A Systematic Review Of The Types And Causes Of Prescribing Errors Generated From Using Computerized Provider Order Entry Systems in Primary and Secondary Care

Objective To understand the different types and causes of prescribing errors associated with computerized provider order entry (CPOE) systems, and recommend improvements in these systems. Materials and Methods We conducted a systematic review of the literature published between January 2004 and June 2015 using three large databases: the Cumulative Index to Nursing and Allied Health Literature, Embase, and Medline. Studies that reported qualitative data about the types and causes of these errors were included. A narrative synthesis of all eligible studies was undertaken. Results A total of 1185 publications were identified, of which 34 were included in the review. We identified 8 key themes associated with CPOE-related prescribing errors: computer screen display, drop-down menus and auto-population, wording, default settings, nonintuitive or inflexible ordering, repeat prescriptions and automated processes, users’ work processes, and clinical decision support systems. Displaying an incomplete list of a patient’s medications on the computer screen often contributed to prescribing errors. Lack of system flexibility resulted in users employing error-prone workarounds, such as the addition of contradictory free-text comments. Users’ misinterpretations of how text was presented in CPOE systems were also linked with the occurrence of prescribing errors. Discussion and Conclusions Human factors design is important to reduce error rates. Drop-down menus should be designed with safeguards to decrease the likelihood of selection errors. Development of more sophisticated clinical decision support, which can perform checks on free-text, may also prevent errors. Further research is needed to ensure that systems minimize error likelihood and meet users’ workflow expectations

Improving Patient Safety and Hospital Service Quality Through Electronic Medical Record: A Systematic Review

ABSTRACT To understand the Electronic medical records (EMR) role in improving patient safety and hospital’s service quality. Articles that included and assessed for the eligibility in this review was an article that show an effect of patient’ safety, and product quality in hospital in correlation on using EMR. The most important function of EMR implementation is to improve patient safety in hospital, in addition to reducing cost. EMR reduce excess cost of Hospital Acquired Condition (HAC) by 16%, reduce death due to HAC by 34%. Doctor and nurse’s belief that the quality of patient data is better when EMR are easier to use and suit with their dialy routine. EMR can improve patient safety, but its use require some skills in technology so it won’t turn to harm patients’ safety. The implementation EMR requires the ability of skilled human resources in using technologies, computer and programs

Computerized Physician Order Entry (CPOE) in Reducing Medication Error: A Narrative Review

ABSTRACT Medication error leads to death and injury every day, causing lower quality of life and spend almost 1% of total global health expenditure. One of the solution of to prescribing error is using technology such as Computer Physician Order Entry (CPOE). This study purpose is to assess the use of CPOE in reducing medication error. The research method is a review of the narrative literature using systematic research, with 14 included studies. CPOE systems in hospitals were found to be capable of reducing medication errors especially in prescribing and administrative stage. However, CPOE system can be associated with new types of medication error, therefore, CPOE system must considered human factor, tailored according to the need of the hospital, and continuous training to reduce medication error

Impact of an inpatient electronic prescribing system on prescribing error causation: a qualitative evaluation in an English hospital

BACKGROUND: Few studies have applied a systems approach to understanding the causes of specific prescribing errors in the context of hospital electronic prescribing (EP). A comprehensive understanding of underlying causes is essential for developing effective interventions to improve prescribing safety. Our objectives were to explore prescribers' perspectives of the causes of errors occurring with EP and to make recommendations to maximise benefits and minimise risks. METHODS: We studied a large hospital using inpatient EP. From April to June 2016, semistructured interviews were conducted with purposively sampled prescribers involved with a prescribing error. Interviews explored prescribers' perceived causes of the error and views about EP; they were audio-recorded and transcribed verbatim. Data were thematically analysed against a framework based on Reason's accident causation model, with a focus on identifying latent conditions. RESULTS: Twenty-five interviews explored causes of 32 errors. Slips and rule-based mistakes were the most common active failures. Error causation was multifactorial; environmental, individual, team, task and technology error-producing conditions were all influenced by EP. There were three broad groups of latent conditions: the EP system's functionality and design; the organisation's decisions around EP implementation and use; and prescribing behaviours in the context of EP. CONCLUSIONS: Errors were associated with the design of EP itself and its integration within the healthcare environment. Findings suggest that EP vendors should focus on revolutionising interface design and usability issues, bearing in mind the wider healthcare context in which such software is used. Healthcare organisations should draw upon human factors principles when implementing EP. Consideration of work environment, infrastructure, training, prescribing responsibilities and behaviours should be considered to address local issues identified

What is the impact of introducing inpatient electronic prescribing on prescribing errors? A naturalistic stepped wedge study in an English teaching hospital

Most studies evaluating the impact of electronic prescribing on prescribing safety have used comparatively weak study designs such as uncontrolled before-and-after studies. This study aimed to apply a more robust naturalistic stepped wedge study design to compare the prevalence and types of prescribing errors for electronic prescribing and paper prescribing. Data were collected weekly during a phased electronic prescribing implementation across 20 wards in a large English hospital. We identified 511 (7.8%) erroneous orders in 6523 paper medication orders, and 312 (6.0%) in 5237 electronic prescribing orders. Logistic regression suggested no statistically significant effect of electronic prescribing use or of study week; patient and ward had significant effects. Errors involving incorrect doses and illegible or incomplete orders were less common with electronic prescribing; those involving duplication, omission, incorrect drug and incorrect formulation were more common. Actions are needed to mitigate these error types; future studies should give more consideration to the effects of patient and ward

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

Learning from electronic prescribing errors: a mixed methods study of junior doctors' perceptions of training and individualised feedback data

OBJECTIVES: To explore the views of junior doctors towards (1) electronic prescribing (EP) training and feedback, (2) readiness for receiving individualised feedback data about EP errors and (3) preferences for receiving and learning from EP feedback. DESIGN: Explanatory sequential mixed methods study comprising quantitative survey (phase 1), followed by interviews and focus group discussions (phase 2). SETTING: Three acute hospitals of a large English National Health Service organisation. PARTICIPANTS: 25 of 89 foundation year 1 and 2 doctors completed the phase 1 survey; 5 participated in semi-structured interviews and 7 in a focus group in phase 2. RESULTS: Foundation doctors in this mixed methods study reported that current feedback provision on EP errors was lacking or informal, and that existing EP training and resources were underused. They believed feedback about prescribing errors to be important and were keen to receive real-time, individualised EP feedback data. Feedback needed to be in manageable amounts, motivational and clearly signposting how to learn or improve. Participants wanted feedback and better training on the EP system to prevent repeating errors. In addition to individualised EP error data, they were positive about learning from general prescribing errors and aggregated EP data. However, there was a lack of consensus about how best to learn from statistical data. Potential limitations identified by participants included concern about how the data would be collected and whether it would be truly reflective of their performance. CONCLUSIONS: Junior doctors would value feedback on their prescribing, and are keen to learn from EP errors, develop their clinical prescribing skills and use the EP interface effectively. We identified preferences for EP technology to enable provision of real-time data in combination with feedback to support learning and potentially reduce prescribing errors