Effects of two commercial electronic prescribing systems on prescribing error rates in hospital in-patients: a before and after study

Longitudinal study of the manifestations and mechanisms of technology-related prescribing errors in pediatrics

OBJECTIVES

To examine changes in technology-related errors (TREs), their manifestations and underlying mechanisms at 3 time points after the implementation of computerized provider order entry (CPOE) in an electronic health record; and evaluate the clinical decision support (CDS) available to mitigate the TREs at 5-years post-CPOE.

MATERIALS AND METHODS

Prescribing errors (n = 1315) of moderate, major, or serious potential harm identified through review of 35 322 orders at 3 time points (immediately, 1-year, and 4-years post-CPOE) were assessed to identify TREs at a tertiary pediatric hospital. TREs were coded using the Technology-Related Error Mechanism classification. TRE rates, percentage of prescribing errors that were TREs, and mechanism rates were compared over time. Each TRE was tested in the CPOE 5-years post-implementation to assess the availability of CDS to mitigate the error.

RESULTS

TREs accounted for 32.5% (n = 428) of prescribing errors; an adjusted rate of 1.49 TREs/100 orders (95% confidence interval [CI]: 1.06, 1.92). At 1-year post-CPOE, the rate of TREs was 40% lower than immediately post (incident rate ratio [IRR]: 0.60; 95% CI: 0.41, 0.89). However, at 4-years post, the TRE rate was not significantly different to baseline (IRR: 0.80; 95% CI: 0.59, 1.08). "New workflows required by the CPOE" was the most frequent TRE mechanism at all time points. CDS was available to mitigate 32.7% of TREs.

DISCUSSION

In a pediatric setting, TREs persisted 4-years post-CPOE with no difference in the rate compared to immediately post-CPOE.

CONCLUSION

Greater attention is required to address TREs to enhance the safety benefits of systems.

The Dispensing Error Rate in an App-Based, Semaglutide-Supported Weight-Loss Service: A Retrospective Cohort Study

Digital weight-loss services (DWLSs) combining pharmacotherapy and health coaching have the potential to make a major contribution to the global struggle against obesity. However, the degree to which DWLSs compromise patient safety through the dispensation of Glucagon-like peptide-1 receptor agonist (GLP-1 RA) medications is unknown. This study retrospectively analysed the rate at which patients reported GLP-1 RA dispensing errors from patient-selected and partner pharmacies of Australia's largest DWLS provider over a six-month period. The analysis found that 99 (0.35%) of the 28,165 dispensed semaglutide orders contained an error. Incorrect dose (58.6%) and unreasonable medication expiry window (21.2%) were the two most common error types. Most errors (84.9%) were deemed to have been of medium urgency, with 11.1% being considered high-urgency errors. Incorrect doses (45.5%) and supplies of the wrong medication (36.3%) comprised most errors reported in high-urgency cases. Female patients reported more dispensing errors than male patients (0.41% vs. 0.12%, p < 0.001). Similarly, reported dispensing error rates were highest among patients aged 18 to 29 years (0.6%) and 30 to 39 years (0.5%). This research provides preliminary evidence that GLP-1 RA dispensing errors within comprehensive Australian DWLSs are relatively low.

Stakeholder perspectives on electronic prescribing in primary care: A scoping review

BACKGROUND

Electronic prescribing (e-prescribing) provides a convenient, efficient, paperless mechanism for the legal transfer of prescriptions between service users, prescribers, and dispensers. There have been advances in e-prescribing processes and increased uptake of e-prescribing globally, in recent years.

OBJECTIVE

To explore stakeholder perspectives on e-prescribing in primary care settings.

METHODS

A scoping review was conducted by systematically searching Medline, EMBASE, Scopus, and International Pharmaceutical Abstracts databases, using the key concepts "primary care", "e-prescribing", and "perspectives". Publications were selected by screening for eligibility against inclusion and exclusion criteria, whereby any publication written in English exploring e-prescribing in primary care settings from the perspective(s) of at least one type of stakeholder was eligible for inclusion. Following a systematic screening process, relevant data were extracted, collated, and synthesized.

RESULTS

Two thousand publications were identified and systematically screened, rendering 44 publications (e.g., primary research articles, abstracts) eligible for inclusion in this review. Most publications reported on studies conducted in the USA, the UK, and Europe and explored the views of pharmacists, pharmacy technicians, and pharmacy staff. Barriers to e-prescribing included system design and technical issues, lack of adequate training and communication issues between stakeholders. Enablers for e-prescribing included time savings, convenience, and increased legibility of prescriptions.

CONCLUSIONS

This review highlights many benefits of e-prescribing such as time efficiency, convenience, increased legibility, and less mishandling. Despite this, key barriers to e-prescribing within primary care settings were also recognized, including system design, technical issues, and lack of adequate training. As such, forcing functions, prescription tracking technologies, and better training have been identified as potential ways to address these barriers. While some negative experiences were reported, stakeholders were generally satisfied and had positive experiences with e-prescribing.

Secondary uses of electronic prescribing and pharmacy data in UK hospital care: a national survey

Electronic hospital pharmacy (EHP) systems are ubiquitous in today's hospitals, with many also implementing electronic prescribing (EP) systems; both contain a potential wealth of medication-related data to support quality improvement. The reasons for reuse and users of this data are generally unknown. Our objectives were to survey secondary use of data (SUD) from EHP and EP systems in UK hospitals, to identify users of and factors influencing SUD.A national postal survey was sent out to all hospital chief pharmacists with pre-notifications and follow-up reminders. Descriptive statistical analysis was performed.Of 187 hospital organisations, 65 (35%) responded. All had EHP systems (for ≥20 years) and all reused data; 50 (77%) had EP systems (established 1-10 years) but only 40 (80%) reused data. Reported facilitators for SUD included medication safety, providing feedback, benchmarking, saving time and patient experience. The purposes of SUD included audits, quality improvement, risk management and general medication-related reporting. Earlier introduction of SUD could provide an opportunity to heighten local improvement initiatives.Data from EHP systems is reused for multiple purposes. Evaluating SUD and sharing experiences could provide richer insight into potential SUD and barriers/factors to consider when implementing or upgrading EP/EHP systems.

An Analysis of Incident Reports Related to Electronic Medication Management: How They Change Over Time

OBJECTIVE

Electronic medication management (EMM) systems have been shown to introduce new patient safety risks that were not possible, or unlikely to occur, with the use of paper charts. Our aim was to examine the factors that contribute to EMM-related incidents and how these incidents change over time with ongoing EMM use.

METHODS

Incidents reported at 3 hospitals between January 1, 2010, and December 31, 2019, were extracted using a keyword search and then screened to identify EMM-related reports. Data contained in EMM-related incident reports were then classified as unsafe acts made by users and the latent conditions contributing to each incident.

RESULTS

In our sample, 444 incident reports were determined to be EMM related. Commission errors were the most frequent unsafe act reported by users (n = 298), whereas workarounds were reported in only 13 reports. User latent conditions (n = 207) were described in the highest number of incident reports, followed by conditions related to the organization (n = 200) and EMM design (n = 184). Over time, user unfamiliarity with the system remained a key contributor to reported incidents. Although fewer articles to electronic transfer errors were reported over time, incident reports related to the transfer of information between different computerized systems increased as hospitals adopted more clinical information systems.

CONCLUSIONS

Electronic medication management-related incidents continue to occur years after EMM implementation and are driven by design, user, and organizational conditions. Although factors contribute to reported incidents in varying degrees over time, some factors are persistent and highlight the importance of continuously improving the EMM system and its use.

Regular Medications in the Emergency Department Short Stay Unit (ReMedIES): Can Prescribing be Improved Without Increasing Resources?

Background: Hospital medication errors are frequent and may result in adverse events. Data on non-prescription of regular medications to emergency department short stay unit patients is lacking. In response to local reports of regular medication omissions, a multi-disciplinary team was tasked to introduce corrective emergency department (ED) process changes, but with no additional financing or resources. Aim: To reduce the rate of non-prescription of regular medications for patients admitted to the ED Short Stay Unit (SSU), through process change within existing resource constraints. Methods: A pre- and post-intervention observational study compared regular medication omission rates for patients admitted to the ED SSU. Included patients were those who usually took regular home medications at 08:00 or 20:00. Omissions were classified as clinically significant medications (CSMs) or non-clinically significant medications (non-CSMs). The intervention included reinforcement that the initially treating acute ED doctor was responsible for prescription completion, formal checking of prescription presence at SSU handover rounds, double-checking of prescription completeness by the overnight SSU lead nurse and junior doctor, and ED pharmacist medication reconciliation for those still identified as having regular medication non-prescription at 07:30. Results: For the 110 and 106 patients in the pre- and post-intervention periods, there was a non-significant reduction in the CSM omission rate of -11% (95% CI: -23 to 2), from 41% (95% CI: 32-50) to 30% (95% CI: 21-39). Conclusion: Non-prescription of regular CSMs for SSU patients was not significantly reduced by institution of work practice changes within existing resource constraints.

[Translation and adaptation of a tool prescribing errors related to computerized physician order entry coding to the French hospital background]

Prescribing errors related to computerized physician order entry are current and may have serious consequences for patients. They can be detected by pharmacists during prescriptions analysis and lead to pharmacist's interventions. In France, few monocentric studies have studied Pharmacist Interventions triggered by prescribing errors identified as System-Related Errors (PISREs) in French hospitals. However, their respective analysis method prevent any comparison between computerized physician order entry systems in order to identify the safest and rule out the most dangerous. A computerized physician prescribing error related to the software is characterized by its causes, consequences and mechanism of occurrence. US researchers have developed and validated a tool to classify and illustrate these three characteristics. The objectives of this article are to present this tool, to propose a French adaptation and to describe the perspectives analyze and understand prescription errors related to computerized physician order entry based on data of Act-IP©. The adaptation was performed using PISREs extracted from the Act-IP© observatory of the French Society of Clinical Pharmacy. Each item of the codification is illustrated with an example of PI. We are considering a training plan in order to allow wide use of this tool. Once adopted this tool, the next step will be to organize a prospective multicenter study including as many computerized prescription order entry systems as possible. The aim of this study will be identifying the safest systems. Consequently, it will then be possible to have arguments to qualify the most dangerous and thus propose their withdrawal from the market.

Data Resource Profile: The Hospital Electronic Prescribing and Medicines Administration (HEPMA) National Data Collection in Scotland

Introduction

To support both electronic prescribing and documentation of medicines administration in secondary care, hospitals in Scotland are currently implementing the Hospital Electronic Prescribing and Medicines Administration (HEPMA) software. Driven by the COVID-19 pandemic, agreements have been put in place to centrally collate data stemming from the operational HEPMA system. The aim was to develop a national data resource based on records created in secondary care, in line with pre-existing collections of data from primary care.

Methods

HEPMA is a live clinical system and updated on a continuous basis. Data is automatically extracted from local systems at least weekly and, in most cases, on a nightly basis, and integrated into the national HEPMA dataset. Subsequently, the data are subject to quality checks including data consistency and completeness. Records contain a unique patient identified (Community Health Index number), enabling linkage to other routinely collected data including primary care prescriptions, hospital admission episodes, and death records.

Results

The HEPMA data resource captures and compiles information on all medicines prescribed within the ward/hospital covered by the system; this includes medicine name, formulation, strength, dose, route, and frequency of administration, and dates and times of prescribing. In addition, the HEPMA dataset also captures information on medicines administration, including dates and time of administration. Data is available from January 2019 onwards and held by Public Health Scotland.

Conclusion

The national HEPMA data resource supports cross-sectional/point-prevalence studies including drug utilisation studies, and also offers scope to conduct longitudinal studies, e.g., cohort and case-control studies. With the possibility to link to other relevant datasets, additional areas of interest may include health policy evaluations and health economics studies. Access to data is subject to approval; researchers need to contact the electronic Data Research and Innovation Service (eDRIS) in the first instance.

System Configuration Evaluation for a Province-Wide Clinical Information System Using the eSafety Checklist

BACKGROUND

According to Digital Health Canada 2013 eSafety Guidelines, an estimated one-third of patient safety incidents following implementation of clinical information systems (CISs) are technology-related. An eSafety checklist was previously developed to improve CIS safety by providing a comprehensive listing of system-agnostic, evidence-based configuration recommendations.

OBJECTIVES

We sought to use the checklist to support safe initial configuration of a provincial system-wide CIS (Alberta, Canada), referred to as Connect Care.

METHODS

The checklist was applied to 13 Connect Care modules in three successive phases. First, the checklist was adapted to an abbreviated high-priority version. Second, demonstrations of each module were recorded. Finally, independent evaluation of each recording was conducted by two eSafety evaluators using the abbreviated eSafety checklist.

RESULTS

All modules achieved greater than 72% compliance, with an average of 84%. Overall, 273 opportunities for improvement were identified, with four major areas or themes emerging: (1) inconsistent date and time, (2) unclear patient identification, (3) ineffective alert system, and (4) insufficient decision support. These opportunities were forwarded to the appropriate build teams for review and implementation.

CONCLUSION

This work is the first to utilize the eSafety checklist in a real-world CIS, which will become one of the largest in Canada. The checklist has shown clinical applicability in identifying gaps in CIS configuration and should be considered for use in future and pre-existing CISs.

The impact of transition to a digital hospital on medication errors (TIME study)

Digital transformation in healthcare improves the safety of health systems. Within our health service, a new digital hospital has been established and two wards from a neighbouring paper-based hospital transitioned into the new digital hospital. This created an opportunity to evaluate the impact of complete digital transformation on medication safety. Here we discuss the impact of transition from a paper-based to digital hospital on voluntarily reported medication incidents and prescribing errors. This study utilises an interrupted time-series design and takes place across two wards as they transition from a paper to a digital hospital. Two data sources are used to assess impacts on medication incidents and prescribing errors: (1) voluntarily reported medication incidents and 2) a chart audit of medications prescribed on the study wards. The chart audit collects data on procedural, dosing and therapeutic prescribing errors. There are 588 errors extracted from incident reporting software during the study period. The average monthly number of errors reduces from 12.5 pre- to 7.5 post-transition (p < 0.001). In the chart audit, 5072 medication orders are reviewed pre-transition and 3699 reviewed post-transition. The rates of orders with one or more error reduces significantly after transition (52.8% pre- vs. 15.7% post-, p < 0.001). There are significant reductions in procedural (32.1% pre- vs. 1.3% post-, p < 0.001), and dosing errors (32.3% pre- vs. 14% post-, p < 0.001), but not therapeutic errors (0.6% pre- vs. 0.7% post-, p = 0.478). Transition to a digital hospital is associated with reductions in voluntarily reported medication incidents and prescribing errors.

Effectiveness of non-interruptive nudge interventions in electronic health records to improve the delivery of care in hospitals: a systematic review

OBJECTIVES

To describe the application of nudges within electronic health records (EHRs) and their effects on inpatient care delivery, and identify design features that support effective decision-making without the use of interruptive alerts.

MATERIALS AND METHODS

We searched Medline, Embase, and PsychInfo (in January 2022) for randomized controlled trials, interrupted time-series and before-after studies reporting effects of nudge interventions embedded in hospital EHRs to improve care. Nudge interventions were identified at full-text review, using a pre-existing classification. Interventions using interruptive alerts were excluded. Risk of bias was assessed using the ROBINS-I tool (Risk of Bias in Non-randomized Studies of Interventions) for non-randomized studies or the Cochrane Effective Practice and Organization of Care Group methodology for randomized trials. Study results were summarized narratively.

RESULTS

We included 18 studies evaluating 24 EHR nudges. An improvement in care delivery was reported for 79.2% (n = 19; 95% CI, 59.5-90.8) of nudges. Nudges applied were from 5 of 9 possible nudge categories: change choice defaults (n = 9), make information visible (n = 6), change range or composition of options (n = 5), provide reminders (n = 2), and change option-related effort (n = 2). Only one study had a low risk of bias. Nudges targeted ordering of medications, laboratory tests, imaging, and appropriateness of care. Few studies evaluated long-term effects.

DISCUSSION

Nudges in EHRs can improve care delivery. Future work could explore a wider range of nudges and evaluate long-term effects.

CONCLUSION

Nudges can be implemented in EHRs to improve care delivery within current system capabilities; however, as with all digital interventions, careful consideration of the sociotechnical system is crucial to enhance their effectiveness.

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.

A Survey of Near-Miss Dispensing Errors in Hospital Pharmacies in Japan: DEPP-J Study-Multi-Center Prospective Observational Study

The aim of this study was to determine the proportion of near-miss dispensing errors in hospital pharmacies in Japan. A prospective multi-center observational study was conducted between December 2018 and March 2019. The primary objective was to determine the proportion of near-miss dispensing errors in hospital pharmacy departments. The secondary objective was to determine the predictive factors for near-miss dispensing errors using multiple logistic regression analysis. The study was approved by the ethical committee at The Institute of Medical Sciences, University of Tokyo, Japan. A multi-center prospective observational study was conducted in 20 hospitals comprising 8862 beds. Across the 20 hospitals, we assessed data from 553 pharmacists and 53039 prescriptions. A near-miss dispensing error proportion of 0.87% (n = 461) was observed in the study. We found predictive factors for dispensing errors in day-time shifts: a higher number of drugs in a prescription, higher number of quantified drugs, such as liquid or powder formula, in a prescription, and higher number of topical agents in a prescription; but we did not observe for career experience level for clinical pharmacists. For night-time and weekend shifts, we observed a negative correlation of near-miss dispensing errors with clinical pharmacist experience level. We found an overall incidence of near-miss dispensing errors of 0.87%. Predictive factors for errors in night-time and weekend shifts was inexperienced pharmacists. We recommended that pharmacy managers should consider education or improved work flow to avoid near-miss dispensing errors by younger pharmacists, especially those working night or weekend shifts.

Efficiency and Safety of Electronic Health Records in Switzerland-A Comparative Analysis of 2 Commercial Systems in Hospitals

OBJECTIVES

Differences in efficiency and safety between 2 electronic health record (systems A and B) in Swiss hospitals were investigated.

METHODS

In a scenario-based usability test under experimental conditions, a total of 100 physicians at 4 hospitals were asked to complete typical routine tasks, like medication or imaging orders. Differences in number of mouse clicks and time-on-task as indicators of efficiency and error type, error count, and rate as indicators of patient safety between hospital sites were analyzed. Time-on-task and clicks were correlated with error count.

RESULTS

There were differences in efficiency and safety between hospitals. Overall, physicians working with system B required less clicks (A: 511, B: 442, P = 0.001) and time (A: 2055 seconds, B: 1713 seconds, P = 0.055) and made fewer errors (A: 40%, B: 27%, P < 0.001). No participant completed all tasks correctly. The most frequent error in medication and radiology ordering was a wrong dose and a wrong level, respectively. Time errors were particularly prevalent in laboratory orders. Higher error counts coincided with longer time-on-task (r = 0.50, P < 0.001) and more clicks (r = 0.47, P < 0.001).

CONCLUSIONS

The variations in clicks, time, and errors are likely due to naive functionality and design of the systems and differences in their implementation. The high error rates coincide with inefficiency and jeopardize patient safety and produce economic costs and burden on physicians. The results raise usability concerns with potential for severe patient harm. A deeper understanding of differences as well as regulative guidelines and policy making are needed.

Stakeholder perspectives of system-related errors: Types, contributing factors, and consequences

BACKGROUND

Despite growing evidence of the benefits of electronic medication management systems (EMMS), research has also identified a range of new safety risks linked with their use. There is limited qualitative research focusing on system-related errors that result from use of EMMS. The aim of this study was to explore in-depth stakeholders' perceptions and experiences of system-related errors.

METHODS

Semi-structured interviews were conducted with EMMS users and other relevant staff (e.g. supporting roles in EMMS) across a local health district in Sydney, Australia. Analysis was conducted iteratively using a general inductive approach, and then mapped to Reason's accident causation model, where codes were categorized as 1) unsafe acts (i.e. what error occurred), 2) latent conditions (i.e. what factors contributed to errors), and 3) consequences resulting from the error.

RESULTS

Twenty-five participants were interviewed between September 2020 and May 2021. Participants most frequently described omission errors (e.g. failure to check for duplicate orders) as unsafe acts, although commission errors and workarounds were also reported. Poor EMMS design was reported to be a significant workplace factor contributing to system-related errors, however participants also described user factors, such as an overreliance on the system, and organizational factors, such as system downtime, as contributing to errors. Reported consequences of system-related errors included medication errors, but also impacts to the EMMS and on workers.

CONCLUSIONS

EMMS design is a significant contributor to system-related errors, but this research showed that user and organizational factors are also at play. As these factors are not independent, minimizing system-related errors requires a multi-faceted approach, where mitigation strategies target not only the EMMS, but also the context in which the system has been implemented.

The electronic prescribing of subcutaneous infusions: A before-and-after study assessing the impact upon patient safety and service efficiency

OBJECTIVES

To assess the impact of electronically prescribed mixed-drug infusions on the prevalence and types of prescription errors and staff time.

DESIGN, SETTING AND PARTICIPANTS

Before-and-after study on acute medical wards of a large UK teaching hospital, utilising patient and staff data from the assessed wards.

INTERVENTION

Electronically-generated mixed-drug infusions.

MAIN OUTCOME MEASURES

(1) Rate of prescription errors (divided into errors of commission and omission); (2) time taken to process patient discharge prescriptions containing a mixed-drug infusion; and (3) time between prescription and administration of mixed-drug infusions.

RESULTS

100 errors of omission were detected pre-intervention, whilst none were detected post intervention. 6 errors of commission were identified at baseline, whilst 2 were highlighted post intervention (p = 0.149). 14 physicochemically incompatible infusions were prescribed at baseline, post-intervention all infusions were compatible (p < 0.01). Time spent processing discharge prescriptions fell from 60 min (SME±1.7) to 26 min (SME± 2.7; p < 0.01). The median time from prescription to administration reduced from 120 min (95 % CI 106-150) to 65 min (95 % CI 43-85; p < 0.01).

CONCLUSIONS

The intervention eliminated errors of omission and facilitated the prescribing of compatible multicomponent infusions. Electronically prescribed mixed-drug infusions also reduced both the time taken to complete discharge prescriptions and the time taken to commence such infusions.

Electronic Medication Management Systems: Analysis of Enhancements to Reduce Errors and Improve Workflow

BACKGROUND

Electronic medication management (eMM) has been shown to reduce medication errors; however, new safety risks have also been introduced that are associated with system use. No research has specifically examined the changes made to eMM systems to mitigate these risks.

OBJECTIVES

To (1) identify system-related medication errors or workflow blocks that were the target of eMM system updates, including the types of medications involved, and (2) describe and classify the system enhancements made to target these risks.

METHODS

In this retrospective qualitative study, documents detailing updates made from November 2014 to December 2019 to an eMM system were reviewed. Medication-related updates were classified according to "rationale for changes" and "changes made to the system."

RESULTS

One hundred and seventeen updates, totaling 147 individual changes, were made to the eMM system over the 4-year period. The most frequent reasons for changes being made to the eMM were to prevent medication errors (24% of reasons), optimize workflow (22%), and support "work as done" on paper (16%). The most frequent changes made to the eMM were options added to lists (14% of all changes), extra information made available on the screen (8%), and the wording or phrasing of text modified (8%). Approximately a third of the updates (37%) related to high-risk medications. The reasons for system changes appeared to vary over time, as eMM functionality and use expanded.

CONCLUSION

To our knowledge, this is the first study to systematically review and categorize system updates made to overcome new safety risks associated with eMM use. Optimization of eMM is an ongoing process, which changes over time as users become more familiar with the system and use is expanded to more sites. Continuous monitoring of the system is necessary to detect areas for improvement and capitalize on the benefits an electronic system can provide.

Automation of penicillin adverse drug reaction categorisation and risk stratification with machine learning natural language processing

BACKGROUND

The penicillin adverse drug reaction (ADR) label is common in electronic health records (EHRs). However, there is significant misclassification between allergy and intolerance within the EHR and most patients can be delabelled after an immunologic assessment. Machine learning natural language processing may be able to assist with the categorisation and risk stratification of penicillin ADRs.

OBJECTIVE

The aim of this study was to use text entered into an EHR to derive and evaluate machine learning models to classify penicillin ADRs and assess the risk of true allergy.

METHODS

Machine learning natural language processing was applied to free-text penicillin ADR data extracted from a public health system EHR. The model was developed by training on labelled dataset. ADR entries were split into training and testing datasets and used to develop and test a variety of machine learning models. These were compared to categorisation with a simple algorithm using keyword search.

RESULTS

The best performing model for the classification of penicillin ADRs as being consistent with allergy or intolerance was the artificial neural network (AUC 0.994, sensitivity 0.99, specificity 0.96). The artificial neural network also achieved the highest AUC in the classification of high- or low-risk of true allergy (AUC 0.988, sensitivity 0.99, specificity 0.99). All ADR labels were able to be classified using these machine learning models, whereas a small proportion were unclassifiable using the simple algorithm as they contained no keywords.

CONCLUSION

Machine learning natural language processing performed similarly to expert criteria in classifying and risk stratifying penicillin ADRs labels. These models outperformed simpler algorithms in their ability to interpret free-text data contained in the EHR. The automated evaluation of penicillin ADR labels may allow real-time risk stratification to facilitate delabelling and improve the specificity of prescribing alerts.

Characteristics of pharmacist's interventions triggered by prescribing errors related to computerised physician order entry in French hospitals: a cross-sectional observational study

OBJECTIVES

Computerised physician order entry (CPOE) systems facilitate the review of medication orders by pharmacists. Reports have emerged that show conception flaws or the misuse of CPOE systems generate prescribing errors. We aimed to characterise pharmacist interventions (PIs) triggered by prescribing errors identified as system-related errors (PISREs) in French hospitals.

DESIGN

This was a cross-sectional observational study based on PIs prospectively documented in the Act-IP observatory database from January 2014 to December 2018.

SETTING

PISREs from 319 French computerised healthcare facilities were analysed.

PARTICIPANTS

Among the 319 French hospitals, 232 (72.7%) performed SRE interventions, involving 652 (51%) pharmacists.

RESULTS

Among the 331 678 PIs recorded, 27 058 were qualified as due to SREs (8.2%). The main drug-related problems associated with PISREs were supratherapeutic (27.5%) and subtherapeutic dosage (17.2%), non-conformity with guidelines/contraindications (22.4%) and improper administration (17.9%). The PI prescriber acceptation rate was 78.9% for SREs vs 67.6% for other types of errors. The PISRE ratio was estimated relative to the total number of PIs. Concerning the certification status of CPOE systems, the PISRE ratio was 9.4% for non-certified systems vs 5.5% for certified systems (p<0.001). The PISRE ratio for senior pharmacists was 9.2% and that for pharmacy residents 5.4% (p<0.001). Concerning prescriptions made by graduate prescribers and those made by residents, the PISRE ratio was 8.4% and 7.8%, respectively (p<0.001).

CONCLUSION

Computer-related prescribing errors are common. The PI acceptance rate by prescribers was higher than that observed for PIs that were not CPOE related. This suggests that physicians consider the potential clinical consequences of SREs for patients to be more frequently serious than interventions unrelated to CPOE. CPOE medication review requires continual pharmacist diligence to catch these errors. The significantly lower PISRE ratio for certified software should prompt patient safety agencies to undertake studies to identify the safest software and discard software that is potentially dangerous.

Implementation of an Electronic Medication Management System in a large tertiary hospital: a case of qualitative inquiry

BACKGROUND

Hospitals across Australia are implementing Clinical Information Systems, e.g. Electronic Medication Management Systems (EMMS) at a rapid pace to moderate health services. The benefits of the EMMS depend on the acceptance of the system by the clinicians. The study hospital used a unique patient-centric implementation strategy that was based on the guiding principle of "one patient, one chart" to avoid a patient being on a hybrid medication chart. This paper aims to study the factors facilitating or hindering the adoption of the EMMS as viewed by clinicians and the implementation team.

METHODS

Four focus groups (FG), one each for (1) doctors, (2) nurses, (3) pharmacists, and (4) implementation team, were conducted. A guide for the FG was based on the Unified Theory of Acceptance and Use of Technology (UTAUT).

RESULTS

A total of 23 unique subthemes were identified and were grouped into five main themes (1) implementation strategy, (2) organisational outcome of EMMS, (3) individual impact of EMMS, (4) IT product, and (5) organisational culture. Clinicians reported improvement in their workflow efficiency post-EMMS implementation. They also reported some challenges in using the EMMS that centered around the area of infrastructure, technical and design issues. Additionally, the implementation team highlighted two crucial factors influencing the success of EMMS implementation, namely: (1) the patient-centric implementation strategy, and (2) the organisation readiness.

CONCLUSION

Overall, this study outlines the implementation process of the EMMS in a large healthcare facility from the clinicians' and the implementation team's perspectives using UTAUT model. The result suggests that clinicians' acceptance of the EMMS was highly influenced by the unique implementation strategy (namely, patient-centric approach and clinical leadership in the implementation team). Whereas the level of adoption of EMMS by clinicians was determined by their level of perceived and realised benefits. On the other hand, a number of barriers to the adoption of EMMS were discovered, namely, general training instead of customised training based on local needs, technical and design issues and lack of availability of computer systems. It is suggested that promptly resolving these issues can improve the adoption of the EMMS.

Changes in medication administration error rates associated with the introduction of electronic medication systems in hospitals: a multisite controlled before and after study

Background

Electronic medication systems (EMS) have been highly effective in reducing prescribing errors, but little research has investigated their effects on medication administration errors (MAEs).

Objective

To assess changes in MAE rates and types associated with EMS implementation.

Methods

This was a controlled before and after study (three intervention and three control wards) at two adult teaching hospitals. Intervention wards used an EMS with no bar-coding. Independent, trained observers shadowed nurses and recorded medications administered and compliance with 10 safety procedures. Observational data were compared against medication charts to identify errors (eg, wrong dose). Potential error severity was classified on a 5-point scale, with those scoring ≥3 identified as serious. Changes in MAE rates preintervention and postintervention by study group, accounting for differences at baseline, were calculated.

Results

7451 administrations were observed (4176 pre-EMS and 3275 post-EMS). At baseline, 30.2% of administrations contained ≥1 MAE, with wrong intravenous rate, timing, volume and dose the most frequent. Post-EMS, MAEs decreased on intervention wards relative to control wards by 4.2 errors per 100 administrations (95% CI 0.2 to 8.3; p=0.04). Wrong timing errors alone decreased by 3.4 per 100 administrations (95% CI 0.01 to 6.7; p<0.05). EMS use was associated with an absolute decline in potentially serious MAEs by 2.4% (95% CI 0.8 to 3.9; p=0.003), a 56% reduction in the proportion of potentially serious MAEs. At baseline, 74.1% of administrations were non-compliant with ≥1 of 10 procedures and this rate did not significantly improve post-EMS.

Conclusions

Implementation of EMS was associated with a modest, but significant, reduction in overall MAE rate, but halved the proportion of MAEs rated as potentially serious.

Predicting self-intercepted medication ordering errors using machine learning

Current approaches to understanding medication ordering errors rely on relatively small manually captured error samples. These approaches are resource-intensive, do not scale for computerized provider order entry (CPOE) systems, and are likely to miss important risk factors associated with medication ordering errors. Previously, we described a dataset of CPOE-based medication voiding accompanied by univariable and multivariable regression analyses. However, these traditional techniques require expert guidance and may perform poorly compared to newer approaches. In this paper, we update that analysis using machine learning (ML) models to predict erroneous medication orders and identify its contributing factors. We retrieved patient demographics (race/ethnicity, sex, age), clinician characteristics, type of medication order (inpatient, prescription, home medication by history), and order content. We compared logistic regression, random forest, boosted decision trees, and artificial neural network models. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). The dataset included 5,804,192 medication orders, of which 28,695 (0.5%) were voided. ML correctly classified voids at reasonable accuracy; with a positive predictive value of 10%, ~20% of errors were included. Gradient boosted decision trees achieved the highest AUROC (0.7968) and AUPRC (0.0647) among all models. Logistic regression had the poorest performance. Models identified predictive factors with high face validity (e.g., student orders), and a decision tree revealed interacting contexts with high rates of errors not identified by previous regression models. Prediction models using order-entry information offers promise for error surveillance, patient safety improvements, and targeted clinical review. The improved performance of models with complex interactions points to the importance of contextual medication ordering information for understanding contributors to medication errors.

How effective are electronic medication systems in reducing medication error rates and associated harm among hospital inpatients? A systematic review and meta-analysis

OBJECTIVE

To conduct a systematic review and meta-analysis to assess: 1) changes in medication error rates and associated patient harm following electronic medication system (EMS) implementation; and 2) evidence of system-related medication errors facilitated by the use of an EMS.

MATERIALS AND METHODS

We searched Medline, Scopus, Embase, and CINAHL for studies published between January 2005 and March 2019, comparing medication errors rates with or without assessments of related harm (actual or potential) before and after EMS implementation. EMS was defined as a computer-based system enabling the prescribing, supply, and/or administration of medicines. Study quality was assessed.

RESULTS

There was substantial heterogeneity in outcomes of the 18 included studies. Only 2 were strong quality. Meta-analysis of 5 studies reporting change in actual harm post-EMS showed no reduced risk (RR: 1.22, 95% CI: 0.18-8.38, P = .8) and meta-analysis of 3 studies reporting change in administration errors found a significant reduction in error rates (RR: 0.77, 95% CI: 0.72-0.83, P = .004). Of 10 studies of prescribing error rates, 9 reported a reduction but variable denominators precluded meta-analysis. Twelve studies provided specific examples of system-related medication errors; 5 quantified their occurrence.

DISCUSSION AND CONCLUSION

Despite the wide-scale adoption of EMS in hospitals around the world, the quality of evidence about their effectiveness in medication error and associated harm reduction is variable. Some confidence can be placed in the ability of systems to reduce prescribing error rates. However, much is still unknown about mechanisms which may be most effective in improving medication safety and design features which facilitate new error risks.

Redesign of computerized decision support system to improve Non Vitamin K oral anticoagulant prescribing-A pre and post qualitative and quantitative study

BACKGROUND

Inappropriate prescribing of non-vitamin K agents (NOAC) contributes to significant economic and personal burden to our society. Studies have shown that when well designed and targeted, computerized alerts can be effective in improving prescribing without contributing to alert fatigue.

METHOD

A collaborative multidisciplinary review group was set up to review and endorse an upgrade and modification to the hospital electronic medication management system (EMS). The intervention focused on implementing tailored electronic patient specific physiological alerts (such as age, renal function weight and drug interactions) built in EMS to improve the appropriateness of NOAC prescribing at this multisite teaching Australian hospital. To assess the qualitative and quantitative impact of the intervention, a pre and post retrospective study of NOAC prescribing of 100 patients' pre and post the implementation stage was conducted in a multisite Australian 650 bed hospital. Appropriateness of NOAC prescribing was assessed by an experienced pharmacist using approved prescribing product information recommendations. Prescriber satisfaction and experience survey was assessed in both stages of the study using a standard satisfaction survey. Associated hospital acquired complications (HAC) with potential inappropriate NOAC prescribing were evaluated as well as related admission cost and average length of stay.

RESULTS

Redesign of computerised decision support in EMS improved appropriateness of NOAC prescribing from 48 % to 91 %, P < 0.05. A total of 67 prescribers accepted the invitation to participate in the qualitative satisfaction study. Half the respondents (n = 33, 50 %) answered positively to a question assessing the usefulness of implementing NOAC alerts in the EMS in improving their practice and patient safety. This rate has increased to 72 % (n = 48) in the post intervention phase. P < 0.05. Additionally, the total number of reported HAC that are likely to be associated with inappropriate NOAC prescribing was reduced by 36 % in the post intervention phase (from 29 to 22 (RR = 0.7454 95 %CI (0.4283-1.2972), P = 0.2986). The cost of associated HAC has also reduced by 29 % (from $1,282,748 to $911,117) as well as the mean length stay by 11 % (from 18 days to 16 days) post the intervention phase.

CONCLUSION

This study highlights that well-designed electronic prescribing alerts that provide context-relevant information to prescribers are likely to result in benefits to clinicians and patients as well reduction in economic burden. Moreover, they could also contribute to reducing hospital acquired complications and lessen the economic burden on our society.

The Effects of Bar-coding Technology on Medication Errors: A Systematic Literature Review

BACKGROUND

The bar-coding technology adoptions have risen drastically in U.S. health systems in the past decade. However, few studies have addressed the impact of bar-coding technology with strong prospective methodologies and the research, which has been conducted from both in-pharmacy and bedside implementations.

OBJECTIVE

This systematic literature review is to examine the effectiveness of bar-coding technology on preventing medication errors and what types of medication errors may be prevented in the hospital setting.

METHODS

A systematic search of databases was performed from 1998 to December 2016. Studies measuring the effect of bar-coding technology on medication errors were included in a full-text review. Studies with the outcomes other than medication errors such as efficiency or workarounds were excluded. The outcomes were measured and findings were summarized for each retained study.

RESULTS

A total of 2603 articles were initially identified and 10 studies, which used prospective before-and-after study design, were fully reviewed in this article. Of the 10 included studies, 9 took place in the United States, whereas the remaining was conducted in the United Kingdom. One research article focused on bar-coding implementation in a pharmacy setting, whereas the other 9 focused on bar coding within patient care areas. All 10 studies showed overall positive effects associated with bar-coding implementation.

CONCLUSIONS

The results of this review show that bar-coding technology may reduce medication errors in hospital settings, particularly on preventing targeted wrong dose, wrong drug, wrong patient, unauthorized drug, and wrong route errors.

Documentation of adverse drug reactions to opioids in an electronic health record

BACKGROUND

Allergy to opioids is the second most common drug allergy label in electronic health records (EHR). Adverse drug reactions (ADR) to opioids cause significant morbidity and contribute to healthcare costs, while incorrect opioid allergy labels may unnecessarily complicate patient management.

AIMS

To examine the documentation of opioid ADR in a large-scale hospital-based EHR.

METHODS

A cross-sectional retrospective review of EHR documentation of opioid ADR at four public hospitals in South Australia was conducted. Data were extracted from all ADR entries including the reported allergen, ADR category (allergy or intolerance) and reaction details. Expert criteria were used to determine consistency of ADR categorisation as allergy or intolerance.

RESULTS

Of 86 727 unique ADR reports, there were 13 781 ADR to opioids with most being entered as allergy (n = 8913, 64.7%) rather than intolerance (n = 4868, 35.3%). The most commonly documented reactions were nausea/vomiting (n = 3912, 28%), rash (n = 647, 5%), itch (n = 642, 5%) and hallucinations (n = 527, 4%). There were 362 (3%) ADR labels of anaphylaxis. Of those ADR containing a reaction description (n = 11 868), 89% of reports entered as allergy had a reaction description that was consistent with intolerance and 8% of the entered intolerances had descriptions consistent with allergy when assessed using predefined criteria.

CONCLUSIONS

This large EHR-based study demonstrates the high rate of opioid ADR labels in EHR. The majority of these labels were for symptoms suggestive of pharmacological intolerance. Reactions consistent with true allergy were uncommon. Systematic review of ADR by a dedicated clinical service would improve the accuracy of documentation.

Impact of electronic health records on predefined safety outcomes in patients admitted to hospital: a scoping review

OBJECTIVES

Review available evidence for impact of electronic health records (EHRs) on predefined patient safety outcomes in interventional studies to identify gaps in current knowledge and design interventions for future research.

DESIGN

Scoping review to map existing evidence and identify gaps for future research.

DATA SOURCES

PubMed, the Cochrane Library, EMBASE, Trial registers.

STUDY SELECTION

Eligibility criteria: We conducted a scoping review of bibliographic databases and the grey literature of randomised and non-randomised trials describing interventions targeting a list of fourteen predefined areas of safety. The search was limited to manuscripts published between January 2008 and December 2018 of studies in adult inpatient settings and complemented by a targeted search for studies using a sample of EHR vendors. Studies were categorised according to methodology, intervention characteristics and safety outcome.Results from identified studies were grouped around common themes of safety measures.

RESULTS

The search yielded 583 articles of which 24 articles were included. The identified studies were largely from US academic medical centres, heterogeneous in study conduct, definitions, treatment protocols and study outcome reporting. Of the 24 included studies effective safety themes included medication reconciliation, decision support for prescribing medications, communication between teams, infection prevention and measures of EHR-specific harm. Heterogeneity of the interventions and study characteristics precluded a systematic meta-analysis. Most studies reported process measures and not patient-level safety outcomes: We found no or limited evidence in 13 of 14 predefined safety areas, with good evidence limited to medication safety.

CONCLUSIONS

Published evidence for EHR impact on safety outcomes from interventional studies is limited and does not permit firm conclusions regarding the full safety impact of EHRs or support recommendations about ideal design features. The review highlights the need for greater transparency in quality assurance of existing EHRs and further research into suitable metrics and study designs.

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.

A qualitative study of prescribing errors among multi-professional prescribers within an e-prescribing system

Background Computerised Physician Order Entry (CPOE) is considered to enhance the safety of prescribing. However, it can have unintended consequences and new forms of prescribing error have been reported. Objective The aim of this study was to explore the causes and contributing factors associated with prescribing errors reported by multidisciplinary prescribers working within a CPOE system. Main Outcome Measure Multidisciplinary prescribers experience of prescribing errors in an CPOE system. Method This qualitative study was conducted in a hospital with a well-established CPOE system. Semi-structured qualitative interviews were conducted with prescribers from the professions of pharmacy, nursing, and medicine. Interviews analysed using a mixed inductive and deductive approach to develop a framework for the causes of error. Results Twenty-three prescribers were interviewed. Six main themes influencing prescribing were found: the system, the prescriber, the patient, the team, the task of prescribing and the work environment. Prominent issues related to CPOE included, incorrect drug name picking, default auto-population of dosages, alert fatigue and remote prescribing. These interacted within a complex prescribing environment. No substantial differences in the experience of CPOE were found between the professions. Conclusion Medical and non-medical prescribers have similar experiences of prescribing errors when using CPOE, aligned with existing published literature about medical prescribing. Causes of electronic prescribing errors are multifactorial in nature and prescribers describe how factors interact to create the conditions errors. While interventions should focus on direct CPOE issues, such as training and design, socio-technical, and environmental aspects of practice remain important.

Medication safety improvements during care transitions in an Australian intensive care unit following implementation of an electronic medication management system

BACKGROUND

For patients requiring admission to the Intensive Care Unit (ICU), transfers of care (TOC) during admission to and discharge from the ICU are particularly high-risk periods for medication errors. In the Australian setting, commonly general wards and the ICU do not share an integrated Electronic Medical ecord (EMR) and specifically an Electronic Medication Management System (EMMS) as part of the EMR.

PURPOSE

To evaluate the effect of a hospital wide integrated EMMS on medication error rates during ICU admission and at TOC.

METHOD

A 6-month historical control study was performed before and after implementation of the EMMS in the ICU of a tertiary hospital. Prescribing errors detected by pharmacists in the study period were divided into phase 1, (pre-EMMS, 6months), phase 2 (3 months post implementation after shakedown stage) and phase 3 (next 3 months of post implementation). They were categorized as prescribing error types under system or clinical intervention. Chi square statistics and interrupted time series analysis were used to determine if there was significant change in the proportion of patients who had an error at TOC during each phase. Logistics regression was used to determine the relationship between the dependent (error type) and the independent variable (study phase) for errors that occurred during TOC.

RESULTS

Errors occurred during TOC in 42 %, 64 % and 19 % of patients in phase 1, 2 and 3 respectively. There was a significant decline in the proportion of patients with an error between phase 1 and 3 (p < 0.01). During a patient's ICU admission, at least one medication error occurred in 28.3 %, 62.6 % and 25.1 % in phase 1, 2 and 3 respectively. Besides procedural errors, the likelihood of an error occurring was greatest in phase 1, compared to phase 2 and 3 across system-related error categories.

CONCLUSION

Medication errors during TOC reduced following implementation of the integrated ICU EMMS. EMMS safety features facilitated reduced system related prescribing errors as well as the severity of errors made.

A randomised trial of pharmacist-led discharge prescribing in an Australian geriatric evaluation and management service

Background Prescribing discharge medications is a potential "next step" for pharmacists in Australian hospitals, however, safety must be demonstrated via a randomised controlled study. Objective To determine if a collaborative, pharmacist led discharge prescribing model results in less patients with medication errors than conventional prescribing for both handwritten and digital prescriptions. Setting Geriatric Medical ward in a quaternary hospital, Australia Methods A prospective, single-blinded randomised controlled study of patients randomised to conventional (control) or a pharmacist-led prescribing (intervention) arms at discharge from hospital. This study had 2 phases; (1) handwritten prescribing and (2) digital prescribing. In addition, the two prescribing methods were compared. Main outcome measures The primary outcome was the percentage of patients with a medication error on their discharge prescription. Results In phase 1, 45 patients were recruited; 21 (control) and 24 (intervention). 95% of control patients and 29% in the intervention arm had at least one medication error, p < 0.0002, relative risk (RR) 0.31, confidence interval (CI) 0.16-0.58. The number of items with at least 1 error reduced from 69 to 4%; p < 0.0001, RR 0.06, CI 0.03-0.11 and fewer items had at least 1 clinically significant error (11% vs 2%, p = 0.0004, RR 0.15, CI 0.04-0.30). In phase 2, 39 patients were recruited; 18 (control) and 21 (intervention). 100% of control patients and 62% in the intervention arm had at least one medication error (p = 0.005, RR 0.62, CI 0.44-0.87). Items with at least 1 error decreased from 21 to 7% (p < 0.0001, RR 0.34, CI 0.44-0.56), there were fewer items with at least 1 clinically significant error (13% vs 5%, p < 0.003, RR 0.4, CI 0.22-0.72). There was no significant change in the primary outcome between handwritten and digital (60% vs 79%, p < 0.055). Conclusion In a geriatric setting, pharmacist-led partnered discharge prescribing results in significantly less patients with medication errors than the conventional method for both handwritten and digital methods.

The development and evaluation of a nationwide training program for oncology health professionals in the provision of genetic testing for ovarian cancer patients

BACKGROUND

BRCA1/2 mutation status has increasing relevance for ovarian cancer treatments, making traditional coordination of genetic testing by genetic services unsustainable. Consequently alternative models of genetic testing have been developed to improve testing at the initial diagnosis for all eligible women.

METHODS

A training module to enable mainstreamed genetic testing by oncology healthcare professionals was developed by genetic health professionals. Oncology healthcare professionals completed questionnaires before and 12 months post-training to assess perceived skills, competence and barriers to their coordinating genetic testing for women with high-grade non-mucinous epithelial ovarian cancer. Genetic health professionals were surveyed 12 months post-training to assess perceived barriers to implementation of mainstreaming.

RESULTS

185 oncology healthcare professionals were trained in 42 workshops at 35 Australasian hospitals. Of the 273 tests ordered by oncology healthcare professionals post-training, 241 (93.1%) met national testing guidelines. The number of tests ordered by genetic health professionals reduced significantly (z = 45.0, p = 0.008). Oncology healthcare professionals' perceived barriers to mainstreamed testing decreased from baseline to follow-up (t = 2.39, p = 0.023), particularly perceived skills, knowledge and attitudes. However, only 58% reported either 'always' or 'nearly always' having ordered BRCA testing for eligible patients at 12 months, suggesting oncology healthcare professionals' perceived barriers were not systematically addressed through training.

CONCLUSIONS

Oncology healthcare professionals have demonstrated a willingness to be involved in the provision of genetic testing in a mainstreaming model. If oncology services are to hold responsibility for coordinating genetic testing, their readiness will require understanding of barriers not addressed by training alone to inform future intervention design.

Prevalence of Medication Errors Among Paediatric Inpatients: Systematic Review and Meta-Analysis

INTRODUCTION

The risk of medication errors is high in paediatric inpatient settings. However, estimates of the prevalence of medication errors have not accounted for heterogeneity across studies in error identification methods and definitions, nor contextual differences across wards and the use of electronic or paper medication charts.

OBJECTIVE

Our aim was to conduct a systematic review and meta-analysis to provide separate estimates of the prevalence of medication errors among paediatric inpatients, depending on hospital ward and the use of electronic or paper medication charts, that address differences in error identification methods and definitions.

METHODS

We systematically searched five databases to identify studies published between January 2000 and December 2018 that assessed medication error rates by medication chart audit, direct observation or a combination of methods.

RESULTS

We identified 71 studies, 19 involved paediatric wards using electronic charts. Most studies assessed prescribing errors with few studies assessing administration errors. Estimates varied by ward type. Studies of paediatric wards using electronic charts generally reported a reduced error prevalence compared to those using paper, although there were some inconsistencies. Error detection methods impacted the rate of administration errors in studies of multiple wards, however, no other difference was found. Definition of medication error did not have a consistent impact on reported error rates.

CONCLUSIONS

Medication errors are a frequent occurrence in paediatric inpatient settings, particularly in intensive care wards and emergency departments. Hospitals using electronic charts tended to have a lower rate of medication errors compared to those using paper charts. Future research employing controlled designs is needed to determine the true impact of electronic charts and other interventions on medication errors and associated harm among hospitalized children.

Improving junior doctor medicine prescribing and patient safety: An intervention using personalised, structured, video-enhanced feedback and deliberate practice

AIMS

This research investigated the effectiveness of an intervention for improving the prescribing and patient safety behaviour among Foundation Year doctors. The intervention consisted of simulated clinical encounters with subsequent personalised, structured, video-enhanced feedback and deliberate practice, undertaken at the start of four-month sub-specialty rotations.

METHODS

Three prospective, non-randomised control intervention studies were conducted, within two secondary care NHS Trusts in England. The primary outcome measure, error rate per prescriber, was calculated using daily prescribing data. Prescribers were grouped to enable a comparison between experimental and control conditions using regression analysis. A break-even analysis evaluated cost-effectiveness.

RESULTS

There was no significant difference in error rates of novice prescribers who received the intervention when compared with those of experienced prescribers. Novice prescribers not participating in the intervention had significantly higher error rates (P = .026, 95% confidence interval [CI] Wald 0.093 to 1.436; P = .026, 95% CI 0.031 to 0.397) and patients seen by them experienced significantly higher prescribing error rates (P = .007, 95% CI 0.025 to 0.157). Conversely, patients seen by the novice prescribers who received the intervention experienced a significantly lower rate of significant errors compared to patients seen by the experienced prescribers (P = .04, 95% CI -0.068 to -0.001). The break-even analysis demonstrates cost-effectiveness for the intervention.

CONCLUSION

Simulated clinical encounters using personalised, structured, video-enhanced feedback and deliberate practice improves the prescribing and patient safety behaviour of Foundation Year doctors. The intervention is cost-effective with potential to reduce avoidable harm.

Categorization of adverse drug reactions in electronic health records

The purpose of this study was to evaluate the quality of adverse drug reaction (ADR) documentation in a state-wide electronic health record (EHR), and to assess the impact of the interface design on documentation accuracy and ability to provide decision support. Data were extracted from 43 011 unique records in a state-wide electronic health record in South Australia, Australia. Information obtained included ADR coding as allergy or intolerance, allergen name, reaction, and occupation of those entering data. Categorization into drug allergy or intolerance was assessed for accuracy. Reactions were entered predominantly by nurses (60.1%), also by doctors (31.0%) and pharmacists (6.1%). Of 27 314 reactions, 86.5% were coded as allergy and 13.5% as intolerance. The majority (78.2%) described reactions to drugs (as opposed to food, environmental or contact allergens), predominantly chosen from the drug database (96.4%). Many entries used free text for the reaction description (27.4%). Terms found in the predefined list under the allergy heading were more likely to be categorized as allergy, even when the mechanism was pharmacological intolerance. Only 45.1% (n = 1671/3705) of reactions consistent with intolerance (eg, "nausea," "diarrhea") were correctly categorized as such, although categorization by pharmacists was more accurate (P < .0001). These data suggest that ADR categorization as allergy or intolerance is influenced by the EHR design. The obligatory classification of ADRs into allergy or intolerance was not well understood and does not appear to have practical benefit.

Mapping the rise of digital mental health technologies: Emerging issues for law and society

The use of digital technologies in mental health initiatives is expanding, leading to calls for clearer legal and regulatory frameworks. However, gaps in knowledge about the scale and nature of change impede efforts to develop responsible public governance in the early stages of what may be the mass uptake of 'digital mental health technologies'. This article maps established and emerging technologies in the mental health context with an eye to locating major socio-legal issues. The paper discusses various types of technology, including those designed for information sharing, communication, clinical decision support, 'digital therapies', patient and/or population monitoring and control, bio-informatics and personalised medicine, and service user health informatics. The discussion is organised around domains of use based on the actors who use the technologies, and those on whom they are used. These actors go beyond mental health service users and practitioners/service providers, and include health and social system or resource managers, data management services, private companies that collect personal data (such as major technology corporations and data brokers), and multiple government agencies and private sector actors across diverse fields of criminal justice, education, and so on. The mapping exercise offers a starting point to better identify cross-cutting legal, ethical and social issues at the convergence of digital technology and contemporary mental health practice.

Medication errors and adverse drug events in a UK hospital during the optimisation of electronic prescriptions: a prospective observational study

BACKGROUND

WHO's Third Global Patient Safety Challenge, Medication Without Harm, focused on reducing the substantial burden of iatrogenic harm associated with medications by 50% in the next 5 years. We aimed to assess whether the number and type of medication errors changed as an electronic prescribing system was optimised over time in a UK hospital.

METHODS

We did a prospective observational study at a tertiary-care teaching hospital. Eight senior clinical pharmacists reviewed patients' records and collected data across four adult wards (renal, cardiology, general medical, and orthopaedic surgical) over a 2-year period (from Sept 29, 2014, to June 9, 2016). All medication errors and potential and actual adverse drug events were documented and the number of medication errors measured over the course of four time periods 7-10 weeks long. Pharmacists also recorded instances where the electronic prescribing system contributed to an error (system-related errors). A negative-binomial model and a Poisson model were used to identify factors related to medication error rates.

FINDINGS

5796 primary errors were recorded over the four time periods (period 1, 47 days [Sep 29-Dec 2, 2014]; period 2, 38 days [April 20-June 12, 2015, for the renal, medical, and surgical wards and April 20-June 15, 2015, for the cardiology ward]; period 3, 35 days [Sep 28-Nov 27, 2015] for the renal ward, 37 days [Sep 28-Nov 23, 2015] for the medical ward, and 40 days [Sep 28-Nov 20, 2015] for the cardiology and surgical wards; and period 4, 37 days [Feb 22-April 15, 2015] for the renal and medical wards and 39 days for the cardiology [April 13-June 7, 2015] and surgery [April 18-June 9, 2015] wards; unanticipated organisational factors prevented data collection on some days during each time period). There was no change in the rate of primary medication errors per admission over the observation periods: 1·53 medication errors in period 1, 1·44 medication errors in period 2, 1·70 medication errors in period 3, and 1·43 medication errors in period 4, per admission. By contrast, the overall rate of different types of medication errors decreased over the four periods. The most common types of error were medicine-reconciliation, dose, and avoidable delay-of-treatment errors. Some types of errors appeared to reduce over time (eg, dose errors [from 52 errors in period 1 to 19 errors in period 4, per 100 admissions]), whereas others increased (eg, inadequate follow-up of therapy [from 12 errors in period 1 to 24 errors in period 4, per 100 admissions]). We also found a reduction in the rates of potential adverse drug events between the first three periods and period 4. 436 system-related errors were recorded over the study period.

INTERPRETATION

Although the overall rates of primary medication errors per admission did not change, we found a reduction in some error types and a significant decrease in the rates of potential adverse drug events over a 2-year period, during which system optimisation occurred. Targeting some error types could have the added benefit of reducing others, which suggests that system optimisation could ultimately help improve patient safety and outcomes.

FUNDING

No funding.

Optimising computerised decision support to transform medication safety and reduce prescriber burden: study protocol for a mixed-methods evaluation of drug-drug interaction alerts

INTRODUCTION

Drug-drug interaction (DDI) alerts in hospital electronic medication management (EMM) systems are generated at the point of prescribing to warn doctors about potential interactions in their patients' medication orders. This project aims to determine the impact of DDI alerts on DDI rates and on patient harm in the inpatient setting. It also aims to identify barriers and facilitators to optimal use of alerts, quantify the alert burden posed to prescribers with implementation of DDI alerts and to develop algorithms to improve the specificity of DDI alerting systems.

METHODS AND ANALYSIS

A controlled pre-post design will be used. Study sites include six major referral hospitals in two Australian states, New South Wales and Queensland. Three hospitals will act as control sites and will implement an EMM system without DDI alerts, and three as intervention sites with DDI alerts. The medical records of 280 patients admitted in the 6 months prior to and 6 months following implementation of the EMM system at each site (total 3360 patients) will be retrospectively reviewed by study pharmacists to identify potential DDIs, clinically relevant DDIs and associated patient harm. To identify barriers and facilitators to optimal use of alerts, 10-15 doctors working at each intervention hospital will take part in observations and interviews. Non-identifiable DDI alert data will be extracted from EMM systems 6-12 months after system implementation in order to quantify alert burden on prescribers. Finally, data collected from chart review and EMM systems will be linked with clinically relevant DDIs to inform the development of algorithms to trigger only clinically relevant DDI alerts in EMM systems.

ETHICS AND DISSEMINATION

This research was approved by the Hunter New England Human Research Ethics Committee (18/02/21/4.07). Study results will be published in peer-reviewed journals and presented at local and international conferences and workshops.

The safety of computerised prescribing in hospitals

The implementation of computerised prescribing can result in large reductions in prescribing error rates. The flow-on effects to patient outcomes are not well studied

The reduction in errors is dependent on prescribers becoming proficient in using the electronic prescribing system. All potential safety benefits are therefore not expected to be achieved immediately

Electronic prescribing systems introduce new types of errors, most frequently errors in selection. Some of these errors can be prevented if the system is well designed

Computerised decision support embedded in electronic prescribing systems has enormous potential to improve medication safety. However, current support systems have a limited capacity to provide context-relevant advice to prescribers

Pharmacist-assisted electronic prescribing at the time of admission to an inpatient orthopaedic unit and its impact on medication errors: a pre- and postintervention study

BACKGROUND

Prescribing and administration errors related to pre-admission medications are common amongst orthopaedic inpatients. Postprescribing medication reconciliation by clinical pharmacists after hospital admission prevents some but not all errors from reaching the patient. Involving pharmacists at the prescribing stage may more effectively prevent errors. The aim of the study was to evaluate the effect of pharmacist-assisted electronic prescribing at the time of hospital admission on medication errors in orthopaedic inpatients.

METHODS

A pre- and postintervention study was conducted in the orthopaedic unit of a major metropolitan Australian hospital. During the 10-week intervention phase, a project pharmacist used electronic prescribing to assist with prescribing admission medications and postoperative venous thromboembolism (VTE) prophylaxis, in consultation with orthopaedic medical officers. The primary endpoint was the number of medication errors per patient within 72 h of admission. Secondary endpoints included the number and consequence of adverse events (AEs) associated with admission medication errors and the time delay in administering VTE prophylaxis after elective surgery (number of hours after recommended postoperative dose-time).

RESULTS

A total of 198 and 210 patients, pre- and postintervention, were evaluated, respectively. The median number of admission medication errors per patient declined from six pre-intervention to one postintervention (p < 0.01). A total of 17 AEs were related to admission medication errors during the pre-intervention period compared with 1 postintervention. There were 54 and 63 elective surgery patients pre- and postintervention, respectively. The median delay in administering VTE prophylaxis for these patients declined from 9 h pre-intervention to 2 h postintervention (p < 0.01).

CONCLUSIONS

Pharmacist-assisted electronic prescribing reduced the number of admission medication errors and associated AEs.