In the first part of this two-part series, we provided an overview of data analytics and business intelligence, and then discussed ways business intelligence systems can and will be used in ASCs. In this second part, we will discuss the different types of business intelligence vendors, how to choose the right one for your ASC and then ways to maximize the benefits of business intelligence.
Business intelligence (BI) technology has become a staple of performance improvement systems. Many different systems provide views into the high-level, foundational metrics that ASCs are required to track and measure today. Separating the winners from the losers often comes down to their service offerings — how they work with you to connect BI applications to your current systems, configure them to deliver the insight you need and train your staff how to use them.
For an ASC, this means it's important to identify the right vendor providing the right mix of services to get the most value from BI, says Amit Jiwani, director of analytics for AmkaiSolutions.
Vendor types: understanding BI options
There are primarily three different types of BI vendors for ASCs to choose from.
Questions to ask
The following are 10 questions Mr. Jiwani recommends ASCs consider asking vendors when evaluating the analytics capabilities of a perioperative practice management or electronic medical record:
1. What key performance metrics are provided and trackable that will help achieve the following OR goals:
• operational efficiency
• clinical excellence
• financial optimization
2. Will the user have the ability to monitor key metrics and drill down into their component building blocks and identify root causes of problems or improvements?
3. How far back historically can data be used to develop key metrics?
4. Can the solution aggregate data for cases performed today or is there a waiting period?
5. How often is the clinical and operational data reloaded?
6. What clinical data elements are automatically generated or can be collected in a discrete format?
7. Can the solution be deployed via a mobile client?
8. Are there push notifications available for user-defined events?
9. Can the analytics system display the future case schedule and resources required for these cases?
10. Which key metrics are calculated based on future case load, and what criteria are used to determine these metrics?
Putting BI to work in your ASC
Generating better outcomes — financial and clinical — requires both insight and action. Armed with valid information, your leadership team should be prepared to work together with your staff to build awareness and execute improvement plans.
A member of the executive team can take ownership of advanced data gathering and implementing changes based on identified issues. Whether this person is on the operational or medical leadership side, he or she should be empowered to drive change and achieve answers. Individuals can sometimes hold back from asking questions because they think their questions are too difficult to answer or that it won't be possible to change from the status quo, so be prepared to help them see what's possible.
"There's a natural culture change that happens when moving from reporting to analytics," says Mr. Jiwani. "It's an opportunity to get answers to the more difficult, follow-up questions that often come with static reports — and that lead to advancement and growth."
The good news is, from a technology standpoint, using BI gets easier and becomes second nature very quickly. Once ASC learn how to extract the data and transform it into a meaningful schema, business and clinical leaders can begin to interact with their numbers and explore their performance. This can lead to some very meaningful epiphanies.
"The technology is getting better, faster and stronger," says Mr. Jiwani. "As analytics takes a deeper hold into the ambulatory surgery space, users are beginning to ask more advanced questions and get deeper insights into their businesses. Today they might look at case volumes and accounts receivable, but over time the regulatory landscape will force us to change and analyze much of our operational and clinical data more closely."