Alongside the potential to remove tasks from the plate of clinical staff, artificial intelligence also enables the collection of thousands of data points a day on each patient. AI technology can recognize connections, formulate subsequent conclusions and can help advance health care practices, but only if the data is available. I attended key healthcare industry event Hlth in November 2022 and spoke to some exhibitors about the work they are doing in this field.
Data access
InterSystems Technologies, feels that “just as the public health advances of the 19th century were driven largely by investment in abundant, clean water, the digital health advances of the 21st will be driven by abundant, clean, healthy data.” They intend to make it faster and easier for data scientists to collect, integrate, and normalise the data required to build and tune accurate AI models and incorporate them into real-time business processes. Ray Deiotte, Co-Founder of Monocle Insights agrees that “everybody is struggling with access to good, consistent, clean data.” Monocle utilizes social network science, novel data engineering, and principles of behavioral economics to provide data that delivers solutions. Similarly, Alyssa Abo, VP Medical Affairs and Strategic Partnerships at Lynx MD believes that revolutionising data access is the key to revolutionising care. She says “we know that hospitals tend to be data rich but information poor. By connecting siloed data into a secure platform, we accelerate the ability of healthcare organizations to gain unique insights to drive innovation and improve patient outcomes.”
An innovative approach is offered by Gesund AI who provide tooling to allow organizations to run an algorithm against a dataset. Enes Hosgor CEO & Founder said “so far, medical AI has been designed for data scientists, by data scientists, and physicians have not been able to get involved without a computer science background. We enable anybody, regardless of their technical background, to build and run models against datasets.”
Other organizations offering data-informed healthcare solutions include Flywheel who curate, manage and organize imaging and associated data for research, Definitive Healthcare who have two million plus profiles on hospitals, physicians, health systems and other providers, and offer data analytics that accelerate growth and Health Catalyst who offer AI models to imbed into healthcare system workflows.
Decision making
AI technology can augment decision-making by uncovering clinically relevant information hidden in a massive amount of data. Merative uses AI to transform complex health information into insights that help improve outcomes and decision-making and Iodine Software uses machine learning (ML) algorithms to generate predictive insights that mimic the interpretations and determinations that a human clinician would make reviewing the same data.
Analysing data
Humans don’t have the ability to analyze and interpret all the data that is collected each day for every day for every patient, but PangaeaData.AI assist by characterizing patients based on their journey by discovering clinically actionable knowledge, which has proven to find undiagnosed, misdiagnosed and miscoded patients across rare and hard to diagnose conditions in a privacy preserving and scalable manner. ClosedLoop uses AI to look at healthcare data and predict who’s most likely to have preventable and costly conditions, events, or outcomes in the future whilst Althea uses AI to transform clinical, behavioural and social data into whole person analytics that help enable early disease detection and disease progression for identified patients who have chronic diseases and drive health equity across diverse populations.
Continuous data collection
The rapid delivery of vital data to the patient and clinical team can help ensure that care shifts from reactive to proactive. BiolntelliSense has a medical-grade rechargeable sensor that passively measures more than 20 vital signs, recording 1,440 measurements a day and, whilst it is still early in this trend, there are examples of new innovations that only exist because of continuous, personalized data collection. January AI uses the previous three days of data from a continuous glucose monitor, combined with vital-sign data, to predict glucose response in real time to individual foods, educating the patient at the point of the decision-making.
Telemedicine
It is evident that there has been a boom in telehealth in the wake of the pandemic. Kahun Medical uses AI to provide a referenced and explainable, evidence based clinical assessment. Tom Goldberg-Abramovici, VP Business Strategy, says “we have developed an engine that mimics clinical reasoning by leveraging a knowledge graph that contains over 30 million evidence based medical insights from the literature. Our engine generates clinical assessments for physicians so they can optimize their time with patients”
Realizing the potential of data can not only alleviate some of the pressures of achieving successful health outcomes, but can also enable enhanced patient experiences. Patient-centered healthcare depends on knowing what patients want and need and data holds the key to unlocking this vital information.
Issac Litman, CEO at Neteera Technologies captured the prospects of the future “we are collecting a huge amount of data, and that, along with AI will improve care, and achieve better results for everyone. What we are about to do with it is going to be mind blowing.”
Understand more about how data is being leveraged to drive innovation and help change the way clinicians and healthcare business leaders identify, manage and treat patients by attending the next annual AIMed Global Summit scheduled for June 5-7th of 2023 in San Diego. Book your place now!
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