Just as the final rule for “meaningful use” in adoption of electronic medical records (EMR’s) has been released, several studies have shown that most “off-the-shelf” EMR’s and even some highly sophisticated systems built in-house still lack some of the important clinical decision support tools we need to improve patient safety. Moreover, these studies highlight the need for practice and workflow transformation. You can’t simply plop an EMR into a practice or a hospital and anticipate all your potential problems will disappear.
On the hospital side, The Leapfrog Group used its simulation tool to test how CPOE systems at over 200 hospitals would handle a variety of medication order entry scenarios. From June 2008 to January 2010, 214 hospitals used the Leapfrog web-based tool to test their CPOE systems’ ability to identify potential problems during medication order entry. The percentage of medication orders that did not receive an appropriate warning was 52% in adult hospitals and 42% in pediatric hospitals. Moreover, for potentially fatal orders, an appropriate warning was not given in about a third of cases at both adult and pediatric hospitals.
Fortunately, the simulation tool is having a positive impact. Nearly all the hospitals used the results of the simulation to improve their CPOE systems. Leapfrog is stressing that ongoing testing and monitoring of CPOE systems is crucial and that collaboration must take place between vendors and hospitals to identify best practices. They call for movement away from proprietary closed systems and call for better sharing of issues and solutions across vendors and across healthcare organizations.
On the outpatient side, Elder et al. looked at management of test results in primary care practices and found that, though those practices with EMR’s did slightly better on certain processes in managing test results, they fell short on notifying patients and in documenting the interpretation and followup of abnormal test results. They did chart audits at 8 family medicine practices in Ohio and compared compliance with certain processes between those practices with and EMR and those without an EMR. Those with EMR’s did have higher percentages of charts with test results in the correct place, signatures by clinicians acknowledging the test results, clinician interpretations of results, and patient notifications. And for the subset of those with abnormal test results 64% of those with an EMR had plans for followup documented, compared to only 40% of those without an EMR.
They also found that methods of patient notification differed between those offices with EMR’s and those without EMR’s. In those practices with EMR’s more patients were notified of test results by mail and fewer were notified of their results only at an office visit.
Note that they also looked at the impact on formalized office processes for test result management. Interestingly, they found that practices with fewer standardized steps were actually more likely to document followup on abnormal test results but that none of the offices had standardized processes for that step.
They often found a discrepancy between high compliance with clinician signature and interpretation of test results but low documentation of followup plans. They point out that EMR’s may automate and make easier the acknowledgement of test results but that does not guarantee the test results get adequate scrutiny and that a plan of action will be undertaken. That is one area where both further refinement of EMR’s and other process changes in workflow and practice procedures will be required. Followup of test results is one of the areas stressed in those practices seeking to become patient-centered medical homes (PCMH’s). It’s also one of the patient safety areas we have most frequently talked about on the ambulatory care side (see our Patient Safety Tips of the Week for December 11, 2007 “Communication…Communication…Communication”, May 1, 2007 “The Missed Cancer”, February 12, 2008 “More on Tracking Test Results”, October 13, 2009 “Slipping Through the Cracks” and our July 2009 What’s New in the Patient Safety World column “Failure to Inform Patients of Clinically Significant Outpatient Test Results”).
And on the e-prescribing side Matvey 2010 found frequent internal discrepancies in e-prescriptions between what was in structured fields and what was in associated free-text fields. Structured fields contain data such as the name of the drug, the dosage form, the route, the frequency, the duration, and the number of refills. The free text fields typically contain instructions like “take with meals” or more complex dosing regimens (eg. take a whole tablet on even days and a half tablet on odd days). They looked at e-prescribing in the ambulatory arena at Partners HealthCare, known for its relatively sophisticated electronic medical record system. Over 42% of such e-prescriptions contained such free text fields. A random sample of those that contained such free text found discrepancies in 16.1% of e-prescriptions. And over 80% of those with discrepancies were deemed potentially capable of leading to an adverse event (potentially severe in almost 17%).
While mismatches in frequency, route, dosage form, duration and quantity were relatively uncommon, the highest frequency of discrepancies (29% of those prescriptions having discrepancies) related to those having complex regimens. These include examples where a different dose is to be taken on different days of the week, regimens where the dosage or frequency of a drug is to be increased or tapered, etc.
Most importantly, the frequency of such discrepancies was much higher for 3 drugs that are already high alert drugs: coumadin, insulin, and digoxin. So these are already high risk drugs and ones for which complex dosing is often necessary and now ones for which internal discrepancies occur frequently.
This study has implications for the design of e-prescribing systems, the user interface and the training that must take place for all providers entering orders into the system. In addition, it highlights the need for pharmacists receiving such prescriptions to contact the ordering physician for clarification. The latter becomes especially problematic when the person who did the order entry is not available and the covering provider may not know what the ordering provider had in mind.
On the positive side, a poster presented by Helen Halpin at the recent annual APIC meeting demonstrated that hospitals using automated surveillance software to help identify infections more accurately and timely using data from multiple sources in the EMR were also more likely to have implemented best practice strategies to avoid infections. Whether that translates into actual lower infection rates remains to be demonstrated but these are best practices that are evidence-based. APIC has published a position paper recommending use of such automated surveillance technologies as part of an effective infection control program.
The key lessons from all these papers are that clinical decision support tools for electronic medical records are still evolving. Though they have a tremendous capability of improving quality of care and patient safety they are still being refined. Moreover, the best practices for delivering that clinical decision support are also just being discovered. And the biggest message is that EMR’s are only a piece of the puzzle. We need to change practice workflows, responsibilities, and processes to redesign our practices around the EMR. During the transition period we need to be extremely vigilant and avoid overreliance on the EMR as a panacea.
Center for Medicare and Medicaid Services (CMS). Final rule for meaningful use:
The Leapfrog Group. Leapfrog Group Report on CPOE Evaluation Tool Results June 2008 to January 2010. Executive Summary. June 2010
Elder NC, McEwen TR, Flach J, Gallimore J, Pallerla H. The Management of Test Results in Primary Care: Does an Electronic Medical Record Make a Difference? Fam Med 2010; 42(5): 327-333
Matvey B, Palchuk MB, Fang EA, Cygielnik JM, et al. An unintended consequence of electronic prescriptions: prevalence and impact of internal discrepancies
Halpin H, Enanoria W, Vanneman M. Hospital Adoption of Automated Surveillance Technology and the Implementation of Infection Prevention and Control Programs. (Poster Presentation). APIC Annual Meeting July 13, 2010
APIC. Computerized Infection Monitoring Systems Enable Hospitals To Mount More Aggressive Efforts Against Healthcare-Associated Infections. APIC press release
July 12, 2010
Greene LR, Cain TA, Khoury R, et al. APIC Position Paper: The Importance of Surveillance Technologies in the Prevention of Healthcare-Associated Infections (HAIs)
APIC May 29, 2009