Intelligent Healthcare Part 3 – Understanding Electronic Health Records

Much if not all of the discussion over the past two years in regards to Healthcare Modernization has revolved around the deployment of Electronic Health Records (EHR) systems. Monies were budgeted to EHR adoption in last year’s Stimulus package and more monies will be allocated towards EHR adoption as a result of the recent Healthcare Reform package. So what does this all mean in regards to Intelligent Healthcare and the application of Semantic technology? First we’ll need to take a closer look at EHRs.
Health Care Record – CCR Format
 
 
 
 
 
 
 
 
 
 
 
 
The term, Electronic Health Record (EHR), is often used synonymously with Electronic Medical Record (EMR) or Longitudinal Health Record to describe systems that capture medical chart data in electronic format. The nature of the data being captured and how it is used varies from system category to system category as well as across individual vendor implementations in every category. There is no standard solution configuration in terms of features, functions and performance. There is some standardization in relation to the data elements employed though as many vendors have attempted compliance with one or more Healthcare Interoperability standards. The design and implementation of EHRs does not necessarily take into consideration the larger ecosystem in which it will inhabit and in fact there are many different types of environments that they may be built to support including:

•    Smaller medical practices
•    Mid-sized Healthcare providers (clinics, specialty care)
•    Larger Healthcare providers (Hospitals)
•    Health Networks
•    Agency / National level (NHS SCR, DoD AHLTA, States etc.)
EHR Conceptual View – OpenEHR
 
 
 
 
 
 
 
 
 
 
 
 
 
The development and use of EHRs has in many instances been controversial and there has been significant resistance to it by practitioners and limited evidence of improved outcomes from organizations which have adopted them. One particular area of controversy revolves around whether the family of EHR solutions has either accurately understood and supported existing Healthcare processes or made any headway in actually improving those processes. Despite this situation, EHR technology has remained the primary focus for Healthcare solutions modernization or transformation. To understand why EHRs have not lived up to their potential, it is worthwhile to explore some of the (perhaps false) assumptions behind them:

•    Assumption 1 – That because much or most of current Healthcare process is ‘paper-based’ that it is necessarily inefficient. Paper-based process can in fact be highly optimized, or sub-optimized thus facilitating processes in situ. The enterprise perspective must also support the needs of component Healthcare delivery.

•    Assumption 2 – That full standardization of a domain of practice as complex and evolutionary in nature as Healthcare is even possible. And that the domain would become subordinated to the woefully incomplete (lagging) standardized view and thus tolerate degradation of care to support the larger goal of automation.

•    Assumption 3 – That technology might be imposed without engaging in full partnership with both care providers and patients. This is particularly critical in determining performance expectations in relation to care practice. In other words, if it takes a doctor 15 minutes to manage a typical patient encounter using a paper-based approach and 30 using an EHR then the EHR has failed to meet minimum expectations and communication between the IT provider and care provider failed.

One of the most interesting value propositions associated with Semantic Technology for Intelligent Healthcare is the ability to use semantic modeling to help define workflows and correlate data to those workflows and associated problem spaces. While few if any EHRs have yet taken advantage of that capability, we will discuss in our next post in the series how that can be accomplished.

Copyright 2010 – Stephen Lahanas

 

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