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April 29, 2015 01:00 AM

Time to clean up our data act

Bruce Johnson
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    Johnson

    Let's face it, we're in an era of healthcare where accountability is permeating all phases of the business. It's not just accountable care or accountability for outcomes. It also includes accountability for the decisions being made about the efficacy of our capital investments.

    We see how challenging it is for hospitals as they work to prove meaningful use of their information technology systems. “Big data” is no longer a buzzword, but it's still difficult to realize the promised benefits in healthcare. The ability to analyze massive amounts of data for improved outcomes, both financial and clinical, has a limitation: inaccurate data. Bad data, or dirty data as it is often called, are the Achilles heel of actionable information. Unfortunately, in healthcare, there's too much of it.

    One of the centerpieces of healthcare data today is the electronic health record. The investment in these systems is significant, often costing hospitals and health systems multimillions of dollars. That's because implementation costs are between two to three times the software costs. One reason that EHRs are so important, beyond the potential for clinical gains and the essential requirement to digitize health records, is that they provide an opportunity for reimbursement improvement and revenue growth.

    These systems are all about information, and unfortunately because of the typical quality of EHR data (from care plans and daily progress notes to implant product information), providers cannot uniformly trust their output for evaluating products' clinical effectiveness and securing reimbursements. There is simply too much erroneous billing and product data. From a clinical perspective, imagine 500 different clinicians charting patient information. The probability of normalized data (i.e., data that is standardized across all fields, using a common language) required for big data analysis is low. Proving meaningful use and improved outcomes needs both accurate product and patient information.

    Exacerbating the challenge is the sheer volume of data a facility must maintain and the ongoing data churn. On average, changes are made each year to one-third of the 30 million-plus medical-surgical products on the U.S. market. For example, our firsthand experience at GHX is that dirty data contribute to over 2 million transactional errors each month. We're also making corrections to hospital databases at a rate of 192,000 edits each month. Maintaining data integrity and accuracy is a significant challenge. Many organizations are implementing product data-standardization initiatives in tandem with EHR implementations, using separate teams. Conducting these initiatives together will net the best result.

    Hospital leaders know that not having complete and accurate data is holding them back from the potential to experience significant progress in delivering accountable and informed care. Critically important to this discussion is understanding that having this information reduces costs. Every time someone assigns the wrong charge codes, revenue could be lost and cash flow could be affected.

    Cleaning up the data is critical. What does that look like? From my perspective, it starts through collaboration with an organization's supply-chain team to ensure that enterprise resource-planning systems and EHRs are tightly integrated, and that complete and accurate product data are feeding the EHR. Establish a master data management strategy through which product data are cleansed and corrected. Enrich item master data by assigning charge codes to the products procured. Only then can hospitals accurately and efficiently improve product categorization and reimbursement accuracy.

    Finally, hospitals should implement a virtual-item master to continually monitor for changes and updates, and then systematically correct product data inaccuracies.

    So much opportunity exists to get healthcare right and demonstrate the efficacy of health IT investments for improved healthcare outcomes. Dirty data should not be the thing that's holding us back.

    Bruce Johnson is CEO at GHX, a supply chain management company based in Louisville, Colo.

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