Driving a New and Improved Patient Experience with Data and AI

The use of data and AI are driving a lot of discussion these days and transforming the way that the healthcare industry can enhance operations, especially the patient experience. While there is some skepticism about applications of modern technology, the good news is that AI can make big differences throughout the patient journey from the start of patient engagement at registration all the way to completion of care with patient collections.

The way modern tech can play a role starts with offering patients a clear understanding of the costs of their care. A recent survey revealed that 40% of patients would either cancel or postpone care without upfront cost information. Makes sense, right? Patients want as much information upfront as possible to avoid perceived surprise costs when they are billed. That type of assurance goes a very long way toward a positive patient experience.

At the same time, healthcare providers want to quickly assess each patient’s ability to pay the costs associated with their care and – if there is a risk of not being able to collect on those costs - recommend additional or alternative financial pathways in real time. Providers need the capability to determine which patients qualify for financial assistance and which ones are likely to pay at or before the point of care.

A win-win scenario for both sides exists, and it is enabled using comprehensive patient data with AI-driven analytics that calculate a patient’s optimal payment plan amount based on their unique financial situation. But this is only one example.

Patient data from a provider’s own system and other sources enables healthcare staff to identify potential gaps in coverage that could later impact collections as well. Armed with accurate information, staff members can connect patients to Medicaid, charity, or other assistance programs they qualify for and even auto-enroll them. Or, depending on the patient, staff can determine personalized payment plans.

This high-personal-touch level of service is more important than ever given news reports that more than one million people lost their Medicaid coverage since continuous enrollment ended earlier this year. It’s critical that providers have a system in place to see which patients no longer qualify and – pending any gaps in coverage – help create a plan for payment.

What Happens When Collections Become Difficult

When patients are unable to meet their outstanding payments, a first line of defense is beginning a patient communication process with automated messages and AI-enabled chat features that – when engaging with a patient – can address frontline questions or issues. Also, these communications can provide bill reminders via secure, cloud-based dialing software, offering queue callback options to keep hold times to a minimum.

Recent developments in generative AI, including the latest version of ChatGPT, now can enable two-way, free-flowing conversations with patients that are virtually limitless. These conversations are powered by scripts that are derived by AI technology that is trained from the patient input it receives as well as data-driven analytics and models.

With these generative-AI advancements, providers have more instant access to information that improves internal operations, delivers much more personalized patient interactions, and helps identify obstacles to collections and possible pathways to reconciling back or delinquent payments.

For example, a key factor to minimizing collections issues is making the patient experience more convenient. According to a recent industry survey, 72% of respondents underscored the importance of online or mobile payment options such as IVR, mobile, kiosk, and patient portals. Effective patient communications can highlight these options for making timely payments.

Another strategy to maximize staff resources involves screening out patient accounts that are unlikely or unable to pay and focusing the staff’s time and energy on ones with a higher‑percentage likelihood of collecting. Automated systems with AI analytics and models that evaluate vast volumes of patient data to ascertain payment trends can help identify the more likely collectible accounts. With this type of decisioning, providers can keep high-yield ones or remove others from the AR file entirely, assigning them to a specialty collection vendor. This strategy ensures that a collections team remains focused on accounts with a greater likelihood of payment, optimizing both efficiency and revenue.

Conclusion

Properly communicating costs to patientsbefore they receive treatment contributes to a strong patient experience and helps mitigate future collection risk. Providers need to be capable of screening for potential gaps in coverage for patients, offering tailored financial assistance pathways for each patient’s unique needs, then automating personalized patient interactions via AI during the payment cycle to help reduce the bad debt that affects their profitability.

While not always an easy transition for providers to apply new software and solutions in their workstreams, the effort and investment are worth it. There’s no question that patients are demanding an upgraded experience and will change providers if their needs are not met. For providers, the staffing shortage challenge is a bubble that will burst if changes are not made soon. Forward‑looking providers can take the next step in evolving their front and back-end processes by employing comprehensive data and advanced AI-driven analytics and modeling to automate many functions, streamline processes, and, ultimately, increase their volume of payments.

About the Author

Clarissa Riggins is Chief Product Officer at Experian Health, the leading provider of revenue cycle management and patient engagement solutions for providers, physician groups and payers.