January 21, 2021

What is Health Intelligence?

Artificial intelligence has transformed the healthcare industry and personalized care management strategies, but what exactly is Health Intelligence, and why does it matter? Below we will explore what it is and why it matters to the future of care management, quality management, and care coordination.

What kind of data does it capture?

Health intelligence uses tools and methods from artificial intelligence to capture data in the process of performing care management, utilization management, assessments, and appeals to work across the populations we serve. 

One of the most valuable assets we have at Kepro is the clinical data captured in the course of our business. This wealth of information is growing daily with each Medicaid application completed, pharmacy claim approved, medical request evaluated, and virtually every time a staff member and technology interact with members. 

Does health data demand a different approach than what other industries may take?

Absolutely. Capturing data is the first step in the process but is more complicated than just storing every bit and byte in a massive database. Strict compliance with all HIPAA and state regulations guides all actions in a healthcare setting, including what data is collected, how to secure the information, and how to use it once captured. Limiting data collection to what is essential for improving member health outcomes while still ensuring their right to privacy is vital.

Data & Analytics and Health Intelligence. What’s the difference?

Think about data and analytics as to the foundation for Health Intelligence. Data points are snapshots in time; an individual piece of data doesn’t tell much of a story. Analytics transforms large volumes of data into useful information: clinical trends, activity reports, and health dashboards are just a few examples of the valuable information derived from analytics.

Health Intelligence is the proverbial “action step.” It’s all about applying insight gained from data and analytics into actions that improve outcomes for the populations we serve.

Example of Health Intelligence

Health Intelligence is not new and ever-evolving. Here at Kepro, our Percolator software is an excellent example of how technology combined with clinical outreach to incorporated into many of our case management contracts. The Percolator’s goal is to apply clinical resources towards members whose services can have the most impact. 

Here’s a quick summary of how The Percolator works: 

  • Data from Kepro’s Atrezzo Care Management Platform gets compiled and evaluated against a diverse and customizable set of input Triggers (like, say, “Member with over 3 ER visits in past 180 days” or “Member has simultaneous prescription fills in past 90 days”)
  • Algorithms based on the Triggers calculate the risk of a potential poor health outcome across the client population
  • The most impactable members “Percolate” to the top as the highest priority
  • Care plans are identified to close gaps for nurse follow-up. 

For example, a well-controlled and compliant diabetic on dialysis will be less impactable than a poorly controlled asthmatic with anxiety attacks and multiple ER visits. Percolator considers the “larger picture”, distinguishes between the two at-risk patients, and recommends follow-up steps by the care manager. That’s Health Intelligence in action. 

What’s next?

In this new year, we will see a continuation of current Health Intelligence capabilities (like Percolator 2.0) and launch several new initiatives applying Natural Language Processing (NLP) to enhance care for members and improve clinical team performance. 

We have several goals in mind with the NLP initiative: 

  1. Identify, highlight, and summarize healthcare-related entities in clinical documents to improve accuracy and reduce review time using Named Entity Recognition (NER)
  2. Generate a clinical index with references/links to where the entities appear in a clinical document or group of documents
  3. Fine-tune NER models with Transformers to identify contextual relationships in clinical records that are unique to our care management and utilization management use cases

Stay tuned to this blog as we’ll publish additional updates from our Health Intelligence team, including an overview of how Kepro is using AI to enhance Percolator 2.0 and a case study highlighting the NLP application in action.

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