The impact of a novel medication scanner on administration errors in the hospital setting: a before and after feasibility study.

OBJECTIVE: The medication administration process is complex and consequently prone to errors. Closed Loop Medication Administration solutions aim to improve patient safety. We assessed the impact of a novel medication scanning device (MedEye) on the rate of medication administration errors in a large UK Hospital. METHODS: We performed a feasibility before and after study on one ward at a tertiary-care teaching hospital that used a commercial electronic prescribing and medication administration system. We conducted direct observations of nursing drug administration rounds before and after the MedEye implementation. We calculated the rate and type ('timing', 'omission' or 'other' error) of medication administration errors (MAEs) before and after the MedEye implementation. RESULTS: We observed a total of 1069 administrations before and 432 after the MedEye intervention was implemented. Data suggested that MedEye could support a reduction in MAEs. After adjusting for heterogeneity, we detected a decreasing effect of MedEye on overall errors (p = 0.0753). Non-timing errors ('omission' and 'other' errors) reduced from 51 (4.77%) to 11 (2.55%), a reduction of 46.5%, which had borderline significance at the 5% level, although this was lost after adjusting for confounders. CONCLUSIONS: This pilot study detected a decreasing effect of MedEye on overall errors and a reduction in non-timing error rates that was clinically important as such errors are more likely to be associated with harm. Further research is needed to investigate the impact on a larger sample of medications.

Eliciting willingness-to-pay to prevent hospital medication administration errors in the UK: a contingent valuation survey.

Medication errors are common in hospitals. These errors can result in adverse drug events (ADEs), which can reduce the health and well-being of patients', and their relatives and caregivers. Interventions have been developed to reduce medication errors, including those that occur at the administration stage. OBJECTIVE: We aimed to elicit willingness-to-pay (WTP) values to prevent hospital medication administration errors. DESIGN AND SETTING: An online, contingent valuation (CV) survey was conducted, using the random card-sort elicitation method, to elicit WTP to prevent medication errors. PARTICIPANTS: A representative sample of the UK public. METHODS: Seven medication error scenarios, varying in the potential for harm and the severity of harm, were valued. Scenarios were developed with input from: clinical experts, focus groups with members of the public and piloting. Mean and median WTP values were calculated, excluding protest responses or those that failed a logic test. A two-part model (logit, generalised linear model) regression analysis was conducted to explore predictive characteristics of WTP. RESULTS: Responses were collected from 1001 individuals. The proportion of respondents willing to pay to prevent a medication error increased as the severity of the ADE increased and was highest for scenarios that described actual harm occurring. Mean WTP across the scenarios ranged from £45 (95% CI £36 to £54) to £278 (95% CI £200 to £355). Several factors influenced both the value and likelihood of WTP, such as: income, known experience of medication errors, sex, field of work, marriage status, education level and employment status. Predictors of WTP were not, however, consistent across scenarios. CONCLUSIONS: This CV study highlights how the UK public value preventing medication errors. The findings from this study could be used to carry out a cost-benefit analysis which could inform implementation decisions on the use of technology to reduce medication administration errors in UK hospitals.

Relationship between labour force satisfaction, wages and retention within the UK National Health Service: a systematic review of the literature.

OBJECTIVES: A systematic review was undertaken to understand the nature of the relationship between the UK National Health Service (NHS) labour force and satisfaction, retention and wages. DESIGN: Narrative systematic review. DATA SOURCES: The literature was searched using seven databases in January 2020: MEDLINE (1996-present), the Cumulative Index to Nursing and Allied Health Literature (CINAHL via EBSCO) (1984-present), Embase (1996-present), PsycINFO (1987-present), ProQuest (1996-present), Scopus (all years) and Cochrane library (all years). We used medical subject headings and key words relating to 'retention', 'satisfaction' and 'wages'. ELIGIBILITY CRITERIA FOR SELECTING STUDIES: Primary research studies or reviews that focused on the following relationships within the NHS workforce: wages and job satisfaction, job satisfaction and retention or wages and retention. DATA EXTRACTION AND SYNTHESIS: Two independent reviewers screened all titles, abstracts and full texts, with arbitration by a third reviewer. RESULTS: 27 803 articles were identified and after removing duplicates (n=17 156), articles were removed at the title (n=10 421), abstract (n=150) and full-text (n=45) stages. A total of 31 full-text articles were included. They identified three broad themes, low job satisfaction impacting negatively on job retention, poor pay impacting negatively on staff satisfaction and the limitations of increasing pay as a means of improving staff retention. Several factors affected these relationships, including the environment, discrimination, flexibility, autonomy, training and staffing levels. CONCLUSIONS: This review highlighted how multiple factors influence NHS labour force retention. Pay was found to influence satisfaction, which in turn affected retention. An increase in wages alone is unlikely to be sufficient to ameliorate the concerns of NHS workers. More research is needed to identify the role of autonomy on retention. A system leadership approach underpinned by data is required to implement bespoke job satisfaction improvement strategies to improve retention and achieve the goals of the NHS Long Term Plan.

A systematic review of the impact of health information technology on nurses' time.

OBJECTIVE: Nursing time represents one of the highest costs for most health services. We conducted a systematic review of the literature on the impact of health information technology on nurses' time. MATERIALS AND METHODS: We followed PRISMA guidelines and searched 6 large databases for relevant articles published between Jan 2004 and December 2019. Two authors reviewed the titles, abstracts, and full texts. We included articles that included a comparison group in the design, measured the time taken to carry out documentation or medication administration, documented the quantitative estimates of time differences between the 2, had nurses as subjects, and was conducted in either a care home, hospital, or community clinic. RESULTS: We identified a total of 1647 articles, of which 33 met our inclusion criteria. Twenty-one studies reported the impact of 12 different health information technology (HIT) implementations on nurses' documentation time. Weighted averages were calculated for studies that implemented barcode medication administration (BCMA) and 2 weighted averages for those that implemented EHRs, as these studies used different sampling units; both showed an increase in the time spent in documentation (+22% and +46%). However, the time spent carrying out medication administration following BCMA implementation fell by 33% (P < .05). HIT also caused a redistribution of nurses' time which, in some cases, was spent in more "value-adding" activities, such as delivering direct patient care as well as inter-professional communication. DISCUSSION AND CONCLUSIONS: Most of the HIT systems increased nursing documentation time, although time fell for medication administration following BCMA. Many HIT systems also resulted in nurses spending more time in direct care and "value-adding" activities.

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.

Improving medication-related clinical decision support.

PURPOSE: Current uses of medication-related clinical decision support (CDS) and recommendations for improving these systems are reviewed. SUMMARY: Using a systematic approach, articles published from 2007 through 2014 were identified in MEDLINE and EMBASE using MeSH terms and keywords relating to the 5 basic medication-related CDS functionalities. A total of 156 full-text articles and 28 conference abstracts were reviewed across each of the 5 areas: drug-drug interaction (DDI) checks (n = 78), drug allergy checks (n = 20), drug dose support (n = 55), drug duplication checks (n = 11), and drug formulary support (n = 20). The success of medication-related CDS depends on users finding the alerts valuable and acting on the information received. Improving alert specificity and sensitivity is important for all domains. Tiering is important for improving the acceptance of DDI alerts. The ability to perform appropriate cross-sensitivity checks is key to producing appropriate drug allergy checks. Drug dosage alerts should be individualized and deliver practical recommendations. How the system is configured to identify certain drug duplications is important to prevent possible patient toxicity. Accurate knowledge databases are needed to produce relevant drug formulary alerts and encourage formulary adherence. Medication-related CDS is still relatively immature in some organizations and has substantial room for improvement. For example, decision support should consider more patient-specific factors, human factors principles should always be considered, and alert specificity must be improved in order to reduce alert fatigue. CONCLUSION: Standardization, integration of patient-specific parameters, and consideration of human factors design principles are central to realizing the potential benefits of medication-related CDS.

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

Objective: To identify and understand the factors that contribute to medication errors associated with the use of computerized provider order entry (CPOE) in pediatrics and provide recommendations on how CPOE systems could be improved. Materials and Methods: We conducted a systematic literature review across 3 large databases: the Cumulative Index to Nursing and Allied Health Literature, Embase, and Medline. Three independent reviewers screened the titles, and 2 authors then independently reviewed all abstracts and full texts, with 1 author acting as a constant across all publications. Data were extracted onto a customized data extraction sheet, and a narrative synthesis of all eligible studies was undertaken. Results: A total of 47 articles were included in this review. We identified 5 factors that contributed to errors with the use of a CPOE system: (1) lack of drug dosing alerts, which failed to detect calculation errors; (2) generation of inappropriate dosing alerts, such as warnings based on incorrect drug indications; (3) inappropriate drug duplication alerts, as a result of the system failing to consider factors such as the route of administration; (4) dropdown menu selection errors; and (5) system design issues, such as a lack of suitable dosing options for a particular drug. Discussion and Conclusions: This review highlights 5 key factors that contributed to the occurrence of CPOE-related medication errors in pediatrics. Dosing support is the most important. More advanced clinical decision support that can suggest doses based on the drug indication is needed.