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What Doctors and Nurses Expect of Big Data Predictive Analytics in the ICU

The Intensive Care Units treat patients with serious, life-threatening illnesses and injuries that require highly specialized care, precise medications and constant monitoring with high-tech equipment.

What Doctors and Nurses Expect of Big Data Predictive Analytics in the ICU

Clinical scenario in intensive care units

The Intensive Care Unit (ICU) is the physical area of the hospital where advanced electromedical equipment with sophisticated techniques to temporarily substitute functions in organ failure, and specially trained medical and nursing staff, enable the practice of Intensive Care Medicine. The latter is defined as the branch of medicine concerned with the diagnosis and care of patients with real or potential life- threatening conditions requiring invasive monitoring (clinical or instrumental) or treatment.

An avalanche of data that helps to paralyze many decisions

The Intensive Care Units treat patients with serious, life-threatening illnesses and injuries that require highly specialized care, precise medications and constant monitoring with high-tech equipment. However the large volumes of data and biosignals being generated by this equipment overwhelm doctors and nurses, and do little to help them set priorities for the activities required in these units.

Reliable data that can generate clinical evidence in the ICU and knowledge for accurate decision-making in this environment is complicated due to the avalanche of data from many devices, the high number of biosignals per minute and the clinical variability of the patients, as well as the difficulty of the medical personnel to enter data at critical moments, when decisions and events happen at a fast pace.

An ICU patient is surrounded by countless gadgets that generate data that is displayed on a monitor, but there is nothing that integrates and manages all of these bio-signals, making it nearly impossible to see what was happening an hour before, which is especially important in these units.

There really is a lot of data available, but:

It is not organized or interconnected.
It is not ordered in terms of clinical value.
Although there are products on the market that can collect and manage data, for the most part they collect useful data for hospital managers and are not user-friendly enough for doctors and nurses.

What is the solution?

We health professionals need to have tools that help us make clinical decisions with greater accuracy and patient safety, especially in complex environments such as the ICU.

More than simple data repositories, doctors and nurses need intelligent solutions that can integrate information from biodevices and EHRs, facilitate data entry to increase the reliability of information in these circumstances (in non-automated input), and return the results as applicable knowledge based on scientific evidence and observation to increase the efficiency of clinical practice.

A useful tool should:

  • Base itself on the real experience of doctors and nurses.
  • Organize and process the data produced by the ICU, returning it as useful information for healthcare workers.
  • Be user-friendly, usable and easy to understand.
  • Provide accurate information to improve the quality, safety and efficiency of clinical events.
  • Have added intelligence in the system to help doctors avoid variability in the practice and make sound decisions.
  • Be able to turn information into knowledge to support better decision-making.
  • Distinguish between effectiveness and futility.
  • Develop new algorithms, clinical pathways and protocols.
  • Generate new knowledge that we can offer to the scientific community.

ehCOS SmartICU: An advanced analytics solution for intelligent decision-making

ehCOS SmartICU is designed as a user-friendly tool for doctors and nurses in the intensive care units to control and monitor patients in a safer and more comprehensive way.

In order to increase the information about the patients admitted to the ICU, as well as their safety, the tool facilitates data entry (also by voice), as well as automatic integration of the information from the EHRs and technological devices or biosignals.

This is expected to reduce the level of underreporting to a minimum in the ICU (which is currently above 30% due to the difficulties associated with recording data and events in critical situations) by providing all the information on the time sequence of the events and using “alerts” to warn medical personnel of possible situations that could otherwise end up as “alarms”.

Patient safety is a priority; hence avoiding preventable adverse effects in patients is vital to improving the quality of care and reducing morbidity and mortality.

The use of analytical and predictive models in intensive care is something new that will allow healthcare professionals to predict what can happen to a patient in a given situation before it occurs, thanks to the advanced and secure analysis of the existing data. At the same time, it will facilitate the most useful and timely treatment decision-making, transforming information into actionable knowledge based on scientific evidence and observation; knowledge that is difficult to obtain without the aid of technology, since the human mind is unable of quickly and accurately processing that much information.

10 Key benefits of ehCOS SmartICU for intensive care units

  1. Intuitive tool that collects, organizes and structures the data in a fast and easy way.
  2. 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.
  3. Event management system that lets you instantly assess the patient’s medical condition and take immediate action.
  4. 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.
  5. Techniques that discover relationships between vital signs and treatments through cross-validation, drawing conclusions and knowledge to design and predict future scenarios in the care of patients in intensive care, critical care and reanimation units.
  6. Implementation of predictive models to detect behavioral patterns to estimate the response to care and the various treatments used.
  7. Improvement of care protocols to maximize results and optimize resources in the ICU.
  8. 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.
  9. Cost-benefit analysis.
  10. Comparison of techniques in relation to costs, repayment terms, effects, etc.

    Thanks for your interest. We will get in touch with you soon.

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