There is a lot of buzz surrounding the potential of artificial intelligence to transform care delivery. New technologies provide advanced capabilities to ensure the right patient receives the right care at the right time – while reducing the administrative burden on clinicians.
But what do doctors and clinicians think about the power of AI to change healthcare and wellness outcomes today? And what are the risks associated with the rapid adoption of AI systems?
We interviewed Dr Carrie Nelson, chief medical officer of telemedicine technology and services company Amwell, to gain insight into where AI is making a difference today in healthcare. – for patients and clinicians – as well as the risks of rapid adoption of AI in care and the keys to implementing a value-based approach.
Q. What do you see some of the most exciting AI tools coming to clinicians?
ONE. Sure, there’s good reason for the excitement.
For example, A recent survey of nurses found that documentation accounts for 15% of every 12-hour nursing shift. According to the analysis, tech-enabled activities — including the use of AI tools — have strong potential to reduce that burden by 35 percent.
By leveraging AI to help clinicians get the best out of their skill sets, we can reduce burnout and enable clinicians to focus more on the people we serve. In conversations I’ve had with doctors, many have been excited about AI’s potential to help improve work-life balance.
We are also seeing a wave of AI innovation that empowers health systems to deliver integrated care at scale to enhance accessibility and improve outcomes. At Spectrum Health, which receives more than 200,000 patients in the emergency department each year, the automated, chat-based check-in process with the patient after discharge helps capture changes in their condition sooner, so care teams can intervene quickly.
The program reduced ED visits by 5% with a $1 million savings, with a 90% patient satisfaction rate. Nurses also find their work more satisfying because they are reaching the right patient at the right time.
At the University Health Network of St. Luke, the use of automated digital behavioral health tools for employees with anxiety and depression helped 71% of participants achieve clinically significant improvement.
In addition, efficiency can be achieved from AI-powered referral management, pre-authorization requirements, and other tasks to ease the administrative burden on clinicians and staff. Automating these tasks gives clinicians more time to care for patients, allowing increased focus on what matters most and minimizing burnout.
Q. How does artificial intelligence have the potential to improve quality of care?
ONE. As the healthcare community gains experience with AI-powered automated conversations – especially for vulnerable populations – new use cases for improving quality of care are emerging. identified and utilized.
Maternal health care. Women in our country today are twice as likely to die from pregnancy complications as their mothers, especially if they have low income or live in rural areas. At Northwell Health, automated, virtual companions for pregnant women helped identify high-risk patients in 16% of interactions.
Many of these conversations happen unexpectedly based on face-to-face interactions. This empowered the organization to report cases to the clinician’s attention between visits, allowing timely professional support for these women and families.
Meanwhile, across more than 35 specialties, Northwell experienced 69% of AI-powered interactions to close the gap in care. These successes, reflected across population groups and conditions, are driving rapid adoption. The more we learn about how to improve quality of care and health outcomes through automation, the more we see the value of this approach for both common and complex disease conditions.
There are also some aspects of care that can be automated in the context of a face-to-face patient visit for better short-term and long-term outcomes. For example, it doesn’t take a doctor to know that a woman over 50 with an average risk of breast cancer needs a mammogram.
Such things can be automated. Even in more complex care situations, automation can be used to gather information regarding a patient’s complex family medical history or other disease risk factors. AI can aggregate relevant information from patients’ medical records to help doctors bridge the gap and ensure accurate medical documentation.
QWcaps are the risks associated with accelerating adoption of AI tools in healthcare?
ONE. Innovation around AI is happening very quickly, and it is entirely risky to move too quickly. For instance, it is said that ChatGPT could be used to help doctors respond to messages from patients received through a patient portal – but is that the right use of AI in healthcare? Are not? That inbox is full of challenges, we must pause and assess the risks before continuing.
We also know that inequities and biases in the age-old health care system will interject themselves and potentially be magnified by AI algorithms. This bias, including the kind of data that has and hasn’t been collected and recorded in our medical records, limits AI’s ability to improve quality of care today, especially for those vulnerable.
It’s essential that we identify those gaps and work to strengthen those data sets if AI is to reach its full potential to help healthcare workers improve quality of care.
More experience with AI-powered care models will be needed to discover what’s possible, what’s not, and how to set up the right railings. Any error in healthcare is unacceptable. While I’m optimistic, recent data suggests we still have a long way to go.
In fact, 60% of consumers say they would feel uncomfortable if a provider relied on AI to take care of them, according to one study. Pew Research Trust’s recent survey.
Q. What is the key to adopting a value-based approach to AI adoption in healthcare?
ONE. Just as a Boston hospital is hiring an AI chat engineer to design and develop AI prompts for large language models like ChatGPT, a combination of intelligent discovery and protection will be required. people to innovate AI in healthcare to deliver value.
The growth of medical knowledge has far exceeded our ability as clinicians to deliver all of it in the context of patient care. Artificial intelligence can help distill the knowledge in that vast literature to help make a complex diagnosis or prepare a treatment plan. I’d love to see us get to the point where doctors are using AI in effective ways to improve diagnostic accuracy.
Diagnostic error is a major patient safety issues. Clinicians can leverage AI tools, applied based on their knowledge of the patient and the patient’s wishes, to tailor care to each individual. optimally and precisely.
To realize our vision of what’s possible, we need to take a structured approach to generalized AI – one that doesn’t incorporate a lot of free messaging. We’ve seen interesting answers AI can provide when we engage in free-flowing conversations with bots and ask it to extrapolate meaning from those encounters.
A better approach at this point is to establish AI-assisted safeguards in managing complex conditions by ensuring chatbots that ask specific questions generate yes or no answers or prompts. patients respond with a separate data point, such as blood glucose level or weight. AI algorithms can then detect when to prompt clinicians to respond based on the data entered.
At Amwell, we’re taking this approach across a number of conditions and patient populations, and it’s making a difference in quality of care and public health.
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