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

ChatGPT can Produce Medical Record Notes…

The AI model ChatGPT can write administrative medical notes up to ten times faster than doctors without compromising quality. This is according to a new study conducted by researchers at...

Can Language Models Read the Genome? Thi…

The same class of artificial intelligence that made headlines coding software and passing the bar exam has learned to read a different kind of text - the genetic code. That code...

Study Shows Human Medical Professionals …

When looking for medical information, people can use web search engines or large language models (LLMs) like ChatGPT-4 or Google Bard. However, these artificial intelligence (AI) tools have their limitations...

Bayer and Google Cloud to Accelerate Dev…

Bayer and Google Cloud announced a collaboration on the development of artificial intelligence (AI) solutions to support radiologists and ultimately better serve patients. As part of the collaboration, Bayer will...

Advancing Drug Discovery with AI: Introd…

A transformative study published in Health Data Science, a Science Partner Journal, introduces a groundbreaking end-to-end deep learning framework, known as Knowledge-Empowered Drug Discovery (KEDD), aimed at revolutionizing the field...

Shared Digital NHS Prescribing Record co…

Implementing a single shared digital prescribing record across the NHS in England could avoid nearly 1 million drug errors every year, stopping up to 16,000 fewer patients from being harmed...

Ask Chat GPT about Your Radiation Oncolo…

Cancer patients about to undergo radiation oncology treatment have lots of questions. Could ChatGPT be the best way to get answers? A new Northwestern Medicine study tested a specially designed ChatGPT...

North West Anglia Works with Clinisys to…

North West Anglia NHS Foundation Trust has replaced two, legacy laboratory information systems with a single instance of Clinisys WinPath. The trust, which serves a catchment of 800,000 patients in North...

Can AI Techniques Help Clinicians Assess…

Investigators have applied artificial intelligence (AI) techniques to gait analyses and medical records data to provide insights about individuals with leg fractures and aspects of their recovery. The study, published in...

AI Makes Retinal Imaging 100 Times Faste…

Researchers at the National Institutes of Health applied artificial intelligence (AI) to a technique that produces high-resolution images of cells in the eye. They report that with AI, imaging is...

Standing Up for Health Tech and SMEs: Sh…

AS the new chair of the health and social care council at techUK, Shane Tickell talked to Highland Marketing about his determination to support small and innovative companies, by having...

GPT-4 Matches Radiologists in Detecting …

Large language model GPT-4 matched the performance of radiologists in detecting errors in radiology reports, according to research published in Radiology, a journal of the Radiological Society of North America...