Healthcare Think Tank

The healthcare industry is expected to undergo significant changes in 2024. Healthcare executives will need to make decisions and resource allocations concerning digital transformation, generative artificial intelligence, ESG, and margin pressures. Healthcare executives will face the challenge of adopting new technologies and business models while under sustained financial pressure. In terms of healthcare costs, estimates suggest that healthcare costs will rise by 7% in 2024, which is higher than the previous two years. This increase is attributed to continued labor shortages, drug price increases,
and new contracts between payers and providers. It is also worth noting that the cost of job-based health care coverage for 2024 is expected to rise at its fastest pace in years as inflation pervades insurance policies. Overall, the healthcare industry is expected to undergo significant changes in 2024, and healthcare executives will need to adapt to the new environment to ensure their organizations’ success.

White box AI can explain itself leading to audit defense and perhaps material defenses in healthcare malpractice lawsuits. The same white box can stop bias depending on how it is built and the results that it generates. This technology is extremely hard to build, but when delivered, will change the industry of healthcare. Let’s look at some examples.  

In the dynamic landscape of healthcare, where meeting patients' needs is paramount, hear about the imperative of integrating technology and AI to enhance personalized patient care within modern contact centers. Recognizing the challenges posed by call wait times and the necessity for prompt access to vital information, solutions, and assistance, we'll delve into the transformative potential of these advancements. Through the implementation of AI-driven systems, such as intelligent call routing and predictive analytics, healthcare organizations can efficiently manage call volumes, minimize wait times, and ensure seamless access to support, thereby elevating the patient experience.

By leveraging machine learning algorithms and natural language processing, healthcare contact centers can tailor communication channels and content to align with individual preferences and needs. We'll discuss how a personalized approach fosters deeper patient engagement, trust, and satisfaction while empowering patients through self-service options like interactive voice response systems and chatbots. 

In an era where cyber threats evolve at an unprecedented pace, Chief Information Security Officers (CISOs) in the healthcare sector face a daunting challenge within a complex landscape of cyber risks. This presentation delves into the transformative potential of AI-Powered Security Validation Platforms to continuously manage their vulnerabilities, attack surfaces, and exposure, thus proactively reducing cyber risks. This AI-driven approach not only prioritizes and validates security efforts but also enhances existing controls without the need for additional personnel or tools.

Value-based payment and delivery transformation is not the future, it is the present. Successful health systems, hospitals, medical groups and other providers are those that seek to engage with members to improve their health and total cost of care, rather than simply providing episodic services when a patient is sick. Cost reduction is no longer primarily about per-visit cost, but rather total cost of care per member per month (PMPM). In addition to looking at cost from the payer perspective, cost reduction must also be viewed in terms of the member’s out-of-pocket expenses. Put another way, providers must aim to reduce the totality of medical costs for each member they manage, rather than focusing only on the costs for a member when they show up at a clinic or hospital

Health equity is when everyone has the opportunity to be as healthy as possible. Innovation can be defined as invention + adoption + diffusion. Successful innovations often possess two key qualities: they are both usable and desirable. We will consider working examples of how clinic innovation is favorably impacting health equity, the associated challenges, risks, and how to evaluate success.

AI is being applied within the healthcare field, especially for the tasks of diagnosis and treatment recommendations, patient engagement and adherence, and administrative activities of the healthcare workforce. Seemingly, the best thing about applying AI in healthcare is that it can be used to improve various spheres: from gathering and processing valuable patient data to being used for programming surgeon robots. Let’s take a closer look at how AI is impacting healthcare diagnosis including detecting and classifying disease; improving decision making process and driving treatment solutions.

Accuracy of diagnosis, data quality and patient centric care are the buzzwords around improving healthcare outcomes. Leveraging artificial intelligence with medical procedures to diagnose disease early, when there is the highest potential for impact. Data quality lives by accuracy, consistency, and relevancy. How can we improve data quality by reducing redundancy and decreasing medical errors? Patient centric care thrives if the partnership among practitioners, patients, and their families align with patients' wants, needs, and preferences. In this session, we will discuss what’s working and what’s not working, as we look to improve diagnosis, data quality and patient centric care.