As artificial intelligence develops, the nuances of its specific use for industries is developing.
ServiceNow is working to digitise and automise siloed processes to dramatically improve experiences, and the company’s Chief Transformation Officer, Manish Shah, believes that the application of AI in healthcare could be transformative for the industry.
With extensive global management experience in IT, Shah helps ServiceNow customers drive digital transformation to create sustainable value and enable organisational change management with the Now Platform. Prior to joining ServiceNow, he held leadership positions at Community Health System, Advocate Aurora Health Care, Information Resources, Inc. (IRI), and Caremark.
We sat down with Shah to discuss the opportunities that AI opens up to bettering patient wellbeing, as well as wider healthcare implications concerning AI uptake.
How can AI deliver intelligence to improve patient care?
It is tough to imagine a more promising area for AI application than healthcare. Neural networks are using AI to generate healthcare advances, from disease diagnosis to new drug development and treatment methods.
During the past few years, we have seen how a combination of computer science and machine learning advancements can create neural networks that mimic the human brain. They can classify and cluster data at a high velocity, with analysis taking minutes versus the hours it takes when performed by humans.
With the introduction of GenAI, we can scale these advanced capabilities to deliver a smoother, more integrated patient and provider experience that dramatically improves care.
Navigating patients through the healthcare system can be riddled with variations and inconsistent experiences. A patient journey—doctor visits, medication, diagnostic results, specialty physician, hospital visits—generates a large digital footprint, often in siloed systems that are not easy to decipher quickly to make informed care decisions.
Healthcare has got good at providing detection and diagnostics. During hospital encounters patients are hooked up to individual functioning devices that generate digital signals but often do not talk to each other or to their Electronic Health Record systems.
When a specific threshold is crossed, each device sets off a signal or alert at the nurse’s station. The nurse must walk into the patient’s room to figure out why the alert went off. Around 99% of these alerts are false positives that require significant human intervention, such as the leads coming off or the patient moving in bed.
The excitement around Gen AI is its ability to deliver more precise, targeted intelligence using large language models that take in large volumes of data and then simulates all the possibilities based on algorithms and history.
With Gen AI, we can go well beyond sharing individual data points. We can assimilate and integrate disparate signals into an intelligent layer that merges the data into a holistic picture across devices and inputs. AI can take individual patient neural sensory networks and bring all the data into one intelligent layer, making it easier for caregivers to respond to the alerts and signals that matter the most. Gen AI helps identify the right resource to oversee patient care and take action at the right time.
Why is AI healthcare model governance key?
In the last decade, we’ve seen other game-changing technologies based on AI: digital cameras that use laser ambient light movement to inspect and monitor patients in their rooms. No human being can process all the signals being read by cameras better than an AI.
But the real promise of AI technology lies in providing the intelligence to deliver a safer, higher quality of patient care. Technology is advancing in real time, delivering visual information that is like what a human sees when they walk into a patient's room. Technology can create a more productive, effective workforce that knows precisely which situations require human intervention and can communicate what is needed in a timely manner.
Gen AI is modelling the human brain but processing significantly greater volumes of data. However, while the human brain naturally understands some fundamental basic concepts like morals and empathy, AI does not.
As an organisation, it is important to think about building the basic core elements of ethics, governance, and morals guard rails into AI models. Modelling best practices must align with basic principles for your organisation, such as delivering the best patient care. In the future, a regulatory body may dictate what those principles are, but as healthcare professionals we need to make sure they are part of AI policies from day one.
Now is the time to apply AI to deliver a smoother, more integrated patient and provider experience. It can play a significant role in building more intelligent neural networks that steer a more proactive diagnosis and treatment.
But with great opportunity comes big responsibility. The big responsibility is building your organisational beliefs about morals and ethics into the AI models as guardrails. The resulting improvement in patient care will be worth it.
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