Providers turn to information governance to overcome RCM challenges

Organizations such as Sharp Healthcare say using best practices for data to streamline processes and improve payment processes.


At Sharp Healthcare in San Diego, data is worth more than all of the organization’s physical assets combined—an estimated $40 billion. It has hundreds of data and personal health information sources. And 24 different systems—each with different structures, interfaces and users—touch the revenue cycle.

The organization already had a dedicated master patient index department that had been cleaning up patient data for a long time. But it needed to go further with an enterprise-wide system to manage information-based assets irrespective of format.

That means specifying “decision rights and an accountability framework to ensure appropriate behavior in the valuation, creation, storage, use, archiving and deletion of information,” according to one frequently-cited definition put forth by Gartner, a healthcare research and consulting firm Gartner. “It includes the processes, roles and policies, standards and metrics that ensure the effective and efficient use of information in enabling an organization to achieve its goals.”

“Having a better, cleaner data set really did translate into better patient care, better patient information and quicker response times,” says Lori Moore, Sharp’s director of data governance. “Think about how many accidents happen inside of hospitals … You know that better patient data is going to save lives, [and] it gave us an opportunity to move the dial on what we could do with our data by first cleaning it.”

Further, says Kathy Downing, vice president of information governance at the American Health Information Management Association (AHIMA), organizations that invest in information governance will have a competitive advantage both short-term and long-term, because they’ll have the “agility and ability to make business decisions based on that trusted data.” Organizations that don’t invest in information governance, she warns, will be left in the dust by others.

“It’s probably one of the most difficult practices that all of healthcare faces,” Moore says. “Healthcare comes with a set of complications that directly affects people in a profound way. Data governance is very difficult but worthwhile—and it pays you back in spades.”

Master the patient data

One function of Sharp’s data governance program office is master-data management, which includes the master lists of patients, providers, locations and organizations. It has a direct impact on revenue, payer relationships, patient billing, which in turn affects the patient experience.

Take, for example, insurance verification. It’s not unusual to find that a payer has a different name for a patient than Sharp does, says Gerilynn Sevenikar, vice president of revenue cycle for Sharp. “That creates a conflict for us. We want the integrity of our patient file to be as sure and as true as possible. But if I submit that claim with what I know to be the legal name of a patient, it will get rejected.”

Sharp has worked to solve that problem in a more efficient way than in the past. The old way: Create a temporary patient identification record for the sole purpose of billing. Staff would update information in the patient record to match the payer’s record, send the bill, then go back into the patient record to change it back to what they knew was the correct information. It wasn’t just inefficient and time-consuming: Changing a record repeatedly only introduces more opportunities for human error.

So Sharp added a field on encounter records with the payer’s version of the patient’s information. That allowed the organization to maintain its own records and meet the payer’s needs.

The change didn’t reduce initial rejections because of a mismatched name. It eliminated them.

And that’s a perfect example of how data governance, a subset of information governance, can pay off for an organization. “It’s OK to have multiple names attached to a single patient as long as you’re defining them separately and using them consistently,” Moore says.

Gauge data quality

From email address to legal name, and date of birth to whether or not a patient is still living, ensuring data accuracy is no easy task. “I’d love to tell you that we have pristine, gorgeous clearwater data,” Moore says. “But medical data is human-created and therefore inherently flawed.”

At Sharp, the front desk asks for a patient’s email address every time a patient checks in. Email is great for sending appointment reminders, but it also helps the revenue cycle: Sharp uses it to gather demographic and insurance information before the patient arrives, further reducing rejected claims.

The organization also embarked on a record cleanup, identifying parameters to determine whether a patient is likely deceased, for example. A check of the records found 8 percent of patients in just one of the organization’s electronic health records were identified as being 120 years or older, so they started there and furthered narrowed the definition by looking at how long it had been since that patient was treated. “Deactivating records gives us a much cleaner view of our patient population and master patient index,” Sevenikar says.

Identify stewards

Sharp’s data governance office also has a policy and procedures arm, which manages roles, responsibilities and data stewardship.

“Standardization of policy and procedure is probably one of the hardest things we do,” Moore says. “We are tackling that through a new data stewardship structure, which will have representation from all of our major stakeholders. They have not only a voice but also a responsibility.”

Data stewards represent their department or their group or their organization's needs for the collective, but when there is, say, a data quality issue, they also have a responsibility to remediate it in their system. They need to be responsible for good data care, quality and practices in their “hometown,” Moore says. “You can’t have a voice without having that responsibility.”

When looking for data stewards, Downing says, start with business process data owners, such as compliance officers, corporate legal staff or chief medical information officers.

Find a springboard

“Cleaning up patient data [is] massive, and finding a place to start is really hard,” Moore says. But you don’t have to do it all at once, she adds. “Just start somewhere. You don’t need a dedicated resource. If you can’t get a full program, that’s OK,” Moore says. “You’re probably closer to data governance than you think you are.”

Downing agrees. “I never want people to feel like they’re starting at ground zero. Right now, every organization is doing some sort of data governance whether they’re calling it that or not,” she says. She suggests taking stock of what policies are already in place, building on existing programs and tapping into existing workgroups, especially multidisciplinary committees that are already looking at information management or electronic records systems. “We really need that coordination and planning to execute on these data governance initiatives,” she says.

“Just start somewhere. You don’t need dedicated resources. If you can’t get a full program, that’s OK,” Moore says. “You’re probably closer to data governance than you think you are. Find your window and go through.”

“Decide what you’re going to focus on and build your roadmap; otherwise, it feels like this is a project that is never going to end,” Downing adds.

Rebranded initiative

Sometimes, opportunities to improve information governance arise organically. The University of Washington is preparing to implement a single electronic health record across its various settings, which include four hospitals, a physician group, and several community clinics and urgent care centers. UW Medicine is part of an AHIMA information governance pilot program and recently rebranded its HIM department to the more encompassing Department of Enterprise Records and Health Information.

“We were already doing information governance, but it wasn’t as broad as we needed it to be,” says Sally Beahan, the department’s senior director. The new name “better describes the work we do, because it’s all records across the organization, not just medical records.”

The department falls under revenue cycle and reports up to the CFO. But it’s also working closely with the IT side of the house. “When I think of data management I think of something unique and data-driven,” says Christine Taylor, director of information governance and integrity.

“But we’re about content—it doesn’t matter what format that content is in. We’re talking about integrity in the authentic record … We hope to help IT come up with some of those standards for data management.”

As it began the journey to a single EHR, UW Medicine took the opportunity to standardize documents and approaches for tasks such as patient matching. “We’re finding ways to collaborate across functional units within the medical center so we can come to some standard approach to patient identity,” Taylor says.

The UW team takes a grassroots approach to outreach and collaboration, looking for opportunities to describe how good information governance could have helped avoid a problem, for example. “We’ve been planting those seeds without being condescending or to say ‘we should have known that,’ ” Taylor says. “But to say ‘this won’t happen when we have good governance.’ ”

Successful communication requires collaboration, explaining why it’s important and customizing messaging, Beahan says. Some stakeholders might not respond to talk about obligations under the public records act, for example. But most will understand the importance of minimizing risk, complying with laws and better managing records. “Telling a horror story or two is helpful,” she adds.

“What we’ve learned is you have to say something several times, several different ways,” Taylor says. “We might have to describe why many different ways on many different levels, in a way that appeals to the individual.”

Measure the payoff

Sometimes the ROI of information and information and data governance is intuitive—it just makes sense. Fewer denials means less time spent re-submitting claims. Having up-to-date emails and eliminating out-of-date records saves the cost of paper and postage. More accurate data means better data analytics, which leads to better care for patients, which leads to fewer adverse events, costly readmissions or duplicate diagnostic tests.

Still, it isn’t always easy to quantify the financial return on investment.

For UW Medicine’s information governance team, they have promised—and plan to deliver—greater efficiency, higher productivity and reduced administrative burden and manual tasks. Time, after all, is money.

“It allows us to turn some of these traditional ways of looking at things on their head,” Taylor says. “It’s a different path to take to create efficiencies and increase productivity. We want to do what’s best for patients and for budgets.”

More for you

Loading data for hdm_tax_topic #better-outcomes...