Factors contributing to medication errors made when using computerized order entry in pediatrics: a systematic review

Strategies used to detect and mitigate system-related errors over time: A qualitative study in an Australian health district

BACKGROUND

Electronic medical record (EMR) systems provide timely access to clinical information and have been shown to improve medication safety. However, EMRs can also create opportunities for error, including system-related errors or errors that were unlikely or not possible with the use of paper medication charts. This study aimed to determine the detection and mitigation strategies adopted by a health district in Australia to target system-related errors and to explore stakeholder views on strategies needed to curb future system-related errors from emerging.

METHODS

A qualitative descriptive study design was used comprising semi-structured interviews. Data were collected from three hospitals within a health district in Sydney, Australia, between September 2020 and May 2021. Interviews were conducted with EMR users and other key stakeholders (e.g. clinical informatics team members). Participants were asked to reflect on how system-related errors changed over time, and to describe approaches taken by their organisation to detect and mitigate these errors. Thematic analysis was conducted iteratively using a general inductive approach, where codes were assigned as themes emerged from the data.

RESULTS

Interviews were conducted with 25 stakeholders. Participants reported that most system-related errors were detected by front-line clinicians. Following error detection, clinicians either reported system-related errors directly to the clinical informatics team or submitted reports to the incident information management system. System-related errors were also reported to be detected via reports run within the EMR, or during organisational processes such as incident investigations or system enhancement projects. EMR redesign was the main approach described by participants for mitigating system-related errors, however other strategies, like regular user education and minimising the use of hybrid systems, were also reported.

CONCLUSIONS

Initial detection of system-related errors relies heavily on front-line clinicians, however other organisational strategies that are proactive and layered can improve the systemic detection, investigation, and management of errors. Together with EMR design changes, complementary error mitigation strategies, including targeted staff education, can support safe EMR use and development.

Prevalence and factors associated with medication administration errors in the neonatal intensive care unit: A multicentre, nationwide direct observational study

AIM(S)

To determine the prevalence of medication administration errors and identify factors associated with medication administration errors among neonates in the neonatal intensive care units.

DESIGN

Prospective direct observational study.

METHODS

The study was conducted in the neonatal intensive care units of five public hospitals in Malaysia from April 2022 to March 2023. The preparation and administration of medications were observed using a standardized data collection form followed by chart review. After data collection, error identification was independently performed by two clinical pharmacists. Multivariable logistic regression was used to identify factors associated with medication administration errors.

RESULTS

A total of 743 out of 1093 observed doses had at least one error, affecting 92.4% (157/170) neonates. The rate of medication administration errors was 68.0%. The top three most frequently occurring types of medication administration errors were wrong rate of administration (21.2%), wrong drug preparation (17.9%) and wrong dose (17.0%). Factors significantly associated with medication administration errors were medications administered intravenously, unavailability of a protocol, the number of prescribed medications, nursing experience, non-ventilated neonates and gestational age in weeks.

CONCLUSION

Medication administration errors among neonates in the neonatal intensive care units are still common. The intravenous route of administration, absence of a protocol, younger gestational age, non-ventilated neonates, higher number of medications prescribed and increased years of nursing experience were significantly associated with medication administration errors.

IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE

The findings of this study will enable the implementation of effective and sustainable interventions to target the factors identified in reducing medication administration errors among neonates in the neonatal intensive care unit.

REPORTING METHOD

We adhered to the STROBE checklist.

PATIENT OR PUBLIC CONTRIBUTION

An expert panel consisting of healthcare professionals was involved in the identification of independent variables.

Use of Computerized Physician Order Entry with Clinical Decision Support to Prevent Dose Errors in Pediatric Medication Orders: A Systematic Review

BACKGROUND

Prescribing is a high-risk task within the pediatric medication-use process and requires defenses to prevent errors. Such system-centric defenses include electronic health record systems with computerized physician order entry (CPOE) and clinical decision support (CDS) tools that assist safe prescribing. The objective of this study was to examine the effects of CPOE systems with CDS functions in preventing dose errors in pediatric medication orders.

MATERIAL AND METHODS

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 criteria and Synthesis Without Meta-Analysis (SWiM) items. The study protocol was registered in PROSPERO (CRD42021277413). The final literature search on MEDLINE (Ovid), Scopus, Web of Science, and EMB Reviews was conducted on 10 September 2023. Only peer-reviewed studies considering both CPOE and CDS systems in pediatric inpatient or outpatient settings were included. Study selection, data extraction, and evidence quality assessment (JBI critical appraisal tool assessment and GRADE approach) were carried out by two individual reviewers. Vote counting method was used to evaluate the effects of CPOE-CDS systems on dose errors rates.

RESULTS

A total of 17 studies published in 2007-2021 met the inclusion criteria. The most used CDS tools were dose range check (n = 14), dose calculator (n = 8), and dosing frequency check (n = 8). Alerts were recorded in 15 studies. A statistically significant reduction in dose errors was found in eight studies, whereas an increase of dose errors was not reported.

CONCLUSIONS

The CPOE-CDS systems have the potential to reduce pediatric dose errors. Most beneficial interventions seem to be system customization, implementing CDS alerts, and the use of dose range check. While human factors are still present within the medication use process, further studies and development activities are needed to optimize the usability of CPOE-CDS systems.

Identifying the data elements and functionalities of clinical decision support systems to administer medication for neonates and pediatrics: a systematic literature review

BACKGROUND

Patient safety is a central healthcare policy worldwide. Adverse drug events (ADE) are among the main threats to patient safety. Children are at a higher risk of ADE in each stage of medication management process. ADE rate is high in the administration stage, as the final stage of preventing medication errors in pediatrics and neonates. The most effective way to reduce ADE rate is using medication administration clinical decision support systems (MACDSSs). The present study reviewed the literature on MACDSS for neonates and pediatrics. It identified and classified the data elements that mapped onto the Fast Healthcare Interoperability Resources (FHIR) standard and the functionalities of these systems to guide future research.

METHODS

PubMed/ MEDLINE, Embase, CINAHL, and ProQuest databases were searched from 1995 to June 31, 2021. Studies that addressed developing or applying medication administration software for neonates and pediatrics were included. Two authors reviewed the titles, abstracts, and full texts. The quality of eligible studies was assessed based on the level of evidence. The extracted data elements were mapped onto the FHIR standard.

RESULTS

In the initial search, 4,856 papers were identified. After removing duplicates, 3,761 titles, and abstracts were screened. Finally, 56 full-text papers remained for evaluation. The full-text review of papers led to the retention of 10 papers which met the eligibility criteria. In addition, two papers from the reference lists were included. A total number of 12 papers were included for analysis. Six papers were categorized as high-level evidence. Only three papers evaluated their systems in a real environment. A variety of data elements and functionalities could be observed. Overall, 84 unique data elements were extracted from the included papers. The analysis of reported functionalities showed that 18 functionalities were implemented in these systems.

CONCLUSION

Identifying the data elements and functionalities as a roadmap by developers can significantly improve MACDSS performance. Though many CDSSs have been developed for different medication processes in neonates and pediatrics, few have actually evaluated MACDSSs in reality. Therefore, further research is needed on the application and evaluation of MACDSSs in the real environment.

PROTOCOL REGISTRATION

(dx.doi.org/10.17504/protocols.io.bwbwpape).

Comparing patient safety culture in primary, secondary and tertiary hospitals in Ghana

Objective

This study compared patient safety culture among health professionals in tertiary, secondary and primary hospitals.

Design

We conducted a cross-sectional survey among thirteen primary, secondary and tertiary hospitals in Ghana. A structured questionnaire was administered to 1,656 health professionals. Data were analysed using descriptive statistics and One-Way Analysis of Variance (ANOVA).

Setting

This study was conducted in the Greater Accra, Bono and Upper East regions, representing the southern, middle and northern ecological zones, respectively.

Participants

Health professionals.

Main outcome measures

The primary outcome was patient safety culture.

Results

Five patient safety culture dimensions were rated moderate positive response, while five were rated high positive response. We found a statistically significant difference in patient safety culture across primary, secondary and tertiary hospitals (p < 0.05). For instance, the mean difference between tertiary and secondary hospitals was statistically significant (p < 0.05). Additionally, the mean difference between tertiary and primary hospitals was statistically significant (p < 0.05). There was also a significant difference in the means between secondary and primary hospitals (p < 0.05).

Conclusion

This study has demonstrated a variation in patient safety culture across Ghana's tertiary, secondary and primary hospitals. Therefore, healthcare managers and professionals should prioritise patient safety.

Funding

This work was supported by the University of Ghana [UGRF/13/MDG-001/2019-2020].

Improving medication safety in a paediatric hospital: a mixed-methods evaluation of a newly implemented computerised provider order entry system

OBJECTIVES

Computerised provider order entry (CPOE) systems have been implemented around the world as a solution to reduce ordering and transcription errors. However, previous literature documented many challenges to attain this goal, especially in paediatric settings. The objectives of this study were to (1) analyse the impact of a paediatric CPOE system on medication safety and (2) suggest potential error prevention strategies.

METHODS

A pre-post observational study was conducted at the pilot ward (n=60 beds) of a paediatric academic health centre through mixed methods. The implementation project and medication management workflows were described through active participation to the project management team, observation, discussions and analysis of related documents. Furthermore, using incident reports, the nature of each error and error rate was compared between the preperiod and postperiod.

RESULTS

The global error rate was lower, but non-statistically significant, in the post implementation phase, which was mostly driven by a significant reduction in errors during order acknowledgement, transmission and transcription. Few errors occurred at the prescription step, and most errors occurred during medication administration. Furthermore, some errors could have been prevented using a CPOE in the pre-implementation period, and the CPOE led to few technology-related errors.

DISCUSSION AND CONCLUSION

This study identified both intended and unintended effects of CPOE adoption through the entire medication management workflow. This study revealed the importance of simplifying the acknowledgement, transmission and transcribing steps through the implementation of a CPOE to reduce medication errors. Improving the usability of the electronic medication administration record could help further improve medication safety.

Short- and long-term effects of an electronic medication management system on paediatric prescribing errors

Electronic medication management (eMM) systems are designed to improve safety, but there is little evidence of their effectiveness in paediatrics. This study assesses the short-term (first 70 days of eMM use) and long-term (one-year) effectiveness of an eMM system to reduce prescribing errors, and their potential and actual harm. We use a stepped-wedge cluster randomised controlled trial (SWCRCT) at a paediatric referral hospital, with eight clusters randomised for eMM implementation. We assess long-term effects from an additional random sample of medication orders one-year post-eMM. In the SWCRCT, errors that are potential adverse drug events (ADEs) are assessed for actual harm. The study comprises 35,260 medication orders for 4821 patients. Results show no significant change in overall prescribing error rates in the first 70 days of eMM use (incident rate ratio [IRR] 1.05 [95%CI 0.92-1.21], but a 62% increase (IRR 1.62 [95%CI 1.28-2.04]) in potential ADEs suggesting immediate risks to safety. One-year post-eMM, errors decline by 36% (IRR 0.64 [95%CI 0.56-0.72]) and high-risk medication errors decrease by 33% (IRR 0.67 [95%CI 0.51-0.88]) compared to pre-eMM. In all periods, dose error rates are more than double that of other error types. Few errors are associated with actual harm, but 71% [95%CI 50-86%] of patients with harm experienced a dose error. In the short-term, eMM implementation shows no improvement in error rates, and an increase in some errors. A year after eMM error rates significantly decline suggesting long-term benefits. eMM optimisation should focus on reducing dose errors due to their high frequency and capacity to cause harm.

Prevalence, Causes and Severity of Medication Administration Errors in the Neonatal Intensive Care Unit: A Systematic Review and Meta-Analysis

INTRODUCTION

Neonates are at greater risk of preventable adverse drug events as compared to children and adults.

OBJECTIVE

This study aimed to estimate and critically appraise the evidence on the prevalence, causes and severity of medication administration errors (MAEs) amongst neonates in Neonatal Intensive Care Units (NICUs).

METHODS

A systematic review and meta-analysis was conducted by searching nine electronic databases and the grey literature for studies, without language and publication date restrictions. The pooled prevalence of MAEs was estimated using a random-effects model. Data on error causation were synthesised using Reason's model of accident causation.

RESULTS

Twenty unique studies were included. Amongst direct observation studies reporting total opportunity for errors as the denominator for MAEs, the pooled prevalence was 59.3% (95% confidence interval [CI] 35.4-81.3, I² = 99.5%). Whereas, the non-direct observation studies reporting medication error reports as the denominator yielded a pooled prevalence of 64.8% (95% CI 46.6-81.1, I² = 98.2%). The common reported causes were error-provoking environments (five studies), while active failures were reported by three studies. Only three studies examined the severity of MAEs, and each utilised a different method of assessment.

CONCLUSIONS

This is the first comprehensive systematic review and meta-analysis estimating the prevalence, causes and severity of MAEs amongst neonates. There is a need to improve the quality and reporting of studies to produce a better estimate of the prevalence of MAEs amongst neonates. Important targets such as wrong administration-technique, wrong drug-preparation and wrong time errors have been identified to guide the implementation of remedial measures.

Duplicate Medication Order Errors: Safety Gaps and Recommendations for Improvement

Background: Duplicate medication orders are a prominent type of medication error that in some circumstances has increased after implementation of health information technology. Duplicate medication orders are commonly defined as two or more active orders for the same medication or medications within the same therapeutic class. While there have been several studies that have identified contributing factors and described potential solutions, duplicate medication order errors continue to impact patient safety. Methods: We analyzed 377 reports from 95 healthcare facilities to more granularly define the types of duplicate medication order errors and the context under which these errors occurred, as well as potential contributing factors. Results: Of the 377 reports reviewed, 304 (80.6%) met the criteria to be defined as a duplicate medication order error. The most frequent duplicate medication order error type was same order (n=131, 43.1%), followed by same therapeutic class (n=98, 32.2%) and same medication (n=70, 23.0%). Errors were identified during different medication process tasks and most commonly during medication reconciliation during the patient’s stay in the hospital (n=72, 23.7%) and during pharmacy verification (n=36, 11.8%). Factors contributing to these errors included health information technology issues (n=63, 20.7%), gaps in care coordination (n=44, 14.5%), and a prior dose or medication order not being discontinued (n=52, 17.1%). Conclusion: Our results highlight specific areas for practice improvement, and we make recommendations for how healthcare facilities can better address duplicate medication order errors.

Participatory Design of a Medication Module in an Electronic Medical Record for Paediatric Palliative Care: A Think-Aloud Approach with Nurses and Physicians

BACKGROUND

Electronic medical records (EMRs) play a key role in improving documentation and quality of care in paediatric palliative care (PPC). Inadequate EMR design can cause incorrect prescription and administration of medications. Due to the fact of complex diseases and the resulting high level of medical complexity, patients in PPC are vulnerable to medication errors. Consequently, involving users in the development process is important. Therefore, the aim of this study was to evaluate the acceptance of a medication module from the perspective of potential users in PPC and to involve them in the development process.

METHODS

A qualitative observational study was conducted with 10 nurses and four physicians using a concurrent think-aloud protocol and semi-structured qualitative interviews. A qualitative content analysis was applied based on a unified theory of acceptance and use of technology.

RESULTS

Requirements from the user's perspective could be identified as possible influences on acceptance and actual use. Requirements were grouped into the categories "performance expectancies" and "effort expectancies".

CONCLUSIONS

The results serve as a basis for further development. Attention should be given to the reduction of display fragmentation, as it decreases cognitive load. Further approaches to evaluation should be taken.

Predicting inpatient pharmacy order interventions using provider action data

Objective

The widespread deployment of electronic health records (EHRs) has introduced new sources of error and inefficiencies to the process of ordering medications in the hospital setting. Existing work identifies orders that require pharmacy intervention by comparing them to a patient’s medical records. In this work, we develop a machine learning model for identifying medication orders requiring intervention using only provider behavior and other contextual features that may reflect these new sources of inefficiencies.

Materials and Methods

Data on providers’ actions in the EHR system and pharmacy orders were collected over a 2-week period in a major metropolitan hospital system. A classification model was then built to identify orders requiring pharmacist intervention. We tune the model to the context in which it would be deployed and evaluate global and local feature importance.

Results

The resultant model had an area under the receiver-operator characteristic curve of 0.91 and an area under the precision-recall curve of 0.44.

Conclusions

Providers’ actions can serve as useful predictors in identifying medication orders that require pharmacy intervention. Careful model tuning for the clinical context in which the model is deployed can help to create an effective tool for improving health outcomes without using sensitive patient data.

The effects of clinical decision support system for prescribing medication on patient outcomes and physician practice performance: a systematic review and meta-analysis

Background

Clinical Decision Support Systems (CDSSs) for Prescribing are one of the innovations designed to improve physician practice performance and patient outcomes by reducing prescription errors. This study was therefore conducted to examine the effects of various CDSSs on physician practice performance and patient outcomes.

Methods

This systematic review was carried out by searching PubMed, Embase, Web of Science, Scopus, and Cochrane Library from 2005 to 2019. The studies were independently reviewed by two researchers. Any discrepancies in the eligibility of the studies between the two researchers were then resolved by consulting the third researcher. In the next step, we performed a meta-analysis based on medication subgroups, CDSS-type subgroups, and outcome categories. Also, we provided the narrative style of the findings. In the meantime, we used a random-effects model to estimate the effects of CDSS on patient outcomes and physician practice performance with a 95% confidence interval. Q statistics and I² were then used to calculate heterogeneity.

Results

On the basis of the inclusion criteria, 45 studies were qualified for analysis in this study. CDSS for prescription drugs/COPE has been used for various diseases such as cardiovascular diseases, hypertension, diabetes, gastrointestinal and respiratory diseases, AIDS, appendicitis, kidney disease, malaria, high blood potassium, and mental diseases. In the meantime, other cases such as concurrent prescribing of multiple medications for patients and their effects on the above-mentioned results have been analyzed. The study shows that in some cases the use of CDSS has beneficial effects on patient outcomes and physician practice performance (std diff in means = 0.084, 95% CI 0.067 to 0.102). It was also statistically significant for outcome categories such as those demonstrating better results for physician practice performance and patient outcomes or both. However, there was no significant difference between some other cases and traditional approaches. We assume that this may be due to the disease type, the quantity, and the type of CDSS criteria that affected the comparison. Overall, the results of this study show positive effects on performance for all forms of CDSSs.

Conclusions

Our results indicate that the positive effects of the CDSS can be due to factors such as user-friendliness, compliance with clinical guidelines, patient and physician cooperation, integration of electronic health records, CDSS, and pharmaceutical systems, consideration of the views of physicians in assessing the importance of CDSS alerts, and the real-time alerts in the prescription.

Prescriber behaviours that could be targeted for change: An analysis of behaviours demonstrated during prescription writing in children

BACKGROUND

The prescribing process for children with cancer is complex, and errors can occur at any step. As a result, many interventions have been used to reduce errors. However, few of them have been designed based on an understanding of the prescriber behaviour that can lead to errors. In order to design effective behaviour change interventions, it is important first to understand the prescribing process and identify prescriber behaviours that could be targeted for change.

OBJECTIVES

To describe the prescribing process in a paediatric oncology ward and to identify prescriber behaviours during prescription writing that could be targeted to reduce errors.

METHODS

This study employed two sequential phases. First, the prescribing process was observed and then described using the hierarchical task analysis (HTA) method. Second, prescriber tasks identified from the HTA were analysed using the behaviour change wheel (BCW) approach to identify promising behaviours for change. These identified behaviours were prioritised based on information collected from four focus groups with prescribers and chart review of errors made in the ward.

RESULTS

The prescribing process was complex and involved multiple tasks performed in varying orders. Applying the BCW identified thirty-two candidate behaviours for potentially reducing prescribing errors. However, after prioritization, only two emerged as promising candidate behaviours for intervention: writing drug indications at the time of prescribing and using a pre-written order when ordering medications through electronic prescribing.

CONCLUSIONS

This research suggests that two behaviours could be promising in reducing errors. Having identified these behaviours, future work could explore what needs to change with respect to individuals and their work environments to achieve the desired change in these identified behaviours.

Medication errors related to computerized provider order entry systems in hospitals and how they change over time: A narrative review

BACKGROUND

Evaluations of computerized provider order entry (CPOE) systems have revealed that reductions in certain types of medication errors occur simultaneously with the emergence of system-related errors - errors that are unlikely or not possible to occur with the use of paper-based medication charts. System-related errors appear to persist many years post-implementation of CPOE, although little is known about whether the types and rates of system-related errors that occur immediately following CPOE implementation are similar to those that endure or emerge after years of system use.

OBJECTIVE

To analyze and synthesize the literature on system-related errors, specifically in relation to the length of time that CPOE systems have been in use, to determine what is currently known about how system-related errors change over time.

METHODS

A literature search was undertaken using the PubMed database to identify English language articles published between January 2005 and March 2020 that provided original data on system-related errors resulting from CPOE system use. Studies were included if they provided results on system-related errors and information relating to the length of time that CPOE had been in use.

RESULTS

Thirty-one studies met the inclusion criteria for this narrative review. System-related errors were identified and described during short, medium and long-term use of CPOE systems, but no single study examined how errors changed over time. In comparing findings across studies, results suggest that system-related errors persist with long-term use of CPOE systems, although likely to occur at a reduced rate.

CONCLUSIONS

This review has highlighted a significant gap in knowledge on how system-related errors change over time. Determining what and when system-related errors occur and the system factors that contribute to their occurrence at different time points after CPOE implementation is necessary for the future prevention and mitigation of these errors.

The impact of health information technology on prescribing errors in hospitals: a systematic review and behaviour change technique analysis

BACKGROUND

Health information technology (HIT) is known to reduce prescribing errors but may also cause new types of technology-generated errors (TGE) related to data entry, duplicate prescribing, and prescriber alert fatigue. It is unclear which component behaviour change techniques (BCTs) contribute to the effectiveness of prescribing HIT implementations and optimisation. This study aimed to (i) quantitatively assess the HIT that reduces prescribing errors in hospitals and (ii) identify the BCTs associated with effective interventions.

METHODS

Articles were identified using CINAHL, EMBASE, MEDLINE, and Web of Science to May 2020. Eligible studies compared prescribing HIT with paper-order entry and examined prescribing error rates. Studies were excluded if prescribing error rates could not be extracted, if HIT use was non-compulsory or designed for one class of medication. The Newcastle-Ottawa scale was used to assess study quality. The review was reported in accordance with the PRISMA and SWiM guidelines. Odds ratios (OR) with 95% confidence intervals (CI) were calculated across the studies. Descriptive statistics were used to summarise effect estimates. Two researchers examined studies for BCTs using a validated taxonomy. Effectiveness ratios (ER) were used to determine the potential impact of individual BCTs.

RESULTS

Thirty-five studies of variable risk of bias and limited intervention reporting were included. TGE were identified in 31 studies. Compared with paper-order entry, prescribing HIT of varying sophistication was associated with decreased rates of prescribing errors (median OR 0.24, IQR 0.03-0.57). Ten BCTs were present in at least two successful interventions and may be effective components of prescribing HIT implementation and optimisation including prescriber involvement in system design, clinical colleagues as trainers, modification of HIT in response to feedback, direct observation of prescriber workflow, monitoring of electronic orders to detect errors, and system alerts that prompt the prescriber.

CONCLUSIONS

Prescribing HIT is associated with a reduction in prescribing errors in a variety of hospital settings. Poor reporting of intervention delivery and content limited the BCT analysis. More detailed reporting may have identified additional effective intervention components. Effective BCTs may be considered in the design and development of prescribing HIT and in the reporting and evaluation of future studies in this area.

Alert Override Patterns With a Medication Clinical Decision Support System in an Academic Emergency Department: Retrospective Descriptive Study

Background

Physicians’ alert overriding behavior is considered to be the most important factor leading to failure of computerized provider order entry (CPOE) combined with a clinical decision support system (CDSS) in achieving its potential adverse drug events prevention effect. Previous studies on this subject have focused on specific diseases or alert types for well-defined targets and particular settings. The emergency department is an optimal environment to examine physicians’ alert overriding behaviors from a broad perspective because patients have a wider range of severity, and many receive interdisciplinary care in this environment. However, less than one-tenth of related studies have targeted this physician behavior in an emergency department setting.

Objective

The aim of this study was to describe alert override patterns with a commercial medication CDSS in an academic emergency department.

Methods

This study was conducted at a tertiary urban academic hospital in the emergency department with an annual census of 80,000 visits. We analyzed data on the patients who visited the emergency department for 18 months and the medical staff who treated them, including the prescription and CPOE alert log. We also performed descriptive analysis and logistic regression for assessing the risk factors for alert overrides.

Results

During the study period, 611 physicians cared for 71,546 patients with 101,186 visits. The emergency department physicians encountered 13.75 alerts during every 100 orders entered. Of the total 102,887 alerts, almost two-thirds (65,616, 63.77%) were overridden. Univariate and multivariate logistic regression analyses identified 21 statistically significant risk factors for emergency department physicians’ alert override behavior.

Conclusions

In this retrospective study, we described the alert override patterns with a medication CDSS in an academic emergency department. We found relatively low overrides and assessed their contributing factors, including physicians’ designation and specialty, patients’ severity and chief complaints, and alert and medication type.

Computerized provider order entry-related medication errors among hospitalized patients: An integrative review

The Institute of Medicine estimates that 7,000 lives are lost yearly as a result of medication errors. Computerized physician and/or provider order entry was one of the proposed solutions to overcome this tragic issue. Despite some promising data about its effectiveness, it has been found that computerized provider order entry may facilitate medication errors.The purpose of this review is to summarize current evidence of computerized provider order entry -related medication errors and address the sociotechnical factors impacting the safe use of computerized provider order entry. By using PubMed and Google Scholar databases, a systematic search was conducted for articles published in English between 2007 and 2019 regarding the unintended consequences of computerized provider order entry and its related medication errors. A total of 288 articles were screened and categorized based on their use within the review. One hundred six articles met our pre-defined inclusion criteria and were read in full, in addition to another 27 articles obtained from references. All included articles were classified into the following categories: rates and statistics on computerized provider order entry -related medication errors, types of computerized provider order entry -related unintended consequences, factors contributing to computerized provider order entry failure, and recommendations based on addressing sociotechnical factors. Identifying major types of computerized provider order entry -related unintended consequences and addressing their causes can help in developing appropriate strategies for safe and effective computerized provider order entry. The interplay between social and technical factors can largely affect its safe implementation and use. This review discusses several factors associated with the unintended consequences of this technology in healthcare settings and presents recommendations for enhancing its effectiveness and safety within the context of sociotechnical factors.

The Impact of Technology on Prescribing Errors in Pediatric Intensive Care: A Before and After Study

BACKGROUND

Increased use of health information technology (HIT) has been advocated as a medication error reduction strategy. Evidence of its benefits in the pediatric setting remains limited. In 2012, electronic prescribing (ICCA, Philips, United Kingdom) and standard concentration infusions (SCIs)-facilitated by smart-pump technology-were introduced into the pediatric intensive care unit (PICU) of an Irish tertiary-care pediatric hospital.

OBJECTIVE

The aim of this study is to assess the impact of the new technology on the rate and severity of PICU prescribing errors and identify technology-generated errors.

METHODS

A retrospective, before and after study design, was employed. Medication orders were reviewed over 24 weeks distributed across four time periods: preimplementation (Epoch 1); postimplementation of SCIs (Epoch 2); immediate postimplementation of electronic prescribing (Epoch 3); and 1 year postimplementation (Epoch 4). Only orders reviewed by a clinical pharmacist were included. Prespecified definitions, multidisciplinary consensus and validated grading methods were utilized.

RESULTS

A total of 3,356 medication orders for 288 patients were included. Overall error rates were similar in Epoch 1 and 4 (10.2 vs. 9.8%; p = 0.8), but error types differed (p < 0.001). Incomplete and wrong unit errors were eradicated; duplicate orders increased. Dosing errors remained most common. A total of 27% of postimplementation errors were technology-generated. Implementation of SCIs alone was associated with significant reductions in infusion-related prescribing errors (29.0% [Epoch 1] to 14.6% [Epoch 2]; p < 0.001). Further reductions (8.4% [Epoch 4]) were identified after implementation of electronically generated infusion orders. Non-infusion error severity was unchanged (p = 0.13); fewer infusion errors reached the patient (p < 0.01). No errors causing harm were identified.

CONCLUSION

The limitations of electronic prescribing in reducing overall prescribing errors in PICU have been demonstrated. The replacement of weight-based infusions with SCIs was associated with significant reductions in infusion prescribing errors. Technology-generated errors were common, highlighting the need for on-going research on HIT implementation in pediatric settings.

Health information technology:Fallacies and Sober realities - Redux A homage to Bentzi Karsh and Robert Wears

Since the publication of "Health Information Technology: Fallacies and Sober Realities" in 2010, health information technology (HIT) has become nearly ubiquitous in US healthcare facilities. Yet, HIT has yet to achieve its putative benefits of higher quality, safer, and lower cost care. There has been variable but largely marginal progress at addressing the 12 HIT fallacies delineated in the original paper. Here, we revisit several of the original fallacies and add five new ones. These fallacies must be understood and addressed by all stakeholders for HIT to be a positive force in achieving the high value healthcare system the nation deserves. Foundational cognitive and human factors engineering research and development continue to be essential to HIT development, deployment, and use.

Looking Behind the Curtain: Identifying Factors Contributing to Changes on Care Outcomes During a Large Commercial EHR Implementation

Objective:

To identify factors contributing to changes on quality, productivity, and safety outcomes during a large commercial electronic health record (EHR) implementation and to guide future research.

Methods:

We conducted a mixed-methods study assessing the impact of a commercial EHR implementation. The method consisted of a quantitative longitudinal evaluation followed by qualitative semi-structured, in-depth interviews with clinical employees from the same implementation. Fourteen interviews were recorded and transcribed. Three authors independently coded interview narratives and via consensus identified factors contributing to changes on 15 outcomes of quality, productivity, and safety.

Results:

We identified 14 factors that potentially affected the outcomes previously monitored. Our findings demonstrate that several factors related to the implementation (e.g., incomplete data migration), partially related (e.g., intentional decrease in volume of work), and not related (e.g., health insurance changes) may affect outcomes in different ways.

Discussion:

This is the first study to investigate factors contributing to changes on a broad set of quality, productivity, and safety outcomes during an EHR implementation guided by the results of a large longitudinal evaluation. The diversity of factors identified indicates that the need for organizational adaptation to take full advantage of new technologies is as important for health care as it is for other services sectors.

Conclusions:

We recommend continuous identification and monitoring of these factors in future evaluations to hopefully increase our understanding of the full impact of health information technology interventions.

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

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.