Odds are you have analysts at your organization with expertise in your EHR systems, and others who can do a deep analysis of your financial and insurance claims data. But in the new world of accountable care, this simply isn’t enough.
Enterprise data warehousing is a data guru’s dream – all the information about your organization gathered in one place, open to a single set of analytical tools. Wouldn’t it be better if clinicians understood costs and financial execs understood patient care? Every stakeholder would have a clear understanding of how their decisions impact others. But how do you make the dream a reality?
Here are 4 steps to implementing an enterprise data warehouse.
1. Getting started
You’ve purchased an enterprise data warehouse (EDW). Now what? The first step is to plan your data warehouse system.
Deciding the data integration strategy of tables needed is challenging and can vary by organization.
Some organizations focus their EDW on gaining efficiencies, while others may choose to begin with a quality focus (such as population management).
No matter the approach, each has the same requirement. You need to determine the order of what data is required and understand legal use of the data and integration points.
You must understand what questions will be asked by users, because the purpose of an EDW is to provide decision-makers with the accurate, timely information they need to make the right choices.
Align your EDW with corporate-wide priorities set by your executive management team. This will ensure you’re on the right track and can guide the decisions for where to start.
Knowing what use cases are important to your organization, then breaking the use case down to data needed for BI reporting, makes it much easier to find what tables to begin with.
2. Resources for bringing data together
You’ve determined and prioritized the key value propositions. Now you should begin the process of resourcing the warehouse and use cases.
Enterprise data warehouse implementations need healthcare business intelligence, data experts and a team of dedicated resources for success. The right staffing levels and skill sets are needed to successfully launch an implementation.
Subject matter experts on the data can minimize rework in moving data sets into the warehouse. Having someone who understands the data and knows which core system to use to pull the data will help the speed of getting data into the warehouse and integrating it for reporting.
Profiling tools may also be needed. These tools can help you evaluate how the data is structured and determine key fields in the data set that you may want to show in your EDW.
And if you have a robust enterprise data warehouse, you’ll need a data architect. The data architect can assure compliance with the data model, determine where data transformation occurs and verify the model stays intact during build-out.
Data integration resources are needed to extract and load data from core systems to the enterprise data warehouse.
Having an expert in business intelligence design reports for users, paired with the ability for analysts to create reports on the fly, is part of the value of an EDW.
And with lots of business intelligence tools on the market, analysts can choose the best one that will allow them to thrive in the EDW setup. A recent article in HealthcareIT News about what to look for in a business intelligence expert reiterates these needs.
3. Project management
I can’t say enough about the need for communication to sponsors. Processes to update executive sponsors on progress should be routine. The HealthcareIT News article I referenced above also expresses a point that causes frustration early on in EDW implementation.
“Conceiving, launching and nurturing a business intelligence program that fits your big picture strategy but integrates into every facet of your organization is a time-consuming, incredibly challenging but ultimately rewarding endeavor.”
”Time-consuming” is the key word. It takes time for staff to understand the approach, their data and how the data should be stored for appropriate reporting. This is why talented, dedicated, focused resources are needed for implementation success.
4. Partnership for future support
Your choice for an enterprise data warehouse shouldn’t just be around price and implementation. It’s a long-term partnership for your EDW to support your efforts, even if core systems and technologies change. It’s important to partner with someone who has a track record in providing support for data analytics as well as infrastructure support.
Are you ready to enter the brave new world of enterprise data warehouses? To remain competitive, it’s time to start making plans.