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Best Practices in Applying Analytics to Population Health Management Programs

Healthcare analytics that stratify large and complex patient populations

The primary goal of any population health management program is to improve health outcomes. These improvements in health outcomes should be measurable and analytics are front and center in the process to achieve this measurability. Prior to jumping into best practices in applying analytics, let’s first look at a brief overview of what needs to be measured. A recently published PHA/HERO’s publication aptly captures these measures as follows:

  • Financial Outcomes: Claims Savings, Reduced Hospitalizations
  • Health Impact: Physical, Mental/Emotional, Health Behaviors, Health Status, and Risk
  • Participation: Identified/Targeted, Reached/Contacted, Participated/Engaged, Impacted
  • Satisfaction: Participant Satisfaction, Client Satisfaction
  • Organizational Support
  • Productivity & Performance
  • ROI (Return On Investment)

Five Best Practices in Applying Analytics to Population Health Management Programs

Needless to say, the answers to the above said questions lie in the data; hence the accurate data collection from disparate sources and ensuring the ease of its usability constitutes the first of the best practices. Be it from the patient (such as coach captured or patient provided in an engagement platform), or the care provider (EHR/EMR), or payer (claims), or the social media, the standardization of data collection and its normalization ensures the quality and ease of use.

In any population health management program, right time of intervention is key to produce cost savings through better health outcomes. Identifying and stratifying the risk (care gaps, disease progression, financial risk, and propensity to change) through predictive analytics is the second of the best practices to get the time of intervention right.

While effective engagement/coaching is a function delivered by the care team, coaches, or campaigns, analytics combined with sound clinical intuition should be the engine driving the personalization for such engagement as the third of the best practices.

An unbiased, academically rigorous evaluation for cost effectiveness should be non-negotiable as the fourth of the best practices to show the certainty of result.

Finally the practice of quality assurance at each step of intervention is indispensable to believe in the outcomes via a set of leading indicators (such as engagement, goal-setting, and behavioral impacts) at appropriate level to effect change in the ultimate evaluation to reflect the speed-to-value.

Health Dialog embodies these analytic best practices in supporting efforts to drive total population health by achieving the personalized health goals for each member, (one person at time) with our best-in-class engagement platform called InteractTM. Developed with a Care Pathways based patient engagement strategy, Interact connects individuals to the health and wellness content, tools, and resources they need most.



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