Making Headway for Patient-centered Care with AI
By Richard Popiel, Executive Vice President, Health Care Services of Cambia Health Solutions
There are a whole host of unanswered clinical questions – if we could answer them, it could improve patient outcomes, lower overall cost, and give people a better healthcare experience overall. With the emerging technologies of artificial intelligence (AI) and machine learning (ML), the health care industry has an opportunity to unearth actionable insights from the wealth of data that exists – and answer questions in ways that were unimaginable before AI came on the scene.
When we think about how doctors spend most of their time, what comes to mind is: talking to patients, making diagnoses, and saving lives. Unfortunately, that’s not really the case. Realistically, many health care professionals spend the majority of their time doing paperwork and other menial tasks better suited for a more algorithmic-oriented mind – today, that’s AI.
AI in health care is the use of algorithms and software to analyze complex medical data. AI and ML can help expedite the evaluation of large-scale data sources that include a person’s genomic, behavioral, and longitudinal health records and allow us to predict when medical interventions are needed and engage the person appropriately.
My work at Cambia Health Solutions instilled in me a deep commitment to transform the health care system to work for everyone’s needs. As the transition to patient-centered care permeates the industry, AI is emerging as a valuable, evidence-based approach to optimizing clinical decision making and improving the patient-provider relationship.
AI in health care can take many forms: it eases clinical decision making, is used for population and disease management, and even assists in surgery.
Studies have shown that AI can reduce the frequency of women receiving false-positive mammograms – an unfortunate reality for 50-63 percent of women who are regularly checked – by 5-10 percent. AI is also able to predict which patients are likely to end up in the ICU tomorrow, notifying physicians and allowing them to intervene and reduce preventable ICU visits. AI is better at pattern recognition than the human eye, so it is more effective at recognizing conditions like rashes and skin cancer and deciphering X-rays and biopsies. AI can also help doctors write prescriptions – notifying doctors during the prescription writing process about the patient’s health and potential adverse events, often saving them from medical complications.
"As the transition to patient-centered care permeates the industry, AI is emerging as a valuable, evidence-based approach to optimizing clinical decision making and improving the patient-provider relationship"
Overall, AI has the capacity to analyze stacks and stacks of patient data and streamline data output that would be nearly impossible for humans to achieve as quickly and accurately. For example, Cambia has developed a broad suite of algorithms that predict utilization at a granular level to enable personalized care coordination and targeting. These range from the probability of ER or in-patient utilization due to specific condition categories, or event-based models such as identifying members of our regional health plans who are likely to be re-admitted to the hospital after an inpatient stay. These predictions enable us to identify and evaluate high-risk members before a potential re-admission.
It is this drive towards actionability that led to the development of solutions to free up clinicians’ times and allow them to focus more on patients. One such solution integrates a range of clinical predictions with other contextual data and the member’s historical utilization. These capabilities enable the care management teams to deliver the right care to the right person at the right time, enabling a sharper focus on more personalized and patient-centered care.
As another example of AI tools empowering consumer experiences at Cambia, we’ve developed a chatbot that assists nurses in care management for consumers. They can ask the chatbot to find information such as in-network specialists or benefit details for a patient -- easing the patient’s health care navigation experience, often one of the most challenging dimensions of accessing care.
When we think about how AI has transformed consumer-focused industries like e-commerce, that’s the evolution we see for the health care system. The abundance of data already collected will be quickly analyzed and leveraged to improve and personalize care for consumers. AI will be a key driver in closing the gap between our idea of a doctor’s day-to-day and its reality. AI’s assistance with clinical decision-making and care administration means less time spent on paperwork and more time listening to and caring for our patients.