How AI adoption by hospitals and health systems can enable value-based care

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The focus of modern-day health care institutions is quickly evolving to prioritize the idea of value-based care, with the demand for this model anticipated to grow at a compound annual growth rate of 6.3% between 2024 and 2032. At the heart of this change is the understanding that patients require not just health care but high-quality service at a reasonable cost. Under this model, hospitals and other health care institutions are rewarded for improving patient health rather than focusing on the quantity of services they deliver. Offering an alternative to the traditional fee-for-service model, which rewards providers for the number of services provided, this model emphasizes the quality of service instead.

While moving to a value-based health care system sounds like a no-brainer on paper, the transition can be challenging for health care organizations — especially when it comes to managing costs associated with such a switch. This is where artificial intelligence (AI) and big data come into play. By harnessing the power of cutting-edge technologies, AI-driven systems are helping make value-based care models more accessible. They can enhance diagnostic accuracy and streamline operations, ultimately improving the quality of care, all while keeping treatment costs in check.

Vijay Aadapala
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Here are a few ways in which hospitals and other health care institutions can leverage AI-based tools and technologies to streamline this transition and provide value-based care to patients.

Power of predictive analysis

One of the primary ways in which AI-based technologies can be used by hospitals to deliver value-based care to their patients is through predictive analytics. With access to patient health data stored on a hospital’s electronic health record (EHR) and electronic prescribing (eRx) platform, AI tools that are compliant with the Health Insurance Portability and Accountability Act also can predict health risks and outcomes for a patient in a secure manner. Depending on how detailed and accurate the stored information about a patient’s lifestyle, family history, and existing conditions is, these AI tools can identify whether a patient is at an increased risk of developing conditions like heart disease or diabetes. This in turn can allow the hospital to provide such patients with personalized care and, more importantly, early intervention for what may eventually turn out to be a life-threatening issue in the future.

Improved workload management of HCPs

For hospitals, the most crucial cog in the value-based health care ecosystem is undeniably the health care providers (HCPs) and their administrative staff. With increasing patient inflow stretching the infrastructural limits of health care institutions, it can be extremely beneficial for hospitals to harness the power of AI for improved management of their resources and the overall workload of the staff involved.

In most cases, decreased workload through the automation of administrative processes and the use of technologies such as predictive analysis for HCPs eventually leads to the creation of a virtuous circle that pushes all involved toward a value-based model of health care, where higher-value tasks get prioritized through incentivization.

Improving diagnostic accuracy

An important factor in ensuring the long-term sustainability of health care systems is to create a value-based health care model that prioritizes improving the patient experience by reducing hospital return rates. To achieve this, enhancing diagnostic accuracy is an essential part of the process, as it ensures patients spend as little time on the treatment table as possible and gets the right medical advice for them on the way. AI-based tools can play an important part in this process by helping HCPs reach the correct diagnosis swiftly. Using the power of big data and trained machine learning algorithms, AI tools can offer a detailed analysis of individual cases by scanning X-rays, CT scans, and MRIs with high accuracy to create a supplementary diagnosis for HCPs.

Further, AI tools that make use of language models can extract valuable information from even old medical records of patients that may not be in the most presentable of forms. This in turn can help HCPs reach an accurate diagnosis faster, thus improving the overall quality of health care being offered to patients.

Nudging informed decision-making

AI also brings with it the promise of enabling HCPs to make more informed decisions at important points of care during a patient’s treatment cycle. Some existing and highly advanced AI-based tools working on AI-based triggers can greatly improve patient care through AI-driven, data-led nudges all within a hospital’s e-health workflow. By delivering highly relevant nudges to HCPs within their existing workflows — EHR, eRx, and telehealth — AI can empower them to make more informed decisions about their patients’ health at critical points of care.

Such AI tools can help foster deeper, more engaging HCP-patient engagements and help hospitals provide value-based health care to their patients by streamlining discovery and eventual offering of innovative and cost-effective treatments tailored to individual patients’ needs.

Endless opportunities!

It won’t be a stretch to suggest that with AI-based tools and technologies thrown into the mix, the landscape of the health care industry can truly change for the better at a rapid pace. Apart from what we’ve already discussed, the adoption of AI by hospitals can help bring value-based care to patients through innovative methods such as remote health monitoring and preliminary care through chatbots and virtual assistants. Through automation of routine administrative tasks, AI can again help free up resources at hospitals and then help them optimally use these resources through intelligent suggestions.

The opportunities truly are endless, so all that remains to be seen is when, and not if, hospitals and other health care institutions start deeper integration of AI-based tools into their workflows to deliver the value-based care that patients are asking for today.

Vijay Adapala is executive vice president of global supply partnerships for Doceree, where he oversees the end-to-end global supply partnerships with health care platforms and publishers. A seasoned executive with 25 years of experience in health care marketing, ad tech, digital media, and consumer tech. He has held leadership positions at Amazon Publisher Services, Yahoo and Motorola.