Errors associated with outpatient computerized prescribing systems.
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ABSTRACT: Objective
To report the frequency, types, and causes of errors associated with outpatient computer-generated prescriptions, and to develop a framework to classify these errors to determine which strategies have greatest potential for preventing them.Materials and methods
This is a retrospective cohort study of 3850 computer-generated prescriptions received by a commercial outpatient pharmacy chain across three states over 4 weeks in 2008. A clinician panel reviewed the prescriptions using a previously described method to identify and classify medication errors. Primary outcomes were the incidence of medication errors; potential adverse drug events, defined as errors with potential for harm; and rate of prescribing errors by error type and by prescribing system.Results
Of 3850 prescriptions, 452 (11.7%) contained 466 total errors, of which 163 (35.0%) were considered potential adverse drug events. Error rates varied by computerized prescribing system, from 5.1% to 37.5%. The most common error was omitted information (60.7% of all errors).Discussion
About one in 10 computer-generated prescriptions included at least one error, of which a third had potential for harm. This is consistent with the literature on manual handwritten prescription error rates. The number, type, and severity of errors varied by computerized prescribing system, suggesting that some systems may be better at preventing errors than others.Conclusions
Implementing a computerized prescribing system without comprehensive functionality and processes in place to ensure meaningful system use does not decrease medication errors. The authors offer targeted recommendations on improving computerized prescribing systems to prevent errors.
SUBMITTER: Nanji KC
PROVIDER: S-EPMC3197998 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveTo understand the different types and causes of prescribing errors associated with computerized provider order entry (CPOE) systems, and recommend improvements in these systems.Materials and methodsWe conducted a systematic review of the literature published between January 2004 and June 2015 using three large databases: the Cumulative Index to Nursing and Allied Health Literature, Embase, and Medline. Studies that reported qualitative data about the types and causes of these errors were included. A narrative synthesis of all eligible studies was undertaken.ResultsA total of 1185 publications were identified, of which 34 were included in the review. We identified 8 key themes associated with CPOE-related prescribing errors: computer screen display, drop-down menus and auto-population, wording, default settings, nonintuitive or inflexible ordering, repeat prescriptions and automated processes, users' work processes, and clinical decision support systems. Displaying an incomplete list of a patient's medications on the computer screen often contributed to prescribing errors. Lack of system flexibility resulted in users employing error-prone workarounds, such as the addition of contradictory free-text comments. Users' misinterpretations of how text was presented in CPOE systems were also linked with the occurrence of prescribing errors.Discussion and conclusionsHuman factors design is important to reduce error rates. Drop-down menus should be designed with safeguards to decrease the likelihood of selection errors. Development of more sophisticated clinical decision support, which can perform checks on free-text, may also prevent errors. Further research is needed to ensure that systems minimize error likelihood and meet users' workflow expectations.
| S-EPMC7651904 | biostudies-literature
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.
| S-EPMC3822121 | biostudies-literature
Project description:OBJECTIVE: Electronic prescribing (e-prescribing) may substantially improve health care quality and efficiency, but the available systems are complex and their heterogeneity makes comparing and evaluating them a challenge. The authors aimed to develop a conceptual framework for anticipating the effects of alternative designs for outpatient e-prescribing systems. DESIGN: Based on a literature review and on telephone interviews with e-prescribing vendors, the authors identified distinct e-prescribing functional capabilities and developed a conceptual framework for evaluating e-prescribing systems' potential effects based on their capabilities. Analyses of two commercial e-prescribing systems are presented as examples of applying the conceptual framework. MEASUREMENTS: Major e-prescribing functional capabilities identified and the availability of evidence to support their specific effects. RESULTS: The proposed framework for evaluating e-prescribing systems is organized using a process model of medication management. Fourteen e-prescribing functional capabilities are identified within the model. Evidence is identified to support eight specific effects for six of the functional capabilities. The evidence also shows that a functional capability with generally positive effects can be implemented in a way that creates unintended hazards. Applying the framework involves identifying an e-prescribing system's functional capabilities within the process model and then assessing the effects that could be expected from each capability in the proposed clinical environment. CONCLUSION: The proposed conceptual framework supports the integration of available evidence in considering the full range of effects from e-prescribing design alternatives. More research is needed into the effects of specific e-prescribing functional alternatives. Until more is known, e-prescribing initiatives should include provisions to monitor for unintended hazards.
| S-EPMC305459 | biostudies-literature
Project description:BackgroundComputerized clinical decision support systems (CCDSSs) for drug therapy management are designed to promote safe and effective medication use. Evidence documenting the effectiveness of CCDSSs for improving drug therapy is necessary for informed adoption decisions. The objective of this review was to systematically review randomized controlled trials assessing the effects of CCDSSs for drug therapy management on process of care and patient outcomes. We also sought to identify system and study characteristics that predicted benefit.MethodsWe conducted a decision-maker-researcher partnership systematic review. We updated our earlier reviews (1998, 2005) by searching MEDLINE, EMBASE, EBM Reviews, Inspec, and other databases, and consulting reference lists through January 2010. Authors of 82% of included studies confirmed or supplemented extracted data. We included only randomized controlled trials that evaluated the effect on process of care or patient outcomes of a CCDSS for drug therapy management compared to care provided without a CCDSS. A study was considered to have a positive effect (i.e., CCDSS showed improvement) if at least 50% of the relevant study outcomes were statistically significantly positive.ResultsSixty-five studies met our inclusion criteria, including 41 new studies since our previous review. Methodological quality was generally high and unchanged with time. CCDSSs improved process of care performance in 37 of the 59 studies assessing this type of outcome (64%, 57% of all studies). Twenty-nine trials assessed patient outcomes, of which six trials (21%, 9% of all trials) reported improvements.ConclusionsCCDSSs inconsistently improved process of care measures and seldomly improved patient outcomes. Lack of clear patient benefit and lack of data on harms and costs preclude a recommendation to adopt CCDSSs for drug therapy management.
| S-EPMC3179735 | biostudies-literature
Project description:Our objective was to identify characteristics associated with high-volume antibiotic prescribing among office-based primary care physicians to target antibiotic stewardship efforts. Physicians aged 40 years and older who were male, located in the South, and in solo or 2-physician practices prescribed higher volumes of antibiotics than their peers by specialty.
| S-EPMC5788066 | biostudies-literature
Project description:Computerized drug prescribing alerts can improve patient safety, but are often overridden because of poor specificity and alert overload. Our objective was to improve clinician acceptance of drug alerts by designing a selective set of drug alerts for the ambulatory care setting and minimizing workflow disruptions by designating only critical to high-severity alerts to be interruptive to clinician workflow. The alerts were presented to clinicians using computerized prescribing within an electronic medical record in 31 Boston-area practices. There were 18,115 drug alerts generated during our six-month study period. Of these, 12,933 (71%) were noninterruptive and 5,182 (29%) interruptive. Of the 5,182 interruptive alerts, 67% were accepted. Reasons for overrides varied for each drug alert category and provided potentially useful information for future alert improvement. These data suggest that it is possible to design computerized prescribing decision support with high rates of alert recommendation acceptance by clinicians.
| S-EPMC1380196 | biostudies-literature
Project description:Background:The objectives of this study were to develop methods to measure population-based outpatient antibiotic prescribing in Massachusetts and to describe the findings as a first step toward institution of ongoing surveillance. Methods:We analyzed outpatient prescription claims from the Massachusetts All-Payers Claims Database from 2011 to 2015. We grouped claims for antibiotics according to the World Health Organization's Anatomical Therapeutic Chemical Classification System using the National Library of Medicine's RXNorm database. We grouped prescribers into 17 specialties. Antibiotic use rates were calculated, and simple frequencies were used to describe patterns. Results:The overall annual rate of outpatient antibiotic use for individuals aged 0-64 years was 696 prescriptions per 1000 people. During 2015, 68% of people in Massachusetts had no antibiotic prescription, and 17% had only 1 prescription. There was dramatic variability in antibiotic use rates by census tract within the state (rates of penicillin use ranged from 31 to 265 prescriptions per 1000 people, macrolides from 28 to 333, cephalosporins from 8 to 89, quinolones from 13 to 118). Antibiotic use rates were generally lower in urban census tracts. From 2011 to 2015, there was a 17% decline in antibiotic prescribing, with the greatest decline for macrolides (28%). Conclusions:There was variability in antibiotic prescribing within Massachusetts by age, sex, and antibiotic class. Variation in antibiotic use across census tracts within the state was similar to the variation in use across US states. Continued measurement and detailed local population rates of antibiotic use in Massachusetts will provide feedback for local prescribers.
| S-EPMC6499896 | biostudies-literature
Project description:Objectives(1) Systematically assemble, analyse and synthesise published evidence on causes of prescribing error in children. (2) Present results to a multidisciplinary group of paediatric prescribing stakeholders to validate findings and establish how causative factors lead to errors in practice.DesignScoping review using Arksey and O'Malley's framework, including stakeholder consultation; qualitative evidence synthesis.MethodsWe followed the six scoping review stages. (1) Research question-the research question was 'What is known about causes of prescribing error in children?' (2) Search strategy-we searched MEDLINE, EMBASE, CINAHL (from inception to February 2018), grey literature and reference lists of included studies. (3) Article selection-all published evidence contributing information on the causes of prescribing error in children was eligible for inclusion. We included review articles as secondary evidence to broaden understanding. (4) Charting data-results were collated in a custom data charting form. (5) Reporting results-we summarised article characteristics, extracted causal evidence and thematically synthesised findings. (6) Stakeholder consultation-results were presented to a multidisciplinary focus group of six prescribing stakeholders to establish validity, relevance and mechanisms by which causes lead to errors in practice.Results68 articles were included. We identified six main causes of prescribing errors: children's fundamental differences led to individualised dosing and calculations; off-licence prescribing; medication formulations; communication with children; and experience working with children. Primary evidence clarifying causes was lacking.ConclusionsSpecific factors complicate prescribing for children and increase risk of errors. Primary research is needed to confirm and elaborate these causes of error. In the meantime, this review uses existing evidence to make provisional paediatric-specific recommendations for policy, practice and education.
| S-EPMC6701596 | biostudies-literature
Project description:OBJECTIVE:Clinicians using clinical decision support (CDS) to prescribe medications have an obligation to ensure that prescriptions are safe. One option is to verify the safety of prescriptions if there is uncertainty, for example, by using drug references. Supervisory control experiments in aviation and process control have associated errors, with reduced verification arising from overreliance on decision support. However, it is unknown whether this relationship extends to clinical decision-making. Therefore, we examine whether there is a relationship between verification behaviors and prescribing errors, with and without CDS medication alerts, and whether task complexity mediates this. METHODS:A total of 120 students in the final 2 years of a medical degree prescribed medicines for patient scenarios using a simulated electronic prescribing system. CDS (correct, incorrect, and no CDS) and task complexity (low and high) were varied. Outcomes were omission (missed prescribing errors) and commission errors (accepted false-positive alerts). Verification measures were access of drug references and view time percentage of task time. RESULTS:Failure to access references for medicines with prescribing errors increased omission errors with no CDS (high-complexity: χ 2(1) = 12.716; p < 0.001) and incorrect CDS (Fisher's exact; low-complexity: p = 0.002; high-complexity: p = 0.001). Failure to access references for false-positive alerts increased commission errors (low-complexity: χ 2(1) = 16.673, p < 0.001; high-complexity: χ 2(1) = 18.690, p < 0.001). Fewer participants accessed relevant references with incorrect CDS compared with no CDS (McNemar; low-complexity: p < 0.001; high-complexity: p < 0.001). Lower view time percentages increased omission (F(3, 361.914) = 4.498; p = 0.035) and commission errors (F(1, 346.223) = 2.712; p = 0.045). View time percentages were lower in CDS-assisted conditions compared with unassisted conditions (F(2, 335.743) = 10.443; p < 0.001). DISCUSSION:The presence of CDS reduced verification of prescription safety. When CDS was incorrect, reduced verification was associated with increased prescribing errors. CONCLUSION:CDS can be incorrect, and verification provides one mechanism to detect errors. System designers need to facilitate verification without increasing workload or eliminating the benefits of correct CDS.
| S-EPMC6353646 | biostudies-literature
Project description:BackgroundPrescribing errors are common. It has been suggested that the severity as well as the frequency of errors should be assessed when measuring prescribing error rates. This would provide more clinically relevant information, and allow more complete evaluation of the effectiveness of interventions designed to reduce errors.ObjectiveThe objective of this systematic review was to describe the tools used to assess prescribing error severity in studies reporting hospital prescribing error rates.Data sourcesThe following databases were searched: MEDLINE, EMBASE, International Pharmaceutical Abstracts, and CINAHL (January 1985-January 2013).Study selectionWe included studies that reported the detection and rate of prescribing errors in prescriptions for adult and/or pediatric hospital inpatients, or elaborated on the properties of severity assessment tools used by these studies. Studies not published in English, or that evaluated errors for only one disease or drug class, one route of administration, or one type of prescribing error, were excluded, as were letters and conference abstracts. One reviewer screened all abstracts and obtained complete articles. A second reviewer assessed 10 % of all abstracts and complete articles to check reliability of the screening process.AppraisalTools were appraised for country and method of development, whether the tool assessed actual or potential harm, levels of severity assessed, and results of any validity and reliability studies.ResultsFifty-seven percent of 107 studies measuring prescribing error rates included an assessment of severity. Forty tools were identified that assessed severity, only two of which had acceptable reliability and validity. In general, little information was given on the method of development or ease of use of the tools, although one tool required four reviewers and was thus potentially time consuming.LimitationsThe review was limited to studies written in English. One of the review authors was also the author of one of the tools, giving a potential source of bias.ConclusionA wide range of severity assessment tools are used in the literature. Developing a basis of comparison between tools would potentially be helpful in comparing findings across studies. There is a potential need to establish a less time-consuming method of measuring severity of prescribing error, with acceptable international reliability and validity.
| S-EPMC3834169 | biostudies-literature