Healthcare business intelligence enjoys growing acceptance by providers, but adoption rates are still surprisingly low. We review the reasons why and how you can avoid the pitfalls that can sabotage your HBI implementation.
U.S. Healthcare Organizations Still Reluctant to Take BI Action
In 2015, HIMSS Analytics found that while adoption was on the rise, at the time only 52 percent of U.S. healthcare organizations were using some form of clinical and business intelligence solution. So, in spite of awareness of BI products and benefits, about half of U.S. healthcare organizations are still standing on the sidelines of BI use. What’s happening?
Tom Lawry, director, worldwide health at Microsoft provides a useful perspective. “Frankly, the technology is the easy part. The real challenge is getting people to think and act and work differently. Nowadays, many more [healthcare organizations] are moving from old data, old processes, to real-time, predictive analytics, driving toward self-service or research-on-demand.”
James Gaston, senior director of maturity models at HIMSS Analytics, comments on the modest but steady progress healthcare providers are making in adopting BI tools and methodologies. “[American healthcare] providers are using what they have on hand and are beginning to find their way around their data. We’re still at the point where we’re trying to develop analytical skills and capabilities, and this hasn’t been broadly operationalized yet.”
Start with the Right People, Processes for Healthcare BI Success
When the time comes to move forward with implementing a healthcare analytics system at your organization (or if you’ve already started), there are plenty of things you can do. Here’s our lineup of best practices gleaned from successful HBI implementations and industry experts.
Develop a first-things-first approach.
The “Crawl first, then walk, then run” philosophy was highlighted in this article. In it, experienced healthcare IT specialists such as Shahid Shaw argued that it pays to square away basic processes such as data quality assurance and building a BI analytics team before starting to use BI tools and methods.
For example, developing and following reporting procedures might be old hat for healthcare organizations. But many clinical reporting and quality assurance measures are new and require strict adherence to procedures to ensure data accuracy. Practice here can help you avoid compliance fines caused by rookie mistakes.
Think of all the practical things that support the analytics process. How to report data accurately, automating data reporting processes and constantly cross-checking data in canned reports against your data warehouse are just a few. This is not exciting stuff. But when you master the practical tasks, there’s a much better chance that your analyses will be accurate.
Get executive and stakeholder buy-in.
Part of the reason adoption rates are low is a lack of confidence in BI tools and methods. Successful business intelligence projects require making your hospital or facility a data-driven organization, and to do so the initiative must either come from the top, or at the very least enhoy the support of the organization’s top brass. It’s not enough to have the tools in place – for people to actually use them they need to understand the value and potential of analyzing and visualizing healthcare data, and this could require a culturul change that must be facilitated by upper management.
Select the right people for your BI team.
Yes, careful, methodical planning of an analytical project can position your organization for success. But you should never underestimate the importance of the human element: create a skilled and effective group of people who know their data and want to use it to improve decision-making processes, and who enjoy digging into the data to find new insights.
Start with people who have empathy for patients and excellent communications and management skills. These are the folks who know that the real bottom line is serving people. And don’t forget your organization’s BI evangelists. Your organization is likely to have at least one. They’re the folks who are passionate about BI and how it can save time, money and lives.
When you mix professionals with varied backgrounds, you are more likely to get your priorities straight—people, then processes, then technology.
Make sure you analyze the right data.
You have a mountain of data that’s growing every day. The siren song of big data might tempt you to “put it to good use” and analyze it as quickly as you can.
Don’t do it. Instead, ask yourself—are you analyzing data that addresses a strategic healthcare problem? Or, are you analyzing data that’s easy to obtain? It’s all about getting answers to questions that matter the most to patient care and efficient operations at your facility.
Steven Escaravage and Joachim Roski, principals at Booz Allen, have discovered that, “When organizations develop a ‘weighted data wish list’ and allocate their resources toward acquiring high-impact data sources as well as easy-to-acquire sources, they discover greater returns on their big data investment.”
Simplify the business intelligence process.
A no-brainer? Perhaps. But when it’s time to select a healthcare analytics solution, it makes sense to choose one that makes data easy to understand and use, and that will enable medical and administrative staff to perform their own data analysis without over-reliance on IT. There’s a strong connection between ease of use and successful adoption. So, think of your analytical dashboards as more than eye candy. They are the eyes into your medical data and operations.
3 Common HBI Implementation Gotchas to Avoid
What about the other recommendations, the please-don’t-do-this items that could destroy the chances of your HBI implementation’s success? Similarly to the recommendations described earlier, they also involve people, processes and technology elements of your implementation.
Viewing business intelligence applications as the latest in a long line of reporting tools.
This oldie but goodie can severely limit the capabilities and value that your initiative delivers. Make sure that everyone—including key executives and stakeholders—understand the core capabilities and value that end-to-end business analytics functions can deliver, such as the ability to combine data from multiple disparate sources for deeper analytical insight. That way, everyone knows how the tool works and more importantly, delivers value to your organization.
Jumping into the data before deciding on your use cases.
Given the availability of nifty BI platforms with self-service analytics, it’s easy to take very deep dives into data that provide information but very little value. Self-service tools are powerful, so define your objectives and medical or business questions you want answered before you start analyzing. If you don’t know what you’re asking, you won’t get answers to questions that matter.
Limiting your HBI team to techies.
If you believe that healthcare analytics initiatives are should be owned by technical specialists alone, think again. IT specialists, no matter how skilled or experienced they might be, can’t understand your operations from provider and patient points of view as well as your clinical staff.
That’s why it’s critical to have clinical and operational professionals on the HBI team. This added point of view will deliver big dividends when you move to a value-for-performance environment.
Need help selling the concept of healthcare analytics in your organization? Check out our free whitepaper: 5 Valuable Insights Healthcare Companies Find in their Big Data, or read about how healthcare can tackle big changes with business intelligence.