smart icu project. dr.francisco murillo_english version

Smart ICU Project Dr. Francisco Murillo Cabezas.Intensive Care CMU.Virgen del Rocio University Hospital. University of Seville.

Clinical scenario in intensive care units

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Clinical scenario in Intensive CareUnits

Critically ill patients.

Numerous professionals

in limited space.

Stressful environment.

Numerous and sophisticated

monitoring and life support

devices generating

multiple streaming.

Need for hard data to make safe

and quick decisions.

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A very complex and heterogeneous enviroment due to:

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The data problem

The dataproblem

An avalanche of data that helps to paralyze our decisions.

Dr. Francisco Murillo

“ ”

Why did we need to develop SMART ICU?

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There are some products that are

able to collect and manage

data.

Most products are exclusively

aimed at collecting useful data for hospital management.

Most of these are not user-

friendly enough for doctors and

nurses.

Because the tool we needed was not available on the market

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We wanted something more.

In short, we needed to refine our clinical practice.

A system with added intelligence to help doctors avoid variability in the practice and make sound decisions.








This data come from many varied sources.

Overall, they are not not well- organized and lack proper connection among them.

They are not ordered in terms of clinical value.

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In reality we have a lot of data available to us, however:






What should we ask of a project of this type?


A user-friendly tool that can collect the enormous volumes of data generated in the UCI.

Accurate information to improve the quality, safety and efficiency of clinical events.


To organize and processe data and return it as useful information for doctors and nurses.








To turn information into knowledge to support decision-making.

To provide knowledge to help distinguish effectiveness from futility.










To develop new algorithms, clinical pathways and protocols.

To generate new knowledge that we can offer to the scientific community.

To base itself on the real experience of doctors and nurses and on Big Data Analytics.






Project objectives and motivation


Project objectives and motivation


The aim of the project is to develop a predictive system for personalized clinical decision support for acute patients in the ICUs that uses selective learning from Big Data Analytics.

An intensive care unit (ICU) is a special department of a hospital or healthcare facility that provides intensive care treatement.






Benefits

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01 02 03 04The modules in charge of collecting and presenting information use agile interfaces, graphs and summary structures that make them easier to understand. The large volume of data collected in these areas (clinical care, biosignals...) makes for complex and painstaking management and interpretation in the absence of an intuitive tool to collect, organize and structure the data in an easy and agile way.

Adopts specific tools to assist in the management of the processes of intensive care patients , generating a more efficient distribution of the health resources used.

Includes an event management system will allow the instant knowledge of the patient’s health status, allowing immediate action to significant changes that require require attention from professionals.

Automated and standardized processes for capturing patient data from biomedical devices, Electronic Health Records, laboratory, etc. to reduce machining time and the risk of error.

05 Discovers relationships between vital signs and treatments through cross-validation techniques, drawing conclusions and knowledge to design and predict future scenarios in the care of patients in intensive care, critical care and reanimation units.

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06 07 08 09Implements predictive models that detect behavioral patterns to estimate the response to the care and the various treatments used.

Improvements in treatment protocols to maximize health outcomes and optimize resources.

Measure the effectiveness of certain protocols, therapies or techniques applied in a coordinated and standardized manner by the platform, allowing comparisons and detection of side effects to consider proactively.

Evaluates the cost-benefit, and even compares different techniques related to costs, repayment terms, effects, etc.

System components

Data sources, PoC details and Clinical Experts involved

Virgen del RocioUniversity Hospital (Spain)

• Reference population: over 800,000 inhabitants of Seville

• Referral hospital for the entire Region of Andalusia.

• More than 1,000 hospital beds.

• 35 doctors for a total of 70 ICU beds.

• More than 3,000 patients admitted to the ICU every year.

• 5 ICU R&D groups.

• It is the largest hospital in Spain.

smart icu project. dr.francisco murillo_english version

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