Taking Members From Disconnected to Engaged
To engage members and close care gaps, health plans are taking a closer look at member data sets and the analytics that can harness them.
Health plans these days are investing time and resources in analytics and investigating new ways to more fully engage with their members. Why? Because engagement is correlated with better outcomes, and while health plans have millions of dollars at risk related to gaps in care, they have relatively few ways to address them. Member engagement is one of those ways.
Fortunately, member data sets are rapidly improving. These increasingly robust data sets make it possible for health plans to segment their member populations and tailor care plans based on such factors as demographics, clinical history, and consumer preferences.
This type of data-driven, personalized plan design has all kinds of positive effects—on utilization, on outcomes, on patient satisfaction.
Not surprisingly, health plan interest in harnessing these data sets is growing because they can be used to support quality improvement, HEDIS, and Medicare Star rating performance, cost containment, and member satisfaction. The catch is that many don’t have the in-house resources to leverage their member data to the fullest. Three key areas will help plans to close gaps in care and improve outcomes.
1. Identify at-risk members
Descriptive analytics can establish a baseline for understanding the shared traits within member populations. Health plans can then use analytics to stratify their members based on such sources as claims history, EHRs, health risk assessments, and social determinants of health. Building propensity models based on those stratifications helps identify at-risk members. Armed with data-driven insight, health plans can deploy effective interventions earlier, tailor them to engage members, and help members to take the steps necessary to protect and improve their health and well-being.
2. Tailor communications and care settings
Once a tailored intervention is developed, additional questions arise for the plan, including how best to communicate with the member and where and when to offer the needed care. Many plans possess member data that can provide a wealth of information about how that member prefers to receive communications. Some prefer an email or a phone call. Others respond better to a traditional mailing. Knowing the communication preferences of members is akin to speaking to them in a language they understand and can be crucial to making a genuine connection and facilitating the desired clinical outcome. Additionally, many plans are now able to offer members alternative care settings, increasing convenience and the likelihood that members will follow through on their care plan.
3. Increase member motivation
Too often, care plans are like road maps for trips not taken. But if health plans fully utilize member data, they can customize a member experience that increases the member’s ability to put care plans into action. By increasing customization and convenience, plans help to improve member motivation, which can trigger a cascade of benefits: greater member satisfaction, reduction of care gaps, improved HEDIS scores, and lower incidence and intensity of illness. Analytics also enables health care teams to measure what is—and what isn’t—working across multiple interventions, care settings, and communication channels. If used properly with feedback loops, those analytics fuel cycles of continuous improvements.
Once member data have been aggregated and propensity models are in place, there are different ways health plans can further optimize member-engagement programs. Many health plans begin by targeting members with high-risk profiles and histories of low engagement. Starting with one segment is a practical place to start. More mature engagement programs will address the needs of all segments. If most of a health plan’s communications suit the needs of only one profile or segment, a significant percentage of the overall member population is likely to remain unengaged. Effective analytics enable health plans to understand their members’ needs in a more granular way so that engagement programs can be equally granular— and therefore have a large effect overall.
Informed member engagement strategies can drive member activation that, in high-risk segments, can have life-saving potential. Greater member engagement supports both health plan and provider efforts to close gaps in care, connecting members to the appropriate care in the care settings of their choice. Members are looking for a customized health care experience. With analytics, health plans can deliver it.
Carrie Cowdin is senior vice president of client analytics for BioIQ.
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Paul Lendner ist ein praktizierender Experte im Bereich Gesundheit, Medizin und Fitness. Er schreibt bereits seit über 5 Jahren für das Managed Care Mag. Mit seinen Artikeln, die einen einzigartigen Expertenstatus nachweisen, liefert er unseren Lesern nicht nur Mehrwert, sondern auch Hilfestellung bei ihren Problemen.