Let's start with our data. News stories churn relentlessly about EHR, skeptical interpretations of "meaningful" use, barriers to value-based care but just try finding the potential solutions. Don't get me wrong. There are business models that have coalesced around solving data problems--for a fee. The problem as I see it, is the lack of literacy around our data. A combination of limited literacy around all things IT and low numeracy around what we can glean from our collected data. Unfortunately, even if you are asking the wrong questions you still get answers.
Data extraction and analysis will require reviewing data and cleaning it up (IV or intravenous, week or wk, etc) can be useful. You may not realize that EHRs store data in a "transactional" form. This is the information needed for the business side of healthcare. In fact many of the limitations cited on the healthcare-provider side mention administrative data of little interest to point-of-care decisions. This includes internal date-time stamps, update codes, workstation origin codes, incremental data updates but you need to realize that this information also allows for tracking across visits.
When you determine how your data is structured you can develop a plan for access and analyses.
What is under the hood in an EMR/EHR database?
- Every EMR has a database
- To enter and retrieve data we typically rely on a programming language for databases - SQL (Structured Query Language)--although RDFS, OWL, and SPARQL--create ontologies, model, and query data--and have emerged to address limitations of SQL.
- Database reporting tools include (Crystal Reports, Microsoft's Access Query tool), and the vendor's customized internal querying tools.
- The data repository in an EHR.EMR includes billing and clinical data (graphic).
- It may seem daunting but once you map your data and learn how to access the relevant information you can create a system that only requires a "refresh" when you want to update your insights.