How Do You Fix a Problem If You Don’t Know You Have It?

CareCentra was recently asked by a 24-hospital health system to identify their Super-Utilzers – the 15% of patients that account for 80% of cost. They wanted CareCentra to help them understand what causes patients to become Super-Utilizers, and to take timely preventive care measures to help patients from developing into high-utilizers.
 
While “Population Health” may be just a buzzword to some, it means real, tangible payback to this healthcare network. Using CareCentra’s analytics, their Super-Utilizer Reduction System is already delivering surprising insights about their patient population. These are patients with the highest clinical risk as well as the highest utilization. The examples below are just a fraction of what they’ve uncovered:

  1. Which patients account for my highest utilizers (patients with the highest clinical risk as well as the highest expenditure)?
  2. What clinical conditions make up this cohort? What are their annual costs?
  3. What is the gender, age, racial distribution?
  4. Which low and medium-utilizers exhibit attributes of potential future high-utilizers?
  5. What treatments/medications are the most efficacious for each condition by gender, race, etc.?
  6. How many claims overall, what is the average claim, by location, condition, physician, etc.?
  7. Which patients are 30-day readmission risks (the CareCentra platform averts their return)?
  8. Which patients account for the highest ER visits and inpatient admission repeats?
  9. Who are my payors, how much more/less do we make by payor, by claim, by condition?

 
Risk1
 
Example 2: Show me a breakdown of patients by risk strata (e.g.: “A1″, Highest Risk / Highest Utilization, to “W3″, Lowest Risk / Lowest Utilization, and any gradation in between). You can slice and dice this information by any relevant criteria, compare one condition to others (including P&L), and drill down to any desired granularity.
 
Risk2
 
There is no limit to the scope or level of decision-support detail that this network now has at their fingertips for analysis of all kinds, and what are some advantages of having such intelligence readily available to you?

  1. You could shortlist the patients on which to focus your limited Care-Coordinator resources, and which to entrust to CareCentra’s MoBe Maps (Motivational Behavior Mapping) platform to shape patient behavior . . . e.g.: Keep patients from developing into high-utilizers and re-admissions.
  2. Monitor and report results against Quality Improvement targets (essential for assessing efficacy of QI efforts).
  3. Discover how much your network could save by prescribing generic drugs when possible, identify the physicians that over-prescribe name brands, and ‘nudge’ them toward less costly alternatives.
  4. Identify candidates for CPT 99490 (Chronic Care Management) billing, and again, use CareCentra’s platform to execute the appropriate patient outreach, and document regulatory compliance.

. . . Indeed, the list is limited only by your imagination.
 
CareCentra recommends a “Crawl, Walk, Run” strategy; identifying small low-cost projects with significant, high-impact financial return. The Super-Utilizer Reduction System described above is an example of exactly that. We aggregated and normalized clinical, claims, utilization, lab and medication data from multiple-siloed EHR systems into one integrated data-warehouse to provide a 360° view of the entire patient population. This network now has a tremendous foundation on which to extend their use of CareCentra analytics to all corners of their organization.

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