AI enhances patient, clinician experience

Key takeaways:

• AI can update electronic medical record fields and select diagnosis codes so doctors can concentrate on talking with their patients.
• AI can correspond with insurance companies, saving even more time for providers.

Medical coding historically has been a manual and disjointed process, with office managers, coding specialists or clinicians reviewing the data after patient visits and coding to the best of their abilities.

As an input, clinicians are often required to update the patient chart in the electronic medical record, usually during the visit. The completion of these fields is so important, it drives the flow of every patient conversation, interrupting a natural, fully attentive exchange.

Now, as the health care industry looks for ways to ease clinician burnout, improve the patient experience and gain efficiencies, it is time for coding and billing to evolve again — this time with an assist from artificial intelligence (AI). And that includes the newest technology on everyone’s minds, generative AI.

AI makes it possible for coding to happen in real time, starting during the patient visit, and not after. Using technology to rethink how and when we collect the inputs for coding can have an immediate and positive impact on the administrative workload and patient and clinician experience.

AI: a technology for today

There is a lot of talk about how health care will use AI in the future. But for coding and billing, we do not have to wait. The technology is available, accessible and usable today.

With AI, data collection for coding begins as soon as your conversation with the patient starts in the care room. AI can transcribe the discussion in real time and tag unstructured data from a natural conversation into a usable and structured format.

From there, the AI, together with robotic process automation, updates the EMR fields, selecting the optimal diagnosis codes, and ultimately using generative AI to propose the most appropriate billing codes.

Not only can we remove the time spent, we also can remove underbilling or miscoding errors. Technology does it for you. Consistently, correctly. Every time.

Reducing the burden on clinicians

The AMA recently made some disturbing findings: nearly two-thirds of physicians have signs of burnout, roughly 10% more than the figure reported in 2022. Administrative burden is a common contributing factor to this condition. But AI is on hand to help.

AI can complete many tasks. For example, it can write letters to insurance providers or trigger phone calls to payers. In addition, with coding happening in real time, AI provides a more cohesive and data-driven story for insurance claims. This means fewer errors and denials and less need for physicians to participate in time-intensive peer-to-peer reviews with insurance providers. Plus, AI learns as it goes, which reduces the likelihood of future coding mistakes, rejections and reviews.

With the help of AI, we can reduce the burden of billing and coding work and help ease the pressure that can so quickly turn into clinician burnout.

Making care more human-centric

Embedding AI in medical coding enhances the patient and clinician experience. It may sound counterintuitive, but technology can nurture human connection. Most of us would agree that a free-flowing conversation with a clinician about our well-being feels more personal than responding to a checklist of rapid-fire questions in the EMR.

AI's ability to glean data and insight from these natural exchanges means you can focus on understanding why your patients are there, determining a diagnosis and fostering a rapport. All the while, AI is generating a proposed set of codes in the background.

With AI as an assistant, practices can rebalance workloads and have an immediate and positive impact on the clinician and patient experience. Try taking these four steps to AI success:

• Find your starting point: Identify the use cases where AI will have most benefit. Take the pulse of your clinicians to understand their biggest pain points and treat your first AI project like a pilot program.
• Co-create a solution: Invite clinicians to be part of the process. They will want to know how and where AI will support them, so include them when defining the workflows so AI is relevant to their situations.
• Try, test and learn: Experimenting before going live is crucial. Address shortfalls and test again. Seek feedback and act on it to build clinician comfort and confidence in the solution.
• Scale sensibly: Consider the next-best uses cases or areas to apply AI and have a roadmap in place for realistic expansion.

And here is a takeaway to apply to each of these steps: Keep humans in the loop throughout, because that is where the intelligence comes from. You need tech-assisted humans and human-assisted tech.

The bottom line

The way that providers manage coding and billing has evolved from processes that don’t enhance the provision of care or the patient or clinician experience to AI-powered approaches enabling more personal and fruitful interactions.

Clinicians now have the opportunity to unlock a smooth flow from consultation to billing, starting the moment a patient conversation begins. It ends with clinicians doing fewer administrative tasks, easing the stresses and burdens on them all. Adopting AI will take your billing and coding to the next level and make an immediate and positive impact on the human side of health care.

Reference:

• What is physician burnout? https://www.ama-assn.org/practice-management/physician-health/what-physician-burnout. Published February 16, 2023. Accessed July 6, 2023.