Does computerized provider order entry reduce prescribing errors for hospital inpatients? A systematic review

Risk Management and Patient Safety in the Artificial Intelligence Era: A Systematic Review

BACKGROUND

Healthcare systems represent complex organizations within which multiple factors (physical environment, human factor, technological devices, quality of care) interconnect to form a dense network whose imbalance is potentially able to compromise patient safety. In this scenario, the need for hospitals to expand reactive and proactive clinical risk management programs is easily understood, and artificial intelligence fits well in this context. This systematic review aims to investigate the state of the art regarding the impact of AI on clinical risk management processes. To simplify the analysis of the review outcomes and to motivate future standardized comparisons with any subsequent studies, the findings of the present review will be grouped according to the possibility of applying AI in the prevention of the different incident type groups as defined by the ICPS.

MATERIALS AND METHODS

On 3 November 2023, a systematic review of the literature according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines was carried out using the SCOPUS and Medline (via PubMed) databases. A total of 297 articles were identified. After the selection process, 36 articles were included in the present systematic review.

RESULTS AND DISCUSSION

The studies included in this review allowed for the identification of three main "incident type" domains: clinical process, healthcare-associated infection, and medication. Another relevant application of AI in clinical risk management concerns the topic of incident reporting.

CONCLUSIONS

This review highlighted that AI can be applied transversely in various clinical contexts to enhance patient safety and facilitate the identification of errors. It appears to be a promising tool to improve clinical risk management, although its use requires human supervision and cannot completely replace human skills. To facilitate the analysis of the present review outcome and to enable comparison with future systematic reviews, it was deemed useful to refer to a pre-existing taxonomy for the identification of adverse events. However, the results of the present study highlighted the usefulness of AI not only for risk prevention in clinical practice, but also in improving the use of an essential risk identification tool, which is incident reporting. For this reason, the taxonomy of the areas of application of AI to clinical risk processes should include an additional class relating to risk identification and analysis tools. For this purpose, it was considered convenient to use ICPS classification.

Clinician Response to Pharmacogenetic Clinical Decision Support Alerts

The objective of this study was to characterize clinician response following standardization of pharmacogenetic (PGx) clinical decision support alerts at University of Florida (UF) Health. A retrospective analysis of all PGx alerts that fired at a tertiary academic medical center from August 2020 through May 2022 was performed. Alert acceptance rate was calculated and compared across six gene-drug pairs, patient care setting, and clinician specialty. The disposition of the triggering medication was compared with the alert response and evaluated for congruence. There were a total of 818 alerts included for analysis of alert response, 557 alerts included in acceptance rate calculations, and 392 alerts with sufficient information to assess clinical response. The overall acceptance rate was 63%. The alert response and clinical response were congruent for 47% of alerts. Alert response was influenced by the triggering gene-drug pair, clinician specialty, patient care setting, and specialty of the provider who initially ordered the PGx test. Clinical response was mostly incongruent with alert response. Alert acceptance is influenced by the triggering gene-drug pair, clinician specialty, and care setting. Alert response is not a reliable surrogate marker for clinical action. Any future research into the impact of clinical decision support (CDS) alerts should focus on clinical response rather than alert response. Given the reliance on CDS alerts to enhance uptake of PGx, it is worthwhile to further investigate their impact on prescribing and patient outcomes.

The association of a critical care electronic prescribing system with the quality of patient care provided by clinical pharmacists - a prospective, observational cohort study

BACKGROUND

Despite the strong face validity of electronic prescribing (EP), the empiric data in support of improved patient safety is sparse. The objective of this study was to compare the clinical significance of pharmacist contributions between an established EP and paper-based prescribing (PBP) system in the intensive care unit (ICU) to understand the EP impact on the quality of patient care.

MATERIALS AND METHODS

We conducted a prospective longitudinal study in two 18-bed ICUs; one with EP and the other, PBP. Pharmacist contributions were analysed over three months. Demographic, clinical and adjunctive intervention data were also collected. A multilevel ordinal logistic regression model was used and patients were followed up for 28 days. The primary outcome was the distribution of clinical significance levels of pharmacist contributions.

RESULTS

There were 303 patients admitted to the ICU between April 1st and June 30th 2018. EP was used in 171 patients and PBP in 132 patients. 1658 contributions were analysed. There were 14.9% highly clinically significant contributions with EP compared to 44.6% with PBP. The EP group had lower odds (OR 0.05, 95% CI 0.02-0.12) for a higher clinical significance contribution compared to the PBP group, but this changed over the admission and differed between groups, with decreasing odds of a higher-level clinical contribution for each additional admission day with PBP (OR 0.57, 95%CI 0.42-0.78).

CONCLUSION

This study showed a significant difference in the distribution of pharmacist contributions made over time, with clinical significance levels remaining stable in the EP group at low severity, as opposed to PBP which were initially high and then gradually decreased in severity over time. This contemporaneous controlled study found that the EP system required less significant input both in the severity and frequency of pharmacist contributions to maintain patient safety.

Developing a minimum data set for cardiovascular Computerized Physician Order Entry (CPOE) and mapping the data set to FHIR: A multi-method approach

Many medical errors occur in the process of treating cardiovascular patients, and most of these errors are related to prescription errors. There are several, one of the methods to prevent prescription errors is the use of a computerized physician order entry (CPOE) system. One of the obstacles of implementing this system is improper design and non-compliance with user needs. one of the issues that should be considered in designing information systems is having a standard minimum data set (MDS). Although many computerized physicians order entry (CPOE) systems have been developed in the world, no study has identified the necessary data and minimum data set (MDS) of CPOE system, and published the process of creating this MDS. This study aimed to develop an MDS for cardiovascular CPOE and standardize it with Fast Healthcare Interoperability Resources (FHIR). A multi-method approach including systematic review for identifying data elements of CPOE, reviewing the content of medical records, validation of the data elements using the expert panel and, determination of the necessary data elements using a survey was conducted. Classification of the data elements and mapping them to FHIR were done to facilitate data sharing and integration with the electronic health record (EHR) system as well as to reduce data diversity. The final data elements of MDS were categorized into 5 main categories of FHIR (foundation, base, clinical, financial, and specialized) and 146 resources, where possible. Mapping was done by one of the researchers and checked and verified by the second researcher. Non-mapped data elements were added to relevant resources as extensions of existing FHIR resources. In total, 270 data elements were identified from the systematic review. After reviewing the content of 20 patients' medical records, 28 data elements were identified. After combination of data elements of two previous phases and removing duplication, 282 data elements remained. Data elements that were considered necessary to be included in CPOE by conducting a survey among cardiovascular physicians were 109 elements. From 146 resources of FHIR, the data elements of this MDS are covered by 5 resources. This study introduced an MDS for cardiovascular CPOE by combining suggested data elements of previous research, and the practical and local requirements identified in patients' medical records. To facilitate data sharing and integration with EHR, reduce data diversity, and also to categorize data, this MDS was standardized with FHIR. The steps we used to develop this MDS could be a model for creating MDS in other CPOEs and health information systems. This is the first time that the process of developing an MDS for cardiovascular CPOE has been presented in the literature.

Benefits of electronic charts in intensive care and during a world health pandemic: advantages of the technology age

AIMS AND OBJECTIVES

This study sets out to describe benefits from the implementation of electronic observation charting in intensive care units (ICU). This was an extension to the existing hospital wide digital health system. We evaluated error reduction, time-savings and the costs associated with conversion from paper to digital records. The world health emergency of COVID-19 placed extraordinary strain on ICU and staff opinion was evaluated to test how well the electronic system performed.

METHODS

A clinically led project group working directly with programmers developed an electronic patient record for intensive care. Data error rates, time to add data and to make calculations were studied before and after the introduction of electronic charts. User feedback was sought pre and post go-live (during the COVID-19 pandemic) and financial implications were calculated by the hospital finance teams.

RESULTS

Error rates equating to 219 000/year were avoided by conversion to electronic charts. Time saved was the equivalent of a nursing shift each day. Recurrent cost savings per year were estimated to be £257k. Staff were overwhelmingly positive about electronic charts in ICU, even during a health pandemic and despite redeployment into intensive care where they were using the electronic charts for the first time.

DISCUSSION

Electronic ICU charts have been successfully introduced into our institution with benefits in terms of patient safety through error reduction and improved care through release of nursing time. Costs have been reduced. Staff feel supported by the digital system and report it to be helpful even during redeployment and in the unfamiliar environment of intensive care.

A Cell-Phone Medication Error eHealth App for Managing Safety in Chronically Ill Young Patients at Home: A Prospective Study

Introduction: Whereas ample information describes medication errors (MEs) in children or in mixed pediatric and adult populations discharged with acute or chronic diseases from hospital to community settings, little is known about MEs in children and adolescents with chronic diseases discharged home, a major concern. To promote home medication safety, we trained parents of children discharged with chronic diseases to record ME with a tailored cell-phone eHealth app. Methods: In a 1-year prospective study, we used the app to monitor ME in patients with chronic diseases discharged home from a tertiary hospital in Rome, Italy. Univariate and multivariate analyses detected the ME incidence rate ratio (IRR). Results: Of the 310 parents enrolled, 194 used the app. The 41 MEs involved all drug management phases. The ME IRR was 0.46 errors per child. Children <1 year had the highest ME risk (1.69 vs. 0.35, p = 0.002). Children discharged from the cardiology unit had a statistically higher ME IRR than others (3.66, 95% confidence interval: 1.01-13.23%). Conclusions: The highest ME risk at home involves children with chronic diseases <1 year old. A significant ME IRR at home concerns children with heart diseases of any age. Parents find a tailored eHealth app for monitoring and reporting ME at home easy to use. At discharge, clinical teams need to identify age-related and disease-residual risks to target additional actions for monitoring ME, thus increasing medication safety at home.

Medication Errors in Intensive Care Units: An Umbrella Review of Control Measures

Medication errors are defined as “any preventable event that may cause or lead to inappropriate medication use or patient harm while the medication is in the control of the health care professional, patient, or consumer.” Such errors account for 30 to 50 percent of all errors in health care. The literature is replete with systematic reviews of medication errors, with a considerable number of studies focusing on systems and strategies to prevent errors in intensive care units, where these errors occur more frequently; however, to date, there appears to be no study that encapsulates and analyzes the various strategies. The aim of this study is to identify the main strategies and interventions for preventing medication errors in intensive care units through an umbrella review. The search was conducted on the following databases: PubMed, CINAHL, PsycInfo, Embase, and Scopus; it was completed in November 2020. Seven systematic reviews were included in this review, with a total of 47 studies selected. All reviews aimed to evaluate the effectiveness of a single intervention or a combination of interventions and strategies to prevent and reduce medication errors. Analysis of the results that emerged identified two macro-areas for the prevention of medication errors: systems and processes. In addition, the findings highlight the importance of adopting an integrated system of interventions in order to protect the system from harm and contain the negative consequences of errors.

Impact of Computerized Provider Order Entry on Chemotherapy Medication Errors: A Systematic Review

Context: Chemotherapy errors are considered the second most common cause of fatal medication errors (ME). Currently, computerized provider order entry (CPOE) is increasingly used to prevent or decrease ME and improve the safety of the medication process. Objectives: This study was conducted to systematically review the impacts of CPOE on the incidence of chemotherapy ME, the severity of errors, and adverse drug events (ADEs) in cancer care units. Data Sources: The literature search was conducted, using 5 databases of PubMed, EMBASE, Scopus, Web of Science, and ScienceDirect between 2000 and 2020. Search terms included keywords and MESH terms related to CPOE, ME, chemotherapy, and cancer care unit. Study Selection: Articles were included in this research if they investigated the CPOE system, reported ME, and were carried out in the oncology department. Non-English papers, duplications, review studies, and conference papers were excluded. Data Extraction: The selected papers were read repeatedly and related papers were extracted. All eligible articles were qualitatively evaluated with a tool provided by Downs. The extracted information included the author’s name, year of publication, study location, type of study, study objectives, and main findings. Results: A total of 829 studies were retrieved. Fourteen articles met the inclusion criteria. Ten studies (71%) reported the impact of CPOE on chemotherapy ME in comparison with the paper-based ordering method. In 4 studies (29%), researchers developed a CPOE for the oncology department, and the system was, then, assessed concerning user experience, safety challenges as well as the effects of CPOE on ME. Nine articles (64%) reported the impact of the CPOE system on ME only in the prescribing phase, and 5 studies (36%) examined ME in all phases of the chemotherapy process. Five studies (36%) reported the impact of the CPOE system on ADEs and the severity of errors. Conclusions: Implementing CPOE is associated with a significant reduction in ME in all phases of the chemotherapy process. However, the CPOE does not prevent all MEs and may cause new errors. The rigorous analysis of the chemotherapy process and considering the designing principles could help develop the CPOE systems and minimize ME.

Analysis of end-user satisfaction with electronic health records in college/university healthcare

ObjectiveTo determine levels of Electronic Health Record (EHR) satisfaction in order to add to the body of knowledge and assist professionals in the college/university health field with system/vendor selection. Methods: Nine health centers, all within highly selective colleges and universities, participated in this benchmarking study. Multidisciplinary staff (n = 316) received an anonymous 32-item survey to assess levels of agreement/satisfaction on statements pertaining to their EHR's functionality. Results: The EHRs most commonly used were Point and Click, Medicat, Allscripts, and EPIC. There was considerable variation on levels of user satisfaction/agreement within features among the EHR systems, but differences were not statistically significant. Conclusion: No systems emerged as clear "winners" in terms of user satisfaction. Features were identified within systems that can be leveraged to meet specific care delivery and quality reporting needs among college/university health professionals, and could be considered in the use of EHRs by health services.

Predicting self-intercepted medication ordering errors using machine learning

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

Wrong-Patient Orders in Obstetrics

OBJECTIVE

To compare rates of wrong-patient orders among patients on obstetric units compared with reproductive-aged women admitted to medical-surgical units.

METHODS

This was an observational study conducted in a large health system in New York between January 1, 2016, and December 31, 2018. The primary outcome was near-miss wrong-patient orders identified using the National Quality Forum-endorsed Wrong-Patient Retract-and-Reorder measure. All electronic orders placed for eligible patients during the study period were extracted retrospectively from the health system data warehouse, and the unit of analysis was the order session (consecutive orders placed by a single clinician for a patient within 60 minutes). Multilevel logistic regression models were used to estimate odds ratios (ORs) and 95% CIs comparing the probability of retract-and-reorder events in obstetric and medical-surgical units, overall, and in subgroups defined by clinician type and order timing.

RESULTS

Overall, 1,329,463 order sessions were placed during the study period, including 676,643 obstetric order sessions (from 45,436 patients) and 652,820 medical-surgical order sessions (from 12,915 patients). The rate of 79.5 retract-and-reorder events per 100,000 order sessions in obstetric units was significantly higher than the rate in the general medical-surgical population of 42.3 per 100,000 order sessions (OR 1.98, 95% CI 1.64-2.39). The obstetric retract-and-reorder event rate was significantly higher for attending physicians and house staff compared with advanced practice clinicians. There were no significant differences in error rates between day and night shifts.

CONCLUSION

Order errors occurred more frequently on obstetric units compared with medical-surgical units. Systems strategies shown to decrease these events in other high-risk specialties should be explored in obstetrics to render safer maternity care.

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.

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

OBJECTIVE

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

MATERIALS AND METHODS

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

RESULTS

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

DISCUSSION AND CONCLUSION

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

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.

Clinical decision support systems-based interventions to improve medication outcomes: A systematic literature review on features and effects

Background: Clinical decision support systems (CDSSs) interventions were used to improve the life quality and safety in patients and also to improve practitioner performance, especially in the field of medication. Therefore, the aim of the paper was to summarize the available evidence on the impact, outcomes and significant factors on the implementation of CDSS in the field of medicine. Methods: This study is a systematic literature review. PubMed, Cochrane Library, Web of Science, Scopus, EMBASE, and ProQuest were investigated by 15 February 2017. The inclusion requirements were met by 98 papers, from which 13 had described important factors in the implementation of CDSS, and 86 were medicated-related. We categorized the system in terms of its correlation with medication in which a system was implemented, and our intended results were examined. In this study, the process outcomes (such as; prescription, drug-drug interaction, drug adherence, etc.), patient outcomes, and significant factors affecting the implementation of CDSS were reviewed. Results: We found evidence that the use of medication-related CDSS improves clinical outcomes. Also, significant results were obtained regarding the reduction of prescription errors, and the improvement in quality and safety of medication prescribed. Conclusion: The results of this study show that, although computer systems such as CDSS may cause errors, in most cases, it has helped to improve prescribing, reduce side effects and drug interactions, and improve patient safety. Although these systems have improved the performance of practitioners and processes, there has not been much research on the impact of these systems on patient outcomes.

The impact of health information technology on prescribing errors in hospitals: a systematic review and behaviour change technique analysis

BACKGROUND

Health information technology (HIT) is known to reduce prescribing errors but may also cause new types of technology-generated errors (TGE) related to data entry, duplicate prescribing, and prescriber alert fatigue. It is unclear which component behaviour change techniques (BCTs) contribute to the effectiveness of prescribing HIT implementations and optimisation. This study aimed to (i) quantitatively assess the HIT that reduces prescribing errors in hospitals and (ii) identify the BCTs associated with effective interventions.

METHODS

Articles were identified using CINAHL, EMBASE, MEDLINE, and Web of Science to May 2020. Eligible studies compared prescribing HIT with paper-order entry and examined prescribing error rates. Studies were excluded if prescribing error rates could not be extracted, if HIT use was non-compulsory or designed for one class of medication. The Newcastle-Ottawa scale was used to assess study quality. The review was reported in accordance with the PRISMA and SWiM guidelines. Odds ratios (OR) with 95% confidence intervals (CI) were calculated across the studies. Descriptive statistics were used to summarise effect estimates. Two researchers examined studies for BCTs using a validated taxonomy. Effectiveness ratios (ER) were used to determine the potential impact of individual BCTs.

RESULTS

Thirty-five studies of variable risk of bias and limited intervention reporting were included. TGE were identified in 31 studies. Compared with paper-order entry, prescribing HIT of varying sophistication was associated with decreased rates of prescribing errors (median OR 0.24, IQR 0.03-0.57). Ten BCTs were present in at least two successful interventions and may be effective components of prescribing HIT implementation and optimisation including prescriber involvement in system design, clinical colleagues as trainers, modification of HIT in response to feedback, direct observation of prescriber workflow, monitoring of electronic orders to detect errors, and system alerts that prompt the prescriber.

CONCLUSIONS

Prescribing HIT is associated with a reduction in prescribing errors in a variety of hospital settings. Poor reporting of intervention delivery and content limited the BCT analysis. More detailed reporting may have identified additional effective intervention components. Effective BCTs may be considered in the design and development of prescribing HIT and in the reporting and evaluation of future studies in this area.

Improving Patients' Medication Adherence and Outcomes in Nonhospital Settings Through eHealth: Systematic Review of Randomized Controlled Trials

Background

Electronic health (eHealth) refers to the use of information and communication technologies for health. It plays an increasingly important role in patients’ medication management.

Objective

To assess evidence on (1) whether eHealth for patients’ medication management can improve drug adherence and health outcomes in nonhospital settings and (2) which eHealth functions are commonly used and are effective in improving drug adherence.

Methods

We searched for randomized controlled trials (RCTs) on PubMed, MEDLINE, CINAHL, EMBASE, EmCare, ProQuest, Scopus, Web of Science, ScienceDirect, and IEEE Xplore, in addition to other published sources between 2000 and 2018. We evaluated the studies against the primary outcome measure of medication adherence and multiple secondary health care outcome measures relating to adverse events, quality of life, patient satisfaction, and health expenditure. The quality of the studies included was assessed using the Cochrane Collaboration’s Risk of Bias (RoB) tool.

Results

Our initial search yielded 9909 records, and 24 studies met the selection criteria. Of these, 13 indicated improvement in medication adherence at the significance level of P<.1 and 2 indicated an improved quality of life at the significance level of P<.01. The top 3 functions that were employed included mechanisms to communicate with caregivers, monitoring health features, and reminders and alerts. eHealth functions of providing information and education, and dispensing treatment and administration support tended to favor improved medication adherence outcomes (Fisher exact test, P=.02). There were differences in the characteristics of the study population, intervention design, functionality provided, reporting adherence, and outcome measures among the included studies. RoB assessment items, including blinding of outcome assessment and method for allocation concealment, were not explicitly reported in a large number of studies.

Conclusions

All the studies included were designed for patient home-based care application and provided a mechanism to communicate with caregivers. A targeted study population such as older patients should be considered to maximize the public health impact on the self-management of diseases.

Trial Registration

International Prospective Register of Systematic Reviews (PROSPERO) CRD42018096627; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=96627

Investigating prescribing errors in the emergency department of a large governmental hospital in Jordan

Background

Although prescribing errors (PEs) are the most common type of medication errors and cause morbidity and mortality, they have been rarely studied.

Objective

The study aimed to investigate PEs incidence, types, severity, causes, predictors, pharmacists' interventions accepted by doctors and computer-related errors.

Setting

This study was conducted in the emergency department of the largest governmental hospital in Jordan.

Method

This was a retrospective observational 4-week study. A validated definition of PEs was adopted, and errors were identified by direct observation of all prescriptions. Structured interviews with doctors to assess the causes of errors were conducted within three days of the prescription date; the severity of PEs was rated by a committee.

Main outcome measure

Prescribing errors incidence, types, severity, causes, predictors, pharmacists' interventions accepted by doctors and computer-related errors.

Results

For 1330 patients, 3470 medication orders were recorded. Almost one in five patients had PEs (n = 288, 21.65%), and the total number of medication orders for patients who had errors was 610. The PEs incidence was 12.5% (95% CI 11.4%–3.5% (n = 450/3597)). Analgesics were the most common medications associated with PEs (232/610, 38.03%). The top two types of PEs detected were wrong drug (165/450, 36.6%) and wrong dose (142/450, 31.5%) respectively. Most PEs were clinically significant errors (342/450, 76%). Doctors refused pharmacists' interventions on their orders in 132 (45.8%) prescriptions. The most common cause of errors was poor skills of doctors in electronic prescribing system (266/450, 59%). Predictors of PEs were the following: drug with multiple dosage forms (OR 2.998; 95% CI 1.41–6.34; P = 0.004) and a prescription with polypharmacy (OR 1.685; 95% CI 1.25%–2.26%; P = 0.001).

Conclusion

A national approach for observing, intervening on and correcting PEs is necessary to improve patient safety.

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.

Interventions to ensure medication safety in acute care: an umbrella review

BACKGROUND

Medication errors are one of the leading avoidable sources of harm to hospital patients. In hospitals, a range of interventions have been used to reduce the risk of errors at each of the points they may occur, such as prescription, dispensing and/or administration. Systematic reviews have been conducted on many of these interventions; however, it is difficult to compare the clinical utility of any of the separate interventions without the use of a rigorous umbrella review methodology.

OBJECTIVES

The aim of this umbrella review was to synthesize the evidence from all systematic reviews investigating the effectiveness of medication safety interventions, in comparison to any or no comparator, for preventing medication errors, medication-related harms and death in acute care patients.

METHOD

The review considered quantitative systematic reviews with participants who were healthcare workers involved in prescribing, dispensing or administering medications. These healthcare workers were registered nurses, enrolled or licensed vocational nurses, midwives, pharmacists or medical doctors. Interventions of interest were those designed to prevent medication error in acute care settings. Eligible systematic reviews reported medication errors, medication-related harms and medication-related death as measured by error rates, numbers of adverse events and numbers of medication-related deaths. To qualify for inclusion, systematic reviews needed to provide a clearly articulated and comprehensive search strategy, and evidence of critical appraisal of the included studies using a standardized tool. Systematic reviews published in English since 2007 were included until present (March 2020). We searched a range of databases such MEDLINE, CINAHL, Web of Science, EMBASE, and The Cochrane Library for potentially eligible reviews. Identified citations were screened by two reviewers working independently. Potentially eligible articles were retrieved and assessed against the inclusion criteria and those meeting the criteria were then critically appraised using the JBI SUMARI instrument for assessing the methodological quality of systematic reviews and research syntheses. A predetermined quality threshold was used to exclude studies based on their reported methods. Following critical appraisal, data were extracted from the included studies by two independent reviewers using the relevant instrument in JBI SUMARI. Extracted findings were synthesized narratively and presented in tables to illustrate the reported outcomes for each intervention. The strength of the evidence for each intervention was indicated using 'traffic light' colors: green for effective interventions, amber for interventions with no evidence of an effect and red for interventions less effective than the comparison.

RESULTS

A total of 23 systematic reviews were included in this umbrella review. Most reviews did not report the number of participants in their included studies. Interventions targeted pharmacists, medical doctors, medical students and nurses, or were nonspecific about the participants. The majority of included reviews examined single interventions. All reviews were published and in English. Four interventions, medication administration education, medication reconciliation or review, specialist pharmacists' roles and physical or design modifications, reported effectiveness in reducing errors; however, heterogeneity between the included studies in these reviews was high.

CONCLUSION

For some interventions, there are strong indications of effectiveness in reducing medication errors in the inpatient setting. Government initiatives, policy makers and practitioners interested in improving medication safety are encouraged to adopt those interventions.

Effects of CPOE-based medication ordering on outcomes: an overview of systematic reviews

BACKGROUND

Computerised provider order entry (CPOE) systems are widely used in clinical settings for the electronic ordering of medications, laboratory tests and radiological therapies. However, evidence regarding effects of CPOE-based medication ordering on clinical and safety outcomes is mixed. We conducted an overview of systematic reviews (SRs) to characterise the cumulative effects of CPOE use for medication ordering in clinical settings.

METHODS

MEDLINE, EMBASE, CINAHL and the Cochrane Library were searched to identify published SRs from inception to 12 February 2018. SRs investigating the effects of the use of CPOE for medication ordering were included. Two reviewers independently extracted data and assessed the methodological quality of included SRs.

RESULTS

Seven SRs covering 118 primary studies were included for review. Pooled studies from the SRs in inpatient settings showed that CPOE use resulted in statistically significant decreases in medication errors and adverse drug events (ADEs); however, there was considerable variation in the magnitude of their relative risk reduction (54%-92% for errors, 35%-53% for ADEs). There was no significant relative risk reduction on hospital mortality or length of stay. Bibliographic analysis showed limited overlap (24%) among studies included across all SRs.

CONCLUSION

SRs on CPOEs included predominantly non-randomised controlled trials and observational studies with varying foci. SRs predominantly focused on inpatient settings and often lacked comparison groups; SRs used inconsistent definitions of outcomes, lacked descriptions regarding the effects on patient harm and did not differentiate among the levels of available decision support. With five of the seven SRs having low to moderate quality, findings from the SRs must be interpreted with caution. We discuss potential directions for future primary studies and SRs of CPOE.

Evaluating users' experiences of electronic prescribing systems in relation to patient safety: a mixed methods study

BACKGROUND

User interface (UI) design features such as screen layout, density of information, and use of colour may affect the usability of electronic prescribing (EP) systems, with usability problems previously associated with medication errors. To identify how to improve existing systems, our aim was to explore prescribers' perspectives of UI features of a commercially available EP system, and how these may affect patient safety.

METHODS

Two studies were conducted, each including ten participants prescribing a penicillin for a test patient with a penicillin allergy. In study 1, eye-gaze tracking was used as a means to explore visual attention and behaviour during prescribing, followed by a self-reported EP system usability scale. In study 2, a think-aloud method and semi-structured interview were applied to explore participants' thoughts and views on prescribing, with a focus on UI design and patient safety.

RESULTS

Study 1 showed high visual attention toward information on allergies and patient information, allergy pop-up alerts, and medication order review and confirmation, with less visual attention on adding medication. The system's usability was rated 'below average'. In study 2, participants highlighted EP design features and workflow, including screen layout and information overload as being important for patient safety, benefits of EP systems such as keeping a record of relevant information, and suggestions for improvement in relation to system design (colour, fonts, customization) and patient interaction.

CONCLUSIONS

Specific UI design factors were identified that may improve the usability and/or safety of EP systems. It is suggested that eye-gaze tracking and think-aloud methods are used in future experimental research in this area. Limitations include the small sample size; further work should include similar studies on other EP systems.

Optimising electronic prescribing in hospitals: a scoping review protocol

INTRODUCTION

Electronic prescribing (ePrescribing) systems can improve the quality of prescribing decisions and substantially reduce the risk of serious medication errors in hospitals. However, realising these benefits depends on ensuring that relevant sociotechnical considerations are addressed. Optimising ePrescribing systems is essential to maximise the associated benefits and minimise the accompanying risks of these large-scale and expensive health informatics infrastructures.

METHODS

We will undertake a systematic scoping review of the literature to identify strategies to achieve optimisation of ePrescribing systems. We will search Medline, Embase and CINAHL for the period 1 January 2010 to 1 June 2019 and the grey literature by using Google Scholar. Independent reviewers will screen the results using predefined inclusion and exclusion criteria and will extract data for narrative and thematic synthesis.

DISCUSSION

This work will be published in a peer-reviewed journal and we will ensure that the findings are both accessible and interpretable to the public, academics, policymakers and National Health Service leaders.

Manually-generated reminders delivered on paper: effects on professional practice and patient outcomes

BACKGROUND

Health professionals sometimes do not use the best evidence to treat their patients, in part due to unconscious acts of omission and information overload. Reminders help clinicians overcome these problems by prompting them to recall information that they already know, or by presenting information in a different and more accessible format. Manually-generated reminders delivered on paper are defined as information given to the health professional with each patient or encounter, provided on paper, in which no computer is involved in the production or delivery of the reminder. Manually-generated reminders delivered on paper are relatively cheap interventions, and are especially relevant in settings where electronic clinical records are not widely available and affordable. This review is one of three Cochrane Reviews focused on the effectiveness of reminders in health care.

OBJECTIVES

1. To determine the effectiveness of manually-generated reminders delivered on paper in changing professional practice and improving patient outcomes. 2. To explore whether a number of potential effect modifiers influence the effectiveness of manually-generated reminders delivered on paper.

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, CINAHL and two trials registers on 5 December 2018. We searched grey literature, screened individual journals, conference proceedings and relevant systematic reviews, and reviewed reference lists and cited references of included studies.

SELECTION CRITERIA

We included randomised and non-randomised trials assessing the impact of manually-generated reminders delivered on paper as a single intervention (compared with usual care) or added to one or more co-interventions as a multicomponent intervention (compared with the co-intervention(s) without the reminder component) on professional practice or patients' outcomes. We also included randomised and non-randomised trials comparing manually-generated reminders with other quality improvement (QI) interventions.

DATA COLLECTION AND ANALYSIS

Two review authors screened studies for eligibility and abstracted data independently. We extracted the primary outcome as defined by the authors or calculated the median effect size across all reported outcomes in each study. We then calculated the median percentage improvement and interquartile range across the included studies that reported improvement related outcomes, and assessed the certainty of the evidence using the GRADE approach.

MAIN RESULTS

We identified 63 studies (41 cluster-randomised trials, 18 individual randomised trials, and four non-randomised trials) that met all inclusion criteria. Fifty-seven studies reported usable data (64 comparisons). The studies were mainly located in North America (42 studies) and the UK (eight studies). Fifty-four studies took place in outpatient/ambulatory settings. The clinical areas most commonly targeted were cardiovascular disease management (11 studies), cancer screening (10 studies) and preventive care (10 studies), and most studies had physicians as their target population (57 studies). General management of a clinical condition (17 studies), test-ordering (14 studies) and prescription (10 studies) were the behaviours more commonly targeted by the intervention. Forty-eight studies reported changes in professional practice measured as dichotomous process adherence outcomes (e.g. compliance with guidelines recommendations), 16 reported those changes measured as continuous process-of-care outcomes (e.g. number of days with catheters), eight reported dichotomous patient outcomes (e.g. mortality rates) and five reported continuous patient outcomes (e.g. mean systolic blood pressure). Manually-generated reminders delivered on paper probably improve professional practice measured as dichotomous process adherence outcomes) compared with usual care (median improvement 8.45% (IQR 2.54% to 20.58%); 39 comparisons, 40,346 participants; moderate certainty of evidence) and may make little or no difference to continuous process-of-care outcomes (8 comparisons, 3263 participants; low certainty of evidence). Adding manually-generated paper reminders to one or more QI co-interventions may slightly improve professional practice measured as dichotomous process adherence outcomes (median improvement 4.24% (IQR -1.09% to 5.50%); 12 comparisons, 25,359 participants; low certainty of evidence) and probably slightly improve professional practice measured as continuous outcomes (median improvement 0.28 (IQR 0.04 to 0.51); 2 comparisons, 12,372 participants; moderate certainty of evidence). Compared with other QI interventions, manually-generated reminders may slightly decrease professional practice measured as process adherence outcomes (median decrease 7.9% (IQR -0.7% to 11%); 14 comparisons, 21,274 participants; low certainty of evidence). We are uncertain whether manually-generated reminders delivered on paper, compared with usual care or with other QI intervention, lead to better or worse patient outcomes (dichotomous or continuous), as the certainty of the evidence is very low (10 studies, 13 comparisons). Reminders added to other QI interventions may make little or no difference to patient outcomes (dichotomous or continuous) compared with the QI alone (2 studies, 2 comparisons). Regarding resource use, studies reported additional costs per additional point of effectiveness gained, but because of the different currencies and years used the relevance of those figures is uncertain. None of the included studies reported outcomes related to harms or adverse effects.

AUTHORS' CONCLUSIONS

Manually-generated reminders delivered on paper as a single intervention probably lead to small to moderate increases in outcomes related to adherence to clinical recommendations, and they could be used as a single QI intervention. It is uncertain whether reminders should be added to other QI intervention already in place in the health system, although the effects may be positive. If other QI interventions, such as patient or computerised reminders, are available, they should be preferred over manually-generated reminders, but under close evaluation in order to decrease uncertainty about their potential effect.

Effect of Electronic Prescribing Strategies on Medication Error and Harm in Hospital: a Systematic Review and Meta-analysis

BACKGROUND

Computerized physician order entry and clinical decision support systems are electronic prescribing strategies that are increasingly used to improve patient safety. Previous reviews show limited effect on patient outcomes. Our objective was to assess the impact of electronic prescribing strategies on medication errors and patient harm in hospitalized patients.

METHODS

MEDLINE, EMBASE, CENTRAL, and CINAHL were searched from January 2007 to January 2018. We included prospective studies that compared hospital-based electronic prescribing strategies with control, and reported on medication error or patient harm. Data were abstracted by two reviewers and pooled using random effects model. Study quality was assessed using the Effective Practice and Organisation of Care and evidence quality was assessed using Grading of Recommendations Assessment, Development, and Evaluation.

RESULTS

Thirty-eight studies were included; comprised of 11 randomized control trials and 27 non-randomized interventional studies. Electronic prescribing strategies reduced medication errors (RR 0.24 (95% CI 0.13, 0.46), I² 98%, n = 11) and dosing errors (RR 0.17 (95% CI 0.08, 0.38), I² 96%, n = 9), with both risk ratios significantly affected by advancing year of publication. There was a significant effect of electronic prescribing strategies on adverse drug events (ADEs) (RR 0.52 (95% CI 0.40, 0.68), I² 0%, n = 2), but not on preventable ADEs (RR 0.55 (95% CI 0.30, 1.01), I² 78%, n = 3), hypoglycemia (RR 1.03 (95% CI 0.62-1.70), I² 28%, n = 7), length of stay (MD - 0.18 (95% - 1.42, 1.05), I² 94%, n = 7), or mortality (RR 0.97 (95% CI 0.79, 1.19), I² 74%, n = 9). The quality of evidence was rated very low.

DISCUSSION

Electronic prescribing strategies decrease medication errors and adverse drug events, but had no effect on other patient outcomes. Conservative interpretations of these findings are supported by significant heterogeneity and the preponderance of low-quality studies.

Impact of an electronic health record transition on chemotherapy error reporting

BACKGROUND

Incident reporting systems allow for frontline employees to report errors and are a critical component of healthcare patient safety programs. Although incident reporting systems cannot quantify total errors, organizations can utilize incident reporting systems to help identify risks and trends to act upon. The objective of this article is to utilize incident reporting systems to evaluate trends in medication error reporting before and after implementation of a new electronic health record system.

METHODS

A five-month pre- and post-analysis was completed in a cancer hospital following electronic health record conversion by reviewing medication errors reported via the institution's voluntary incident reporting systems. Error reports included medication error category, date error was reported/occurred, patient location at time of error, harm severity score, medication(s) involved, medication use system node error originated/discovered in, medication source, narrative summary, and contributing factors. Data were analyzed using descriptive statistics within Office Excel.

RESULTS

Oncology medication error reports submitted pre- and post-electronic health record were 68 vs. 57, respectively. During the pre- and post-electronic health record conversion, a majority of errors had a harm severity index of 0 or 1; 12 (18%) in pre-electronic health record and 3 (5%) in post-electronic health record were level 2, and one (1%) in pre-electronic health record vs. 0 in post-electronic health record were level 3. Reported medication errors originated most commonly during the prescribing, administration, and preparation/dispensing phase and were primarily identified in the administration phase of the medication use process. The most frequently reported error category was 'wrong dose' followed by 'other' and 'overdose' in the pre-electronic health record phase and 'missing dose/delayed delivery' and 'order incorrect' in the post-electronic health record phase. The most frequently reported medications included methotrexate, chemotherapy (unspecified), and cisplatin.

CONCLUSION

Analyzing data from incident reporting system reports allowed our institution to understand different trends of reporting in the cancer hospital following electronic health record adoption. Utilization of incident reporting systems must be combined with proactive risk identification approaches to enable systems-focused improvements to improve patient safety.

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.

How to Prevent or Reduce Prescribing Errors: An Evidence Brief for Policy

- Preventing prescribing errors is critical to improving patient safety.- We developed an evidence brief for policy to identify effective interventions to avoid or reduce prescribing errors.- Four options were raised: promoting educational actions on prudent prescribing directed to prescribers; incorporating computerized alert systems into clinical practice; implementing the use of tools for guiding medication prescribing; and, encouraging patient care by a multidisciplinary team, with the participation of a pharmacist.- These options can be incorporated into health systems either alone or together, and for that, it is necessary that the context be considered.- Aiming to inform decision makers, we included considerations on the implementation of these options regarding upper-middle income countries, like the Brazilian, and we also present considerations regarding equity.

Implementation of a new health information technology for the management of cancer chemotherapies

Background

Cancer chemotherapy drugs are classified as high-risk molecules. Safety of the cancer chemotherapy process is often achieved with the implementation of a health information technology to each step or to the entire process. However, computerisation could lead to the emergence of new unintended medication errors. The aim of the study was to evaluate the impact of new software designed for the management of anticancer chemotherapies.

Method

The cartography of the process and the failure modes, effects and criticality analysis were performed by a multidisciplinary team. Criticality indexes were calculated considering or not the implementation of the commercial software (CytoWeb). Quality and satisfactory indicators were measured before the implementation and during the use of the software.

Results

Our results demonstrated the complexity of the cancer chemotherapy process in the hospital. Risk analysis highlighted the positive impact of CytoWeb on the process safety but pointed out some steps that were not positively influenced by the software. Although a decrease of 38.6% of error rate was observed with the electronic system, new unintended medication errors emerged. These errors were due to inadequate use of the software (encoding of the wrong drug, the wrong dose, the wrong patient parameters or lab results and lack of prescriber adherence). Our satisfaction survey showed that the hospital pharmacists and doctors were less satisfied by the software than the nurses, mostly in terms of task achievement and time saving. Survey's results highlighted some weaknesses in the user training and in the collaboration between the medical staff.

Conclusions

Our work showed the emergence of unintended medication errors linked to computerisation that were due to an inadequate use of the software. Other issues were highlighted such as the lack of collaboration between the medical staff, the lack of prescriber implication and weaknesses in the user training or in the information related to CytoWeb.

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.

Review of medication errors that are new or likely to occur more frequently with electronic medication management systems

Objective The aim of the present study was to identify and quantify medication errors reportedly related to electronic medication management systems (eMMS) and those considered likely to occur more frequently with eMMS. This included developing a new classification system relevant to eMMS errors. Methods Eight Victorian hospitals with eMMS participated in a retrospective audit of reported medication incidents from their incident reporting databases between May and July 2014. Site-appointed project officers submitted deidentified incidents they deemed new or likely to occur more frequently due to eMMS, together with the Incident Severity Rating (ISR). The authors reviewed and classified incidents. Results There were 5826 medication-related incidents reported. In total, 93 (47 prescribing errors, 46 administration errors) were identified as new or potentially related to eMMS. Only one ISR2 (moderate) and no ISR1 (severe or death) errors were reported, so harm to patients in this 3-month period was minimal. The most commonly reported error types were ‘human factors’ and ‘unfamiliarity or training’ (70%) and ‘cross-encounter or hybrid system errors’ (22%). Conclusions Although the results suggest that the errors reported were of low severity, organisations must remain vigilant to the risk of new errors and avoid the assumption that eMMS is the panacea to all medication error issues. What is known about the topic? eMMS have been shown to reduce some types of medication errors, but it has been reported that some new medication errors have been identified and some are likely to occur more frequently with eMMS. There are few published Australian studies that have reported on medication error types that are likely to occur more frequently with eMMS in more than one organisation and that include administration and prescribing errors. What does this paper add? This paper includes a new simple classification system for eMMS that is useful and outlines the most commonly reported incident types and can inform organisations and vendors on possible eMMS improvements. The paper suggests a new classification system for eMMS medication errors. What are the implications for practitioners? The results of the present study will highlight to organisations the need for ongoing review of system design, refinement of workflow issues, staff education and training and reporting and monitoring of errors.

Qualitative study exploring the phenomenon of multiple electronic prescribing systems within single hospital organisations

Background

A previous census of electronic prescribing (EP) systems in England showed that more than half of hospitals with EP reported more than one EP system within the same hospital. Our objectives were to describe the rationale for having multiple EP systems within a single hospital, and to explore perceptions of stakeholders about the advantages and disadvantages of multiple systems including any impact on patient safety.

Methods

Hospitals were selected from previous census respondents. A decision matrix was developed to achieve a maximum variation sample, and snowball sampling used to recruit stakeholders of different professional backgrounds. We then used an a priori framework to guide and analyse semi-structured interviews.

Results

Ten participants, comprising pharmacists and doctors and a nurse, were interviewed from four hospitals. The findings suggest that use of multiple EP systems was not strategically planned. Three co-existing models of EP systems adoption in hospitals were identified: organisation-led, clinician-led and clinical network-led, which may have contributed to multiple systems use. Although there were some perceived benefits of multiple EP systems, particularly in niche specialities, many disadvantages were described. These included issues related to access, staff training, workflow, work duplication, and system interfacing. Fragmentation of documentation of the patient’s journey was a major safety concern.

Discussion

The complexity of EP systems’ adoption and deficiencies in IT strategic planning may have contributed to multiple EP systems use in the NHS. In the near to mid-term, multiple EP systems may remain in place in many English hospitals, which may create challenges to quality and patient safety.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3750-1) contains supplementary material, which is available to authorized users.

Checking the potential shift to perceived usefulness-The analysis of users' response to the updated electronic health record core features

OBJECTIVE

The primary objective of this paper is to identify the main factors which have an impact on the users' attitude towards the functionalities representing the perceived ease of use and to those representing the perceived usefulness. Another objective is to examine whether there occurred a shift towards the perceived usefulness of users' behavior over a period of time. To support these objectives, two different cases are examined - the case in which users are simultaneously offered basic and updated functionalities, and the one in which users are offered a completely new set of features. The results of this study are expected to exert a significant impact on a further development of new software components, as well as the updates of the existing ones.

MATERIAL AND METHODS

As the starting point, there were employed the user behavior indicators defined in similar researches and conducted in the countries with a similar cultural background or with a comparatively similar national healthcare system. What ensued was an updated set of functionalities offered within the electronic health record based medical information system. Instead of the survey being posted, the effects of implanted updates were measured through the analysis of the collected data. The data collected in the Nis Primary and Ambulatory Care Center during a four-year period represented the material used in the research. The obtained records indicating the usage of the initial and updated visit registration form, as well as the usage of the new types of visits, were examined in relation to the technology acceptance model and integrated behavior model.

RESULTS

The response to the initial functionalities, perceived as easy to use, was high as expected since they kept the users in their "comfort zone". As regards the updated features, the ones corresponding to the perceived usefulness, the initial overall acceptance rate was 60%, while the overall increase of their acceptance was around 20%. The overall usage of the newly introduced features was doubled in some cases throughout the four-year period, while some of them were not accepted as expected.

DISCUSSION

Carefully designed additional functionalities, aimed to improve the most common daily activities, have a significant potential to be accepted by the medical professionals. The shift from the perceived ease of use to the perceived usefulness is not uniform, nor is its use in different departments or by the users of the same department. A higher acceptance rate was observed in the departments with more complex administrative procedures, as well as among the users having contacts with more patients and using the system for a longer period.

CONCLUSION

When accepting new features, medical professionals will initially choose the simpler ones with obvious benefits. If the usage of a feature triggers indirect benefits, the number of examined patients is of a crucial importance for the acceptance of that feature. In the event of the advanced functionality with an extended set of options competing with the simple functionality covering basic requirements, the latter will be used. A feature design, together with a proper training, system stability and ensuring utilization, represent a key point for increasing the positive impact that the information system can have in many application areas, including the healthcare.

[Analysis of drug-related problems in a tertiary university hospital in Barcelona (Spain)]

OBJECTIVE

To describe drug-related problems identified in hospitalized patients and to assess physicians' acceptance rate of pharmacists' recommendations.

METHODS

Retrospective observational study that included all drug-related problems detected in hospitalized patients during 2014-2015. Statistical analysis included a descriptive analysis of the data and a multivariate logistic regression to evaluate the association between pharmacists' recommendation acceptance rate and the variable of interest.

RESULTS

During the study period 4587 drug-related problems were identified in 44,870 hospitalized patients. Main drug-related problems were prescription errors due to incorrect use of the computerized physician order entry (18.1%), inappropriate drug-drug combination (13.3%) and dose adjustment by renal and/or hepatic function (11.5%). Acceptance rate of pharmacist therapy advice in evaluable cases was 81.0%. Medical versus surgical admitting department, specific types of intervention (addition of a new drug, drug discontinuation and correction of a prescription error) and oral communication of the recommendation were associated with a higher acceptance rate.

CONCLUSIONS

The results of this study allow areas to be identified on which to implement optimization strategies. These include training courses for physicians on the computerized physician order entry, on drugs that need dose adjustment with renal impairment, and on relevant drug interactions.

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.

Determinant of successful implementation of Computerized Provider Order Entry (CPOE) system from physicians' perspective: Feasibility study prior to implementation

Background

Health information technology is a solution for medical error reduction through the implementation of Computerized Provider Order Entry (CPOE).

Objective

The aim of this study was to determine physicians’ attitudes toward the implementation of CPOE.

Methods

This cross-sectional study was started in March 2017 and completed in June 2017. The study used a questionnaire to collect data from physicians in hospitals affiliated to Urmia University of Medical Sciences. We invited 200 physicians who were not using a CPOE system. Questionnaires were randomly distributed among physicians. In order to understand the physicians’ attitude about implementation the CPOE system, we used the Diffusion of Innovation Theory, developed by E.M. Rogers. Data were analyzed by SPSS version 16.0, using descriptive statistics and one-way ANOVA. A p value <0.05 was considered to be statistically significant.

Results

Most of the physicians were women (n=54, 60%) and the average age of the physicians was 36.39±8.42 years. About three-quarters of the physicians (76.66%) reported that they found the CPOE system adapted to their specific professional practice. The relative advantage of the CPOE system was estimated to be 42.22% for physicians and the complexity of that was 13.33%. There was no significant relationship between Compatibility, Relative advantages and Complexity with physicians’ experience in HIS use and physicians’ degree of education (p>0.05).

Conclusion

Since the role of CPOE systems is very important in hospitals in order to reduce medication errors and to improve the quality of care, our results can be used to assist the planning and introduction of CPOE systems.

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.

Validation of a score to identify inpatients at risk of a drug-related problem during a 4-year period

Objective

Drug-related problems (DRP) produce high morbidity and mortality. It is therefore essential to identify patients at higher risk of these events. This study aimed to validate a DRP risk score in a large number of inpatients.

Material and methods

Validation of a previously designed score to identify inpatients at risk of experiencing at least one DRP in a tertiary university hospital from 2010 to 2013. DRP were detected by a pharmacy warning system integrated in the electronic medical record. The score included the following variables associated with a higher risk of DRP: prescription of a higher number of drugs, greater comorbidity, advanced age, specific ATC groups and certain major diagnostic categories.

Results

The study included a total of 52,987 admissions; of these, at least one DRP occurred in 14.9%. After validation of the score (period range, 2010–2013: 0.746–0.764), the area under the curve (AUC) was 0.751 (95% CI: 0.745–0.756).

Conclusions

This value is higher than those reported in other studies describing validation of risk scores. The score showed good capacity to identify those patients at higher risk of DRP in a much larger sample of inpatients than previously described in the literature. This tool allows optimization of drug therapy monitoring in admitted patients.

Using EHR Data to Detect Prescribing Errors in Rapidly Discontinued Medication Orders

BACKGROUND

Previous research developed a new method for locating prescribing errors in rapidly discontinued electronic medication orders. Although effective, the prospective design of that research hinders its feasibility for regular use.

OBJECTIVES

Our objectives were to assess a method to retrospectively detect prescribing errors, to characterize the identified errors, and to identify potential improvement opportunities.

METHODS

Electronically submitted medication orders from 28 randomly selected days that were discontinued within 120 minutes of submission were reviewed and categorized as most likely errors, nonerrors, or not enough information to determine status. Identified errors were evaluated by amount of time elapsed from original submission to discontinuation, error type, staff position, and potential clinical significance. Pearson's chi-square test was used to compare rates of errors across prescriber types.

RESULTS

In all, 147 errors were identified in 305 medication orders. The method was most effective for orders that were discontinued within 90 minutes. Duplicate orders were most common; physicians in training had the highest error rate (p < 0.001), and 24 errors were potentially clinically significant. None of the errors were voluntarily reported.

CONCLUSION

It is possible to identify prescribing errors in rapidly discontinued medication orders by using retrospective methods that do not require interrupting prescribers to discuss order details. Future research could validate our methods in different clinical settings. Regular use of this measure could help determine the causes of prescribing errors, track performance, and identify and evaluate interventions to improve prescribing systems and processes.

Prevalence of computerized physician order entry systems-related medication prescription errors: A systematic review

OBJECTIVE

The positive impact of computerized physician order entry (CPOE) systems on prescription safety must be considered in light of the persistence of certain types of medication-prescription errors. We performed a systematic review, based on the PRISMA statement, to analyze the prevalence of prescription errors related to the use of CPOE systems.

MATERIALS AND METHODS

We searched MEDLINE, EMBASE, CENTRAL, DBLP, the International Clinical Trials Registry, the ISI Web of Science, and reference lists of relevant articles from March 1982 to August 2017. We included original peer-reviewed studies which quantitatively reported medication-prescription errors related to CPOE. We analyzed the prevalence of medication-prescription errors according to an adapted version of the National Coordinating Council for Medication Error Reporting and Prevention (NCCMERP) taxonomy and assessed the mechanisms responsible for each type of prescription error due to CPOE.

RESULTS

Fourteen studies were included. The prevalence of CPOE systems-related medication errors relative to all prescription medication errors ranged from 6.1 to 77.7% (median = 26.1% [IQR:17.6-42,1]) and was less than 6.3% relative to the number of prescriptions reviewed. All studies reported "wrong dose" and "wrong drug" errors. The "wrong dose" error was the most frequently reported (from 7 to 67.4%, median = 31.5% [IQR:20.5-44.5]). We report the associated mechanism for each type of medication described (those due to CPOE or those occurring despite CPOE).

DISCUSSION

We observed very heterogeneous results, probably due to the definition of error, the type of health information system used for the study, and the data collection method used. Each data collection method provides valuable and useful information concerning the prevalence and specific types of errors related to CPOE systems.

CONCLUSIONS

The reporting of prescription errors should be continued because the weaknesses of CPOE systems are potential sources of error. Analysis of the mechanisms behind CPOE errors can reveal areas for improvement.

Computerized prescriber order entry-related patient safety reports: analysis of 2522 medication errors

Objective

To examine medication errors potentially related to computerized prescriber order entry (CPOE) and refine a previously published taxonomy to classify them.

Materials and Methods

We reviewed all patient safety medication reports that occurred in the medication ordering phase from 6 sites participating in a United States Food and Drug Administration-sponsored project examining CPOE safety. Two pharmacists independently reviewed each report to confirm whether the error occurred in the ordering/prescribing phase and was related to CPOE. For those related to CPOE, we assessed whether CPOE facilitated (actively contributed to) the error or failed to prevent the error (did not directly cause it, but optimal systems could have potentially prevented it). A previously developed taxonomy was iteratively refined to classify the reports.

Results

Of 2522 medication error reports, 1308 (51.9%) were related to CPOE. Of these, CPOE facilitated the error in 171 (13.1%) and potentially could have prevented the error in 1137 (86.9%). The most frequent categories of "what happened to the patient" were delays in medication reaching the patient, potentially receiving duplicate drugs, or receiving a higher dose than indicated. The most frequent categories for "what happened in CPOE" included orders not routed to or received at the intended location, wrong dose ordered, and duplicate orders. Variations were seen in the format, categorization, and quality of reports, resulting in error causation being assignable in only 403 instances (31%).

Discussion and Conclusion

Errors related to CPOE commonly involved transmission errors, erroneous dosing, and duplicate orders. More standardized safety reporting using a common taxonomy could help health care systems and vendors learn and implement prevention strategies.

Impact of commercial computerized provider order entry (CPOE) and clinical decision support systems (CDSSs) on medication errors, length of stay, and mortality in intensive care units: a systematic review and meta-analysis

Objective

To conduct a systematic review and meta-analysis of the impact of commercial computerized provider order entry (CPOE) and clinical decision support systems (CDSSs) on medication errors, length of stay (LOS), and mortality in intensive care units (ICUs).

Methods

We searched for English-language literature published between January 2000 and January 2016 using Medline, Embase, and CINAHL. Titles and abstracts of 586 unique citations were screened. Studies were included if they: (1) reported results for an ICU population; (2) evaluated the impact of CPOE or the addition of CDSSs to an existing CPOE system; (3) reported quantitative data on medication errors, ICU LOS, hospital LOS, ICU mortality, and/or hospital mortality; and (4) used a randomized controlled trial or quasi-experimental study design.

Results

Twenty studies met our inclusion criteria. The transition from paper-based ordering to commercial CPOE systems in ICUs was associated with an 85% reduction in medication prescribing error rates and a 12% reduction in ICU mortality rates. Overall meta-analyses of LOS and hospital mortality did not demonstrate a significant change.

Discussion and Conclusion

Critical care settings, both adult and pediatric, involve unique complexities, making them vulnerable to medication errors and adverse patient outcomes. The currently limited evidence base requires research that has sufficient statistical power to identify the true effect of CPOE implementation. There is also a critical need to understand the nature of errors arising post-CPOE and how the addition of CDSSs can be used to provide greater benefit to delivering safe and effective patient care.

Towards patient safety: assessment of medication errors in the intensive care unit in a developing country's tertiary care teaching hospital

Objectives

To determine the incidence, causes, patterns and outcomes of medication errors (MEs) in the intensive care unit.

Methods

The ME reporting system was established using the principles based on prospective, voluntary, open, anonymous and stand-alone surveillance in a tertiary care teaching hospital located in southern India. MEs involving patients of either sex were included in the study, and the reporters were given the choice to remain anonymous. The analysis was carried out to determine the patterns, causes and outcomes of the reported errors and was discussed with healthcare professionals (HCPs) to minimise the recurrence of MEs.

Results

A total of 292 MEs were reported voluntarily among 5137 admitted patients and the incidence of MEs was 5.6%. Administration errors (n=143, 49%) were the most common type of MEs reported followed by prescription errors (n=56, 19%) and dispensing errors (n=43, 15%). Factors responsible for MEs were related to performance deficit of HCPs due to excessive workload, fatigue, unclear interpersonnel communications and patient-related factors, which accounted for 37.6%, 13.1%, 9.6% and 7.7%, respectively. The majority of the reported MEs had an outcome of category C and A, based on the National Coordinating Council for ME Reporting and Prevention (NCC MERP) outcome category scale, amounting to 42.2% and 41.7%, respectively.

Conclusions

Although the majority of MEs that reached the patients did not cause any harm, providing continuous education and awareness of MEs to HCPs and patients may minimise the scope of the factors that may contribute to MEs and improve overall patient safety.

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.