Using Data Analytics to Reach Five-Star Medicare Quality Measures - Welltok l Consumer Health Activation
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Using Data Analytics to Reach Five-Star Medicare Quality Measures

Geisinger Health Plan leveraged highly specific survey data to improve their Medicare quality measures.

Medicare quality measures, survey data, HOS, HEDIS, data analytics

Source: Thinkstock

 By Kelsey Waddill

August 20, 2019 – Over three years ago when Yvonne Krashkevich became director of quality and accreditation at Geisinger Health Plan, the multi-faceted nature of Medicare quality measures was an enigma to the Pennsylvania-based health plan.

The key quality measurements that health plans have to consider are many, Krashkevich said in an interview with, and include the Health Outcomes Survey (HOS), the Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys, Healthcare Effectiveness Data and Information Set (HEDIS), the pharmacy and operational measures, and the clinical services measurements.

And these are only for a Medicare plan.

Geisinger decided to develop a more personal, off-cycle simulation survey based on the HOS that would be conducted prior to the HOS. Designed to improve on the HOS survey feedback, the off-cycle simulation survey zoomed in on the four areas which HOS analyzes. It would also prepare the Medicare population to respond to the HOS.

“Even though we gain insight into the components under HOS, which is mental health, physical health, fall risk, and bladder control…we never get to a member specific detail. We get to a global understanding of where some of the concerns are, but never member specific,” Krashkevich states.

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For the off-cycle simulation survey, Geisinger worked with Welltok to conduct a nationwide interactive digital voice phone survey of all 91,000 of their Medicare members and achieved a significant survey response. The survey made over 182,000 calls and had a 60 percent authentication rate, according to the case study.

It is one challenge to collect the data, but it is a far greater challenge to know how to use it effectively. Furthermore, communicating the many components of achieving a five-star health plan to Geisinger’s diverse team had been difficult in the past.

So to make an actionable plan and get the team on board, Krashkevich took the issue to an internal quality metrics meeting, which serves as an intersection for many different departments.

“That’s the venue we used to say, ‘okay, we have this data, now we have to build an action plan around it and let’s talk about what makes sense and who gets what,’” Krashkevich explained. “Everybody bought into it, supported it, and made sure that they had the resources and staffing around it to support the outreach that needed to happen.”

In this way, Krashkevich and her team were able to segment the population into the four HOS categories and assign the interventions to the most appropriate departments in order to more knowledgeably address their members’ specific needs.

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Of the four segments, mental health was considered the foremost concern.

“Even if they had any of the other problems, mental health trumped everything,” Krashkevich said. “That list of members was given to our mental health vendor and they actually did an outreach to those members to get them the care and the services they needed to address the mental health.”

Because mental health can be a precursor to many types of diseases and conditions, the company addressed the mental health concern first as a preventive measure.

For physical health conditions, such as COPD, Geisinger found that the HOS survey again fell short in its lack of specificity. The member’s response that their health is in a negative condition tells the payer it needs to intervene but does not elucidate what kind of intervention will be best for the member.

Krashkevich and her team segmented chronically ill members into their own population to address their chronic conditions.

Based on a member’s level of fall risk, Geisinger either called them—if the risk was severe—or sent information by mail regarding the wellness program. Geisinger has a number of programs, such as Matter of Balance, that educate members about how to prevent falls.

The last category that Geisinger addressed was bladder control. Because this condition is surrounded by stigma and often leaves patients embarrassed, the health plan approached their members’ providers instead of addressing it with the member directly.

When more than one of a provider’s Geisinger patients struggled with bladder control, the payer contacted that provider and offered educational materials to inform them and their staff about bladder control treatment options.

Geisinger also offered other resources for the provider to give her members when they come into the office or, as Geisinger encouraged, if the provider chose to reach out to the members directly.

But it wasn’t enough to just educate Geisinger’s health plan staff about quality measures. Senior leadership also made it a priority to educate in-network providers about how to drive high quality measure scores.

 “You really have to go at quality from a member standpoint and a provider standpoint,” Krashkevich explains. “If you’re not attacking it in both, you’re leaving something on the table there. We always feel that anytime we’re doing either incentives or education to the member or outreach, we have to be doing the same types of things with the provider offices. We’re coming at it from both directions.”

But going forward Krashkevich is not satisfied with smaller “buckets” of data, including physical health, mental health, bladder control, and fall risk. She wants to see the company drill down deeper into the individual experience through expanded data analytics.

Data about member finances, the social determinants of health, and consumer data will be useful. Put together, this information would construct a better image of the member and how to reach out to them more meaningfully, Krashkevich explained.

To achieve this, Krashkevich is looking to the next frontier: the CAHPS survey. She will also work on developing a stronger engagement method as well to make this immense amount of data actionable.