ePrescribing systems reduce errors but not time with patients
New research has shown that the use of ePrescribing systems in the acute care setting can prevent more errors than they cause, and that the introduction of electronic medication management has a negligible effect on time spent on patient care.
Two papers published recently in the Journal of the American Medical Informatics Association (JAMIA) by University of NSW researchers add to the weight of published research on ePrescribing and eMedications management in the acute care setting.
Led by Joanna Westbrook, director of the Centre for Health Systems and Safety Research at UNSW's Australian Institute of Health Innovation, one paper builds on research published last year which showed that the introduction of commercial ePrescribing systems can reduce prescribing errors by up to 66 per cent.
That research found that while prescribing errors were reduced, new types of system or computer-related errors can occur. The new research looks at what exactly those new errors are, and how this research can be used by vendors to tweak their systems for better safety.
The other paper looks at the hotly debated issue of whether the introduction of computerised physician order entry (CPOE) can mean that clinicians spend more time on the computer and less time on patient care. The new research finds that there was little difference in time spent on patient care by doctors or nurses after the introduction of an eMM system, although that time seemed to be spent in different ways.
The first paper, The safety of electronic prescribing: manifestations, mechanisms, and rates of system-related errors associated with two commercial systems in hospitals, involved an audit of 629 inpatient admissions at two hospitals in Sydney using CSC's MedChart and Cerner's Millennium ePrescribing modules. Professor Westbrook's previous research had also studied these systems.
That previous research had found that new errors appeared when using ePrescribing systems that did not occur with paper charts; for example, ordering a drug unrelated to the patient's condition that was located directly above or below the likely drug in the drop-down menu.
The researchers have now developed a classification system based on the manifestation of the error – such as wrong dose or route – and the mechanism of the error, such as selecting incorrect items or errors in constructing or editing orders.
The results showed that of the 1164 prescribing errors found, 42 per cent were system-related. It also found that the two systems prevented significantly more errors than they generated. There was no real difference between the amount of errors found between the two systems, although the type of error was different.
The main errors manifested were time of dose and wrong dose strength, while the mechanism of error was predominately selection, editing and failure to complete new tasks required by the ePrescribing system.
“Selection errors occurred when prescribers made an incorrect selection from a drop-down menu,” the researchers write. “They were the most frequent mechanism of system-related errors accounting for 43.4 [per cent].”
Editing errors accounted for 21.1 per cent of system-related errors and occurred when prescribers modified a predefined order sentence, and construction errors occurred when a prescriber formulated a new order sentence and an element was incorrect.
Errors introduced by new tasks required by the ePrescribing system included a failure to provide a reminder that a patient had a dermal patch that needed removal. At the time of the study, neither of the systems had the capability to record times for both administration and removal of dermal patches.
One benefit of the research was to assist the two vendors to make alterations to their systems and changes were made as a result of this study, the researchers write.
“The positions of some drop-down menu items were changed, for example to bring frequently used items to the top of long lists, and some default times were changed. The eight errors found in order sentences at the Cerner site were corrected.
“The vendor of MedChart made software changes, for example, to display pre-defined order sentences (quick lists) for selected drug-products on the first accessible prescribing screen in order to discourage clinicians from long-hand prescribing to reduce the risk of selection errors.
“Therefore, if the study was repeated today, it would be expected that many of the system-related errors identified would no longer appear and there would be a lower overall rate for both systems.”
In the second paper, Impact of an electronic medication management system on hospital doctors’ and nurses’ work: a controlled pre–post, time and motion study, Professor Westbrook and her team studied the effect of the introduction of the Cerner system on the doctors and nurses using it, and whether it had an effect on direct patient care, medication-related tasks and interactions before and after its introduction.
The researchers had interviewed 50 hospital clinicians and managers prior to the trial to understand what their concerns were. “Work practice change associated with the system was the most strongly and frequently raised issue by all groups,” they found.
“Specific issues often [centre] on the perceived increased time it takes for doctors to prescribe medications and for nurses to perform medication administration using a computer compared to paper medication charts.
“As a result of this, there are concerns that there will be less time for clinicians to spend on direct patient care activities. These beliefs are often in contrast to the system benefits promoted to clinicians, namely that information systems will improve efficiency and patient care.”
The research found that there was no significant change in the intervention wards in proportions of time spent on direct care or medication-related tasks relative to control wards.
“In the post-period control ward, doctors spent 19.7% (2 h/10 h shift) of their time on direct care and 7.4% (44.4 min/10 h shift) on medication tasks, compared to intervention ward doctors (25.7% (2.6 h/shift; p=0.08) and 8.5% (51 min/shift; p=0.40), respectively).
“Control ward nurses in the post-period spent 22.1% (1.9 h/8.5 h shift) of their time on direct care and 23.7% on medication tasks compared to intervention ward nurses (26.1% (2.2 h/shift; p=0.23) and 22.6% (1.9 h/shift; p=0.28), respectively).”
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