Challenges with extracting and using data

Professionals from MCIS address common gripes about EHRs in this exclusive Q&A series. This is the fourth of five questions that will be answered by MCIS in the coming months.

What are the most common stumbling blocks for extracting data from an EHR to create usable and actionable information?

Extracting the data

“Extracting large amounts of data can be expensive and time-consuming,” says Kate Konitzer, chief informatics architect, Marshfield Clinic Information Services in Wisconsin. Konitzer says that some warehouses update their data monthly or even quarterly, while few EHRs extract data that takes at least 48 hours.

Konitzer says that once the data is in the data warehouse, it has to be normalized to remove any inconsistencies in the data because EHRs don’t always follow the same set of standards, which adds time and expense to the process. Additionally, some organizations use multiple EHRs, so extracting data from more than one place and knowing the single source of truth further complicates the process.

Using the data

Once data has been normalized, it is ready for analysis, either via a query or via business intelligence (BI) tool.

However BI tools can still pose a challenge for those wanting to use the data in their practice because most users aren’t considered super users — and are unable to proficiently use the BI tools when they need to.

Casual users often aren’t able to use advanced BI tools they’re given, which can be frustrating to administrative staff and physicians who don’t have time to query and re-learn the tools every time they want to query that data, Konitzer says, “So you almost have to be trained every time you use the tool.”

Konitzer says you need a technical staff to put a framework together to support data-driven initiatives such as accountable care organization (ACO) requirements. Although BI tools are making good progress, Konitzer says, your EHR vendor should be able to help you facilitate access to your data and provide easy to use reporting modules.

Finding a solution

MCIS has put a population health framework in place within the EHR, delivering data in real time in a format that is usable. Real-time availability of data is the difference in supporting care teams to provide effective care to the population of patients they serve.

“With analytics, it starts with one question and leads to five more, says Konitzer, which is why you want that framework in place to answer a robust set of questions on the front end."

For example, a population health framework might answer the question, “Who are my diabetic patients with their A1c not at goal?” Once that question is incorporated into the framework, you can assume which questions would follow, Konitzer says, such as “Which of those patients have results at 8% versus 10%? Are they scheduled for a follow-up visit?”

Moving to real-time analytics is challenging, but obtainable. Gaining accurate, real-time insight out of data collected in your EHR is key.