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Using Technology To Navigate the Care Journey – MedCity News


For healthcare consumers, the patient journey is more complicated and frustrating than ever. But with far more choices of primary care providers, specialists, health insurers, coverage plans, where they get their prescriptions filled, and even where they go to get treatment, why is that the case?

While choice is empowering, it also can be overwhelming and discouraging for patients struggling to navigate a fragmented, siloed health system. Anyone who has interacted with the U.S. healthcare system has experienced long waits on the phone to schedule an appointment or request test results, been bounced around to different support staff (and sometimes disconnected) or failed to get assistance from a contact center agent or other employee because that person lacked enough information to help.

Along with more choices, today’s consumers demand frictionless, personalized service. Unfortunately, healthcare organizations too often leave the hard work of navigating the care journey to consumers, many of whom may lack the resources, language skills, or understanding necessary to take a proactive role in their care.

And while adding more care coordinators or other staff to the system might ease the burden on consumers trying to manage their care journeys, it is not a viable option for healthcare organizations chronically understaffed and operating on tight margins. The only way to effectively scale care coordination to meet the needs of digital consumers is through technology, combined with empowered staff and transformed processes.

Streamlining patient encounters

Automation and artificial intelligence (AI), for example, can be used in healthcare contact centers to improve care coordination and streamline the patient journey at scale without adding more human care coordinators or requiring patients to have high health literacy. These technologies shift the onus of navigating the healthcare system off of consumers by leveraging information healthcare organizations already know about a specific patient.

Let’s say a patient who has an outstanding referral for an MRI, calls into a provider contact center. AI can analyze patient records and past interactions with the provider, using that information to guess that the patient is following up about scheduling this imaging test.

Though there may be a chance the patient is reaching out to the provider contact center about another topic, routing them via automation to an employee who books imaging appointments is a logical step that can save contact center employees time and prevent the patient from enduring multiple phone transfers before landing in the right place.

AI and automation enable this process to be 1) conducted in seconds and 2) repeated thousands of times a day or more. Without these technologies, the caller likely would be left on hold, transferred several times, and perhaps eventually told they must call a different facility to book an MRI appointment.

Customer self-service and support for agents

This hypothetical would also mean healthcare organization employees may have spent lots of extra time trying to help the caller (possibly to no avail) with a fairly straightforward need. Neither callers nor contact center workers are well-served by this cumbersome manual process, which can cause customers to seek other healthcare organizations, and contact center agents to wind up spending large portions of their day on repetitive and low-complexity tasks.

By removing the burden of care navigation from humans, AI and automation allow provider and payer organizations to better meet the expectations of patients and members while giving agents the tools they require to do their jobs effectively.

Today’s digital consumers have a strong preference for the convenience and efficiency of self-service options, even for highly regulated tasks like personal and business banking, or relatively complex ones like booking multi-leg travel. Healthcare self-service has traditionally relied on an “FAQ” approach, where common questions have articles that patients can read to determine what they should do to access care or services. Consumers are also often directed to online portals where they can self-manage parts of their care. But no portal can fully deflect every call or chat, and FAQs are, by necessity, written to be general for the widest possible audience, as opposed to the sort of specific answers consumers look for when they reach out to a contact center.

Technologies such as generative AI (GenAI) can be deployed to assist patients/members in finding information and getting answers to specific questions. The ability of GenAI to retrieve and summarize information from policies, articles, patient records, and other sources allows healthcare consumers to quickly and efficiently help themselves.

In cases where patients/members want or need to interact with an agent, AI and automation can empower contact center support workers to be fully informed and knowledgeable when dealing with callers by providing them with relevant, summarized, and contextualized information about that patient before the agent accepts the call. The agent doesn’t have to look for information in the contact center/provider system or ask callers to repeat themselves (yet again).

In addition to the pressure of interacting with callers who may have serious health concerns, contact center support agents typically work with tech that is complex and often stores more information than what an agent can read and process in real-time while assisting a consumer. Given these complex conversations, overwhelming call volume, and chronic understaffing, it’s no surprise that contact centers experience high employee churn.

This turnover can cost organizations from $10,000 to $20,000 for each departed agent, according to a study from consulting group McKinsey. Further, burned-out agents who stay in their jobs tend to underperform, particularly if they lack sufficient support, tools, and training to be effective.

Conversely, the McKinsey study notes “contact center employees who are satisfied with their jobs overall are four times more likely to stay with their companies for at least a year.” Providing healthcare contact center agents with the right information at the right time inevitably makes them better able to assist patients and members, increasing job satisfaction and helping to reduce agent burnout and attrition.

Conclusion

Technologies such as AI and automation are transformative, but healthcare organizations will always need humans to interact with patients/members along their care journeys. However, this can’t be done at scale. Integrating AI and automation capabilities into cloud-based contact centers enables healthcare organizations to meet demand for support services at scale while increasing agent performance and job satisfaction.

Photo: steved_np3, Getty Images



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