evaluate the impact of remote monitoring using a Web system-Telemonitorización de la Enfermedad de Crohn y Colitis Ulcerosa or Telemonitoring of Crohn's Disease and Ulcerative Colitis (TECCU)-as compared to standard care and telephone care on health outcomes and health care in patients with complex IBD.

Methods: We performed a 3-arm randomized controlled trial.

The effect of telehealth, telephone support or usual care on quality of life, mortality and healthcare utilization in elderly high-risk patients with multiple chronic conditions. A prospective study.

Background And Objective: To assess the effect of home based telehealth or structured telephone support interventions with respect to usual care on quality of life, mortality and healthcare utilization in elderly high-risk multiple chronic condition patients.

Patients And Methods: 472 elderly high-risk patients with plurimorbidity in the region of Valencia (Spain) were recruited between June 2012 and May 2013, and followed for 12 months from recruitment. Patients were allocated to either: (a) a structured telephone intervention, a nurse-led case management program with telephone follow up every 15 days; (b) telehealth, which adds technology for remote self-management and the exchange of clinical data; or (c) usual care.

Telemedicine in the treatment of patients with inflammatory bowel disease.

Inflammatory bowel disease (IBD) is a chronic and relapsing disorder with significant medical, social and financial impacts. IBD patients require continuous follow-up, and healthcare resource use in this context increases over time. In the last decade, telemedicine has influenced the treatment of chronic diseases like IBD via the application of information and communication technologies to provide healthcare services remotely.

Telemedicine in inflammatory bowel disease: opportunities and approaches.

This review article summarizes the evidence about telemedicine applications (e.g., telemonitoring, teleconsulting, and tele-education) in the management of patients with inflammatory bowel disease (IBD), and we aim to give an overview of the acceptance and impact of these interventions on health outcomes.

Using process mining for automatic support of clinical pathways design.

The creation of tools supporting the automatization of the standardization and continuous control of healthcare processes can become a significant helping tool for clinical experts and healthcare systems willing to reduce variability in clinical practice. The reduction in the complexity of design and deployment of standard Clinical Pathways can enhance the possibilities for effective usage of computer assisted guidance systems for professionals and assure the quality of the provided care. Several technologies have been used in the past for trying to support these activities but they have not been able to generate the disruptive change required to foster the general adoption of standardization in this domain due to the high volume of work, resources, and knowledge required to adequately create practical protocols that can be used in practice.

Heart Cycle: facilitating the deployment of advanced care processes.

Current trends in health management improvement demand the standardization of care protocols to achieve better quality and efficiency. The use of Clinical Pathways is an emerging solution for that problem. However, current Clinical Pathways are big manuals written in natural language and highly affected by human subjectivity.

Caffeine does not alter RPE or pain perception during intense exercise in active women.

Attenuated perceptions of exertion and leg pain are typically reported during exercise with caffeine ingestion, yet these responses are relatively unexplored in women. The primary aim of this study was to assess the effect of caffeine on rating of perceived exertion (RPE) and pain perception during a simulated time trial. Ten active women (age=22.

Accessing to electronic medical history using a mobility intra hospital system.

The aim of this paper is to describe the solution that has been developed in Valencia Region (Spain) to provide health professionals (physicians and nurses) access to all the functionalities of a Hospital Information System (HIS) already available at fixed clients workstations. These functionalities are adapted to the care process carried out at patient bedside. In this way, professionals will have access to treatment and administration, recording of vital signs, nursing assessment, scales, care plan, extractions, medical records, progress notes so that they have all necessary information at the bedside, and record swiftly changes that occur in-situ.

e_Disease Management. A system for the management of the chronic conditions.

Disease Management (DM) is a system of coordinated healthcare intervention and communications for populations with conditions in which patient self-care efforts are significant. e-DM makes reference to processes of DM based on clinical guidelines sustained in the scientific medical evidence and supported by the intervention of Information and Telecommunication Technology (ICT) in all levels where these plans are developed. This paper discusses the design and implementation of a e-DM system which meets the requirements for the integrated chronic disease management following the recommendations of the Disease Management Association and the American Heart Association.