Data Governance Required For Healthcare Data Warehouse
Before implementing its ambitious data warehouse, OhioHealth focused on data governance to ensure data is accurate, clean, and usable.
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For decades, the data OhioHealth staff collected resided in silos spread across its 10 hospitals and countless departments. Two years ago, the nonprofit healthcare organization began investing in data governance and an enterprise data warehouse to cleanse and safely store data so business users could access, analyze, and act on the critical information.
The advent of electronic health records (EHRs), e-prescriptions, accountable care organizations, and value-based payments that demand analysis of cost versus quality meant the family of eight hospitals and about 55 healthcare organizations could no longer continue treating data in this manner, said Dr. Mrunal Shah, a practicing physician and system VP for healthcare informatics at OhioHealth. It also meant the organization could not advance without a data warehouse -- a trusted, secure central repository for all information, he said in an interview.
Digging into data governance Data governance provides a set of rules and a framework to ensure data is accurate and current, contain no duplicates, and are treated correctly. Unreliable, incomplete, or poor-quality data cost organizations between 15% and 20% of their operating budgets, according to the US Insurance Data Management Association.
With more data pouring in via EHRs and rules related to the Affordable Care Act and other regulations, healthcare's existing lag in data-governance use will grow if organizations don't get moving, according to experts. With healthcare providers considering how to incorporate even more information from medical devices ranging from implants to fitness trackers, it's even more vital for them to figure out governance. Healthcare already has a reputation for being behind in big-data use, a tool vital for healthcare providers' ability to reduce costs while simultaneously improving performance. Using big data could slash healthcare spending between $300 billion and $450 billion, according to management consulting firm McKinsey.
Data warehouses demand more than a database investment, however. To succeed, organizations must achieve departmental buy-in, develop strong guidelines, and spend time developing a governance plan, Dr. Jyoti Kamal, chief data scientist at Health Care Dataworks, told us.
OhioHealth's plan Recognizing the benefits of a comprehensive database and the access it would give employees to analytics and big data, OhioHealth committed to investing in a data warehouse. To build consensus for the software, Shah created a data-governance committee headed by a business executive -- not the CIO or other IT leader -- to analyze the data definitions for the initial stages of its data-governance process, he said.
"Then it's a project that the business side has a stake in," says Shah. "The value, ultimately, is to the business people. If they are in it, part of their ownership is in the project this way."
OhioHealth's CMO headed the executive committee, working closely with Shah and his team. Leadership buy-in was critical to success, he says. It's vital for executives to make time for data-governance meetings to discuss build versus buy, the organization's existing data governance and storage policies, and implementation plans, Shah. Department managers also worried about losing staff due to new efficiencies, an unrealistic concern since employees became more efficient, not jeopardized, he says.
Also critical was determining how leaders explain and demonstrate the
Alison Diana has written about technology and business for more than 20 years. She was editor, contributors, at Internet Evolution; editor-in-chief of 21st Century IT; and managing editor, sections, at CRN. She has also written for eWeek, Baseline Magazine, Redmond Channel ... View Full Bio
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