One of the biggest misconceptions amongst business and clinical leaders in healthcare is the notion that most organizations have an enterprise data warehouse. Let me be the bearer of bad news – they don’t, which means you also may not. There are very few organizations that actually have a true enterprise data warehouse; that is, a place where all of their data is integrated and modeled for analysis, from source systems across the organization independent of care settings, technology platform, how it’s collected, or how it’s used. Some organizations have data warehouses, but these are often limited to the vendor source system they’re sitting on and the data within the vendor application (i.e., McKesson’s HBI and Epic’s Clarity). This means that you are warehousing data from only one source and thus only analyzing and making decisions from one piece of a big puzzle. I’d also bet that the data you’ve started integrating is financial and maybe operational. I understand, save the hard stuff (quality and clinical data) for last.
This misconception is not limited to a single group in healthcare. I’ve heard this from OR Managers, Patient Safety & Quality staff, Service Line Directors, physicians, nurses, and executives.
You say, “Yes we have a data warehouse”…
I say, “Tell me some of the benefits” and “what is your ROI in this technology?”
So, what is it? Can you provide quantitative evidence of the benefits you’ve realized from your investment and use of your “data warehouse”? If you’re struggling, consider this:
- When you ask for a performance metric, say Length of Stay (LOS), do you get the same results every time you ask independent of where your supporting data came from or who you asked?
- Do you have to ask for pieces of information from disparate places or “data handlers” in order to answer your questions? A report from an analyst; a spreadsheet from a source system SME, a tweak here and a tweak there and Voila! A number whose calculation you can’t easily recreate, that changes over time, and requires proprietary knowledge from the report writer to produce.
- What is the loss in your productivity, as a manager or decision maker, in getting access to this data? More importantly, how much time do you have left to actually analyze, understand and act on the data once you’ve received it?
- Can you quickly and easily track, measure and report all patient data throughout the continuum of care? Clinical, quality, financial, and operational? Third-party collected (i.e., HCAHPS Patient Satisfaction)? Third-party calculated (i.e., CMS Core Measures)? Market share?
Aside from the loss in productivity and the manual, time-consuming process of piecing together data from disparate places and sources, a true enterprise data warehouse is a single version of the truth. Independent of the number of new applications and source systems you add, business rules you create, definitions you standardize, and analyses you perform, you will get the same answer every time. You can ask any question of an enterprise data warehouse. You don’t have to consider, “Wait, what source system will give me this data? And who knows how to get that data for me?”
In the event you do have an enterprise data warehouse, you should be seeing some of these benefits:
- Accurate and trusted, real–time, data-driven decision making
- Savings: Allocate and deploy resources for localized intervention ensuring the most efficient use of scare resources based upon trusted information available.
- Consistent definition and understanding of data and measures reported across the organization
- Savings: Less time and money spent resolving differences in how people report the same information from different source systems
- Strong master data – you have a single, consistent definition for a Patient, Provider, Location, Service Line, and Specialty.
- Savings: less time resolving differences in patient and provider identifiers when measuring performance; elimination of duplicate or incomplete patient records
- A return on the money you spend in your operating budget for analysts and decision support
- Savings: quantitative improvements from projects and initiatives targeted at clinical outcomes, cost reductions, lean process efficiencies, and others
- Savings: less time collecting data, more time analyzing and improving processes, operations and outcomes
- More informed and evidence-based negotiations with surgeons, anesthesiologists, payers, vendors, and suppliers
In the end, you want an enterprise data warehouse that can accommodate the enterprise data pipeline from when data is captured, through its transformations, to its consumption. Can yours?