Real-time experience response tracking helps improve customer satisfaction across a broad swath of industries, such as retail. However, health plans are lagging in this area. In our discussions with clients, we’ve found that most plans still rely on traditional feedback gathering methods, including periodic surveys, to gauge customer satisfaction. These survey responses are then analyzed to identify gaps and create an action plan, which is then graded by another round of customer feedback.
While this approach has worked reasonably well in the past, it’s not ideal for today’s changing member experience needs for the following reasons:
- Lag between encounters and feedback gathering: Traditional surveys gather feedback long after the actual encounter, which means that feedback isn’t accurate or specific to the encounter. Using this traditional approach, members who are happy with the plan rate every touchpoint or encounter highly in terms of customer satisfaction and members who aren’t engaged rate everything low. So, touchpoint and encounter-level differentiation in experience isn’t clear.
- No long-term view of member experience: Feedback from periodic surveys doesn’t provide accurate or consistent experience KPIs Point-in-time feedback from members may introduce biases based on when the data was collected and won’t be helpful in showing consistent underlying reasons for suboptimal member experience.
- Significant lag between listening and responding: Traditional approaches can take up to four to six months to collect data, analyze it and come up with a response plan. Once response plans are implemented, it may again take three to four months to repeat the feedback loop to measure effectiveness. The whole cycle of listening to the customer and responding to their needs is long. And during this period, another part of the customer journey might become more important.
So, what can health plans do? Real-time experience tracking and response, which can help build an effective member experience program, is the answer. It’s not easy to adopt this approach in healthcare, since gathering in-the-moment feedback about encounters with several stakeholders (plans, providers and pharmacies) involved in providing care may be complicated. However, higher levels of digitization, including telehealth and e-prescription, will help.
Real-time experience tracking is like our nervous system: it gathers information in a continuous manner through sensors or dendrites, transmits the information to a central database through neurons and synthesizes and produces a response recommendation using a brain-like analysis engine. Here’s how to implement it:
Step 1: Listen through “always-on” sensors: Build sensors along the customer journey or sub-journeys to record member feedback after each encounter. Sensors could be in the form of direct customer feedback after their visit to the member portal, after a telehealth interaction or after getting discharged from the hospital. Operational data including call center metrics such as wait time, call volume, first time resolution rate, number of switches from member portal to placing a call as well as claims processing time and claims rejection rates can also monitor real-time member experience through those sub-journeys.
Step 2: Aggregate information at a sub-journey level: Sensors should then pass information to respective “nerve centers” and aggregate information for each sub-journey such as product selection, enrollment and onboarding, receiving care and customer support interaction. The experience at each level can be summed up to come up with an overall customer experience rating.
Step 3: Synthesize and react using a suggestion engine: A smart suggestion engine, acting like our brain, synthesizes data and provides real-time suggestions to improve suboptimal experience for a part of member journey, a demographic or a geography. For example, a suggestion engine might suggest reviewing the formulary guidelines upon a spike in pharmacy claim rejections for certain drugs. Suggestion engines could also recommend outreach to a certain segment of members if you’re getting too many calls from that segment with a specific type of inquiry, or recommend having more PCPs in a network if its geography shows less than optimal customer experience.
A synthesis engine could also use information from external sources, such as COVID-19 insights, and combine it with aggregated sub-journey level observations to suggest actions. For example, a spike in COVID cases in a geography may prompt the suggestion engine to recommend additional call center resources to answer questions or a quick email campaign to push relevant information to impacted geographies. A new COVID-19 policy could also prompt a similar reaction to keep members informed, providing better over experience and reduction of inquiry calls to the call center.
Apart from generating real-time recommendations, the synthesis engine could also analyze data over time and help in coming up with mid to long-term changes.
Putting together a real-time monitoring and response plan may seem like a daunting task, but health plans can take small steps to achieve this goal. First and foremost, make member experience a priority at all levels of your organization and communicate it clearly so you get the right level of support to implement it. Second, start with a pilot program by establishing real-time monitoring for one member journey or sub-journey, such as enrollment process or finding a doctor. Third, gradually make your synthesis and recommendations engine more sophisticated. Plans can start with simple, business rule-driven suggestions, and as they learn and gather more data, they can use more sophisticated AI-driven synthesis and insights generation processes. Taking steps to build real-time monitoring now will help health plans create a better overall customer experience in the future.
