Last week, we hosted one of our Executive Council meetings up in Park City, Utah. These meetings bring together executives from many of our client sites to discuss the challenges they’re facing and ways in which 3M Health Information Systems can help them achieve their goals. It wasn’t always easy keeping the group focused on the topics instead of the view of the snow-covered mountains through the window behind me, but when the subject of analytical needs came up, I had their attention. The discussion quickly turned to the challenges they face in getting the data needed to manage regulatory requirements, reduce costs, and improve quality of care. The client executives participating voiced a number of concerns, including:
– Difficulty in getting longitudinal data across the healthcare continuum
– Inability to get data from unstructured text within their EMR
– Limitations of claims data only
– Use of data to identify “avoidable care” so they can reduce costs and improve outcomes
– Data needed to manage compliance risk
Let’s dig into each of these a little deeper.
1. Difficulty in getting longitudinal data across the continuum
All those present voiced the need to have better data to manage/coordinate patient care, but with many physicians and facilities within their organizations using different EMR systems, and given the lack of standards, it’s often challenging to get data that’s useful. Many facilities have resorted to building their own data warehouse to solve this issue. Even so, the lack of standards creates additional work to make the data useful.
2. Inability to get data from unstructured text within an EMR
The executives noted physician frustration with documentation templates and voiced a need for free text sections that capture information such as the patient history of present illness, medical decision making, and treatment plans that failed prior to admission. Although many facilities now allow free text areas within their templates, this becomes problematic, since the data captured isn’t structured.
3. Limitations of claims data
Clients discussed the need to get deeper than claims information to manage population health. Many said their organization is challenged to identify patients with certain diagnoses that require more rigid case management because these diagnoses may not have been documented correctly. They want to be able to search the record for patients by diagnosis code, by diagnostic study, or by medication administered to identify patients with a chronic disease that needs more focused attention.
4. Data to identify “avoidable care”
This topic earned the most attention since all those attending the meeting are concerned with improving outcomes and taking cost out of the delivery of care. Clients discussed how to utilize data, benchmarks, and predictive analytics to identify preventable events such as complications, readmissions, unnecessary admissions and ED visits, and overutilization of ancillary services.
5. Data to manage compliance risk
Compliance has become a huge focus with increased scrutiny from the RACs, OIG, and many payers. Frequent requests for records have the facilities playing defense instead of working on offense. Data and benchmarks are needed to assist them in proactively preventing errors in real-time before they drop a bill. Analytics can assist them in “keeping the fox out of the henhouse.”
Overall, the major takeaway from our discussions is the critical importance of data analytics. Actionable data will be essential for success under healthcare reform and to address the increased regulatory scrutiny healthcare organizations are facing today.
Garri Garrison is Director of Emerging Business with 3M Health Information Systems.