Navigating Healthcare Dynamics With Technology

Ashish Kachru is CEO of DataLink.

Paper charts, millions of file folders and filing cabinets stuffed to the brim. This was once the reality of record-keeping for healthcare. In the 1960s, however, healthcare took its first deep dive into the new frontier of electronic health records. Since that time, the impact of technology has continued to evolve, pushing boundaries and improving patient care.

While progress has undoubtedly been made, there’s so much more to do. Just look at Medicare. Medicare provides health insurance coverage to 67 million people in the United States. Of those, more than 50% are covered by Medicare Advantage private plans.

This growth of Medicare Advantage members as the population ages presents the Centers for Medicare & Medicaid Services (CMS) with many challenges, including rising healthcare costs, health inequities, improving quality of care and evolving needs for an aging population.

Policy updates are addressing many of these challenges. However, the truly exciting part is the new era of technology, with artificial intelligence (AI) and machine learning (ML) leading the way to positive change for the industry and the individuals it serves.

New Policy Creates New Challenges

Every few years, CMS recalibrates its risk adjustment model to focus spending on critical issues while controlling costs and improving outcomes. The latest model, Version 28 (V28), represents the most comprehensive change to the risk adjustment model since its inception.

This change is turning the industry on its head and effectively reducing revenue for health plans and providers serving Medicare Advantage patients. What does this mean for the industry?

Ultimately, patients should continue to receive better care and improved outcomes. However, health plans and providers will need to find more ways to keep costs down to maintain revenue. This shift creates an open door for AI and ML to finally make an impact.

Opportunities For Healthcare Tech

The evolving landscape in healthcare creates opportunities for AI and ML to drive fast-paced innovation that can enable providers and payers to prioritize essential aspects of care that create efficiencies and cost savings.

Telehealth

Before the pandemic, telehealth was scarcely used among Medicare beneficiaries. Since 2020, there’s been a surge in telehealth, especially with the Medicare population.

In the first year of the pandemic alone, over 28 million Medicare beneficiaries used telehealth services, which emerged as a crucial tool during the Covid-19 crisis—particularly in granting older adults access to vital mental health services.

The expansion of telehealth with the ability to integrate interaction data within an electronic health record and the use of AI/ML solutions can convert speech/video to text. This allows for summarized actionable prescription, appointment and/or referral notes or even the ability to identify conditions for risk accuracy. The result: reduced downstream effort and a decreased risk of losing out on valuable information.

Remote Patient Monitoring

Remote patient monitoring complements telemedicine by using wearable devices, sensors and mobile apps to collect, transmit and analyze patient health data. This technology enables healthcare providers to monitor vital signs and health metrics in real time, offering valuable insights into patients’ overall well-being.

AI/ML-driven solutions can help address the challenge of data overload, assisting healthcare providers in efficiently analyzing the vast amount of information that remote patient monitoring devices generate. By prioritizing relevant data, these algorithms empower providers to track the progress of patients with chronic conditions closely.

This facilitates early interventions to prevent potential complications or anomalies and enables the creation of personalized treatment plans. Ultimately, this approach could minimize hospital visits, readmissions and emergency visits, potentially reducing healthcare costs.

Clinical Decisions Using AI/ML Algorithms

The Food and Drug Administration has cleared over 700 AI healthcare algorithms, with radiology making up 76% of them, contributing to healthcare improvements by enabling early and accurate identification of underlying, undiagnosed, progressive or existing conditions.

AI serves as a valuable tool to enhance the efficiency of radiologists, providing a secondary review to help identify potential issues that may have been missed. Additionally, AI technology is increasingly used to organize work lists, conduct measurements, automatically populate report fields and expedite reading times.

These advancements have become crucial topics of discussion within the radiology field, particularly as the industry faces significant shortages of radiologists and radiology technologists, with staffing deficiencies worsening each year.

Growth In Medical Large Language Models

LLMs hold significant promise in revolutionizing medical practice across various fronts, such as enhancing diagnostic precision, forecasting disease advancement and bolstering clinical decision making processes.

LLMs are instrumental in facilitating and enhancing clinical decision making by undertaking clinical summarization tasks, which encompass a wide array of activities, including analyzing radiology reports, addressing patient inquiries, summarizing progress notes and facilitating doctor-patient dialogues. By streamlining these tasks, LLMs not only alleviate the administrative burden on healthcare professionals but also contribute to reducing overall costs associated with medical practice.

What This Means For The Industry

When it comes to innovation and adoption of new technology, healthcare has traditionally lagged behind other sectors. The good news is that this may be changing.

As new policies are implemented, stakeholders need to balance the cost impact with the delivery of quality care while serving the needs of an aging population. Payers and providers must embrace technology and continue to find new ways to incorporate tools like AI, ML and LLM into the delivery of care.

It’s time for healthcare to push the envelope, stand at the forefront of technology and serve as an example to other industries when it comes to innovation.

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