By Harbinder Raina
Oct. 1, 2020
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.
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