A Decision Support System Incorporating a Validated Patient-specific, Multi-scale Balance Hyper Model Towards Early Diagnostic Evaluation and Efficient Management Plan Formulation of Balance Disorders (EMBalance)
A Decision Support System Incorporating a Validated Patient-specific, Multi-scale Balance Hyper Model Towards Early Diagnostic Evaluation and Efficient Management Plan Formulation of Balance Disorders (EMBalance)
Balance is crucial for an individual's mobility and independence. Human balance is achieved and maintained by a complex set of sensorimotor systems that include sensory input from vision, proprioception and the vestibular system (motion, equilibrium, spatial orientation). This information is then integrated by the brain. This complexity leads to undiagnosed or mistreated patients with balance disorders for long period which can affect their daily activities.
The EMBalance project is a research project funded by the European Union, involving 10 universities across Europe. Its aim is to create a Decision Support System (DSS) to support doctors in diagnosing and treating balance disorders. It will be available to primary and secondary care doctors of different specialties, levels of training and in different parts of the country.
The DSS will:
The EMBalance randomised clinical trial (RCT) is a proof-of-concept, multicentre, single-blind, and parallel group study, conducted in Belgium, Germany, Greece and United Kingdom. At present, the question that this study aims to answer is whether the algorithms developed for the EMBalance Platform will yield meaningful information and how these algorithms and platform can be improved, performing an offline comparison of the classical diagnostic approach and the outcome of the EMBalance platform, without any consequence for the patient.
Patients who present with balance related symptoms at primary care will be randomised to either intervention group (non-specialist doctor +DSS) or control group (non-specialist doctor -DSS). An overseeing expert will then confirm the diagnosis and management decisions made by the non-specialist doctors in order to determine whether the use of the DSS can help them in a more precise assessment.
Balance is crucial for an individual's mobility and independence. Dizziness and imbalance symptoms are one of the most common reasons for visits to a doctor and affect up to 30-40% of the population by 60 years of age. The healthcare service provision to address vestibular pathology remains inadequate and is regarded as low priority. The complexity of balance control mechanisms, the lack of medical expertise, and the absence of specialised equipment can be contributory factors to the mismanagement of patients suffering balance disorders. However, the mean number for patient visits to their Health Care providers required to establish a correct diagnosis and start appropriate treatment, both in the US and the UK, is 4.5. The overall socio-economic impact of balance disorders on the affected individual, patient's families as well as the burden on society and the health services is considerable.
Advances in computer science and artificial intelligence have allowed the development of computer systems that support clinical diagnosis or therapeutic and treatment decisions based on individualised patient data. However, a review of existing Decision Support Systems used in Medicine demonstrated there are not many successful integrated software systems or standalone tools that address the early diagnosis and effective management of balance disorders.
All this said, the EMBalance DSS has been developed as a supplementary and supportive tool for non-expert physicians faced with the challenge of addressing vestibular disorders.
The current study will assess the effectiveness of the EMBalance Decision Support System (DSS) for diagnosis and management of balance disorders in a feasibility/proof of concept study. Patients who present with balance related symptoms (specifically vertigo or dizziness exacerbated by head movements) in primary care, will be seen by a non-specialist doctor either with or without the support of the DSS, on a ratio 1:1.
Non-specialist doctors in each participating country are defined as follow:
Overseeing experts in each participating country are defined as follow:
It is anticipated 100 participants will be recruited to each of the two treatment groups, giving a total of 200 participants across Europe. Each participating site in Greece, Belgium, Germany and United Kingdom will recruit 50 patients. Allocation will be performed based on randomisation tables that are produced in advance for each centre.
Statistical data analysis will be performed by the National and Kapodistrian University of Athens. The statistical analysis has been developed by the National and Kapodistrian University of Athens and reviewed by the Institute of Communication and Computer Science (Greece).
Quality and ethical assurance are supervised by the Trial Steering Committee (TSC) and Trial Management Group (TMG)
Inclusion Criteria:
Exclusion Criteria: