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Why is Data the Medicine to Cure Modern Healthcare?

 

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The world of healthcare analytics is vast and can encompass a wide range of data that has the incredible potential to tell stories about health and healthcare delivery: right from individual patients to entire populations. Having numbers and an easy-to-use visualization at hand gives providers and caregivers the power to not only look into the lives of individual patients but also track the ongoing activities in their organizations. Simply showing visualizations are not enough and to fully understand their value, healthcare organizations have to take a few steps beyond basic graphs.

The Case for Data Visualization

In the words of Edward O. Wilson, the father or social biology,

“You teach me, I forget.
You show me, I remember.
You involve me, I understand.”

There are many disparate data sources healthcare providers have to deal with: EHRs, departmental data, claims data, resource utilization, administrative data, etc. Consolidating the data and spreading it out in a visually adaptive manner offers a more agile approach to managing complex population health data.

Data visualization was developed with the aim to make it easier to gain actionable insights from volumes of information and work on improving health programs, clinical healthcare delivery, and post-episode care management. Visualization provides real value in learning from disparate data sources, finding outliers, bringing out hidden trends out on the front, and delivering better health outcomes.

Streamlining Different Data Sources into a Single Source of Truth

Since the data pertaining to a patient’s health comes in from various sources, it is vital to pool all the data sets and obtain an aggregated, standard format of data every authorized person can view and manipulate.

Data in the healthcare industry can broadly be categorized into two sources:

  • Claims data: that comes from payers and contains extremely uniform and updated data about the care patients receive and how they are billed for it. This data is usually structured and has all the meaningful data required for provider reimbursement.
  • Clinical data: this data comes in from the providers’ end and contains valuable information about their diagnoses, claims, and medical history. While this data isn’t often structured, incorporates data elements critical to analyze a patient’s health in every time frame.

Fine-tuning Real-Time Visualization

The amount of data healthcare institutions aggregate is enormous: by 2012, it was estimated to be a whopping 150 Exabyte’s (150 million * million * million) and is growing at a rate of 48% per year. As the volume grows, healthcare organizations need state-of-the-art, real-time analytical capabilities to improve the care quality and its effectiveness. Real-time analytics can turn the tables in ways more than one:

  • Monitoring end-to-end care delivery across a wide range of facilities.
  • Observing the progress of clinical decision support systems.
  • Identifying overhead cost drivers and detect care or documentation gaps.

Since data visualization holds great advantage to understand the going-ons in the organization in real-time, here are some key elements that count as best practices for data visualization:

  • Customized reports: Each set of users in healthcare requires different metrics and different orders. Offering customized reports with specific visualization provides actionable insights and can answer specific questions about risks, rewards, and success of the organization.
  • Visually adaptive: Data presented on the dashboards has to be complete with functional and visual features that aim to improve cognition and quick interpretation. Data listed in a color coded-manner will provide physicians with functional features and real-time alerts.
  • Create actionable insights: A dashboard or any other visualization tool will provide clinicians with the data, but unless someone looks at it, it will go unnoticed and may have potentially critical outcomes. Users should be made aware of how to review the dashboard, drill down to every immediate level, and initiate corrective actions.
  • The end user’s ultimate need: It’s paramount that end users can communicate their needs and demands and what is even more important is that their demands and performance indicators are incorporated well in advance of structuring the report.

Wrap-up with Healthcare IT

By leveraging healthcare IT, organizations can have their hands on simple but effective visualization and take a look at additional, important information that might have been difficult to notice in tabular format. Here are some ways healthcare IT can drive real-time data visualization to success:

  • Immediate access and sharing: Putting bidirectional interoperability to use, providers can access and share relevant data across the network, despite technological barriers.
  • Clear data visualization: Graphic, color-coded cues help physicians swiftly learn about the areas that need performance improvement or track the growth their organization is making.
  • Drilling down: To learn more about the reason behind certain shortfall, physicians can always drill down and narrow their area of focus to pinpoint the anomaly, and take quick remedial actions.

Driving Value with Visualization

With healthcare IT now an integral part of the value-based care system, there is little doubt that convenient, real-time data visualization will be heavily used to achieve positive health outcomes. Combining real-time data with advanced analytics will completely reshape how healthcare IT can improve clinical and operational outcomes. Once physicians move away from long, incomprehensible data flows, and find an alternative that helps them instinctively read, isolate, and act upon the insights, only then can we be one step closer to a data-driven value-based care.


 

 

About the author: Abhinav Shashank

Abhinav Shashank is the cofounder of Innovaccer. Shashank, an Indian Institute of Technology Kharagpur graduate, came up with the idea for Innovaccer while working on a project at Harvard. The big data startup provides businesses with a tool for pooling and analyzing large volumes of information from multiple sources. It is actively used by healthcare firms, hedge funds, and in e-commerce.

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