Why healthcare needs governance for information and not just for data
As with the terms telehealth and telemedicine, there is some debate about data governance versus information governance and whether they are interchangeable or have distinct definitions.
Opinions vary, but the majority view of those working in the analytics field is that each term has its own identity and meaning.
In manufacturing parlance, data is raw material, while information is the finished product. Both have governance procedures specific to their state in cyberspace.
"We are all collecting data, but if it has no value, it is not considered information," said Eric Rock, CEO for Plano, Texas-based Vivify Health. "Information is the true value, an outcome from the data. Governance is not just how to store, secure and ensure data is scalable, but is available to apply it. How to maintain, deliver and secure data – all of those components should be considered governance."
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Data governance and information governance may be separate terms, but the definitions "overlay with one another," observed Mark Heinemeyer, chief collaboration officer for San Francisco-based Wanda.
"One could say information governance tends to be more of a multi-disciplinary approach, as opposed to data governance, which tends to be more focused on handling data points, depending on what you do with it," he said. "Information can be broader, going beyond legal and regulatory and into operational requirements."
Heinemeyer sees the role of governance as "having a set of procedures and a plan – observable and auditable – to ensure the security" of both data and information. How data governance has evolved isn't an easy narrative, he said, because "I don't know if it actually has evolved or if it has just come under greater scrutiny with levels of adherence."
In analyzing data types, Heinemeyer breaks it down into three basic categories: Retrospective, real time and behavioral data.
Retrospective data includes claims and clinical data from electronic health records; real-time data includes remote monitoring of patients in the home and from the active care process; behavioral data provides insight into how patient behavior can improve outcomes.
In evaluating how each category of data relates to governance, Heinemeyer calls retroactive data "limited," and real-time data "valuable, but limited unless there is behavioral understanding." The greatest risk factor in any care plan is adherence, he said, adding "all the analytics are understandable, but behavioral data makes it actionable."
Actionable data can be trends in patient outcomes, a community's spikes in acute illnesses and best options for treatment plans, offered Adrianna Iorillo, vice president of professional services for Jacksonville, Florida-based CSI Healthcare IT. Conversely, she said discrete data entered accurately can attribute to improved billing processes and reduced claim or patient statement errors that take costly resources to remedy.
Retrospective and real-time data can also be considered part of traditional episodic data "and the opportunity to collect it is more abundant than ever before," Rock said. Aggregating episodic data from patients "tells a story that goes well beyond those episodic moments and that is an opportunity for data governance."
David Delaney, MD, chief medical officer for SAP America, sees data governance as "more granular, validating provenance and degree of trust." When amalgamating information across systems, the data element is "the unstructured format, the raw commodity," while information "drives from data governance origination and interpretation."
The genesis of data governance stems from the era of data warehousing – taking data from different sources and understanding the underlying meaning, Delaney said.
"It was understanding the core data and managing it across the enterprise," he said. "The challenge is in getting apples-to-apples comparisons."
The American Health Information Management Association defines information governance as "an organization wide framework for managing information throughout its lifecycle and supporting the organization's strategy, operations, regulatory, legal, risk and environmental requirements."
That lofty description outlines the ambitious job that is waiting to be done at many healthcare organizations.
Iorillo, said the concept is not a new one – it's just new to healthcare. Other industries such as banking, finance, military, and pharmaceuticals have all embraced information governance as they have dealt with big data for much longer than healthcare.
Now it is the healthcare industry's turn to tackle information governance, spurred by "pressure from the ongoing explosion of data in the electronic health record," said Kathy Downing, director of health information management practice excellence at AHIMA. A sound information governance program, assembled and executed properly, she said, will bring lower costs, risk reductions, more accurate payments and regulatory compliance – a favorable competitive advantage in the marketplace for every healthcare organization that has it.
"Our data is expanding exponentially and the details can make us or break us," Downing said. "With the right governance strategy, information from that data can help us make the right decisions across every area of the healthcare organization."
Iorillo maintains that information governance is an offshoot of medical records management. "It is the next phase in the original goals of creating a structure around medical record keeping." And though not a new concept, "the application and purpose of it have evolved as technology has advanced rapidly over the past few years," she said.
Conceptually, Iorillo said information governance has developed to meet the challenges of security in electronic data and has matured to encompass every phase of data in a system, including data entry, maintenance and usage of data for business and healthcare purposes, medical record storage and information disposal.
"The healthcare industry is constantly in flux to respond to governmental and environmental changes in how data is collected, utilized, stored and protected," she said. "Regulatory changes define what needs to be transmitted, what threats to security affect encryption standards, how patient visit types will alter what data is shared, how government standards alter what data is reported and how business projections will alter what financial data is gathered to create actionable items for operations."
Governance will be among the topics at the HIMSS and Healthcare IT News Big Data & Analytics Forum in Boston, Oct. 24-25. What to expect:
⇒ Charlotte hospitals analyze social determinants of health to cut ER visits
⇒ Big Data: Healthcare must move beyond the hype
⇒ Tips for reading Big Data results correctly
⇒ Small hospital makes minor investment in analytics and reaps big rewards
⇒ MIT professor's quick primer on two types of machine learning for healthcare
⇒ Must-haves for machine learning to thrive in healthcare