The 5th blog in the Healthcare Predictions & Perspectives blog series. This blog series is focused on healthcare transformational strategies that are enabled through Health IT and Health Information Governance best practices.
The industry’s abuzz with talk about governance so why am I still talking about EMPI? Well, it all goes back to usability. You can establish the framework and layer on some IG policies but at the end of the day the usability of your data remains directly tied to its integrity. The Master Patient Index (MPI) database is perhaps the greatest example of this.
The MPI database is the lifeline of any healthcare organization. It is the single source by which providers map patients to their medical record. In addition, it is the underlying foundation of some of the most mission critical initiatives. For example, advancing patient safety, improving interoperability and achieving more accurate and timely claims and billing processes all tie back to the data housed in the MPI database. Yet, despite the criticality of this data, many organizations continue to struggle with the prevention, identification and elimination of errors from their MPI system. With so many competing priorities and so few resources, this critical component of IG is often overlooked, de-prioritized or inadequately undertaken. Yet it doesn’t have to be. This issue can be addressed in a timely and cost effective manner; however, it does require some robust analytics and some strategic planning.
- Identify: Leverage proven analytic and rule based software to analyze the MPI data from all facilities across your enterprise to determine what types of errors and duplication exist and where they are most prevalent. Be sure to secure a view collectively as well as at the facility level. Note, generally the level of detail required cannot be acquired through the add-on modules you’ll find in your EMR system. Yes, they can help hedge the problem but they won’t provide the comprehensive analytics and reporting needed to cleanly identify root cause, effectively prioritize data populations or accurately scope the project.
- Remediate: With a clear understanding of the project scope, move to develop an effective clean-up plan that facilitate timely clean up without over-burdening or distracting your internal resources. In many cases you won’t want to cleanse all errors. Identify a cut off year or last active date – addressing only the most recent and active subsets. Also, where possible, take advantage of software that enables you to auto-merge duplicates to minimize the people and financial resources required to complete the project.
- Maintain: After taking on a project to of this size and scope, the last thing you’ll want to do is add on another expense but that’s exactly what I’m going to suggest you do. Why? You’ve just spend a large sum of time, resources and/or money to achieve an acceptable MPI error rate. The last thing you want to do is find yourself back in the same position a few years from now. License analytics software that enables you to proactively review and manage your EMPI data integrity on an ongoing basis. While at first, you may find it difficult to bit the financial bullet, in the end you’ll be glad you opted for a manageable, predictable expense rather than the variable, recurring expense associated with inconsistent MPI integrity management.
We’d like to hear your thoughts on how MPI integrity impacts your organization; if you are at HIMSS ’16, be sure to stop by Booth 843 and let us know what you think.
Join our Twitter Chat: Healthcare Transformation: Predictions and Perspectives #InfoTalk
On March 17th at 9:00 PT/12:00 pm ET, @IronMtnHealth is hosting a Twitter chat using #InfoTalk to further the dialog on transformational strategies that are enabled through Health IT and Health Information Governance. If you have been involved in Health IT and information governance-related projects, we’d love to have you join.