Trends, Insights & Analysis

How Artificial Intelligence in Healthcare is Helping Physicians Better Prescribe Treatments

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The last few years have seen significant growth in the use of artificial intelligence (AI) in healthcare. IBM’s Watson is being deployed to develop better treatment options for cancer patients, for example, and Google’s Deep Mind Health technology is addressing macular degeneration in aging eyes. The rapid growth of this once futuristic field is bringing physicians new systems and resources for treating patients and prescribing medications, all of which have the potential to significantly increase the quality and speed of getting patients access to the medication they need.

Machine Learning and Medicine

While some physicians remain hesitant about supplementing their expertise with technology solutions, a study by TechEmergence found that over 50% of respondents believe that “AI will be ubiquitous in healthcare by 2025.” And it makes sense why. The healthcare industry collects a vast amount of data, from R&D, to the information physicians gather about their patients at each visit, to provider prescribing.

While it’s impossible for busy physicians to consider the sheer volume of data available when treating patients, with machine learning, the more data the better. AI technology uses advanced algorithms to analyze information and provide solutions. Using AI in healthcare enables the sorting and parsing of data to understand symptoms and provide suggested treatment options. The more data points the technology has to work with, such as patient history, past treatment options, and available medications, the better conclusions it can make. By analyzing possibilities and learning from successes, AI in healthcare leads to refined and specialized treatment options drawn from disparate data points.

In the case of the Human Diagnosis Project (Human DX), an online system that combines collective human intelligence with machine learning, AI is already having a significant impact on patient care,. The system allows primary care physicians to plug into a network of more than 6,000 providers and specialists to solve tricky cases on the spot, rather than issuing referrals. A physician can enter symptoms, medical history, test results and imaging into the platform, which uses machine learning technology to consider the data, send the case to specialists who offer diagnoses, and then sort and combine each curated finding to create a single diagnosis. Crowdsourcing medical advice through the platform allows primary care physicians to confidently order tests and prescribe medications patients would typically need to be referred to a specialist to receive.

The American Medical Association, along with other health groups, recently teamed up with Human DX and will encourage its own large provider membership to volunteer on the project, bringing Human DX closer to its goal of providing more accurate, affordable and accessible care around the world. Platforms like Human DX are using AI in healthcare to improve patient access to medication by allowing physicians to access the industry’s large pool of data and collective knowledge, order tests, and prescribe medications.

The Future of AI in Healthcare and Prescribing Medication

The number and scope of AI healthcare platforms is continuing to grow, but one of the biggest remaining obstacles is how to effectively bring together all the different available data sets to provide better analysis and treatment—all while protecting patient data. Human DX, for example, is working to build “a common frame of reference for all stakeholders in the health system,” which would provide “patients, family members, physicians, hospitals, and others a shared path to helping any person.” Such integration offers increasing opportunities for patients to receive tailored care with prescriptions that best meet their needs.

Researchers at the Massachusetts Institute of Technology (MIT) are developing Intelligent Electronic Health Records, which will feature built-in medical diagnoses, such as offering treatment suggestions, reviewing patient history, and making documentation faster through the incorporation of machine learning and AI.

This kind of tool helps physicians to prescribe the ideal medication for each patient, and, as AI in healthcare progresses, will even allow them to create personalized doses for each patient based on past history and how people of different ages, weight or other demographics responded to certain treatment plans. Research from Indiana University found that physicians using AI to predict treatment outcomes could “reduce health care costs by over 50 percent while also improving patient outcomes by nearly 50 percent.”

The Influence of AI on Patient Access

The benefit of using AI in healthcare is that it can begin to make full use of the data sources available to the industry, in turn allowing physicians, consumers, manufacturers, insurers, and regulators to make better decisions and reach as many people as possible with individualized and effective treatment options. Already, large pharmaceutical manufacturers are using machine learning to improve drug discovery, such as the partnership between Merck and Atomwise, a company that developed the first deep learning neural network for structure-based drug design and discovery.

If the data resources of the industry can be brought together, patient access can be integrated into the larger healthcare process. Pharmaceutical manufacturers will have solid data on which to build the case for getting specific medicines to the people who need them most. When deciding what medicine is best for certain patients, the data gathered from R&D to clinical trials as well as real-world patient access and engagement programs can help match each medicine to a patient’s symptoms and biology.

Technology’s progression is creating significant opportunities for greater transparency in and improvements to the healthcare system. At Truveris, we’re working to help our clients navigate the complexity of the system and create solutions to the rising cost of medication by combining human expertise with technology. We’re excited about the potential of data-driven innovation, such as AI in healthcare, to ensure patients have access to the medications they need.

Topics: Trends, Insights & Analysis

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Truveris Team