Duplicate Orders: An Unintended Consequence of Computerized provider/physician order entry (CPOE) Implementation

This is a review of Magid, Forrer, and Shaha’s 2012 article, Duplicate Orders: An Unintended Consequence of Computerized provider/physician order entry (CPOE) Implementation: Analysis and Mitigation Strategies

Background

The benefits of computerized provider/physician order (CPOE) entry - particularly with clinical decision support (CDS) - has been shown to increase patient safety. CPOE has also been reported to improve:

• The utilization of health care services
• Decrease costs
• Reduce hospital length of stay
• Decrease medical errors
• Improve compliance with guidelines

CPOE systems improve legibility and decrease errors relating to look-alike, sound-alike medications. Reductions in medication errors have been noted for:

• Dosing
• Frequency
• Route
• Substitution
• Allergies

The authors’ objective in this report was to describe the nature of duplicate orders, report their analysis of them and describe the methods used to reduce them.

Methods

Duplicate medication orders (“duplicates”) were defined for the study as two or more active orders for the identical medication regardless of dose. The second order entered was labeled as the duplicate order. Certain orders were not considered to be duplicates and were excluded from analysis. These include:

1. Dose range ordering (e.g. acetaminophen: one pill for mild pain and two pills for severe pain)
2. Combination drug plus component (e.g. losartan/HCTZ plus HCTZ or Percocet plus acetaminophen)
3. The same drug prescribed for different indications (e.g. acetaminophen for pain and acetaminophen for fever)
4. Large volume parenterals

Results

A total of 316,160 orders were captured during the 84 weeks, averaging 3,764 orders per weekly sampling period.

• There were 5,442 duplicate orders over this period, an average duplication rate of 1.8%.
• The highest rate was 5.0% (211/4,220) in week 1, and the lowest rate was 0.3% (8/2,667) in week 75.
• The duplication rate was 0.82% (32/3,888) in the last week (84) of the study.

There was an 84.8% decrease in the duplication rate from week 1 (211 duplicates) to week 84 (32 duplicates), and a 94.6% decrease from the highest (week 1) to the lowest (week 75). The duplication rate of 3.7% Pre-interventions (780/21,081) was reduced to 0.9% Post-interventions (211/23,444); from nearly one duplicate for every 25 orders to fewer than nine in every 1,000 representing a decrease of 75.7%.

Discussion

The goals of the study were to identify the drugs, which were being duplicated most frequently and create strategies to reduce them. These strategies included the following interventions:

1. Many duplicated drugs were defaulted within order sets; wherever possible they were “un-defaulted”
2. Many drugs were removed from order sets altogether (and now require a specific order to prescribe)
3. Additional duplicate alerts were activated for high-risk and high frequency drugs
4. The pharmacy was asked to discontinue certain duplicate orders.

Conclusion

By studying the specific drugs, the type and role of prescribers, the origin of the duplicate orders, and workflow, the authors were able to devise reduction strategies:

• Changes in order sets to avoid overlapping medications
• Changes in work-flow
• Additional training strategies
• Altering pharmacy procedure
• Broadening duplicate warnings.

It was through implementation of these methods that the authors were able to decrease duplicate orders significantly.

Comments

The journal article was an interesting read because it took a different approach than most published papers when looking at duplicate orders. Instead of looking directly at the alert function of the CPOE system, the author’s decided to look at the source and work-flow causes that were creating duplicate orders.

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