Patient at Risk in EMR System

Here is a case from the Agency for Healthcare Research and Quality (AHRQ) in which errors in an electronic medical record (EMR) led to an inaccurate diagnosis at an academic medical center in the US. It took three days for the patient’s care team to realize that the results entered into his EMR were for a biopsy they did not order of a lesion he did not have. Before the error was recognized, it had caused the patient “tremendous pain and mental anguish.”

At bottom, the error got as far as it did because of the “medical team” approach – no single person was responsible for this patient’s care. Each person relied on the (erroneous) electronic medical record for his view of the whole.

Rather than acknowledge that excessive reliance on EMRs may pose real risks for real patients, particularly for complex cases run by nebulously defined teams, the case analysis asserts that “the EMR did not fail here. Rather, the errors were in (i) weak linkages among computer systems, (ii) insufficient safeguards against patient misidentification, and (iii) poor hospital work-processes and data fragmentation.”

The commentator’s solution to these problems are typical of those offered for any failing government program – blame the problems on something else (the computer systems that host and create EMRs), issue nebulous calls to make the failing system better, deflect focus by arguing for a cure based on an expanded reach for the program, and, finally, fix known problems by requiring other systems to adapt to known program weaknesses (in this case everyone should be numbered so that people have unique identifiers that keep the system from being confused).

Specifically, the author concludes that problems with EMRs like the ones in this case study can be corrected by

1. More EMRs and more integrated EMRs.
2. Better EMRs
3. Smarter EMR implementations
4. Attention to EMR-generated errors (“Most research on EMRs has focused on documenting the advantages over traditional paper systems. Let’s declare victory in that battle, and now examine the neglected reality of EMR-generated errors. As these errors are revealed, we must seek solutions for them.”)
5. Less unnecessary customization (“EMRs that are well designed from the get-go would eliminate many of these struggles.”)
6. Unique patient identification (“Because the United States prohibits a unique medical ID, as EMRs and interoperability grow, identity errors will increase, causing more avoidable errors and death.”)

The author is not alone in his nebulous recommendations. The Joint Commission has produced a similar set of gauzy recommendations for fixing what it says are known problems with health information systems.

Have the millions of dollars allocated to implementing EMRs, whether they are needed or not, finally succeeded in blurring the line between analysis and cheerleading at the AHRQ?

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