Methodological variability in detecting prescribing errors and consequences for the evaluation of interventions

Errors associated with co-names of medicines: The nomenclature of combination medicinal products

In comparison to the efforts required to bring a new drug or formulation to the clinic, bestowing a name on a medicine is relatively simple. However, if the name we choose causes confusion-by making its contents ambiguous or if it is too alike another drug-it can precipitate clinical errors. This prompted the World Health Organization to set up the International Nonproprietary Naming Committee in the 1970s to select unambiguous names for drugs. Unfortunately, multidrug products-which are becoming increasingly popular-do not fall under the remit of conventional International Non-proprietary Nomenclature. We have identified 26 combination formulations that have been historically named with the co-drug format in the United Kingdom. Most of them have also been prescribed in the United Kingdom in the past year, and although several of them are not prescribed very often, 11 were prescribed more than 2000 times. In this paper, we have explored the literature to identify prescribing errors with co-drug products and found several idiosyncrasies that have caused drug errors in the past. We advocate for a standard nomenclature (state the international nonproprietary name [INN] of each component followed by dose information in the x + y format) for these products on the box and in prescribing resources. We hope that this will enhance clarity and safety during prescribing and administration, particularly for high-volume drugs like paracetamol + codeine (co-codamol), amoxicillin + clavulanic acid (co-amoxiclav) and trimethoprim + sulfamethoxazole (co-trimoxazole).

Exploring the Role of Guidelines in Contributing to Medication Errors: A Descriptive Analysis of National Patient Safety Incident Data

INTRODUCTION

Clinical guidelines can contribute to medication errors but there is no overall understanding of how and where these occur.

OBJECTIVES

We aimed to identify guideline-related medication errors reported via a national incident reporting system, and describe types of error, stages of medication use, guidelines, drugs, specialties and clinical locations most commonly associated with such errors.

METHODS

Retrospective analysis of reports to the National Reporting and Learning System for England and Wales. A hierarchical task analysis (HTA) was developed, describing expected practice when using guidelines. A free-text search was conducted of medication incident reports (2016-2021) using search terms related to common guidelines. All identified reports linked to moderate-severe harm or death, and a random sample of 5100 no/low-harm reports were coded to describe deviations from the HTA. A random sample of 500 cases were independently double-coded.

RESULTS

In total, 28,217 reports were identified, with 608 relating to moderate-severe harm or death. Fleiss' kappa for interrater reliability was 0.46. Of the 5708 reports coded, 642 described an HTA step discrepancy (including four linked to a death), suggesting over 3200 discrepancies in the entire dataset of 28,217 reports. Discrepancies related to finding guidelines (n = 300 reports), finding information within guidelines (n = 166) and using information (n = 176). Discrepancies were most frequently identified for guidelines produced by a local organisation (n = 405), and most occurred during prescribing (n = 277) or medication administration (n = 241).

CONCLUSION

Difficulties finding and using information from clinical guidelines contribute to thousands of prescribing and medication administration incidents, some of which are associated with substantial patient harm.

Automated search methods for identifying wrong patient order entry-a scoping review

Objective

To investigate: (1) what automated search methods are used to identify wrong-patient order entry (WPOE), (2) what data are being captured and how they are being used, (3) the causes of WPOE, and (4) how providers identify their own errors.

Materials and Methods

A systematic scoping review of the empirical literature was performed using the databases CINAHL, Embase, and MEDLINE, covering the period from database inception until 2021. Search terms were related to the use of automated searches for WPOE when using an electronic prescribing system. Data were extracted and thematic analysis was performed to identify patterns or themes within the data.

Results

Fifteen papers were included in the review. Several automated search methods were identified, with the retract-and-reorder (RAR) method and the Void Alert Tool (VAT) the most prevalent. Included studies used automated search methods to identify background error rates in isolation, or in the context of an intervention. Risk factors for WPOE were identified, with technological factors and interruptions deemed the biggest risks. Minimal data on how providers identify their own errors were identified.

Discussion

RAR is the most widely used method to identify WPOE, with a good positive predictive value (PPV) of 76.2%. However, it will not currently identify other error types. The VAT is nonspecific for WPOE, with a mean PPV of 78%-93.1%, but the voiding reason accuracy varies considerably.

Conclusion

Automated search methods are powerful tools to identify WPOE that would otherwise go unnoticed. Further research is required around self-identification of errors.

Risk factors associated with medication ordering errors

OBJECTIVE

We utilized a computerized order entry system-integrated function referred to as "void" to identify erroneous orders (ie, a "void" order). Using voided orders, we aimed to (1) identify the nature and characteristics of medication ordering errors, (2) investigate the risk factors associated with medication ordering errors, and (3) explore potential strategies to mitigate these risk factors.

MATERIALS AND METHODS

We collected data on voided orders using clinician interviews and surveys within 24 hours of the voided order and using chart reviews. Interviews were informed by the human factors-based SEIPS (Systems Engineering Initiative for Patient Safety) model to characterize the work systems-based risk factors contributing to ordering errors; chart reviews were used to establish whether a voided order was a true medication ordering error and ascertain its impact on patient safety.

RESULTS

During the 16-month study period (August 25, 2017, to December 31, 2018), 1074 medication orders were voided; 842 voided orders were true medication errors (positive predictive value = 78.3 ± 1.2%). A total of 22% (n = 190) of the medication ordering errors reached the patient, with at least a single administration, without causing patient harm. Interviews were conducted on 355 voided orders (33% response). Errors were not uniquely associated with a single risk factor, but the causal contributors of medication ordering errors were multifactorial, arising from a combination of technological-, cognitive-, environmental-, social-, and organizational-level factors.

CONCLUSIONS

The void function offers a practical, standardized method to create a rich database of medication ordering errors. We highlight implications for utilizing the void function for future research, practice and learning opportunities.

The impact of computerised physician order entry on prescribing in general paediatric units in Hong Kong

OBJECTIVES

This study aimed to evaluate the effect of a closed-loop computerised physician order entry (CPOE) system on prescribing in a general paediatric unit in Hong Kong. We studied the effect of the CPOE system on medication prescribing error and the characteristics of these errors before and after the implementation of the system.

METHODS

This was a single-site, prospective, observational study at a public hospital's general paediatric unit in Hong Kong, conducted during the pre- and post-implementation of the system from March to April 2019 and 2020, respectively. Collected data included the number of medication orders processed, the number of prescribing errors identified, and the characteristics of errors, such as the severity, children's age group, drug formulation, and drug class.

KEY FINDINGS

The prescribing error rate was significantly reduced from 6.7% to 3.9% after CPOE implementation. The causes of prescribing errors were found to be significantly different, as the implementation eradicated handwriting-related errors and reduced dosage selection-related errors. However, we found that CPOE increased other causes of error, such as missing entry of patient information that might affect the dispensing process, thus delaying patients in receiving their medications on time.

CONCLUSION

The CPOE system significantly reduced prescribing errors and altered some of the characteristics of these errors. Poor system design or inadequate user training could result in the creation of new causes of error.

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.

Standardising the Classification of Harm Associated with Medication Errors: The Harm Associated with Medication Error Classification (HAMEC)

Classifying harm associated with a medication error can be time consuming and labour intensive and limited studies undertake this step. There is no standardised process, and few studies that report harm assessment provide adequate methods to allow for study replication. Studies typically mention that a clinical review panel classified patient harm and provide a reference to a classification tool. Moreover, in many studies it is unclear whether potential or actual harm was classified as studies refer only to ‘error severity’. The tools used to categorise the severity of patient harm vary widely across studies and few have been assessed for inter-rater reliability and criterion validity. In this paper, we describe the systematic process we undertook to synthesise the defining elements and strengths, while mitigating the limitations, of existing harm classification tools to derive the Harm Associated with Medication Error Classification (HAMEC). This new tool provides a harm classification for use across clinical and research settings. The provision of an explicit process for its application and guiding category descriptors are designed to reduce the risk of misclassification and produce results that are comparable across studies. As the World Health Organisation embarks on its international safety challenge of reducing medication-related harm by 50%, accompanying methodological advances are required to measure progress.

The impact of drug order complexity on prospective medication order review and verification time

OBJECTIVE

To assess if the amount of time a pharmacist spends verifying medication orders increases as medication orders become more complex.

MATERIALS AND METHODS

The study was conducted by observing pharmacist verification of adult medication orders in an academic medical center. Drug order complexity was prospectively defined and validated using a classification system derived from 3 factors: the degree of order variability, ISMP high-alert classification, and a pharmacist perception survey. Screen capture software was used to measure pharmacist order review time for each classification. The annualized volume of low complexity drug orders was used to calculate the potential time savings if these were verified using an alternate system that did not require pharmacist review.

RESULTS

The primary study hypothesis was not achieved. Regression results did not show statistical significance for moderate (n = 30, 23.7 seconds, sd = 23.3) or high complexity (n = 30, 18.6 seconds, sd = 23.1) drugs relative to the low complexity drugs (n = 30, 8.0 seconds, sd = 14.4) nor for moderate vs high complexity; (βmoderate vs low = 15.6, P = .113), (βhigh vs low = 10.3, P = .235), (βmoderate vs high = 5.3, P = .737). The sensitivity analysis showed statistical significance in the high vs low comparison (βhigh vs low = 13.8, P = .017).

DISCUSSION

This study showed that verifying pharmacists spent less time than projected to verify medication orders of different complexities, but the time did not correlate with the classifications used in our complexity scale. Several mitigating factors, including operational aspects associated with timing antimicrobial orders, likely influenced order verification time. These factors should be evaluated in future studies which seek to define drug order complexity and optimize pharmacist time spent in medication order verification.

CONCLUSION

The findings suggest that there may be other factors involved in pharmacist decision-making that should be considered when categorizing drugs by perceived complexity.

Electronic prescribing in paediatric secondary care: are harmful errors prevented?

OBJECTIVE

The aim of this research was to ascertain the effectiveness of current electronic prescribing (EP) systems to prevent a standardised set of paediatric prescribing errors likely to cause harm if they reach the patient.

DESIGN

Semistructured survey.

SETTING

UK hospitals using EP in the paediatric setting.

OUTCOME MEASURES

Number and type of erroneous orders able to be prescribed, and the level of clinical decision support (CDS) provided during the prescribing process.

RESULTS

90.7% of the erroneous orders were able to be prescribed across the seven different EP systems tested. Levels of CDS varied between systems and between sites using the same system.

CONCLUSIONS

EP systems vary in their ability to prevent harmful prescribing errors in the hospital paediatric setting. Differences also occur between sites using the same system, highlighting the importance of how a system is set up and optimised.

The Prevalence of Dose Errors Among Paediatric Patients in Hospital Wards with and without Health Information Technology: A Systematic Review and Meta-Analysis

INTRODUCTION

The risk of dose errors is high in paediatric inpatient settings. Computerized provider order entry (CPOE) systems with clinical decision support (CDS) may assist in reducing the risk of dosing errors. Although a frequent type of medication error, the prevalence of dose errors is not well described. Dosing error rates in hospitals with or without CPOE have not been compared.

OBJECTIVE

Our aim was to conduct a systematic review assessing the prevalence and impact of dose errors in paediatric wards with and without CPOE and/or CDS.

METHODS

We systematically searched five databases to identify studies published between January 2000 and December 2017 that assessed dose error rates by medication chart audit or direct observation.

RESULTS

We identified 39 studies, nine of which involved paediatric wards using CPOE with or without CDS. Studies of paediatric wards using paper medication charts reported approximately 8-25% of patients experiencing a dose error, and approximately 2-6% of medication orders and approximately 3-8% of dose administrations contained a dose error, with estimates varying by ward type. The nine studies of paediatric wards using CPOE reported approximately 22% of patients experiencing a dose error, and approximately 1-6% of medication orders and approximately 3-8% of dose administrations contained a dose error. Few studies provided data for individual wards. The severity and prevalence of harm associated with dose errors was rarely assessed and showed inconsistent results.

CONCLUSIONS

Dose errors occur in approximately 1 in 20 medication orders. Hospitals using CPOE with or without CDS had a lower rate of dose errors compared with those using paper charts. However, few pre/post studies have been conducted and none reported a significant reduction in dose error rates associated with the introduction of CPOE. Future research employing controlled designs is needed to determine the true impact of CPOE on dosing errors among children, and any associated patient harm.

Systematic review of computerized prescriber order entry and clinical decision support

PURPOSE

Results of a systematic review of published data on the effect of computerized prescriber order entry (CPOE) with clinical decision support on medication error (ME) and adverse drug event (ADE) rates are presented.

METHODS

Literature searches of MEDLINE, Embase, and other databases were conducted to identify English- and Spanish-language articles on selected CPOE outcomes published from 1995 through 2016; in addition, 5 specific journals were searched for pertinent articles published during the period 2010-16. Publications on controlled prospective studies and before-and-after studies that assessed MEs and/or ADEs as main outcomes were selected for inclusion in the review.

RESULTS

Nineteen studies met the inclusion criteria. Data on MEs and ADEs could not be pooled, mainly due to heterogeneity in outcome definitions and study methodologies. The reviewed evidence indicated that CPOE implementation led to an overall reduction in errors at the prescription stage of the medication-use process (relative risk reduction, 0.29 [95% confidence interval, 0.10-0.85]; I ² = 99%) and reductions in most types of prescription errors, but CPOE also resulted in the emergence of other types of errors.

CONCLUSION

CPOE reduces the overall ME rate in the prescription process, as well as specific types of errors, such as wrong dose or strength, wrong drug, frequency, administration route, and drug-drug interaction errors. The implementation of CPOE can lead to new errors, such as wrong drug selection from drop-down menus.

Drug-drug interactions and pharmacists' interventions among psychiatric patients in outpatient clinics of a teaching hospital in Saudi Arabia

Background

Lack of recognition of labeled drug-drug interactions (DDIs) is a type of medication error of particular relevance to the treatment of psychiatric patients. Pharmacists are in a position to detect and address potential DDIs.

Objective

This study aimed to explore pharmacists' role in the identification and management of DDIs among psychiatric patients in psychiatric outpatient clinics of a university-affiliated tertiary care hospital in Riyadh, Saudi Arabia.

Method

This study was a retrospective, cross-sectional medical chart review of patients visiting outpatient psychiatric clinics. It utilized medical records of patients who were taking any psychotropic medications and were prescribed at least one additional drug. The hospital Computerized Physician Order Entry system was used to identify DDIs and determine the pharmacists' interventions. The Beers criteria were applied to detect inappropriate prescribing among older patients.

Results

On average, the pharmacists intervened in 12 out of 213 (5.6%) cases of major or moderate DDIs. Older age, higher number of prescription medications, the severity of DDIs, and the utilization of lithium and anticoagulants were positively associated with the pharmacist undertaking an action.

Conclusion

Future studies should explore the prevalence rate of harmful DDIs among psychiatric patients on a large scale and examine the effectiveness of different pharmacy policies in the detection and management of DDIs.

Preventable Adverse Drug Events Among Inpatients: A Systematic Review

: media-1vid110.1542/5799876436001PEDS-VA_2018-0805Video Abstract CONTEXT: Patient harm resulting from medication errors drives prevention efforts, yet harm associated with medication errors in children has not been systematically reviewed.

OBJECTIVE

To review the incidence and severity of preventable adverse drug events (pADEs) resulting from medication errors in pediatric inpatient settings.

DATA SOURCES

Data sources included Cumulative Index of Nursing and Allied Health Literature, Medline, Scopus, the Cochrane Library, and Embase.

STUDY SELECTION

Selected studies were published between January 2000 and December 2017, written in the English language, and measured pADEs among pediatric hospital inpatients by chart review or direct observation.

DATA EXTRACTION

Data extracted were medication error and harm definitions, pADE incidence and severity rates, items required for quality assessment, and sample details.

RESULTS

Twenty-two studies were included. For children in general pediatric wards, incidence was at 0 to 17 pADEs per 1000 patient days or 1.3% of medication errors (of any type) compared with 0 to 29 pADEs per 1000 patient days or 1.5% of medication errors in ICUs. Hospital-wide studies contained reports of up to 74 pADEs per 1000 patient days or 2.6% of medication errors. The severity of pADEs was mainly minor.

LIMITATIONS

Limited literature on the severity of pADEs is available. Additional study will better illuminate differences among hospital wards and among those with or without health information technology.

CONCLUSIONS

Medication errors in pediatric settings seldom result in patient harm, and if they do, harm is predominantly of minor severity. Implementing health information technologies was associated with reduced incidence of harm.

Impact of a commercial order entry system on prescribing errors amenable to computerised decision support in the hospital setting: a prospective pre-post study

Background

In this UK study, we investigated the impact of computerised physician order entry (CPOE) and clinical decision support (CDS) implementation on the rate of 78 high-risk prescribing errors amenable to CDS.

Methods

We conducted a preintervention/postintervention study in three acute hospitals in England. A predefined list of prescribing errors was incorporated into an audit tool. At each site, approximately 4000 prescriptions were reviewed both pre-CPOE and 6 months post-CPOE implementation. The number of opportunities for error and the number of errors that occurred were collated. Error rates were then calculated and compared between periods, as well as by the level of CDS.

Results

The prescriptions of 1244 patients were audited pre-CPOE and 1178 post-CPOE implementation. A total of 28 526 prescriptions were reviewed, with 21 138 opportunities for error identified based on 78 defined errors. Across the three sites, for those prescriptions where opportunities for error were identified, the error rate was found to reduce significantly post-CPOE implementation, from 5.0% to 4.0% (P<0.001). CDS implementation by error type was found to differ significantly between sites, ranging from 0% to 88% across clinical contraindication, dose/frequency, drug interactions and other error types (P<0.001). Overall, 43/78 (55%) of the errors had some degree of CDS implemented in at least one of the hospitals.

Conclusions

Implementation of CPOE with CDS was associated with clinically important reductions in the rate of high-risk prescribing errors. Given the pre-post design, these findings however need to be interpreted with caution. The occurrence of errors was found to be highly dependent on the level of restriction of CDS presented to the prescriber, with the effect that different configurations of the same CPOE system can produce very different results.

Patient-reported safety incidents as a new source of patient safety data: an exploratory comparative study in an acute hospital in England

Objectives

To compare a new co-designed, patient incident reporting tool with three established methods of detecting patient safety incidents and identify if the same incidents are recorded across methods.

Method

Trained research staff collected data from inpatients in nine wards in one university teaching hospital during their stay. Those classified as patient safety incidents were retained. We then searched for patient safety incidents in the corresponding patient case notes, staff incident reports and reports to the Patient Advice and Liaison Service specific to the study wards.

Results

In the nine wards, 329 patients were recruited to the study, of which 77 provided 155 patient reports. From these, 68 patient safety incidents were identified. Eight of these were also identified from case note review, five were also identified in incident reports, and two were also found in the records of a local Patient Advice and Liaison Service. Reports of patients covered a range of events from their immediate environment, involving different health professionals and spanning the entire spectrum of care.

Conclusion

Patient safety incidents reported by patients are unlikely to be found through other established methods of incident detection. When hospitalized patients are asked about their care, they can provide a unique perspective on patient safety. Co-designed, real-time reporting could be a helpful addition to existing methods of gathering patient safety intelligence.

Clinical Practice Guideline: Safe Medication Use in the ICU

OBJECTIVE

To provide ICU clinicians with evidence-based guidance on safe medication use practices for the critically ill.

DATA SOURCES

PubMed, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, CINAHL, Scopus, and ISI Web of Science for relevant material to December 2015.

STUDY SELECTION

Based on three key components: 1) environment and patients, 2) the medication use process, and 3) the patient safety surveillance system. The committee collectively developed Population, Intervention, Comparator, Outcome questions and quality of evidence statements pertaining to medication errors and adverse drug events addressing the key components. A total of 34 Population, Intervention, Comparator, Outcome questions, five quality of evidence statements, and one commentary on disclosure was developed.

DATA EXTRACTION

Subcommittee members were assigned selected Population, Intervention, Comparator, Outcome questions or quality of evidence statements. Subcommittee members completed their Grading of Recommendations Assessment, Development, and Evaluation of the question with his/her quality of evidence assessment and proposed strength of recommendation, then the draft was reviewed by the relevant subcommittee. The subcommittee collectively reviewed the evidence profiles for each question they developed. After the draft was discussed and approved by the entire committee, then the document was circulated among all members for voting on the quality of evidence and strength of recommendation.

DATA SYNTHESIS

The committee followed the principles of the Grading of Recommendations Assessment, Development, and Evaluation system to determine quality of evidence and strength of recommendations.

CONCLUSIONS

This guideline evaluates the ICU environment as a risk for medication-related events and the environmental changes that are possible to improve safe medication use. Prevention strategies for medication-related events are reviewed by medication use process node (prescribing, distribution, administration, monitoring). Detailed considerations to an active surveillance system that includes reporting, identification, and evaluation are discussed. Also, highlighted is the need for future research for safe medication practices that is specific to critically ill patients.

Outpatient CPOE orders discontinued due to 'erroneous entry': prospective survey of prescribers' explanations for errors

BACKGROUND

Computerised prescriber order entry (CPOE) systems users often discontinue medications because the initial order was erroneous.

OBJECTIVE

To elucidate error types by querying prescribers about their reasons for discontinuing outpatient medication orders that they had self-identified as erroneous.

METHODS

During a nearly 3 year retrospective data collection period, we identified 57 972 drugs discontinued with the reason 'Error (erroneous entry)." Because chart reviews revealed limited information about these errors, we prospectively studied consecutive, discontinued erroneous orders by querying prescribers in near-real-time to learn more about the erroneous orders.

RESULTS

From January 2014 to April 2014, we prospectively emailed prescribers about outpatient drug orders that they had discontinued due to erroneous initial order entry. Of 2 50 806 medication orders in these 4 months, 1133 (0.45%) of these were discontinued due to error. From these 1133, we emailed 542 unique prescribers to ask about their reason(s) for discontinuing these mediation orders in error. We received 312 responses (58% response rate). We categorised these responses using a previously published taxonomy. The top reasons for these discontinued erroneous orders included: medication ordered for wrong patient (27.8%, n=60); wrong drug ordered (18.5%, n=40); and duplicate order placed (14.4%, n=31). Other common discontinued erroneous orders related to drug dosage and formulation (eg, extended release versus not). Oxycodone (3%) was the most frequent drug discontinued error.

CONCLUSION

Drugs are not infrequently discontinued 'in error.' Wrong patient and wrong drug errors constitute the leading types of erroneous prescriptions recognised and discontinued by prescribers. Data regarding erroneous medication entries represent an important source of intelligence about how CPOE systems are functioning and malfunctioning, providing important insights regarding areas for designing CPOE more safely in the future.

Medicines Optimisation Assessment Tool (MOAT): a prognostic model to target hospital pharmacists' input to improve patient outcomes. Protocol for an observational study

INTRODUCTION

Medicines optimisation is a key role for hospital pharmacists, but with ever-increasing demands on services there is a need to increase efficiency while maintaining patient safety. The aim of this study is to develop a prognostic model, the Medicines Optimisation Assessment Tool (MOAT), which can be used to target patients most in need of pharmacists' input while in hospital.

METHODS AND ANALYSIS

The MOAT will be developed following recommendations of the Prognosis Research Strategy partnership. Using a cohort study we will prospectively include 1500 adult patients from the medical wards of two UK hospitals. Data on medication-related problems (MRPs) experienced by study patients will be collected by pharmacists at the study sites as part of their routine daily clinical assessment of patients. Data on potential risk factors such as polypharmacy, renal impairment and the use of 'high risk' medicines will be collected retrospectively from the information departments at the study sites, laboratory reporting systems and patient medical records. Multivariable logistic regression models will then be used to determine the relationship between potential risk factors and the study outcome of preventable MRPs that are at least moderate in severity. Bootstrapping will be used to adjust the MOAT for optimism, and predictive performance will be assessed using calibration and discrimination. A simplified scoring system will also be developed, which will be assessed for sensitivity and specificity.

ETHICS AND DISSEMINATION

This study has been approved by the Proportionate Review Service Sub-Committee of the National Health Service Research Ethics Committee Wales REC 7 (16/WA/0016) and the Health Research Authority (project ID 197298). We plan to disseminate the results via presentations at relevant patient/public, professional, academic and scientific meetings and conferences, and will submit findings for publication in peer-reviewed journals.

TRIAL REGISTRATION NUMBER

NCT02582463.

Improving patient safety through the involvement of patients: development and evaluation of novel interventions to engage patients in preventing patient safety incidents and protecting them against unintended harm

Background

Estimates suggest that, in NHS hospitals, incidents causing harm to patients occur in 10% of admissions, with costs to the NHS of > £2B. About one-third of harmful events are believed to be preventable. Strategies to reduce patient safety incidents (PSIs) have mostly focused on changing systems of care and professional behaviour, with the role that patients can play in enhancing the safety of care being relatively unexplored. However, although the role and effectiveness of patient involvement in safety initiatives is unclear, previous work has identified a general willingness among patients to contribute to initiatives to improve health-care safety.

Aim

Our aim in this programme was to design, develop and evaluate four innovative approaches to engage patients in preventing PSIs: assessing risk, reporting incidents, direct engagement in preventing harm and education and training.

Methods and results

We developed tools to report PSIs [patient incident reporting tool (PIRT)] and provide feedback on factors that might contribute to PSIs in the future [Patient Measure of Safety (PMOS)]. These were combined into a single instrument and evaluated in the Patient Reporting and Action for a Safe Environment (PRASE) intervention using a randomised design. Although take-up of the intervention by, and retention of, participating hospital wards was 100% and patient participation was high at 86%, compliance with the intervention, particularly the implementation of action plans, was poor. We found no significant effect of the intervention on outcomes at 6 or 12 months. The ThinkSAFE project involved the development and evaluation of an intervention to support patients to directly engage with health-care staff to enhance their safety through strategies such as checking their care and speaking up to staff if they had any concerns. The piloting of ThinkSAFE showed that the approach is feasible and acceptable to users and may have the potential to improve patient safety. We also developed a patient safety training programme for junior doctors based on patients who had experienced PSIs recounting their own stories. This approach was compared with traditional methods of patient safety teaching in a randomised controlled trial. The study showed that delivering patient safety training based on patient narratives is feasible and had an effect on emotional engagement and learning about communication. However, there was no effect on changing general attitudes to safety compared with the control.

Conclusion

This research programme has developed a number of novel interventions to engage patients in preventing PSIs and protecting them against unintended harm. In our evaluations of these interventions we have been unable to demonstrate any improvement in patient safety although this conclusion comes with a number of caveats, mainly about the difficulty of measuring patient safety outcomes. Reflecting this difficulty, one of our recommendations for future research is to develop reliable and valid measures to help efficiently evaluate safety improvement interventions. The programme found patients to be willing to codesign, coproduce and participate in initiatives to prevent PSIs and the approaches used were feasible and acceptable. These factors together with recent calls to strengthen the patient voice in health care could suggest that the tools and interventions from this programme would benefit from further development and evaluation.

Trial registration

Current Controlled Trials ISRCTN07689702.

Funding

The National Institute for Health Research Programme Grants for Applied Research programme.

Developing consensus on hospital prescribing indicators of potential harm for infants and children

AIMS

The aim of the study was to develop a list of hospital based paediatric prescribing indicators that can be used to assess the impact of electronic prescribing or clinical decision support tools on paediatric prescribing errors.

METHODS

Two rounds of an electronic consensus method (eDelphi) were carried out with 21 expert panellists from the UK. Panellists were asked to score each prescribing indicator for its likelihood of occurrence and severity of outcome should the error occur. The scores were combined to produce a risk score and a median score for each indicator calculated. The degree of consensus between panellists was defined as the proportion that gave a risk score in the same category as the median. Indicators were included if a consensus of 80% or higher was achieved and were in the high risk categories.

RESULTS

Each of the 21 panellists completed an exploratory round and two rounds of scoring. This identified 41 paediatric prescribing indicators with a high risk rating and greater than 80% consensus. The most common error type within the indicators was wrong dose (n = 19) and the most common drug classes were antimicrobials (n = 10) and cardiovascular (n = 7).

CONCLUSIONS

A set of 41 paediatric prescribing indicators describing potential harm for the hospital setting has been identified by an expert panel. The indicators provide a standardized method of evaluation of prescribing data on both paper and electronic systems. They can also be used to assess implementation of clinical decision support systems or other quality improvement initiatives.

Analysis of medication prescribing errors in critically ill children

Medication prescribing errors (MPE) can result in serious consequences for patients. In order to reduce errors, we need to know more about the frequency, the type and the severity of such errors. We therefore performed a prospective observational study to determine the number and type of medication prescribing errors in critically ill children in a paediatric intensive care unit (PICU). Prescribing errors were prospectively identified by a clinical pharmacist. A total of 1129 medication orders were analysed. There were 151 prescribing errors, giving an overall error rate of 14 % (95 % CI 11 to 16). The medication groups with the highest proportion of MPEs were antihypertensives, antimycotics and drugs for nasal preparation with error rates of each 50 %, followed by antiasthmatic drugs (25 %), antibiotics (15 %) and analgesics (14 %). One hundred four errors (70 %) were classified as MPEs which required interventions and/or resulted in patient harm equivalent to 9 % of all medication orders (95 % CI 6.5 to 14.4). Forty-five MPEs (30 %) did not result in patient harm.

CONCLUSION

With a view to reduce MPEs and to improve patient safety, our data may help to prevent errors before they occur.

WHAT IS KNOWN

• Prescribing errors may be the most frequent medication errors. • In paediatric populations, the incidence of prescribing errors is higher than in adults. What is New: • Several risk factors for medication prescribing errors, such as medication groups, long PICU stay, and mechanical ventilation could be presented. • Analysing the combination of the most frequent prescribing errors and the severity of these errors.

Prevalence, nature and predictors of prescribing errors in mental health hospitals: a prospective multicentre study

OBJECTIVE

To determine the prevalence, nature and predictors of prescribing errors (PEs) in three mental health hospitals.

SETTING

Inpatient units in three National Health Service (NHS) mental health hospitals in the North West of England.

PARTICIPANTS

Trained clinical pharmacists prospectively recorded the number of PEs in newly written or omitted prescription items screened during their routine work on 10 data collection days. A multidisciplinary panel reviewed PE data using established methods to confirm (1) the presence of a PE, (2) the type of PE and (3) whether errors were clinically relevant and likely to cause harm.

PRIMARY OUTCOME MEASURES

Frequency, nature and predictors of PEs.

RESULTS

Of 4427 screened prescription items, 281 were found to have one or more PEs (error rate 6.3% (95% CI 5.6 to 7.1%)). Multivariate analysis revealed that specialty trainees (OR 1.23 (1.01 to 1.51)) and staff grade psychiatrists (OR 1.50 (1.05 to 2.13)) were more likely to make PEs when compared to foundation year (FY) one doctors, and that specialty trainees and consultant psychiatrists were twice as likely to make clinically relevant PEs (OR 2.61 (2.11 to 3.22) and 2.03 (1.66 to 2.50), respectively) compared to FY one staff. Prescription items screened during the prescription chart rewrite (OR 0.52 (0.33 to 0.82)) or at discharge (OR 0.87 (0.79 to 0.97)) were less likely to be associated with PEs than items assessed during inpatient stay, although they were more likely to be associated with clinically relevant PEs (OR 2.27 (1.72 to 2.99) and 4.23 (3.68 to 4.87), respectively). Prescription items screened at hospital admission were five times more likely (OR 5.39 (2.72 to 10.69)) to be associated with clinically relevant errors than those screened during patient stay.

CONCLUSIONS

PEs may be more common in mental health hospitals than previously reported and important targets to minimise these errors have been identified.

The effectiveness of computerized order entry at reducing preventable adverse drug events and medication errors in hospital settings: a systematic review and meta-analysis

BACKGROUND

The Health Information Technology for Economic and Clinical Health (HITECH) Act subsidizes implementation by hospitals of electronic health records with computerized provider order entry (CPOE), which may reduce patient injuries caused by medication errors (preventable adverse drug events, pADEs). Effects on pADEs have not been rigorously quantified, and effects on medication errors have been variable. The objectives of this analysis were to assess the effectiveness of CPOE at reducing pADEs in hospital-related settings, and examine reasons for heterogeneous effects on medication errors.

METHODS

Articles were identified using MEDLINE, Cochrane Library, Econlit, web-based databases, and bibliographies of previous systematic reviews (September 2013). Eligible studies compared CPOE with paper-order entry in acute care hospitals, and examined diverse pADEs or medication errors. Studies on children or with limited event-detection methods were excluded. Two investigators extracted data on events and factors potentially associated with effectiveness. We used random effects models to pool data.

RESULTS

Sixteen studies addressing medication errors met pooling criteria; six also addressed pADEs. Thirteen studies used pre-post designs. Compared with paper-order entry, CPOE was associated with half as many pADEs (pooled risk ratio (RR) = 0.47, 95% CI 0.31 to 0.71) and medication errors (RR = 0.46, 95% CI 0.35 to 0.60). Regarding reasons for heterogeneous effects on medication errors, five intervention factors and two contextual factors were sufficiently reported to support subgroup analyses or meta-regression. Differences between commercial versus homegrown systems, presence and sophistication of clinical decision support, hospital-wide versus limited implementation, and US versus non-US studies were not significant, nor was timing of publication. Higher baseline rates of medication errors predicted greater reductions (P < 0.001). Other context and implementation variables were seldom reported.

CONCLUSIONS

In hospital-related settings, implementing CPOE is associated with a greater than 50% decline in pADEs, although the studies used weak designs. Decreases in medication errors are similar and robust to variations in important aspects of intervention design and context. This suggests that CPOE implementation, as subsidized under the HITECH Act, may benefit public health. More detailed reporting of the context and process of implementation could shed light on factors associated with greater effectiveness.

Detection of medication-related problems in hospital practice: a review

This review examines the effectiveness of detection methods in terms of their ability to identify and accurately determine medication-related problems in hospitals. A search was conducted of databases from inception to June 2012. The following keywords were used in combination: medication error or adverse drug event or adverse drug reaction, comparison, detection, hospital and method. Seven detection methods were considered: chart review, claims data review, computer monitoring, direct care observation, interviews, prospective data collection and incident reporting. Forty relevant studies were located. Detection methods that were better able to identify medication-related problems compared with other methods tested in the same study included chart review, computer monitoring, direct care observation and prospective data collection. However, only small numbers of studies were involved in comparisons with direct care observation (n = 5) and prospective data collection (n = 6). There was little focus on detecting medication-related problems during various stages of the medication process, and comparisons associated with the seriousness of medication-related problems were examined in 19 studies. Only 17 studies involved appropriate comparisons with a gold standard, which provided details about sensitivities and specificities. In view of the relatively low identification of medication-related problems with incident reporting, use of this method in tracking trends over time should be met with some scepticism. Greater attention should be placed on combining methods, such as chart review and computer monitoring in examining trends. More research is needed on the use of claims data, direct care observation, interviews and prospective data collection as detection methods.

Prescribing errors in hospital practice

Prescribing errors that occur in hospitals have been a source of concern for decades. This narrative review describes some of the recent work in this field. There is considerable heterogeneity in definitions and methods used in research on prescribing errors. There are three definitions that are used most frequently (one for prescribing errors specifically and two for the broader arena of medication errors), although many others have also been used. Research methods used focus primarily on investigating either the prescribing process (such as errors in the dose prescribed) or the outcomes for the patient (such as preventable adverse drug events). This complicates attempts to calculate the overall prevalence or incidence of errors. Errors have been reported in handwritten descriptions of almost 15% and with electronic prescribing of up to 8% of orders. Errors are more likely to be identified on admission to hospital than at any other time (usually failure to continue ongoing medication) and errors of dose occur most commonly throughout the patients' stay. Although there is evidence that electronic prescribing reduces the number of errors, new types of errors also occur. The literature on causes of error shows some commonality with both handwritten and electronic prescribing but there are also causes that are unique to each. A greater understanding of the prevalence of the complex causal pathways found and the differences between the pathways of minor and severe errors is necessary. Such an understanding would underpin theoretically-based interventions to reduce the occurrence of prescribing errors.

Categorising paediatric prescribing errors by junior doctors through prescribing competency assessment: does assessment reflect actual practice?

PURPOSE

It is recognised that paediatric prescribing errors are prevalent, and that most are made by junior doctors; however, detecting errors in order to demonstrate actual error rates can be difficult. There is evidence to suggest that dosing errors are the most common type of prescribing error in practice, but there has been little research on whether prescribing assessments are an effective reflection of actual practice.This article aims to determine if prescribing error types in a paediatric prescribing competency assessment reflects error types seen in actual practice.

METHODS

This study was conducted in Royal Manchester Children's Hospital (RMCH) and the participants were junior doctors working at RMCH in 2010-2011. The intervention was a prescribing competency assessment package at RMCH.The main outcome measurement was the category and rate of prescribing errors. Results were taken from the junior doctors' prescribing competency assessment. The assessment papers were analysed for errors and the errors were then broken down into pre-defined categories.

RESULTS

Rates of prescribing errors in the competency assessment are higher than published results shown in practice (23.1 %). The most common type of prescribing error (incorrect calculation of dose) reflects results seen in actual practice.

CONCLUSION

The types of prescribing errors made in the competency assessment are reflective of errors made in actual practice. Prescribing teaching can be tailored according to the types of errors noted; and the prescribing competency package as a whole can be used to educate junior doctors on good prescribing practice and reduce prescribing errors.

Improvement in the detection of adverse drug events by the use of electronic health and prescription records: an evaluation of two trigger tools

PURPOSE

To test if two of the adverse event triggers proposed by the Institute of Healthcare Improvement can detect adverse drug events (ADEs) in a UK secondary care setting, using an electronic prescribing and health record system.

METHODS

In order to identify triggers for over-anticoagulation and potential opioid overdose and we undertook a retrospective review of electronic medical and prescription records from 54,244 hospital admissions over a 1-year period, alongside a review of medical incident reports. Once prescription data were linked to triggers and duplicates were removed, case note review eliminated the false positive ADEs. Additionally, we tested the use of an electronic algorithm for the International Normalized Ratio (INR) ≥6 trigger.

RESULTS

The INR ≥6 electronic trigger identified 46 potential ADEs and the naloxone electronic trigger identified 82 ADEs. Based on the available case note review, the INR ≥6 trigger had a positive predictive value (PPV) of 38 % (14/37) and the naloxone trigger had a PPV of 91 % (61/67). The electronic algorithm for the INR ≥6 trigger identified 12 ADEs, thus reducing the need of case note review. This was in comparison with one and two critical incidents reported in the trust medical incident reports system, which respectively related to over-coagulation with warfarin and over-sedation with opioid medication.

CONCLUSIONS

We have integrated automated and manual methods of detecting ADEs using previously defined triggers. Incorporating electronic triggers in already established electronic health records with prescription and laboratory test data can improve the detection of ADEs, and potentially lead to methods to avert them.

Failure mode and effects analysis outputs: are they valid?

BACKGROUND

Failure Mode and Effects Analysis (FMEA) is a prospective risk assessment tool that has been widely used within the aerospace and automotive industries and has been utilised within healthcare since the early 1990s. The aim of this study was to explore the validity of FMEA outputs within a hospital setting in the United Kingdom.

METHODS

Two multidisciplinary teams each conducted an FMEA for the use of vancomycin and gentamicin. Four different validity tests were conducted: Face validity: by comparing the FMEA participants' mapped processes with observational work. Content validity: by presenting the FMEA findings to other healthcare professionals. Criterion validity: by comparing the FMEA findings with data reported on the trust's incident report database. Construct validity: by exploring the relevant mathematical theories involved in calculating the FMEA risk priority number.

RESULTS

Face validity was positive as the researcher documented the same processes of care as mapped by the FMEA participants. However, other healthcare professionals identified potential failures missed by the FMEA teams. Furthermore, the FMEA groups failed to include failures related to omitted doses; yet these were the failures most commonly reported in the trust's incident database. Calculating the RPN by multiplying severity, probability and detectability scores was deemed invalid because it is based on calculations that breach the mathematical properties of the scales used.

CONCLUSION

There are significant methodological challenges in validating FMEA. It is a useful tool to aid multidisciplinary groups in mapping and understanding a process of care; however, the results of our study cast doubt on its validity. FMEA teams are likely to need different sources of information, besides their personal experience and knowledge, to identify potential failures. As for FMEA's methodology for scoring failures, there were discrepancies between the teams' estimates and similar incidents reported on the trust's incident database. Furthermore, the concept of multiplying ordinal scales to prioritise failures is mathematically flawed. Until FMEA's validity is further explored, healthcare organisations should not solely depend on their FMEA results to prioritise patient safety issues.

Medicines reconciliation using a shared electronic health care record

OBJECTIVE

: This study aimed to evaluate the use of a shared electronic primary health care record (EHR) to assist with medicines reconciliation in the hospital from admission to discharge.

METHODS

: This is a prospective cross-sectional, comparison evaluation for 2 phases, in a short-term elderly admissions ward in the United Kingdom. In phase 1, full reconciliation of the medication history was attempted, using conventional methods, before accessing the EHR, and then the EHR was used to verify the reconciliation. In phase 2, the EHR was the initial method of retrieving the medication history-validated by conventional methods.

RESULTS

: Where reconciliation was led by conventional methods, and before any access to the EHR was attempted, 28 (28%) of hospital prescriptions were found to contain errors. Of 99 prescriptions subsequently checked using the EHR, only 50 (50%) matched the EHR. Of the remainder, 25% of prescriptions contained errors when verified by the EHR. However, 26% of patients had an incorrect list of current medications on the EHR.Using the EHR as the primary method of reconciliation, 33 (32%) of 102 prescriptions matched the EHR. Of those that did not match, 39 (38%) of prescriptions were found to contain errors. Furthermore, 37 (36%) of patients had an incorrect list of current medications on the EHR.The most common error type on the discharge prescription was drug omission; and on the EHR, wrong drug. Common potentially serious errors were related to unidentified allergies and adverse drug reactions.

CONCLUSIONS

: The EHR can reduce medication errors. However, the EHR should be seen as one of a range of information sources for reconciliation; the primary source being the patient or their carer. Both primary care and hospital clinicians should have read-and-write access to the EHR to reduce errors at care transitions. We recommend further evaluation studies.

Pharmaceutical interventions on prescription problems in a Danish pharmacy setting

BACKGROUND

International studies regarding pharmacists' interventions towards prescription problems produce highly variable results. The only peer-reviewed study in a Danish setting estimated an intervention rate of 2.3 per 1,000 prescriptions. With the introduction of a new tool for registration, we hypothesized that a better estimate could be obtained.

OBJECTIVE

We aimed to produce an up-to-date estimate of the extent and type of pharmacists' interventions towards prescription problems in a Danish pharmacy setting

SETTING

The study was conducted at Copenhagen Sønderbro Pharmacy, a large urban 24-hour pharmacy.

METHOD

Data were collected prospectively through an electronic form. All interventions were primarily classified as either clinical or administrative in nature, and further classified in a number of pre-determined subcategories. Furthermore, information about age, sex, time of day, the wording of the prescription, the performed intervention, the person performing the intervention and the type of prescriber were recorded. All entries were manually validated by a study pharmacist.

MAIN OUTCOME MEASURE

The intervention rate, given as the number of interventions per 1,000 prescriptions.

RESULTS

We found 599 validated interventions. Thirty-two percent of the interventions were clinical and 68% administrative by nature. Fifty-one percent of the administrative and 35% of the clinical interventions were regarding antibiotics. In the study period, a total of 55,522 prescriptions were filled out together with 3,069 dose-dispensing packages, giving a rate of 10.2 (9.4-11.1) interventions per 1,000 prescriptions.

CONCLUSION

We found an intervention rate substantially higher than reported in previous Danish studies.

Patient involvement in patient safety: Protocol for developing an intervention using patient reports of organisational safety and patient incident reporting

BACKGROUND

Patients have the potential to provide a rich source of information on both organisational aspects of safety and patient safety incidents. This project aims to develop two patient safety interventions to promote organisational learning about safety - a patient measure of organisational safety (PMOS), and a patient incident reporting tool (PIRT) - to help the NHS prevent patient safety incidents by learning more about when and why they occur.

METHODS

To develop the PMOS 1) literature will be reviewed to identify similar measures and key contributory factors to error; 2) four patient focus groups will ascertain practicality and feasibility; 3) 25 patient interviews will elicit approximately 60 items across 10 domains; 4) 10 patient and clinician interviews will test acceptability and understanding. Qualitative data will be analysed using thematic content analysis.To develop the PIRT 1) individual and then combined patient and clinician focus groups will provide guidance for the development of three potential reporting tools; 2) nine wards across three hospital directorates will pilot each of the tools for three months. The best performing tool will be identified from the frequency, volume and quality of reports. The validity of both measures will be tested. 300 patients will be asked to complete the PMOS and PIRT during their stay in hospital. A sub-sample (N = 50) will complete the PMOS again one week later. Health professionals in participating wards will also be asked to complete the AHRQ safety culture questionnaire. Case notes for all patients will be reviewed. The psychometric properties of the PMOS will be assessed and a final valid and reliable version developed. Concurrent validity for the PIRT will be assessed by comparing reported incidents with those identified from case note review and the existing staff reporting scheme. In a subsequent study these tools will be used to provide information to wards/units about their priorities for patient safety. A patient panel will provide steering to the research.

DISCUSSION

The PMOS and PIRT aim to provide a reliable means of eliciting patient views about patient safety. Both interventions are likely to have relevance and practical utility for all NHS hospital trusts.

A trigger tool fails to identify serious errors and adverse events in pediatric otolaryngology

OBJECTIVE: To identify and quantify errors and adverse events on an inpatient academic tertiary-care pediatric otolaryngology service, a trigger tool was developed and validated as part of a quality improvement initiative.

STUDY DESIGN: Retrospective record review.

SETTING: Children's Hospital Boston quality improvement initiative.

SUBJECTS AND METHODS: Fifty inpatient admissions were reviewed. The gold standard for errors and adverse events identification was a detailed chart review by two board-certified otolaryngologists blinded to trigger tool findings.

RESULTS: Trigger tool interrater reliability ranged from poor to high for admission triggers (kappa = 0.35, 95% confidence interval [95% CI] —0.07 to 0.76), discharge triggers (kappa = 0.63, 95% CI 0.27–0.99), medical records triggers (kappa = 0.61, 95% CI 0.11–1.00), and medication triggers (kappa = 0.90, 95% CI 0.71–1.00). Errors and adverse events were found in all admissions: three percent were potentially harmful, and 93 percent were documentation-related.

CONCLUSION: The trigger tool was successful in identifying clerical and administrative errors and adverse events but failed to identify complex errors and adverse events. A hybrid approach for chart review may be cost-effective in pediatric otolaryngology.

Testing a trigger tool as a method of detecting harm from medication errors in a UK hospital: a pilot study

Objectives

The aim was to adapt a US adverse drug event (ADE) trigger tool for UK use, and to establish its positive predictive value (PPV) and sensitivity in comparison to retrospective health record review for the identification of preventable ADEs, in a pilot study on one hospital ward.

Methods

An established US trigger tool was adapted for UK use. We applied it retrospectively to 207 patients' health records, following up positive triggers to identify any ADEs (both preventable and non-preventable). We compared the preventable ADEs to those identified using full health record review.

Key findings

We identified 168 positive triggers in 127 (61%) of 207 patients. Seven ADEs were identified, representing an ADE in 3.4% of patients or 0.7 ADEs per 100 patient days. Five were non-preventable adverse drug reactions and two were due to preventable errors. The prevalence of preventable ADEs was 1.0% of patients, or 0.2 per 100 patient days. The overall PPV was 0.04 for all ADEs, and 0.01 for preventable ADEs. PPVs for individual triggers varied widely. Five preventable ADEs were identified using health record review. The sensitivity of the trigger tool for identifying preventable ADEs was 0.40, when compared to health record review.

Conclusions

Although we identified some ADEs using the trigger tool, more work is needed to further refine the trigger tool to reduce the false positives and increase sensitivity. To comprehensively identify preventable ADEs, retrospective health record review remains the gold standard and we found no efficiency gain in using the trigger tool.

Developing a patient safety surveillance system to identify adverse events in the intensive care unit

Aggregation of adverse drug event data has evolved in the last decade. Several approaches are available to augment the standard voluntary incident reporting system. Most of these methods are applicable to nonmedication adverse events as well. To identify appropriately system trends as well as process failures, intensive care units should participate in various collection methods. Several different methods are available for robust adverse drug event data collection, such as target chart review, nontargeted chart review, and direct observation. As the various methods usually capture different types of events, employing more than one technique will improve the assessment of intensive care unit care. Some of these surveillance methods offer real-time or near real-time identification of adverse drug events and potentially afford the practitioner time for intervention. Continued development of adverse drug event detection will allow for further quality improvement efforts and preventive strategies to be utilized.

Electronic prescribing--safer, faster, better?

The study, first published in 2006, looks at how we should evaluate electronic prescribing systems in hospitals, particularly to improve patient safety. It provides an evaluation framework, compares methodologies to detect prescribing errors and describes the advantages of approaching evaluation of these systems from a sociotechnical perspective. Two electronic prescribing systems are studied using simultaneous quantitative and qualitative approaches. Electronic prescribing systems can reduce the incidence of prescribing error, however their implementation is not straight forward and they should be considered a constant 'work in progress'.