Home Data The Use of Structured and Unstructured Data in Public Health Initiatives

The Use of Structured and Unstructured Data in Public Health Initiatives

by Heidi Bullman

Editor’s Note: This article was originally published on GovDataDownload and leverages insights from Lisa Hines, MBA, former director of telehealth services for the Greenville Health System, and now strategic advisor for healthcare at NetApp, on the challenges and opportunities of data-driven public health. Hines also offers a 3-progned approach to data management that enables state and local governments to address public health issues.

State and local governments stand at the forefront of protecting the health and well-being of the populations they serve. Using both structured and unstructured data, these agencies work to combat drug addiction in communities as well as outbreaks and health threats. State and local government agencies also use data to develop and implement telehealth programs to improve community health through targeted points of action.  To better understand the use of structured and unstructured data in flighting public health crises we sat down with Strategic Advisor for Healthcare, Lisa Hines, MBA, of NetApp.

“Data is no good, unless we use it,” shared Hines during our conversation. “While all that data collected by state and local government agencies is deposited in data lakes, it has no value until it’s analyzed and applied to solve the opioid crisis, contain a measles outbreak, or help us fight whatever the next public health crisis is.”

“The Department of Health and Human Services oversees funding of programs, but state and local governments run the day-to-day implementation of the systems and solutions that both store the data and make sense of it,” said Hines. “When the data is managed effectively, the information can be used to improve lives and care. But if it’s trapped in a silo, it’s of no use to anyone and the agencies can’t fulfill their missions.” Data lakes – the centralized repositories that store structured and unstructured data – are fueling accessibility and analysis, but proper management is key.

Here are Hines’s top three tips for state and local governments to successfully manage data lakes:

Protect the Data

Scalability and data protection are top concerns for any IT manager and when it comes to healthcare, that concern is magnified.  The mandates for guarding personally identifiable information (PII or PHI) require the highest levels of data protection, which are often a challenge. “Whether it is immunization records or prescribing and dispensing activities to manage the opioid crisis, all of these repositories collect a vast amount of sensitive data,” shared Hines. Coupled with exponential data growth, scale and security must be built into any system.  Hines recommends looking at  “solutions that can capture, store, and manage massive volumes of data securely, while also reducing IT costs and complexity.”

Build an Infrastructure to Transform Data into Insights

To successfully create an environment where data can feed valuable insights, agencies need systems able to effectively store and manage disparate data sets. Given the number of data sources and storage locations, and ideal infrastructure will be able to integrate a data pipeline from edge, to core, to cloud, while streamlining the flow of the data securely from on-premise to the cloud and back.  To that, agencies can then add robust artificial intelligence (AI) tools for analysis.

Leverage Knowledge to Improve Public Health Objectives

 “Massive amounts of data can quickly shift from a burden to an asset when the right technologies are put into place,” according to Hines. She points to the opioid crisis as an example. Data is being used to create drug monitoring programs, where physicians must report every time a controlled substance is prescribed to a patient. Leveraging artificial intelligence (AI) and machine learning (ML), the massive amounts of data collected in these types of repositories can be used to identify health indicators and drive population health management.  With the development of AI and ML algorithms and other high-performance analytics tools, this data informs, detects, and alerts decision makers of issues so they can quickly take action. Not only does it lower costs, but it improves care, patient outcomes, and community health.

Take the First Step: Meet NetApp at HIMSS20

To continue the conversation about how NetApp can help you simplify and modernize data management, stop by Booth #7347 at HIMSS20.

 

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