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How artificial intelligence is revolutionizing decision-making in health care

Understanding how AI can help providers — as well as its limitations and what checks can mitigate its downsides — will help foster trust and confidence in it.

Paola Bianchi Delp: ©CareNu

Paola Bianchi Delp: ©CareNu

Many health care professionals understand the transformative potential of artificial intelligence (AI) but remain wary of using it in their own clinical practice. In one recent study, 83% of doctors said they believed AI would eventually help health providers, but 70% said they were concerned about the technology’s use during the diagnosis process. While concerns about its application are valid, the potential of AI to enhance patient outcomes makes cautious optimism from providers warranted.

Artificial intelligence technology can dramatically improve patient health and is already reshaping the health care landscape. Understanding how AI can help providers — as well as its limitations and what checks can mitigate its downsides — will help foster trust and confidence in it.

While the public conversation around artificial intelligence is relatively new, AI already gives doctors, nurses and other health care professionals vital information. While artificial intelligence shouldn’t make final decisions about patient treatment or replace human judgment, it can be a powerful tool that augments a doctor or nurse’s clinical decision-making and speeds up administrative processes in their office. By detecting patterns across wide populations, AI allows providers to act proactively rather than reactively and personalize care for each individual, boosting health across the board.

With AI deployment, gone are the days of one-size-fits-all approaches to health care. Predictive models can alert medical professionals of high-risk situations based on individual health data, allowing for proactive intervention before symptoms develop. Data analytics and algorithmic projections, powered by AI, can map out the likely health care future for every American, allowing doctors to evaluate available treatment options and draft informed care plans tailored to each individual.

It also enables doctors to compare a patient’s health data with their entire patient population or a regional population, identifying patterns that could otherwise go unnoticed. And since doctors have only so many hours in the day, AI helps prioritize interventions, allowing providers to focus on their most urgent cases.

Beyond direct patient interactions, AI offers significant benefits to the broader health care ecosystem, where it contributes to research, population health management and enhancing patient experience and outcomes. Countless factors impact our health: genetics, diet, age, lifestyle habits, the environment we live in, social factors like family income, education, food security and many more. Artificial intelligence can help researchers detect patterns to understand risk factors for diseases. So many variables are involved that technological tools can help healthcare professionals work efficiently, using algorithms to find trends in data banks that shed light on the development of diseases.

Take the example of mental health treatment, which shows how artificial intelligence can boost health in a variety of ways. AI can track patient data from many sources – medical records, transcripts of patient discussions, even wearable devices – and can quickly analyze it, identifying relevant patterns that reveal mental illness indicators that professionals can screen for. Such tools require no action from the patient – but could prevent life-threatening crises.

AI can support behavioral health providers in other ways too: one recent study used AI to analyze 20 million text conversations of counseling sessions, successfully predicting clinical outcomes and patient satisfaction. The study was able to examine the effectiveness of patient/clinician interactions, finding a direct correlation between empathetic counseling, enhanced clinical outcomes and reported patient satisfaction.

AI has already helped solve long standing health care problems. In 2010 the Agency for Healthcare Research and Quality found that many hospitalizations involved preventable conditions – but there was no clear solution. Today, artificial intelligence has given us the tools to address it. AI suggests interventions to doctors and caregivers that decrease the likelihood of unnecessary hospitalizations.

What’s more, machine-learning models continuously improve over time. As more data is included and a wider range of scenarios are accounted for, algorithms are refined and models get better at predicting outcomes and delivering increasingly personalized health insights.

While artificial intelligence has the potential to transform health care in America, giving these algorithms access to personal health data raises valid concerns over privacy and data security. Who should be allowed to view such data? Under what conditions should access be granted?

Fortunately, new encryption technologies, strict access controls and anonymization techniques can make sure data doesn’t get into the wrong hands. Requiring consent to share data also empowers everyday Americans and the health care providers they trust. By addressing concerns head-on, providers can strike a balance between the many benefits afforded by AI technology and the legitimate concerns surrounding data privacy.

At the same time, AI can help end the harmful information silos that fragment the health care system and doesn’t allow providers to view a person’s full health history, making it hard for them to make informed decisions.

Artificial intelligence has become a ubiquitous part of day-to-day life. While some health care professionals are skeptical about implementing AI into their clinical practice, the transformative results it brings are worth it. At the end of the day, doctors want to make the most informed decisions possible about their patients. AI allows them to do so.

Paola Bianchi Delp is the President of CareNu, a data-forward health care organization using predictive analytics to revolutionize care for the medically vulnerable and their families.

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