The Rise of Artificial Intelligence in Healthcare

Key takeaways:

• The public has been concerned about the collection and potential misuse of personal data for more than a decade, a conversation amplified by the increased adoption of artificial intelligence (AI).
• AI tools in healthcare – such as Premier’s PINC AI^™ solutions – utilize standardized data, support quality and transparency, drive innovation and empower providers and patients.
• In addition to our AI-enabled solutions, Premier supports policies that enhance the creation of AI tools that support providers, patient-centered care and drive operational and clinical excellence.

For years, stakeholders have been concerned about the potential misuse of personal data. People were uncomfortable with the various ways that companies could track their movements online or their potential to gather credit card numbers, addresses and other critical information. Concerns like these led to the passage of measures in the U.S. and Europe guaranteeing internet users some level of control over their personal data and images.

But as technology evolves, more and more companies are embedding artificial intelligence (AI) into products and processes, shifting the concern to potential risk for bad or biased decisions by algorithms — particularly the complex, evolving kind that can help inform clinical decisions made by providers and health plans.

A recent Bain report survey revealed that 75 percent of health system executives believe that generative AI will have a transformative impact on the delivery of healthcare. However, the report found that only 6 percent have worked to establish a generative AI strategy. AI is poised to help reshape future healthcare operations, cost, and value, and it’s crucial that health system leaders evaluate the opportunities and hurdles that new technology presents or risk facing a competitive disadvantage.

Premier strives to work with partners to facilitate the use of AI in healthcare in a way that builds trust and transparency in AI systems, empowers patients and providers, and drives innovation and competition. While Premier believes that AI can play a critical role in advancing healthcare and spurring innovation, Premier does not believe that AI can or should replace the practice of medicine.

Below are five ways that Premier’s PINC AI^™ solutions support AI in healthcare to help empower providers; enable supply chain visibility; increase the use of high-quality, unbiased data; support innovation in clinical trials and help advance health equity.

1. Empowering High-Quality Patient Care

Of the many use cases for AI in healthcare, the biggest drivers center around empowering providers to care for patients. In the near term, hospital systems have identified analysis of patient data and workflow optimization as high priorities. Over the coming years, providers remain the focus as high-priority use cases shift towards clinical decision support (CDS) and diagnostic or treatment recommendations.¹

To unlock the potential of AI, Premier recognizes that providers need tools that are user-friendly, save time and create efficiencies, so they can focus on providing optimal patient care. PINC AI^™ Stanson tools help reduce clinician burnout, enhance the clinician experience and increase productivity.

The PINC AI^™ Stanson tools work to reduce low-value and unnecessary care by delivering real-time CDS alerts and relevant analytics to guide physician decisions, improve patient outcomes, reduce waste and safely lower healthcare costs.

The PINC AI^™ Stanson CDS is an AI solution that supports better clinical decisions. The solution relies on machine learning (ML) to help hospitals and health systems streamline alerts so that providers receive them for the right patient at the point of care. These alerts are driven by evidence-based, clinician-designed logic, ensuring that an alert will only be triggered if the patient meets a specific profile and only provides recommendations that are relevant to the clinician who has final decision-making authority.

2. Enabling Healthcare Supply Chain Visibility

Historically, hospitals lacked the ability to predict when a product might become short.

Longitudinal visibility across the supply chain, where providers can see demand signals, point-of-use information and supplier resiliency metrics, is vital to accurately manage forecasting and predict supply shortages.

Predictive models driven by enterprise resource planning (ERP) and organization-specific data, combined with ML, can help provide this much-needed longitudinal visibility, enabling healthcare leaders to anticipate and preempt problems rather than continuing to react to them.

Enter the award-winning PINC AI^™ Supply Disruption Manager, which is aiding hospitals and health systems in predicting demand surges and product shortages far in advance with over 90 percent accuracy – while extending the efficiency of scarce workforce resources.

The solution can afford supply chain and clinical staff reduced time to manage supply stock issues, reduced cost due to changing alternatives and reduced canceled procedures due to inadequate supplies.

Together with our customers, Premier continues to provide innovative solutions for resiliency and risk mitigation, supply continuity, competitive pricing and quality enhancement to help ensure access to high-quality products providers need to care for patients.

3. Utilizing Robust, Real-World Data

The Healthcare industry in general is continuously seeking high-quality data but the data needs to be standardized, connected, representative of large diverse communities and reflect the state of clinical practice in the general population.

The PINC AI™ Healthcare Database (PHD) is a comprehensive electronic healthcare data repository that has been a valuable resource for the pharmaceutical and device industries, academia, federal and national healthcare agencies including the Centers for Disease Control and Prevention, Centers for Medicare Services,² Food and Drug Administration,³ and National Institutes of Health, as well as for Premier’s member hospitals and health systems to improve healthcare delivery, quality and cost reduction. The PHD provides a unique source of real-world data (RWD) to conduct evidence- and population-based analyses of drugs, devices, other treatments, disease states, epidemiology, resource utilization, healthcare economics and clinical outcomes. Since data accrues from a large diverse population, rare outcomes and long-term effects can be studied, and data collection bias is negated.

With new research highlighting how ChatGPT 3.5 and 4 occasionally cite fake research articles, accurate and reliable data is more important than ever in healthcare. That’s why healthcare AI trained directly on RWD from actual hospital admissions, like the PHD, adds unique value for providers, researchers, and patients.

4. Supporting Innovation in Clinical Trials

AI has begun to play a big part in some of the functions surrounding clinical trials. RWD from the PHD and AI tools such as ML and natural language processing (NLP) can help providers enhance clinical trial design, feasibility and execution and improve life cycle management.

In the past, traditional clinical trial sites were selected solely based on experience and relationships with Principal Investigators (PI) and/or at the site level. Data and innovative solutions, including NLP, are changing that by estimating eligible patient population volumes with a new level of granularity and efficiency previously unattainable when screening sites to match trial protocols. These technologies allow clinical trial developers to assess the suitability of sites on a larger scale based on appropriate patient populations, investigator availability, experience in therapeutic area and historical performance metrics. Based on this assessment, sites that have the best chance to outperform enrollment expectations can be selected.

Tech-enabled RWD allows clinical trial staff to rapidly, accurately and at scale screen for potential patients instead of needing to manually identify patients who met complex inclusion/exclusion (I/E) criteria. With tech-enabled RWD and real-world evidence (RWE), clinical research timelines can be compressed, and solutions have the potential to be delivered at reduced costs thereby increasing patient access. Tech-enabled RWD/RWE can also increase diversity in clinical trials by helping identify barriers to enrollment and informing strategies to reach underrepresented populations.

5. Advancing Health Equity

The White House’s Office of Science and Technology Policy issued a blueprint for an AI Bill of Rights which highlighted the concern that some automated systems may unfairly impact certain populations.

PINC AI^™ data is perfectly suited for efforts aimed at advancing health equity because it includes:

• More than 20 years’ worth of data from 45 percent of U.S. hospital discharges, 812 million hospital outpatient and clinic encounters and 131 million office visits.
• Data tokenization that allows linkage with very specialized data sources.
• Data that spans the continuum of care, medication/device SKU-level utilization and different types of coverage from cash and commercial payer to Medicare and Medicaid.

Public health and clinical researchers are continuously seeking more information about social drivers of health (SDOH), including their impact on health outcomes, costs and healthcare resource utilization. In fact, the Centers for Medicare and Medicaid Services (CMS) will start requiring providers to screen and report on SDOH starting in 2024.⁴ Information that must be collected includes data on food insecurity, housing status, transportation needs, financial challenges and interpersonal safety concerns.

With this information, researchers and providers are better able to analyze unjust disparities and support communities and health systems to develop solutions, including connections to community resources, treatment options and access to care.

Combining patient and community voices with the standardized, comprehensive data contained within the PINC AI^™ Healthcare Database (PHD) can lead to deeper insights into unjust disparities and inform solutions to address drivers of health and advance health equity. This robust data can provide a longitudinal view of the patient journey, illuminating critical touchpoints in care, and promote innovation and patient-centered care that incorporates patient preferences, needs, values and goals.

Advocating for Responsible AI in Healthcare

Premier supports the responsible development and implementation of AI tools in the healthcare industry, where numerous applications of this technology are already improving patient outcomes and clinician efficiency. Last summer, Premier submitted comments to the White House Office of Science and Technology Policy (OSTP) in response to an RFI to inform the Administration as it develops its national artificial intelligence (AI) strategy. In its comments, Premier outlined recommendations to advance equity, build trust and transparency, and promote economic growth, while remaining mindful of the potential threats that AI could pose to individual safety and national security if misused.

Premier feels that clear statutory, regulatory and subregulatory guidelines can help to better prepare providers and payers to deploy AI technology to its full potential, while still protecting individual rights and safety.

AI and the Future of Healthcare

AI continues to evolve and its use in healthcare will most likely increase. It’s been noted that AI will play a role in nearly every major industry down the road and in healthcare it has already spurred innovation in drug discovery, personalized medicine and to advance mental health treatments.

One study even demonstrated how ML — which excels at digesting reams of complex data — could improve and personalize treatments for conditions ranging from cancer to diabetes.

While we all feel AI has a bright future, the creation and utilization of AI tools has to be thoughtful and transparent as the technology evolves.

Premier supports policies and regulations that enhance the creation of AI tools and the use of AI in healthcare to empower providers, patients and improve clinical and operational efficiency. At the same time, it is critical that a regulatory framework for AI remain nimble and flexible to adapt to an evolving technology landscape and not stifle innovation.

For more on this topic:

• Read Premier’s AI Roadmap that supports the responsible development and implementation of AI tools across the healthcare industry.
• Deep dive into five key AI trends shaping the healthcare industry. Download our new eBook – The Pulse of AI: The Future of Technology in Healthcare.
• Learn more about PINC AI^™ Solutions and how they are changing the healthcare landscape.

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