New FP7 eHealth Project - COMOESTAS

COMOESTAS aims to develop an innovative ICT system that allows patients with Medication Overuse Headache (MOH), a common condition and a major cause of disability, to receive continuous and personalised treatment. The system will be based on an advanced Alerting and Decision Support System that follows patients from the diagnosis and supports the physician in managing the therapy, controlling relevant events impacting on patient safety.

Medication Overuse Headache (MOH) results from the chronicisation of primary forms of headaches, as a consequence of the progressive increase in the intake of symptomatic drugs. The first choice treatment for MOH is the withdrawal of the overused medication(s) (detoxification), which is preferentially done by hospitalising the patients. Even if most patients improve as a result of detoxification, up to 45% of patients relapse, reverting to the overuse of symptomatic drugs.

Paper diaries and calendars for recording headache attacks have long been used in the clinical practice for the management of headache patients. Isolated attempts to electronically record headache attacks have also been performed, based on the use of single common files.

At present, however, there is no scientifically validated informative tool that could manage patient's treatment, from the first observation to the whole follow-up. The availability of such a tool would grant an innovative approach to MOH.

Objectives of the project and project description
The general objective of the COMOESTAS project is to improve and integrate the management of MOH with an innovative electronic tool that makes the patient himself a key node in the treatment process. The new system, will be based on a complex informative system called Interactive Electronic Patient Record (IEPR) and will constitute an "all-inone" solution that will allow constant monitoring of the clinical condition of the patient by the doctor and provide a system of alerts and warnings should selected parameters exceed given thresholds. The system will also be designed in order to improve the patientdoctor communication.

Expected Results and Impacts
The constant monitoring by means of the electronic diary and programmed or alertprompted follow-up visits permit and favour a better interaction between patient and physician in order to ameliorate the management of these patients after the withdrawal. Furthermore, this will increase patient safety by optimising medical interventions, preventing errors and reducing drug-induced side effects (i.e. gastritis, hypertension). As a consequence, direct (consultations, hospitalisations, etc.) and indirect (i.e. linked to the disability and complications caused by the disease) costs provoked by the condition will be reduced.

Work in progress

  • The kick-off meeting took place in Pavia, on February 14-16
  • Indicators, clinical protocol and clinical tools have been devised, and will be finalised in April
  • The beta version of the IEPR system will be ready for pilot testing by the end of May
  • Clinical centres in Argentina and Chile are collecting data on the epidemiological impact of MOH in Latin America

For further information, please visit:
http://www.comoestas-project.eu

Related article:

Most Popular Now

AI Tool Offers Deep Insight into the Imm…

Researchers explore the human immune system by looking at the active components, namely the various genes and cells involved. But there is a broad range of these, and observations necessarily...

Do Fitness Apps do More Harm than Good?

A study published in the British Journal of Health Psychology reveals the negative behavioral and psychological consequences of commercial fitness apps reported by users on social media. These impacts may...

AI Tool Beats Humans at Detecting Parasi…

Scientists at ARUP Laboratories have developed an artificial intelligence (AI) tool that detects intestinal parasites in stool samples more quickly and accurately than traditional methods, potentially transforming how labs diagnose...

Making Cancer Vaccines More Personal

In a new study, University of Arizona researchers created a model for cutaneous squamous cell carcinoma, a type of skin cancer, and identified two mutated tumor proteins, or neoantigens, that...

AI System Finds Crucial Clues for Diagno…

Doctors often must make critical decisions in minutes, relying on incomplete information. While electronic health records contain vast amounts of patient data, much of it remains difficult to interpret quickly...

A New AI Model Improves the Prediction o…

Breast cancer is the most commonly diagnosed form of cancer in the world among women, with more than 2.3 million cases a year, and continues to be one of the...

AI, Health, and Health Care Today and To…

Artificial intelligence (AI) carries promise and uncertainty for clinicians, patients, and health systems. This JAMA Summit Report presents expert perspectives on the opportunities, risks, and challenges of AI in health...

Improved Cough-Detection Tech can Help w…

Researchers have improved the ability of wearable health devices to accurately detect when a patient is coughing, making it easier to monitor chronic health conditions and predict health risks such...

AI can Better Predict Future Risk for He…

A landmark study led by University' experts has shown that artificial intelligence can better predict how doctors should treat patients following a heart attack. The study, conducted by an international...

Multimodal AI Poised to Revolutionize Ca…

Although artificial intelligence (AI) has already shown promise in cardiovascular medicine, most existing tools analyze only one type of data - such as electrocardiograms or cardiac images - limiting their...

New AI Tool Makes Medical Imaging Proces…

When doctors analyze a medical scan of an organ or area in the body, each part of the image has to be assigned an anatomical label. If the brain is...