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Population Health Management

Consumer Segmentation Analytics

The evolving medical benefit landscape makes consumer segmentation a must

Healthcare Exchanges have brought a new level of complexity to the payer and employer benefits landscape. No longer are payers able to assess individuals' health status prior to providing benefit options, and traditional plans & rates may not be as attractive to employers who could opt to contribute for less expensive options.

How do plans retain employers and attract individuals while managing the risk pool? They must attract the right risk from exchanges, retain their existing good risk and manage the poor risk. One of the key factors to determine the level of risk is to utilize consumer segmentation to understand the health and behavioral factors of the consumer and how they will behave in the future with respect to utilization of health services, medication compliance, preventive screenings, etc. This infographic aims to illustrate the evolving medical benefit landscape and the importance of consumer segmentation for designing plans and strategies.

Exchange Landscape
Exchange regulations and policies will vary from state to state across the country. States have opted to create their own state-run exchanges, be run federally or a combination of both. Each scenario creates unique variables and challenges that will geographically affect the marketplace for health plans. For this reason, health plans should employ a software platform that allows them to assess risk factors common within a particular region or zip code.

Population Segments
Demographics, life events, financial disposition, geographic location, Value Based Benefit Design (VBBD) and risk analytic outputs are used to create segments within a population. VBBD uses plan design and incentives to encourage preventive and evidence-based healthcare behaviors. Risk analytics identifies members with the greatest opportunity to improve. Socio-demographic data identifies non-health related factors which can indirectly impact members' health.

Product design has typically used VBBD, risk analysis and socio-demographic information as separate initiatives. Advanced analytics combines these facets into a holistic member profile that allows for sophisticated healthcare consumer segmentation. Population segments are derived from finding similarities within a population across multiple data points including: member demographics, medical cost/utilization patterns, lifestyle preferences and consumerism around benefits.

Plan Design Optimization
The ultimate goal of Consumer Segmentation analytics will be to design plans that retain employer groups, attract a balanced risk and optimize plan effectiveness. Each of the business units within a plan will use this data to create products around member attributes, improve messaging and communication with members, reduce healthcare costs and improve outcomes.

Lalithya Yerramilli is a senior healthcare data analyst of SCIO Health Analytics.

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