Fewer Errors Seen in Computerized Prescribing System That Selects Medications Based on Indications

A computerized physician order entry (CPOE) system that incorporated drug indications into prescription ordering workflows improved clinicians’ efficiency and lowered prescribing errors compared with two leading commercial CPOE systems, according to an AHRQ-funded project that developed and tested the model. Current CPOE systems do not effectively support adding indications to prescriptions. The CPOE system developed by researchers gave clinicians the option of starting with the indication and allowing the system to offer alternatives for common primary care problems such as poorly controlled hypertension, migraine prevention, gout flare and newly diagnosed diabetes. In addition to requiring fewer clicks and less time to complete orders, the prototype resulted in fewer errors. Access the abstract of the study published in JAMA Network Open.

2019 Mar 1;2(3):e191514. doi: 10.1001/jamanetworkopen.2019.1514.

Comparison of a Prototype for Indications-Based Prescribing With 2 Commercial Prescribing Systems.

Garabedian PM1, Wright A2,3, Newbury I3, Volk LA1, Salazar A3, Amato MG3,4, Nathan AW3,5, Forsythe KJ1, Galanter WL6, Kron K3, Myers S3, Abraham J7, McCord SK4, Eguale T3,4, Bates DW1,2,3, Schiff GD2,3.

Author information

Abstract

IMPORTANCE:

The indication (reason for use) for a medication is rarely included on prescriptions despite repeated recommendations to do so. One barrier has been the way existing electronic prescribing systems have been designed.

OBJECTIVE:

To evaluate, in comparison with the prescribing modules of 2 leading electronic health record prescribing systems, the efficiency, error rate, and satisfaction with a new computerized provider order entry prototype for the outpatient setting that allows clinicians to initiate prescribing using the indication.

DESIGN, SETTING, AND PARTICIPANTS:

This quality improvement study used usability tests requiring internal medicine physicians, residents, and physician assistants to enter prescriptions electronically, including indication, for 8 clinical scenarios. The tool order assignments were randomized and prescribers were asked to use the prototype for 4 of the scenarios and their usual system for the other 4. Time on task, number of clicks, and order details were captured. User satisfaction was measured using posttask ratings and a validated system usability scale. The study participants practiced in 2 health systems' outpatient practices. Usability tests were conducted between April and October of 2017.

MAIN OUTCOMES AND MEASURES:

Usability (efficiency, error rate, and satisfaction) of indications-based computerized provider order entry prototype vs the electronic prescribing interface of 2 electronic health record vendors.

RESULTS:

Thirty-two participants (17 attending physicians, 13 residents, and 2 physician assistants) used the prototype to complete 256 usability test scenarios. The mean (SD) time on task was 1.78 (1.17) minutes. For the 20 participants who used vendor 1's system, it took a mean (SD) of 3.37 (1.90) minutes to complete a prescription, and for the 12 participants using vendor 2's system, it took a mean (SD) of 2.93 (1.52) minutes. Across all scenarios, when comparing number of clicks, for those participants using the prototype and vendor 1, there was a statistically significant difference from the mean (SD) number of clicks needed (18.39 [12.62] vs 46.50 [27.29]; difference, 28.11; 95% CI, 21.47-34.75; P < .001). For those using the prototype and vendor 2, there was also a statistically significant difference in number of clicks (20.10 [11.52] vs 38.25 [19.77]; difference, 18.14; 95% CI, 11.59-24.70; P < .001). A blinded review of the order details revealed medication errors (eg, drug-allergy interactions) in 38 of 128 prescribing sessions using a vendor system vs 7 of 128 with the prototype.

CONCLUSIONS AND RELEVANCE:

Reengineering prescribing to start with the drug indication allowed indications to be captured in an easy and useful way, which may be associated with saved time and effort, reduced medication errors, and increased clinician satisfaction.