To Understand What’s Driving Healthcare Data Growth – You Must Consider the “Vital V’s of Data”

In Affinite Quality, Artificial Intelligence, Care Coordination, Data Science by Marketing

Gain Perspective With This Healthcare Specific Definition of Big Data Terms

Data is a critical component in every aspect of healthcare, from research, to diagnosis, to treatment.  Simply accumulating and analyzing data does not lead to greater clinical insights and more positive patient outcomes.  It’s how you use the data that matters. 

But for every member of the healthcare ecosystem, from payers, to providers, to individual members – it is a struggle to “manage and make use of the data” created.    

 This fact is one of the greatest challenges facing payers.  To understand the factors making this so, it’s important to understand, “The Vital V’s of Data;” volume, veracity, variety, velocity and visibility.  These affect every health plan’s ability to do more with less and achieve greater value from the data they have.  

This post provides a holistic overview of these dimensions in order to better understand the effect of today’s data landscape on better managing care, quality and risk.

The Vital V’s of Data:

  • Volume – Everybody wants to harness big data. In healthcare, more data often generates better outcomes. But there is such a thing as data overload. Often just a few sources, can lead to building effective data science models that micro-segment populations to more precisely formulate treatments and interventions to create more positive results.
  • Veracity – To be valuable, data must be reliable, the trustworthiness of various data models need to be maintained and should incorporate data from both adjudicated and non-adjudicated claims, eligibility history and records, longitudinal studies, and be validated by other data validation methods. .

  • Variety – It is important to collate data from a range of sources and media: including SDoH factors, EMR/EHR notes, voice recordings, and operational output data.  Yet, health plans struggle to integrate non-traditional and/or unstructured data types due to limitations common to on-premise legacy solutions. However, new cloud-based or SaaS care management, quality and risk solutions enable health plans to utilize Natural Language Processing (NLP) and Machine Learning to include these data types for a more holistic view of every member.  This insight can enable better clinical outcomes.

  • Velocity – Data velocity is the rate at which data is “coming in” to the health plan and changing.  The ability to capture these changes is best managed in a cloud-based infrastructure capable of infinitely scaling, enabling real-time prioritization of members based on key care management, and drill down into granular patient populations.

  • Visibility – What you can’t see, you cannot manage. Data is no different.  It must be made visible in order to provide value. Data can provide a 360-degree view of a healthcare plan’s operation and a member’s care.  Visibility can uncover workflow bottlenecks, system inefficiencies, and wasted resources. 
  • Value – Obtaining impactful value from healthcare data to better inform clinical and quality decision making is only possible when the information and related insights are made rapidly accessible in daily operations.  Using weeks old data to determine care management interventions, for instance, is less than ideal – yet very common.  For example, health plans using Vital Data Technology’s Affinitē platform are able to instantly risk stratify and prioritize members based on disease type and other criterion significant in real-time, resulting in timely application of interventions, rather than care plans based on weeks-old data. 

Put the V’s to work for your health plan with VDT

To learn more about how to gain clinical and operational insights from your healthcare data and to create value throughout the entire ecosystem, including plans, providers, and patients talk to our data expert.

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