The safety of electronic prescribing: manifestations, mechanisms, and rates of system-related errors associated with two commercial systems in hospitals

Abstract

Objectives: To compare the manifestations, mechanisms, and rates of system-related errors associated with two electronic prescribing systems (e-PS). To determine if the rate of system-related prescribing errors is greater than the rate of errors prevented.

Methods: Audit of 629 inpatient admissions at two hospitals in Sydney, Australia using the CSC MedChart and Cerner Millennium e-PS. System related errors were classified by manifestation (eg, wrong dose), mechanism, and severity. A mechanism typology comprised errors made: selecting items from drop-down menus; constructing orders; editing orders; or failing to complete new e-PS tasks. Proportions and rates of errors by manifestation, mechanism, and e-PS were calculated.

Results: 42.4% (n=493) of 1164 prescribing errors were system-related (78/100 admissions). This result did not differ by e-PS (MedChart 42.6% (95% CI 39.1 to 46.1); Cerner 41.9% (37.1 to 46.8)). For 13.4% (n=66) of system-related errors there was evidence that the error was detected prior to study audit. 27.4% (n=135) of system-related errors manifested as timing errors and 22.5% (n=111) wrong drug strength errors. Selection errors accounted for 43.4% (34.2/100 admissions), editing errors 21.1% (16.5/100 admissions), and failure to complete new e-PS tasks 32.0% (32.0/100 admissions). MedChart generated more selection errors (OR=4.17; p=0.00002) but fewer new task failures (OR=0.37; p=0.003) relative to the Cerner e-PS. The two systems prevented significantly more errors than they generated (220/100 admissions (95% CI 180 to 261) vs 78 (95% CI 66 to 91)).

Conclusions: System-related errors are frequent, yet few are detected. e-PS require new tasks of prescribers, creating additional cognitive load and error opportunities. Dual classification, by manifestation and mechanism, allowed identification of design features which increase risk and potential solutions. e-PS designs with fewer drop-down menu selections may reduce error risk.

Keywords: CPOE; Clinical information systems; Information technology; Prescribing errors; Unintended consequences.

Figure 1

Screenshots of Cerner and MedChart electronic prescribing systems.

Figure 2

Example of a selection error (mechanism) made while ordering resulting in a wrong drug error (manifestation). The prescriber selected methylprednisolone acetate for intravenous (IV) administration instead of methylprednisolone sodium succinate (the correct salt for IV use). Methylprednisolone acetate is an oily solution for intra-articular or intramuscular (IM) use, and must NOT be injected intravenously. A warning alert that the two salts of methylprednisolone are available and must be selected correctly appeared not to have been noticed by the prescriber who had to override the alert to continue prescribing.

Figure 3

Selection error when editing (mechanism) a predefined order sentence resulting in a wrong route error (manifestation). The prescriber modified a predefined order sentence for sodium chloride 0.9% IV infusion, and mistakenly selected the epidural route from the dropdown menu of available routes.

Figure 4

Error when editing (mechanism) a predefined order sentence resulting in four clinical errors: wrong formulation, wrong dose, wrong route, wrong frequency. The prescriber wanted to order nystatin oral drops 1 ml, oral, qid (four times daily), but chose an order sentence with the wrong formulation (the topical cream order sentence sat at the top of a long menu), then modified this order sentence. The resultant order (for 10 ml of the topical cream to be applied every 4 days) contains four errors.