Data Governance: How Hospitals Can Overcome The 3 Biggest Challenges

By George Dealy, Vice President of Healthcare Applications at Dimensional Insight

Big Data and analytics are among the hottest topics being discussed within healthcare right now, and for good reason. The proliferation of information has begun to alter the way both providers and patients view healthcare information. Financial, operational, and clinical data have all become crucial assets in helping hospitals transition from traditional fee-for-service to value-based care models, where healthcare entities are being reimbursed for the quality of care that they provide rather than the quantity.

In order to succeed in this transition, hospitals have begun to compile enormous amounts of data to pinpoint where improvements can be made and costs can be reduced. Data by itself however, no matter the size and scope, is of limited value. Both data and the metadata that defines what it is and how it is intended to be used, need to be carefully and formally managed across the healthcare enterprise to ensure integrity of information and appropriateness of use. That’s the real goal of data governance.

An effective, yet practical approach to data governance is essential for any hospital hoping to successfully navigate the transition into the world of quality-based care. The information available as a result of governance processes represents the foundation for data driven decision making. If the governance is good, there’s at least an opportunity to make good decisions. Without it, the quality of decisions will likely be compromised.

As critical as this may be, many organizations haven’t yet reached an adequate level of data governance maturity. A 2015 Deloitte report found that less than half of hospitals surveyed had a clear, integrated data and analytics strategies in place, while another 25 percent had no data governance model at all. But why?

Though it’s not a new concept, many hospitals have been slow to adopt data governance strategies due to the many obstacles associated with implementation. While implementing effective data governance will likely pose challenges for any organization, hospitals and health systems that lack a data-centric culture face the biggest hurdles.

Below are three of the most significant challenges associated with data governance and three proven approaches that healthcare leaders can use to overcome them.

Challenge 1: Leadership Mishap

Because the importance of Big Data and analytics has risen so quickly, some organizations lack leaders who are data-savvy and comfortable making data-driven decisions. Information technology and hospital executives may be unable to provide the necessary support and guidance to build the foundation for a data governance strategy because they themselves lack the necessary tools and knowledge. They may also provide conflicting direction resulting in division and confusion within the organization. Without this foundation of governance and good data, decisions are made with incomplete, and often unreliable, information. Without confidence in their data, executives, front-line and back-office workers alike will understandably revert to their gut instincts.

• Solution: Building an effective data governance foundation doesn’t need to be complicated, nor does it need to be done all at once. Start by identifying the information that is most critical to achieving strategic goals and important tactical objectives. Unfortunately, regulatory compliance tends to consume an inordinate amount of the data management, reporting and analytics resources that are critical to defining good governance and producing relevant information. Given this, it’s critical to dedicate a sufficient amount of leaderships’ time and energy to determining priorities and then holding the organization accountable for progress. Start with a limited number of important, but attainable, initiatives to prove what’s possible. Then build on your success. If you aren’t confident that you can pull this off with your own resources, retain outside help from experienced and reputable professionals who have a proven record of success in helping organizations to reach their governance goals.

Challenge 2: Lack of Resources

While getting a good data governance strategy in place is an important initial step, it’s the day-to-day execution that actually leads to results. The technology necessary to help with this is evolving rapidly. But because large, complex and varied datasets have emerged fairly recently, with the rise of electronic health records systems, the skill sets necessary to build and maintain the systems that implement governance are relatively scarce. You may be able to find outside resources to help, but they won’t necessarily know your business and culture. Additionally, you want to be in control of your own destiny when it comes to something as important as the information you rely on to make your most crucial decisions.

• Solution: The approach with the highest long term return lies in building a knowledge-driven culture from within. Take advantage of external training and opportunities for peer interactions to help the people on your staff who already understand your organization drive the governance and implementation processes forward. Many organizations have already been successful in these areas and are typically willing to share what they’ve learned — and even help you avoid the mistakes they’ve previously made. Assigning a small, core team to work on the initial governance and implementation projects will serve to both build knowledge and instill confidence. Success breeds excitement and optimism, so do everything you can to ensure it. From there, you can incrementally expand the team as necessary. You’ll find that your most talented people will want in.

Challenge 3: Fragmented Trust

Healthcare data is notoriously complex. But mastering it is essential to developing high levels of decision making competency. That starts with ensuring that your information is well understood, relevant, reliable and timely. But is also requires that staff throughout the enterprise know how to take advantage of that information to guide their decisions. Both low confidence in information and a lack of skills or willingness to use it will derail even the best governance strategy. Perfect information is essentially useless if it’s not used to improve the quality of decisions — and ultimately the willingness of the organization to embrace data-driven decision making.

• Solution: Unfortunately there aren’t any good shortcuts for getting to good data. It’s hard work and requires a great deal of perseverance. However, good data governance will at least ensure that you have a destination to drive toward. Once you’ve arrived, it’s critical to make the information that represents the fruits of your labor available to the people in your organization who can best take advantage of it. If you’ve executed well on your governance strategy, they’ll have a good understanding of what data they can use, what it means and how it fits in with what they do. Combining it with intuitive analytical capabilities will likely get them excited about the treasure trove of information they now have at their disposal.

No doubt, taking on data governance and the ensuing implementation work will test the mettle of the entire enterprise. But not taking it seriously now will compromise your ability to make truly data-driven decisions when it becomes most important. Taking even small, well calculated steps now will pay future dividends in your organization’s confidence in its information and ability to capitalize on it.

About The Author

George Dealy is a veteran healthcare information technology leader with more than 25 years’ experience helping organizations design, develop, and implement innovative commercial software solutions. As vice president of healthcare applications at Dimensional Insight, George is responsible for product direction in the healthcare market. His previous work experience with companies such as PatientKeeper, Epiphany and Sybase provides George with a unique perspective on the challenges organizations face in effectively distributing business-critical information to varied user sets. George holds a master’s degree in computer science from Union College and a bachelor’s in applied economics from Cornell University.