AI can ease the pain points in healthcare for patients, physicians and payers

Anupriya Ramraj
Principal, PwC US

Patients, providers, and payers are all looking for more from healthcare. In PwC’s customer experience survey, healthcare ranked in the top three industries in which a significant gap exists between what customers expect versus the service they’re actually getting. Artificial Intelligence (AI) holds great promise in improving the current system.

Trust in AI doesn’t come easily — organizations must tread carefully, particularly in this industry. The ethical adoption of AI is critical. These are hurdles data scientists are working to overcome, but our sector can’t wait to begin unlocking the potential of AI in healthcare.

Where are the major pain points in healthcare today?

1. Patients: A major challenge today is long wait times. In 2022, the average wait time for a physician appointment in the 15 largest U.S. metro markets was 26 days.⁽¹⁾ It’s not difficult to connect the dots—the longer the wait time, the higher the risk of illness, mortality and possibly avoidable hospital visits.

2. Physicians: There’s outdated technology, inefficient workflows and a shortage of skilled workers. The outcome: burnout. A study published by Mayo Clinic Proceedings shows that 62.8%⁽²⁾ of the physicians rwho responded to a survey said they experienced at least one symptom of burnout in 2021.

3. Payers: Organizations are grappling with improving operational efficiency, reducing the cost of care for members and delivering personalized customer experiences. This, in turn, is driving the focus toward preventive care.

It’s more imperative than ever to bring personalization and efficiency into the patient, physician and operator experience. The positive is that we are now ready with technology powered by AI to speed up this transformation journey.

Three key areas for transformation

1. Improve patient engagement

Consumer engagement and positive experiences are essential to achieving better patient outcomes, preventing unnecessary trips to the emergency room and eventually easing the burden on the strained healthcare system.

And an integrated contact center that can share information across pharmacies, payers and other health systems can help provide a seamless self-service experience designed to increase customer satisfaction and client retention.

2. Decrease time for diagnostics

With AI-enabled diagnostics, clinicians can intervene before medical crises occur by using predictive models that analyze patient data and activities. The first step toward this goal is setting up data repositories. For example, Microsoft and PwC recently collaborated with Open Source Imaging Consortium (OSIC) to create a groundbreaking OSIC data repository with anonymous imaging data that can be shared. This helps medical professionals make quicker, more accurate diagnoses. Although this project focuses on a rare lung disease, it’s expected that the applications will broaden in the future.

3. Achieve operational efficiencies in billing and records management

Medical coding and billing can be cumbersome. They require manual documentation, which is often costly and prone to error. The transactional nature of these processes makes them one of the better use cases for the application of AI-enabled software. AI-led automation powered by machine learning (ML) and natural language processing (NLP) can convert physician notes into billable medical codes. It can also conduct real-time audits to identify errors in bills and rectify them. Using ML, providers can identify medical billing cases that require prior authorization, and payers can accelerate the approval cycle by using intelligence in processing. Billing staff can also predict the likelihood of a claim being rejected before it goes to the payer based on past data. More accurate coding and billing translates into fewer claims being reworked and more dollars saved.

Physicians have an administrative burden to create extensive documentation in the electronic health record systems for billing and regulatory compliance. AI-powered NLP solutions can help physicians efficiently and effectively capture clinical documentation from pre-charting through post-encounter, contextualizing it with ambient clinical intelligence and thus improving the quality of documentation without physicians sacrificing time with patients.

Overall, 80% of healthcare providers plan to increase investment in digital health over the next five years, according to research results from HIMSS.⁽³⁾ And there’s increased focus on industry clouds and healthcare solutions by cloud providers, integrators and software vendors to turbocharge this journey.

These are just a few of the ways that A1 can improve the health care experience for patients, providers, and payers while ensuring ethical adoption of AI in healthcare. Now is the time to explore developing or augmenting an AI strategy. A strategic partner can help guide organizations through the principles of ethical AI in healthcare with an emphasis on transparency, inclusion, accountability, security and resilience.

Explore how PwC and Microsoft Cloud for Healthcare are helping to deliver better AI-enabled experiences, insights and outcomes. A version of this article originally appeared in Forbes December 12, 2022.

_{^{1. Survey conducted by AMN Healthcare and the company's physician search division, Merritt Hawkins.

2. Physician survey published by Elsevier Inc. on behalf of Mayo Foundation for Medical Education and Research.

3. 2021 Future of Healthcare Report from HIMSS and its Trust partners}}

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