The US healthcare system stands at a pivotal crossroads, with the potential for transformative change within reach. By simplifying care journeys, embracing telehealth, harnessing the power of automation and robotics, promoting quality care transparency, and personalizing care delivery, we can create a more efficient, accessible, and patient-centered system. In this article, CitiusTech Senior VP and Market Head, Healthcare Providers, John Squeo, shares five game-changing shifts that will redefine the future of US healthcare and unlock a more streamlined, accessible and patient-centric system. Specifically, Squeo outlines how to create a more efficient healthcare system through simplifying care journeys, embracing telehealth, utilizing automation and robotics, quality care transparency and care personalization.

How healthcare leaders in the US prioritize patient satisfaction and what this signifies for the future of healthcare delivery.

As valued-based care has exceeded fifty percent of all reimbursements, providing quality care, encouraging patients to be actively involved in their own health and ensuring adherence to their care plan has become increasingly important to capture bonuses and gain share income for care providers.  There is an increasing acceptance of the fact that happier patients are more engaged and active. Healthcare leaders, including payers and health systems are now focusing and investing to improve patient satisfaction. This is done to increase patient engagement and make access to care easier, ensuring more frequent involvement and assurance that patients will attend appointments and follow-ups, ultimately leading to increased brand loyalty.

Leaders now aspire to enhance the experience of accessing healthcare, engaging with health resources on a day-to-day basis and treating patients through a highly personalized experience at every touchpoint like Amazon, Instagram, Facebook and Netflix. This will transform healthcare as we know it, seamlessly integrating it into our daily lives and activities.

AI is now being used in process workflows to supplant activities that were traditionally performed by humans.

The greater the ability to conduct healthcare interactions virtually, either synchronously or asynchronously, the simpler it becomes for patients and providers to “check in” with each other, assess status, modify care plans and ensure health maintenance. If the new care models attain this vision, we will see far fewer appointment “no shows”, greater patient adherence to care plans and lower utilization of acute care due to higher success of preventative care.

Telehealth is evolving to address broader accessibility issues and enhance patient care experiences in the future.

As an analogy, nowadays no one talks of “tele-banking.” People just expect to do most of their banking online, making a bank visit an exception. The same evolution is occurring in specific medical specialties, but not all. Telehealth adoption is most significant in psychiatry and psychological therapy, while specialties requiring physical interaction see less uptake. However, the administrative activities such as appointment scheduling and reminders are going through digital transformation, like online banking.

Data analytics and artificial intelligence can help meet demands of personalized healthcare interventions and outcomes.

The increasing demand for healthcare services from seniors, specifically the baby boomer generation, and the decreasing number of healthcare professionals available to provide care is creating a challenge in meeting the healthcare needs. The requirements for documentation of care activities have significantly increased for quality reporting, utilization authorization and reimbursement. This has added a significant additional burden on providers. The meaningful-use mandate has facilitated the digitization of documentation, unlocking the ability to use analytics to thoroughly analyze the electronic structured data in EMRs. This enables data driven approaches to health maintenance, diagnosis, intervention and research; however, the documentation requirements and the volume of digital data now exceed the capacity of the strained

clinical workforce to perform their primary activity of interacting with patients. Therefore, AI is now being used in process workflows to supplant activities that were traditionally performed by humans. This brings in several key benefits, including increased capacity and speed, fewer errors and the ability for healthcare workers to focus on the rewarding work of interacting with patients, which humans are best suited to do.

Value-based care continues to shape the future landscape of healthcare, particularly in terms of quality, equity and cost.

Value-based care aims to reduce healthcare costs by tying a portion of provider reimbursements to achieving specific quality measures. However, the cost reduction is primarily achieved via reduced utilization of services such as advanced diagnostics, reduced length of treatment and fewer inpatient admissions compared to the previous baselines in the fee-for-

A challenge in assessing the effectiveness of value-based care lies in the “one size fits all” approach to quality and equity measures.

service model. The question of whether value-based care is achieving healthier outcomes, preventing or prolonging the need for acute interventions is still being researched.

A challenge in assessing the effectiveness of value-based care lies in the “one size fits all” approach to quality and equity measures. These measures may not accurately reflect the nuances of different medical specialties or patient care customs, leading to concerns over their fairness and relevance. Current methods set static achievement levels for a set period, lacking the flexibility to adapt to specific circumstances. Advancements in AI technology hold the potential to introduce the needed flexibility, allowing for dynamic adjustment of baseline measures to better suit diverse medical practices and patient populations. Improved measurement of quality and equity could enhance patient choice by providing more accurate representations of healthcare provider performance. To foster trust and encourage the adoption of these measures, it’s essential to publish them in an easily accessible format and in plain language. This approach ensures that individuals across the medical literacy spectrum can make informed healthcare decisions.

Intelligent automation will continue to provide broader transformations in healthcare processes and workforce dynamics – overall system efficiency and patient experiences.

The new paradigm using robotic process automation and generative AI is to “trust but verify”.  That means setting up intelligent automation to handle as much work that can be described in a workflow as possible, inserting human interaction at checkpoints to ensure validity for quality and safety and providing a “sanity check” of the digital output.