Dataset Information

Errors and electronic prescribing: a controlled laboratory study to examine task complexity and interruption effects.

ABSTRACT:

Objective

To examine the effect of interruptions and task complexity on error rates when prescribing with computerized provider order entry (CPOE) systems, and to categorize the types of prescribing errors.

Design

Two within-subject factors: task complexity (complex vs simple) and interruption (interruption vs no interruption). Thirty-two hospital doctors used a CPOE system in a computer laboratory to complete four prescribing tasks, half of which were interrupted using a counterbalanced design.

Measurements

Types of prescribing errors, error rate, resumption lag, and task completion time.

Results

Errors in creating and updating electronic medication charts that were measured included failure to enter allergy information; selection of incorrect medication, dose, route, formulation, or frequency of administration from lists and drop-down menus presented by the CPOE system; incorrect entry or omission in entering administration times, start date, and free-text qualifiers; and omissions in prescribing and ceasing medications. When errors occurred, the error rates across the four prescribing tasks ranged from 0.5% (1 incorrect medication selected out of 192 chances for selecting a medication or error opportunities) to 16% (5 failures to enter allergy information out of 32 error opportunities). Any impact of interruptions on prescribing error rates and task completion times was not detected in our experiment. However, complex tasks took significantly longer to complete (F(1, 27)=137.9; p<0.001) and when execution was interrupted they required almost three times longer to resume compared to simple tasks (resumption lag complex=9.6 seconds, SD=5.6; resumption lag simple=3.4 seconds, SD=1.7; t(28)=6.186; p<0.001).

Conclusion

Most electronic prescribing errors found in this study could be described as slips in using the CPOE system to create and update electronic medication charts. Cues available within the user interface may have aided resumption of interrupted tasks making CPOE systems robust to some interruption effects. Further experiments are required to rule out any effect interruption might have on CPOE error rates.

SUBMITTER: Magrabi F

PROVIDER: S-EPMC2995669 | biostudies-literature | 2010 Sep-Oct

REPOSITORIES: biostudies-literature

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Publications

Errors and electronic prescribing: a controlled laboratory study to examine task complexity and interruption effects.

Magrabi Farah F Li Simon Y W SY Day Richard O RO Coiera Enrico E

Journal of the American Medical Informatics Association : JAMIA 20100901 5

<h4>Objective</h4>To examine the effect of interruptions and task complexity on error rates when prescribing with computerized provider order entry (CPOE) systems, and to categorize the types of prescribing errors.<h4>Design</h4>Two within-subject factors: task complexity (complex vs simple) and interruption (interruption vs no interruption). Thirty-two hospital doctors used a CPOE system in a computer laboratory to complete four prescribing tasks, half of which were interrupted using a counterb ...[more]

PMID: 20819867

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Project description:BackgroundPrescribing error represent a significant source of preventable harm to patients. Prescribing errors at discharge, including omission of pre-admission medications (PAM), are particularly harmful as they frequently propagate following discharge. This study assesses the impact of an educational intervention and introduction of an electronic patient record (EPR) in the same centre on omission of PAM at discharge using a pragmatic design. A survey of newly qualified doctors is used to contextualise findings.MethodsDischarge prescriptions and discharge summaries were reviewed at discharge, and compared to admission medicine lists, using a paper-based chart system. Discrepancies were noted, using Health Information and Quality Authority guidelines for discharge prescribing. An educational intervention was conducted. Further review of discharge prescriptions and discharge summaries took place. Following introduction of an EPR, review of discharge summaries and discharge prescriptions was repeated. A survey was administered to recently qualified doctors (interns), and analysed using descriptive statistics and thematic analysis.ResultsOmission of PAM as prescribed or discontinued items at discharge occurs frequently. An educational intervention did not significantly change prescribing error rates (U = 1255.5, p = 0.206). EPR introduction did significantly reduce omission of PAM on discharge prescribing (U = 694, p < 0.001), however there was also a reduction in the rate of deliberate discontinuation of PAM at discharge (U = 1237.5, p = 0.007). Survey results demonstrated that multiple sources are required to develop a discharge prescription. Time pressure, access to documentation and lack of admission medicine reconciliation are frequently cited causes of discharge prescribing error.ConclusionThis study verified passive educational interventions alone do not improve discharge prescribing. Introduction of EPR improved discharge prescribing, but negatively impacted deliberate discontinuation of PAM at discharge. This is attributable to reduced access to key sources of information used in formulating discharge prescriptions, and separation of the discontinuation function from the prescribing function on the EPR discharge application.

Project description:Healthcare providers previously using older electronic health records (EHRs) with electronic prescribing (e-prescribing) are transitioning to newer systems to be eligible for federal meaningful use incentives. Little is known about the safety effects of transitioning between systems.To assess the effect of transitioning between EHR systems on rates and types of prescribing errors, as well as provider perceptions about the effect on prescribing safety.Prospective, case study of 17 physicians at an academic-affiliated ambulatory clinic from February 2008 through August 2009. All physicians transitioned from an older EHR with minimal clinical decision support (CDS) for e-prescribing to a newer EHR with more robust CDS.Prescribing errors were identified by standardized prescription and chart review. A novel survey instrument was administered to evaluate provider perceptions about prescribing safety.We analyzed 1298 prescriptions at baseline, 1331 prescriptions 12 weeks post-implementation, and 1303 prescriptions one year post-implementation. Overall prescribing error rates were highest at baseline (35.7 per 100 prescriptions, 95% confidence interval (CI) 23.2-54.8) and lowest one year post-implementation (12.2 per 100 prescriptions, 95% CI 8.6-17.4) (p?<?0.001). Improvement in prescribing safety was mainly a result of reducing inappropriate abbreviation errors. However, rates for non-abbreviation prescribing errors were significantly higher at 12 weeks post-implementation than at baseline (17.7 per 100 prescriptions, 95% CI 9.5-33.0 versus 8.5 per 100 prescriptions, 95% CI 4.6-15.9) (p <0.001) and no different at baseline than one year (10.2 per 100 prescriptions, 95% CI 6.2-18.6) (p?=?0.337). Survey results complemented quantitative findings.Results from this case study suggest that transitioning between systems, even to those with more robust CDS, may pose important safety threats. Recognizing the challenges associated with transitions and refining CDS within systems may help maximize safety benefits.

Project description:BackgroundA lack of ability to inhibit prepotent responses, or more generally a lack of impulse control, is associated with several disorders such as attention-deficit/hyperactivity disorder and schizophrenia as well as general damage to the prefrontal cortex. A stop-signal task (SST) is a reliable and established measure of response inhibition. However, using the SST as an objective assessment in diagnostic or research-focused settings places significant stress on participants as the task itself requires concentration and cognitive effort and is not particularly engaging. This can lead to decreased motivation to follow task instructions and poor data quality, which can affect assessment efficacy and might increase drop-out rates. Gamification-the application of game-based elements in nongame settings-has shown to improve engaged attention to a cognitive task, thus increasing participant motivation and data quality.ObjectiveThis study aims to design a gamified SST that improves participants' engagement and validate this gamified SST against a standard SST.MethodsWe described the design of our gamified SST and reported on 2 separate studies that aim to validate the gamified SST relative to a standard SST. In study 1, a within-subject design was used to compare the performance of the SST and a stop-signal game (SSG). In study 2, we added eye tracking to the procedure to determine if overt attention was affected and aimed to replicate the findings from study 1 in a between-subjects design. Furthermore, in both studies, flow and motivational experiences were measured.ResultsIn contrast, the behavioral performance was comparable between the tasks (P<.87; BF01=2.87), and the experience of flow and intrinsic motivation were rated higher in the SSG group, although this difference was not significant.ConclusionsOverall, our findings provide evidence that the gamification of SST is possible and that the SSG is enjoyed more. Thus, when participant engagement is critical, we recommend using the SSG instead of the SST.

Project description: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.

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Dataset Information

Errors and electronic prescribing: a controlled laboratory study to examine task complexity and interruption effects.

Objective

Design

Measurements

Results

Conclusion

Publications

Errors and electronic prescribing: a controlled laboratory study to examine task complexity and interruption effects.

Similar Datasets

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