Reports From the Field

Preventing Wrong-Patient Electronic Orders in the Emergency Department

Journal of Clinical Outcomes Management. 2016 December;23(12)

Author(s):

Daniel Lombardi, DO

Jacqueline Gaston-Kim

David Perlstein, MD, MBA

Ann Marie McDonald, EdD, RN

Kathleen McAuliffe, MS, RN

Jeffrey Lazar, MD, MPH

Eric C. Appelbaum, DO

Zane Last, PharmD

Renee C. Hulen, RN, BS-HCA

References

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4. Reckmann, MH, Westbrook JI, Koh Y, et al. Does computeized provider order entry reduce prescribing errors for hospital inpatients? A systematic review. J Am Med Inform Assoc 2009;16:613–23.

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8. Adelman, JS, Kalkut GE, Schechter CB, et al. Understanding and preventing wrong-patient electronic orders: a randomized controlled trial. JAM Med Inform Assoc 2013;20:305–10.

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11. Institute for Safe Medication Practices. Oops, sorry, wrong patient! A patient verification process is needed everywhere, not just at the bedside. 10 Mar 2011. Accessed at www.ismp.org/Newsletters/acutecare/articles/20110310.asp.

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From SBH Health System, Bronx, NY .

Abstract

Objective: To decrease the number of near-miss wrong-patient orders in a computerized physician order entry (CPOE) system.
Methods: A CPOE alert was built that prompted the ordering clinician to reaffirm the identity of the patient by entering the patient’s initials and year of birth prior to placing an order. We used a retract and reorder tool to measure the frequency of near-miss wrong-patient order errors before and after implementation of the alert.
Results: The ID reentry function decreased near-miss wrong-patient orders in the ED by 35% during the 8-week pilot period. The system was also successful in helping to decrease the percentage of all CPOE near-miss events by 49%.
Conclusion: An alert that requires the prescriber to enter the patient’s initials and birth year is effective in decreasing wrong-patient orders in the CPOE system.

Key words: CPOE, near miss, patient safety, medical errors, wrong-patient errors.

Computerized provider order entry (CPOE) systems are commonly used to place orders. CPOE has been shown to reduce errors [1–4]. However, medication errors also can be caused or exacerbated by the CPOE system [5–7]. One type of error that can occur is placing orders on the wrong patient [8]. Wrong-patient CPOE errors can lead to significant morbidity and mortality [8–11]. To reduce wrong-patient CPOE errors in our health system, we developed an alert that required the ordering clinician to verify the identity of the patient. In this paper, we describe our project and outcomes attained.

Methods

Setting

SBH Health System is a not for profit health system located in Bronx, New York. The SBH Health System also has academic affiliations, and AOA and ACGME residency and fellowship programs. St. Barnabas Hospital, SBH Health System’s acute care facility, is a safety net hospital, Level 1 trauma center, primary stroke center, and STEMI receiving center. St. Barnabas Hospital has 422 licensed beds and had a total of 91,476 emergency department visits in 2015. The electronic health record in use at the time of the project was Allscripts 6.1. The Allscripts product, including its CPOE functions, has been in use in the SBH emergency department (ED) since 2011.

Review of Current Process

A team of multidisciplinary stakeholders was assembled comprised of hospital senior leadership, ED leadership, and front-line staff. Representatives from all disciplines involved in the CPOE process were invited, including nursing, pharmacy, radiology, clinical laboratory, and information technology.

A review was conducted of the CPOE ordering process. First, a fishbone diagram was created that identified contributing factors to the problem of CPOE patient identification error ( Figure 1 ). Interruptions, multiple log-ins into the EHR, and the lack of an active patient identification process were found to be repeated contributing factors leading to CPOE ID/wrong-patient errors.

Next, we assessed our current error rate using a “retract and reorder” tool, which flags orders that have been placed for one patient, then erased and added to another patient’s file by the same clinician within a 10-minute time frame [8]. This tool, developed by Adelman et al, picks up near-miss errors, self-caught by the provider before causing harm [8]. Safety research has demonstrated that near-miss errors share the same causal pathway; therefore, measuring and preventing near-miss wrong-patient errors should reduce related errors that reach the patient.

A Computer-Assisted Process to Reduce Discharge of Emergency Department Patients with Abnormal Vital Signs