An investigation of healthcare professionals’ experiences of training and using electronic prescribing systems: four literature reviews and two qualitative studies undertaken in the UK hospital context

Electronic prescribing (ePrescribing) is the process of ordering medicines electronically for a patient and has been associated with reduced medication errors and improved patient safety. However, these systems have also been associated with unintended adverse consequences. There is a lack of published research about users’ experiences of these systems in UK hospitals. The aim of this research was therefore to firstly describe the literature pertaining to the recent developments and persisting issues with ePrescribing and clinical decision support systems (CDS) (chapter 2). Two further systematic literature reviews (chapters 3 and 4) were then conducted to understand the unintended consequences of ePrescribing and clinical decision support (CDS) systems across both adult and paediatric patients. These revealed a taxonomy of factors, which have contributed to errors during use of these systems e.g., the screen layout, default settings and inappropriate drug-dosage support. The researcher then conducted a qualitative study (chapters 7-10) to explore users’ experiences of using and being trained to use ePrescribing systems. This study involved conducting semi-structured interviews and observations, which revealed key challenges facing users, including issues with using the ‘Medication List’ and how information was presented. Users experienced benefits and challenges when customising the system, including the screen display; however, the process was sometimes overly complex. Users also described the benefits and challenges associated with different forms of interruptive and passive CDS. Order sets, for instance, encouraged more efficient prescribing, yet users often found them difficult to find within the system. A lack of training resulted in users failing to use all features of the ePrescribing system and left some healthcare staff feeling underprepared for using the system in their role. A further literature review (chapter 5) was then performed to complement emerging themes relating to how users were trained to use ePrescribing systems, which were generated as part of a qualitative study. This review revealed the range of approaches used to train users and the need for further research in this area. The literature review and qualitative study-based findings led to a follow-on study (chapter 10), whereby the researcher conducted semi-structured interviews to examine how users were trained to use ePrescribing systems across four NHS Hospital Trusts. A range of approaches were used to train users; tailored training, using clinically specific scenarios or matching the user’s profession to that of the trainer were preferred over lectures and e-learning may offer an efficient way of training large numbers of staff. However, further research is needed to investigate this and whether alternative approaches such as the use of students as trainers could be useful. This programme of work revealed the importance of human factors and user involvement in the design and ongoing development of ePrescribing systems. Training also played a role in users’ experiences of using the system and hospitals should carefully consider the training approaches used. This thesis provides recommendations gathered from the literature and primary data collection that can help inform organisations, system developers and further research in this area

Association between workarounds and medication administration errors in bar-code-assisted medication administration in hospitals

Objective: To study the association of workarounds with medication administration errors using barcode-assisted medication administration (BCMA), and to determine the frequency and types of workarounds and medication administration errors. Materials and Methods: A prospective observational study in Dutch hospitals using BCMA to administer medication. Direct observation was used to collect data. Primary outcome measure was the proportion of medication administrations with one or more medication administration errors. Secondary outcome was the frequency and types of workarounds and medication administration errors. Univariate and multivariate multilevel logistic regression analysis were used to assess the association between workarounds and medication administration errors. Descriptive statistics were used for the secondary outcomes. Results: We included 5793 medication administrations for 1230 inpatients. Workarounds were associated with medication administration errors (adjusted odds ratio 3.06 [95% CI: 2.49-3.78]). Most commonly, procedural workarounds were observed, such as not scanning at all (36%), not scanning patients because they did not wear a wristband (28%), incorrect medication scanning, multiple medication scanning, and ignoring alert signals (11%). Common types of medication administration errors were omissions (78%), administration of non-ordered drugs (8.0%), and wrong doses given (6.0%). Discussion: Workarounds are associated with medication administration errors in hospitals using BCMA. These data suggest that BCMA needs more post-implementation evaluation if it is to achieve the intended benefits for medication safety. Conclusion: In hospitals using barcode-assisted medication administration, workarounds occurred in 66% of medication administrations and were associated with large numbers of medication administration errors

Clinical rules in hospital pharmacy practice to prevent adverse drug events

Adverse drug events (ADEs) refer to any injury from the use of a drug. ADEs occur frequently in hospitalized patients and a substantial proportion are considered preventable. A method to prevent ADEs is computerized physician order entry (CPOE) combined with a clinical decision support system (CDSS). This thesis describes the development and validation of our CDSS with clinical rules, called Adverse Drug Event Alerting System (ADEAS). The development and validation of ADEAS was successful but time-consuming. Further, this thesis describes the investigations in which 1) the ability of ADEAS to identify patients at risk of ADEs are studied and 2) the ability in which these potential ADEs can be prevented by interventions by the hospital pharmacist are studied. The results of the clinical validity studies show that ADEAS is able to identify patients at risk of ADEs and that this method is a useful addition to the conventional medication surveillance. The clinical utility studies show that ADEAS can effectively be used in daily hospital pharmacy practice to identify patients at risk of potential ADEs and that ADEAS based interventions by the hospital pharmacist can reduce the number of preventable ADEs. For future use the rule effectiveness and positive predictive value of the clinical rules should be improved.UBL - phd migration 201

Reducing medication errors for adults in hospital settings

Adulto; Errores de medicación; FarmacéuticosAdult; Medication errors; PharmacistsAdult; Errors de medicació; FarmacèuticsBackground: Medication errors are preventable events that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the healthcare professional or patient. Medication errors in hospitalised adults may cause harm, additional costs, and even death. Objectives: To determine the effectiveness of interventions to reduce medication errors in adults in hospital settings

Mapping Turnaround Times (TAT) to a Generic Timeline: A Systematic Review of TAT Definitions in Clinical Domains

<p>Abstract</p> <p>Background</p> <p>Assessing turnaround times can help to analyse workflows in hospital information systems. This paper presents a systematic review of literature concerning different turnaround time definitions. Our objectives were to collect relevant literature with respect to this kind of process times in hospitals and their respective domains. We then analysed the existing definitions and summarised them in an appropriate format.</p> <p>Methods</p> <p>Our search strategy was based on Pubmed queries and manual reviews of the bibliographies of retrieved articles. Studies were included if precise definitions of turnaround times were available. A generic timeline was designed through a consensus process to provide an overview of these definitions.</p> <p>Results</p> <p>More than 1000 articles were analysed and resulted in 122 papers. Of those, 162 turnaround time definitions in different clinical domains were identified. Starting and end points vary between these domains. To illustrate those turnaround time definitions, a generic timeline was constructed using preferred terms derived from the identified definitions. The consensus process resulted in the following 15 terms: admission, order, biopsy/examination, receipt of specimen in laboratory, procedure completion, interpretation, dictation, transcription, verification, report available, delivery, physician views report, treatment, discharge and discharge letter sent. Based on this analysis, several standard terms for turnaround time definitions are proposed.</p> <p>Conclusion</p> <p>Using turnaround times to benchmark clinical workflows is still difficult, because even within the same clinical domain many different definitions exist. Mapping of turnaround time definitions to a generic timeline is feasible.</p

Reducing medication errors for adults in hospital settings

Background: Medication errors are preventable events that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the healthcare professional or patient. Medication errors in hospitalised adults may cause harm, additional costs, and even death. Objectives: To determine the effectiveness of interventions to reduce medication errors in adults in hospital settings. Search methods: We searched CENTRAL, MEDLINE, Embase, five other databases and two trials registers on 16 January 2020. Selection criteria: We included randomised controlled trials (RCTs) and interrupted time series (ITS) studies investigating interventions aimed at reducing medication errors in hospitalised adults, compared with usual care or other interventions. Outcome measures included adverse drug events (ADEs), potential ADEs, preventable ADEs, medication errors, mortality, morbidity, length of stay, quality of life and identified/solved discrepancies. We included any hospital setting, such as inpatient care units, outpatient care settings, and accident and emergency departments. Data collection and analysis: We followed the standard methodological procedures expected by Cochrane and the Effective Practice and Organisation of Care (EPOC) Group. Where necessary, we extracted and reanalysed ITS study data using piecewise linear regression, corrected for autocorrelation and seasonality, where possible. Main results: We included 65 studies: 51 RCTs and 14 ITS studies, involving 110,875 participants. About half of trials gave rise to 'some concerns' for risk of bias during the randomisation process and one-third lacked blinding of outcome assessment. Most ITS studies presented low risk of bias. Most studies came from high-income countries or high-resource settings. Medication reconciliation –the process of comparing a patient's medication orders to the medications that the patient has been taking– was the most common type of intervention studied. Electronic prescribing systems, barcoding for correct administering of medications, organisational changes, feedback on medication errors, education of professionals and improved medication dispensing systems were other interventions studied. Medication reconciliation. Low-certainty evidence suggests that medication reconciliation (MR) versus no-MR may reduce medication errors (odds ratio [OR] 0.55, 95% confidence interval (CI) 0.17 to 1.74; 3 studies; n=379). Compared to no-MR, MR probably reduces ADEs (OR 0.38, 95%CI 0.18 to 0.80; 3 studies, n=1336; moderate-certainty evidence), but has little to no effect on length of stay (mean difference (MD) -0.30 days, 95%CI -1.93 to 1.33 days; 3 studies, n=527) and quality of life (MD -1.51, 95%CI -10.04 to 7.02; 1 study, n=131). Low-certainty evidence suggests that, compared to MR by other professionals, MR by pharmacists may reduce medication errors (OR 0.21, 95%CI 0.09 to 0.48; 8 studies, n=2648) and may increase ADEs (OR 1.34, 95%CI 0.73 to 2.44; 3 studies, n=2873). Compared to MR by other professionals, MR by pharmacists may have little to no effect on length of stay (MD -0.25, 95%CI -1.05 to 0.56; 6 studies, 3983). Moderate-certainty evidence shows that this intervention probably has little to no effect on mortality during hospitalisation (risk ratio (RR) 0.99, 95%CI 0.57 to 1.7; 2 studies, n=1000), and on readmissions at one month (RR 0.93, 95%CI 0.76 to 1.14; 2 studies, n=997); and low-certainty evidence suggests that the intervention may have little to no effect on quality of life (MD 0.00, 95%CI -14.09 to 14.09; 1 study, n=724). Low-certainty evidence suggests that database-assisted MR conducted by pharmacists, versus unassisted MR conducted by pharmacists, may reduce potential ADEs (OR 0.26, 95%CI 0.10 to 0.64; 2 studies, n=3326), and may have no effect on length of stay (MD 1.00, 95%CI -0.17 to 2.17; 1 study, n=311). Low-certainty evidence suggests that MR performed by trained pharmacist technicians, versus pharmacists, may have little to no difference on length of stay (MD -0.30, 95%CI -2.12 to 1.52; 1 study, n=183). However, the CI is compatible with important beneficial and detrimental effects. Low-certainty evidence suggests that MR before admission may increase the identification of discrepancies compared with MR after admission (MD 1.27, 95%CI 0.46 to 2.08; 1 study, n=307). However, the CI is compatible with important beneficial and detrimental effects. Moderate-certainty evidence shows that multimodal interventions probably increase discrepancy resolutions compared to usual care (RR 2.14, 95%CI 1.81 to 2.53; 1 study, n=487). Computerised physician order entry (CPOE)/clinical decision support systems (CDSS). Moderate-certainty evidence shows that CPOE/CDSS probably reduce medication errors compared to paper-based systems (OR 0.74, 95%CI 0.31 to 1.79; 2 studies, n=88). Moderate-certainty evidence shows that, compared with standard CPOE/CDSS, improved CPOE/CDSS probably reduce medication errors (OR 0.85, 95%CI 0.74 to 0.97; 2 studies, n=630). Low-certainty evidence suggests that prioritised alerts provided by CPOE/CDSS may prevent ADEs compared to non-prioritised (inconsequential) alerts (MD 1.98, 95%CI 1.65 to 2.31; 1 study; participant numbers unavailable). Barcode identification of participants/medications. Low-certainty evidence suggests that barcoding may reduce medication errors (OR 0.69, 95%CI 0.59 to 0.79; 2 studies, n=50,545). Reduced working hours. Low-certainty evidence suggests that reduced working hours may reduce serious medication errors (RR 0.83, 95%CI 0.63 to 1.09; 1 study, n=634). However, the CI is compatible with important beneficial and detrimental effects. Feedback on prescribing errors. Low-certainty evidence suggests that feedback on prescribing errors may reduce medication errors (OR 0.47, 95%CI 0.33 to 0.67; 4 studies, n=384). Dispensing system. Low-certainty evidence suggests that dispensing systems in surgical wards may reduce medication errors (OR 0.61, 95%CI 0.47 to 0.79; 2 studies, n=1775). Authors' conclusions: Low- to moderate-certainty evidence suggests that, compared to usual care, medication reconciliation, CPOE/CDSS, barcoding, feedback and dispensing systems in surgical wards may reduce medication errors and ADEs. However, the results are imprecise for some outcomes related to medication reconciliation and CPOE/CDSS. The evidence for other interventions is very uncertain. Powered and methodologically sound studies are needed to address the identified evidence gaps. Innovative, synergistic strategies –including those that involve patients– should also be evaluated.Fil: Ciapponi, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Fernandez Nievas, Simon E. No especifíca;Fil: Seijo, Mariana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Inmunología, Genética y Metabolismo. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Inmunología, Genética y Metabolismo; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Rodriguez, Maria Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; ArgentinaFil: Vietto, Valeria. Instituto Universidad Escuela de Medicina del Hospital Italiano; ArgentinaFil: García Perdomo, Herney A.. Universidad del Valle; ColombiaFil: Virgilio, Sacha. No especifíca;Fil: Fajreldines, Ana V.. Universidad Austral; ArgentinaFil: Tost, Josep. No especifíca;Fil: Rose, Christopher J.. No especifíca;Fil: Garcia Elorrio, Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Centro de Investigaciones en Epidemiología y Salud Pública. Instituto de Efectividad Clínica y Sanitaria. Centro de Investigaciones en Epidemiología y Salud Pública; Argentin