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Population Health Analytics: The Devil Is Truly In the Details

By Truven Staff
Grant Hoffman image“Population Health” is an oft-discussed topic, but the definition is variable depending on the vantage point of the presenter. Likewise, “Population Health Analytics” attempts to measure and improve an array of risk-bearing, clinically-integrated activities, ranging from aggregate risk analysis to predictive interventions at the point of the care.

Regardless of your particular turf, some common challenges lurk behind the application of analytics to these business challenges. The roadblocks stem from the fundamental fact that the data sources on which you depend for decision-making were not captured with cross-encounter analytics in mind. Source IT systems such as EMRs, billing systems, and electronic prescribing solutions were constructed to accomplish transactional goals for siloed provider organizations, not to support improved outcomes and cost control across the patient care continuum.

 We’ve identified three areas of focus to help you avoid pitfalls: 
  • Anticipate information-sharing challenges: Technical integration of data isn’t the hard part. The tough stuff is setting the trust conditions for authentic multi-stakeholder data sharing and governance.
  • Navigate the context of data creation: Operational processes obscure analytic classification of data, terminology standards are variable, and information arrives at different periodicities. Amidst this noise, reliable prediction, reporting, and alerting all require an “analytically-aware” implementation of data streams and measures.
  • Start with analytics you can take action on: Massive projects get everyone excited, but a moon launch isn’t necessarily your first step. Work backwards from where you have operational capacity to make improvements (basic quality measures across the continuum of care? risk and disease prevalence? alerting and interventions?) and focus your attention on a set of trusted measures to get you there.
Watch our four-part video series on population health analytics.

Grant Hoffman
VP, Clinical Integration


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