Recently, a group of Republican senators issued a white paper criticizing the federal government’s efforts to foster the widespread adoption of electronic health records (EHR) systems. They claimed that interoperability issues should have been resolved before providers were required to demonstrate meaningful use of EHR technology and that flaws in the system could endanger patients. In addition, they contended that the use of EHR systems led to upcoding and facilitated fraud and that inappropriate copying and pasting of data contributed to confusion that could harm patients. Yet, Leapfrog’s May 2013 patient safety report, which graded general hospitals for patient safety, might indicate that at least computerized provider order entry (CPOE) decreases risks to patient safety.
Certainly, interoperability is crucial to the ultimate success of the EHR initiative. Because many hospitals build their information technology (IT) systems piecemeal, interoperability issues arise among databases in the same institution. The lag can slow down EHR systems and increase risk to patients. A physician who presented a paper at a convention of nephrologists in November 2012 found that all the physicians he surveyed in his hospital’s intensive care unit (ICU) experienced “cognitive drift” when their hospitals’ systems failed to respond as promptly as they expected, In other words, they stopped paying attention to the computer. Sometimes, they even left the computer altogether. And the length of time from the click of the mouse to the drift was ten seconds. In April 2010, when an automatic anti-virus software update incorrectly caused uncontrolled restarts of computers and loss of network functionality, one-third of the hospitals in Rhode Island had to postpone elective surgeries and divert “non-life-threatening emergencies.”
Writers who analyzed the relationship between EHR and national patient safety goals in the New England Journal of Medicine in November 2012 suggested a three-phase approach to EHR safety issues. In the first phase, the focus is on new safety issues presented by the technology. To prevent or minimize the effects of an incident like the one in Rhode Island, they recommend setting an EHR-specific patient safety goal (ePSG) of reducing the effects of EHR downtime on clinical operations and patient safety. Another phase one ePSG might be to reduce medication errors that result from the mismatch of data fields between the sender and recipient of an e-prescription, for example, elimination of “sustained release” from the description of a prescribed drug.
The second phase addresses the potential harm that could result from incorrect or inappropriate use of the technology. For example, the use of CPOE, in some departments or for some orders but not others, could create a risk to patients because of the ease with which an order might be overlooked if clinicians have to check multiple locations. Other issues that might arise during the second phase include inconsistent use of free-text or structured data fields. When the structured data fields are available but a physician puts a key element of the order in free text, such as a date to discontinue medication, the chances of miscommunication are magnified. The designers and users of clinical decision support systems might have to analyze the work flow to assure that alerts or automatic stops are generated at the optimal times, to prevent “alert fatigue” and inappropriate overrides of the system as well as clinical error. They also could consider addressing the copy-and-paste problem because unnecessary copying and pasting of history notes or other material actually has been found to detract from the usability of an EHR.
Only in the third phase would the safety focus turn to the functions that take advantage of the ability to mine the data for root causes of adverse events of the data. The authors urged that the teams that design and refine EHR systems include cognitive scientists and human-factor engineers as well as physicians who would have to use the system.