Association of patient photographs and reduced retract-and-reorder events.

Background: Wrong-patient order entry (WPOE) is a potentially dangerous medical error. It remains unknown if patient photographs reduce WPOE in the pediatric inpatient population. Materials and Methods: Order sessions from a single pediatric hospital system were examined for retract-and-reorder (RAR) events, a surrogate WPOE measure. We determined the association of patient photographs with the proportion of order sessions resulting in a RAR event, adjusted for patient, provider, and ordering context. Results: In multivariable analysis, the presence of a patient photo in the electronic health record was associated with 40% lower odds of a RAR event (aOR: 0.60, 95% CI: 0.48-0.75), while cardiac and ICU contexts had higher RAR frequency (aOR: 2.12, 95% CI: 1.69-2.67 and 2.05, 95% CI: 1.71-2.45, respectively). Discussion and Conclusion: Patient photos were associated with lower odds of RAR events in the pediatric inpatient setting, while high acuity locations may be at higher risk. Patient photographs may reduce WPOE without interruptions.

Retrospective evaluation of clinical decision support for within-laboratory optimization of SARS-CoV-2 NAAT workflow.

The unprecedented demand for severe acute respiratory syndrome coronavirus 2 (SARS­CoV­2) testing led to challenges in prioritizing and processing specimens efficiently. We describe and evaluate a novel workflow using provider- and patient-facing ask at order entry (AOE) questions to generate distinctive icons on specimen labels for within-laboratory clinical decision support (CDS) for specimen triaging. A multidisciplinary committee established target turnaround times (TATs) for SARS-CoV-2 nucleic acid amplification test (NAAT) based on common clinical scenarios. A set of AOE questions was used to collect relevant clinical information that prompted icon generation for triaging SARS-CoV-2 NAAT specimens. We assessed the collect-to-verify TATs among relevant clinical scenarios. Our study included a total of 1,385,813 SARS-CoV-2 NAAT conducted from March 2020 to June 2022. Most testing met the TAT targets established by institutional committees, but deviations from target TATs occurred during periods of high demand and supply shortages. Median TATs for emergency department (ED) and inpatient specimens and ambulatory pre-procedure populations were stable over the pandemic. However, healthcare worker and other ambulatory test TATs varied substantially, depending on testing volume and community transmission rates. Median TAT significantly differed throughout the pandemic for ED and inpatient clinical scenarios, and there were significant differences in TAT among label icon-signified ambulatory clinical scenarios. We describe a novel approach to CDS for triaging specimens within the laboratory. The use of CDS tools could help clinical laboratories prioritize and process specimens efficiently, especially during times of high demand. Further studies are needed to evaluate the impact of our CDS tool on overall laboratory efficiency and patient outcomes. IMPORTANCE We describe a novel approach to clinical decision support (CDS) for triaging specimens within the clinical laboratory for severe acute respiratory syndrome coronavirus 2 (SARS­CoV­2) nucleic acid amplification tests (NAAT). The use of our CDS tool could help clinical laboratories prioritize and process specimens efficiently, especially during times of high demand. There were significant differences in the turnaround time for specimens differentiated by icons on specimen labels. Further studies are needed to evaluate the impact of our CDS tool on overall laboratory efficiency and patient outcomes.

Assessing the impact of an electronic chemotherapy order verification checklist on pharmacist reported errors in oncology infusion centers of a health-system.

PURPOSE: Chemotherapies are medications with narrow therapeutic indices and potential for severe adverse events that account for at least 1 to 3% of medication errors in all adult and pediatric oncology patients. The use of an electronic chemotherapy order verification (ECOV) checklist can standardize the steps of chemotherapy verification by pharmacists, which can potentially increase medication error detection at the point of dispensing. This study evaluated the implementation of a standardized chemotherapy order verification checklist on pharmacist error reporting, particularly good-catches or near-misses type errors. METHODS: This retrospective, quasi-experimental, pre-/post-analysis of internal voluntary medication errors reported from 12 University Hospitals Seidman oncology infusion centers from June 2022 through December 2022. Error reports, categorized based on severity, were compared pre/post-implementation of the ECOV checklist. RESULTS: A total of 62 and 71 cases of medication errors were reported in the pre-intervention and post-intervention periods, respectively. The rate of pharmacy reported medication errors was 2.4 times greater in the post-intervention period of the ECOV checklist (p < 0.006). Pharmacy reported errors increased among all error severities reported. However, the finding did not deduce a statistically significant difference (p < 0.244). CONCLUSION: This study demonstrates the effectiveness of implementing the ECOV checklist in increasing the rate of pharmacy reported medication errors. The checklist was designed to complement existing pharmacist workflow and provide a source of documentation for steps of sequential pharmacist evaluation.

Post-implementation optimization of medication alerts in hospital computerized provider order entry systems: a scoping review.

OBJECTIVES: A scoping review identified interventions for optimizing hospital medication alerts post-implementation, and characterized the methods used, the populations studied, and any effects of optimization. MATERIALS AND METHODS: A structured search was undertaken in the MEDLINE and Embase databases, from inception to August 2023. Articles providing sufficient information to determine whether an intervention was conducted to optimize alerts were included in the analysis. Snowball analysis was conducted to identify additional studies. RESULTS: Sixteen studies were identified. Most were based in the United States and used a wide range of clinical software. Many studies used inpatient cohorts and conducted more than one intervention during the trial period. Alert types studied included drug-drug interactions, drug dosage alerts, and drug allergy alerts. Six types of interventions were identified: alert inactivation, alert severity reclassification, information provision, use of contextual information, threshold adjustment, and encounter suppression. The majority of interventions decreased alert quantity and enhanced alert acceptance. Alert quantity decreased with alert inactivation by 1%-25.3%, and with alert severity reclassification by 1%-16.5% in 6 of 7 studies. Alert severity reclassification increased alert acceptance by 4.2%-50.2% and was associated with a 100% acceptance rate for high-severity alerts when implemented. Clinical errors reported in 4 studies were seen to remain stable or decrease. DISCUSSION: Post-implementation medication optimization interventions have positive effects for clinicians when applied in a variety of settings. Less well reported are the impacts of these interventions on the clinical care of patients, and how endpoints such as alert quantity contribute to changes in clinician and pharmacist perceptions of alert fatigue. CONCLUSION: Well conducted alert optimization can reduce alert fatigue by reducing overall alert quantity, improving clinical acceptance, and enhancing clinical utility.

Closed-Loop Medication Management with an Electronic Health Record System in U.S. and Finnish Hospitals.

Many medication errors in the hospital setting are due to manual, error-prone processes in the medication management system. Closed-loop Electronic Medication Management Systems (EMMSs) use technology to prevent medication errors by replacing manual steps with automated, electronic ones. As Finnish Helsinki University Hospital (HUS) establishes its first closed-loop EMMS with the new Epic-based Electronic Health Record system (APOTTI), it is helpful to consider the history of a more mature system: that of the United States. The U.S. approach evolved over time under unique policy, economic, and legal circumstances. Closed-loop EMMSs have arrived in many U.S. hospital locations, with myriad market-by-market manifestations typical of the U.S. healthcare system. This review describes and compares U.S. and Finnish hospitals' EMMS approaches and their impact on medication workflows and safety. Specifically, commonalities and nuanced differences in closed-loop EMMSs are explored from the perspectives of the care/nursing unit and hospital pharmacy operations perspectives. As the technologies are now fully implemented and destined for evolution in both countries, perhaps closed-loop EMMSs can be a topic of continued collaboration between the two countries. This review can also be used for benchmarking in other countries developing closed-loop EMMSs.

An Evaluation of Drug-Drug Interaction Alerts Produced by Clinical Decision Support Systems in a Tertiary Hospital.

Introduction Drug-drug interactions (DDIs) have the potential to harm patients. Hence, DDI alerts are meant to prevent harm; as a result, their usefulness is reduced when most alerts displayed to providers are ignored. This study aims to explore the rates and reasons for overriding alerts of DDI. Methods This is a retrospective study of DDI alert overrides that occurred between January 2020 and December 2020 within the inpatient medical records at a tertiary hospital, Medina City, Kingdom of Saudi Arabia. Results A total of 7,098 DDI alerts were generated from inpatient settings, of which 6,551(92.2%) were overridden by the physicians at the point of prescribing. "Will Monitor as Recommended" (33%) was the most common reason for the override, followed by 'Will Adjust the Dose as Recommended (27.1%)," "The Patient Has Already Tolerated the Combination" (25.7%), and "No Overridden Reason Selected" (13.0%). Discussion The DDI alert overriding is still high and is comparable to other studies. However, this study reveals that physicians are ready to deal with the consequences of around 58% of DDI alerts. Additionally, 13% of physicians were not willing to report the reason for overriding. This indicates an urgent need to review and restructure the DDI alert system. Conclusion The DDI alert override rates are high, and this is undesirable. It is recommended to revise the DDI alert system. Future studies should dig deep for real reasons for overriding and seek inputs from all stakeholders, including developing actionable metrics to track and monitor DDI alerting system.

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

Objective: To investigate: (1) what automated search methods are used to identify wrong-patient order entry (WPOE), (2) what data are being captured and how they are being used, (3) the causes of WPOE, and (4) how providers identify their own errors. Materials and Methods: A systematic scoping review of the empirical literature was performed using the databases CINAHL, Embase, and MEDLINE, covering the period from database inception until 2021. Search terms were related to the use of automated searches for WPOE when using an electronic prescribing system. Data were extracted and thematic analysis was performed to identify patterns or themes within the data. Results: Fifteen papers were included in the review. Several automated search methods were identified, with the retract-and-reorder (RAR) method and the Void Alert Tool (VAT) the most prevalent. Included studies used automated search methods to identify background error rates in isolation, or in the context of an intervention. Risk factors for WPOE were identified, with technological factors and interruptions deemed the biggest risks. Minimal data on how providers identify their own errors were identified. Discussion: RAR is the most widely used method to identify WPOE, with a good positive predictive value (PPV) of 76.2%. However, it will not currently identify other error types. The VAT is nonspecific for WPOE, with a mean PPV of 78%-93.1%, but the voiding reason accuracy varies considerably. Conclusion: Automated search methods are powerful tools to identify WPOE that would otherwise go unnoticed. Further research is required around self-identification of errors.

Design, implementation, and evaluation of a CPOE system in a cancer care setting: A case study on the gastric cancer patients.

BACKGROUND: Chemotherapy is a complex, multi-disciplinary, and error-prone process. Information technology is being increasingly used in different health care settings with complex work procedures such as cancer care to enhance the quality and safety of care. In this study, we aimed to develop a computerized physician order entry (CPOE) for chemotherapy prescribing in patients with gastric cancer and to evaluate the impact of CPOE on medication errors and order problems. MATERIALS AND METHODS: A multi-disciplinary team consisting of a chemotherapy council group and system design and implementation team was formed for chemotherapy process evaluation, requirement analysis, developing computer-based protocols, and implementation of CPOE. A before and after study was conducted to evaluate the impact of CPOE on the chemotherapy process and medication errors and problem orders. To evaluate the level of end-user satisfaction, an ISO Norm 9241/110 usability questionnaire was chosen for the evaluation. RESULTS: Before the implementation of the CPOE system, 37 medication errors (46.25%) and 53 problem orders (66.25%) were recorded for 80 paper-based chemotherapy prescriptions. After implementation of the CPOE system, 7 (8.7%) medication errors and 6 (7.5%) problem orders were recorded for 80 CPOE prescriptions. The implementation of CPOE reduced the medication error by 37.55% and the problematic order by 58.75%. The results for usability evaluation indicate that the CPOE was within the first class of the ISONORM level rating; this shows that a CPOE is with very high satisfaction and a very high functionality rate. CONCLUSION: Developing a CPOE system significantly improved safety and quality of the chemotherapy process in cancer care settings by reducing the medication error, deleting unnecessary steps, improving communication and coordination between providers, and use of updated evidence-based medicine in direct chemotherapy orders. However, the CPOE system does not prevent all medication errors and may cause new errors. These errors can be human-related factors or associated with the design and implementation of the systems.

Examining medication ordering errors using AHRQ network of patient safety databases.

BACKGROUND: Studies examining the effects of computerized order entry (CPOE) on medication ordering errors demonstrate that CPOE does not consistently prevent these errors as intended. We used the Agency for Healthcare Research and Quality (AHRQ) Network of Patient Safety Databases (NPSD) to investigate the frequency and degree of harm of reported events that occurred at the ordering stage, characterized by error type. MATERIALS AND METHODS: This was a retrospective observational study of safety events reported by healthcare systems in participating patient safety organizations from 6/2010 through 12/2020. All medication and other substance ordering errors reported to NPSD via common format v1.2 between 6/2010 through 12/2020 were analyzed. We aggregated and categorized the frequency of reported medication ordering errors by error type, degree of harm, and demographic characteristics. RESULTS: A total of 12 830 errors were reported during the study period. Incorrect dose accounted for 3812 errors (29.7%), followed by incorrect medication 2086 (16.3%), and incorrect duration 765 (6.0%). Of 5282 events that reached the patient and had a known level of severity, 12 resulted in death, 4 resulted in severe harm, 45 resulted in moderate harm, 341 resulted in mild harm, and 4880 resulted in no harm. CONCLUSION: Incorrect dose and incorrect drug orders were the most commonly reported and harmful types of medication ordering errors. Future studies should aim to develop and test interventions focused on CPOE to prevent medication ordering errors, prioritizing wrong-dose and wrong-drug errors.

Implementation outcomes of the Structured and Codified SIG format in electronic prescription directions.

OBJECTIVE: To determine the extent of implementation, completeness, and accuracy of Structured and Codified SIG (S&C SIG) directions on electronic prescriptions (e-prescriptions). MATERIALS AND METHODS: A retrospective analysis of a random sample of 3.8 million e-prescriptions sent from electronic prescribing (e-prescribing) software to outpatient pharmacies in the United States between 2019 and 2021. Natural language processing was used to identify direction components, including action verb, dose, frequency, route, duration, and indication from free-text directions and were compared to the S&C SIG format. Inductive qualitative analysis of S&C direction identified error types and frequencies for each component. RESULTS: Implementation of the S&C SIG format in e-prescribing software resulted in 32.4% of e-prescriptions transmitted with these standardized directions. Directions using the S&C SIG format contained a greater percentage of each direction component compared to free-text directions, except for the indication component. Structured and codified directions contained quality issues in 10.3% of cases. DISCUSSION: Expanding adoption of more diverse direction terminology for the S&C SIG formats can improve the coverage of directions using the S&C SIG format. Building out e-prescribing software interfaces to include more direction components can improve patient medication use and safety. Quality improvement efforts, such as improving the design of e-prescribing software and auditing for discrepancies, are needed to identify and eliminate implementation-related issues with direction information from the S&C SIG format so that e-prescription directions are always accurately represented. CONCLUSION: Although directions using the S&C SIG format may result in more complete directions, greater adoption of the format and best practices for preventing its incorrect use are necessary.

Key factors of clinicians' acceptance of CPOE system and their link to change management.

The successful implementation of a Computerized Provider Order Entry (CPOE) system is a challenging process for any healthcare organization. It requires a dramatic change not only to the way the care is provided but also to the way clinicians work. Because of the required change complexity, organizations must consider key factors of clinicians' acceptance to avoid resistance and maximize chances of success. This paper aims to identify the different factors that affect clinicians' acceptance of CPOE systems and their relation to existing change management models. A systematic literature review was conducted to identify barriers and recommendations to the clinicians' acceptance of CPOE systems. Then, a comparative analysis was used to explain the relationship between the discovered factors and change management, with a focus on Kotter's model. The review included 23 articles. A total of 28 barriers and 25 recommendations have been identified. In conclusion, factors of clinicians' acceptance fall into two categories: one related to the used implementation strategy and the other related to how the system was designed. Most of the factors are similar to change management principles. The systematic incorporation of change management principles during CPOE implementation would likely improve clinicians' acceptance of the system.

Harnessing the Electronic Health Record and Computerized Provider Order Entry Data for Resource Management During the COVID-19 Pandemic: Development of a Decision Tree.

BACKGROUND: The COVID-19 pandemic has resulted in shortages of diagnostic tests, personal protective equipment, hospital beds, and other critical resources. OBJECTIVE: We sought to improve the management of scarce resources by leveraging electronic health record (EHR) functionality, computerized provider order entry, clinical decision support (CDS), and data analytics. METHODS: Due to the complex eligibility criteria for COVID-19 tests and the EHR implementation-related challenges of ordering these tests, care providers have faced obstacles in selecting the appropriate test modality. As test choice is dependent upon specific patient criteria, we built a decision tree within the EHR to automate the test selection process by using a branching series of questions that linked clinical criteria to the appropriate SARS-CoV-2 test and triggered an EHR flag for patients who met our institutional persons under investigation criteria. RESULTS: The percentage of tests that had to be canceled and reordered due to errors in selecting the correct testing modality was 3.8% (23/608) before CDS implementation and 1% (262/26,643) after CDS implementation (P<.001). Patients for whom multiple tests were ordered during a 24-hour period accounted for 0.8% (5/608) and 0.3% (76/26,643) of pre- and post-CDS implementation orders, respectively (P=.03). Nasopharyngeal molecular assay results were positive in 3.4% (826/24,170) of patients who were classified as asymptomatic and 10.9% (1421/13,074) of symptomatic patients (P<.001). Positive tests were more frequent among asymptomatic patients with a history of exposure to COVID-19 (36/283, 12.7%) than among asymptomatic patients without such a history (790/23,887, 3.3%; P<.001). CONCLUSIONS: The leveraging of EHRs and our CDS algorithm resulted in a decreased incidence of order entry errors and the appropriate flagging of persons under investigation. These interventions optimized reagent and personal protective equipment usage. Data regarding symptoms and COVID-19 exposure status that were collected by using the decision tree correlated with the likelihood of positive test results, suggesting that clinicians appropriately used the questions in the decision tree algorithm.

Healthcare Quality Improvement Analytics: An Example Using Computerized Provider Order Entry.

Evaluation of sustainability after quality improvement (QI) projects in healthcare settings is an essential part of monitoring and future QI planning. With limitations in adopting quasi-experimental study design in real-world practice, healthcare professionals find it challenging to present the sustained effect of QI changes effectively. To provide quantitative methodological approaches for demonstrating the sustainability of QI projects for healthcare professionals, we conducted data analyses based on a QI project to improve the computerized provider order entry system to reduce patients' dosing frequencies in Korea. Data were collected for 5 years: 24-month pre-intervention, 12-month intervention, and 24-month post-intervention. Then, analytic approaches including control chart, Analysis of Variance (ANOVA), and segmented regression were performed. The control chart intuitively displayed how the outcomes changed over the entire period, and ANOVA was used to test whether the outcomes differed between groups. Last, segmented regression analysis was conducted to evaluate longitudinal effects of interventions over time. We found that the impact of QI projects in healthcare settings should be initiated following the Plan-Do-Study-Act cycle and evaluated long-term effects while widening the scope of QI evaluation with sustainability. This study can serve as a guide for healthcare professionals to use a number of statistical methodologies in their QI evaluations.

Implementation of a Computerized Provider Order Entry System in a Pediatric Hospital in Canada.

The Centre Hospitalier Universitaire Sainte-Justine (Montreal, Canada) is a pediatric academic tertiary hospital that has begun the implementation of a commercial computerized provider order entry system (CPOE) in October 2019. The objectives of this paper are 1) to estimate the impact of the CPOE system on medication errors, and 2) to identify vulnerability issues related to the configuration of the CPOE system's design. Using a pre-post implementation methodology measuring medication errors captured by clinical pharmacists revealed that the implementation of a CPOE has eliminated all prescription conformity (e.g., missing fields) and legibility errors. Pharmacists have continued to detect medication errors, especially inappropriate dosing instructions, and to intervene in similar clinical situations (medication reconciliation, deprescribing, adjusting orders). Additionally, the vulnerability analysis, based on typical clinical order test cases in an inpatient pediatric setting, highlighted the need to configure a clinical decision support system that can identify inappropriate dosing instructions for pediatric patients.

The use of a metacognition and contemplation intervention in improving student abilities to recognize order entry errors.

BACKGROUND AND PURPOSE: To describe a pilot study testing a metacognition and contemplative pedagogy intervention designed to improve student abilities to identify errors on orders entered into a computerized provider order entry (CPOE) system. Educational activity and setting: Student teams worked up five patient cases and entered new orders into a CPOE system. All orders entered by teams were analyzed for errors and faculty members identified fifteen orders representing the top errors and selected these for the pre-exercise, in-class contemplation activity, and post-exercise. Course instructors instructed students to identify all errors on these orders. Students completed a pre/post-survey rating their ability to enter new orders. Two weeks later, students worked up a new patient case and entered orders into the CPOE. These orders were graded and scores were compared to the 2017 cohort to determine any differences in error rates. FINDINGS: Study participants included 205 students The average score of correctly identified errors increased from 22% on the pre-exercise to 62.8% on the post-exercise. On the survey of their skills, students rated their ability to "accurately enter medication orders into the [electronic health record] EHR" more highly after the intervention. The 2017 cohort made 73 errors on 170 orders compared to 45 errors on 165 orders by the 2018 cohort. SUMMARY: Based on improvements in student ability to identify order entry errors and overall positive student feedback, this strategy may be adopted by other educators looking to improve student identification of errors on orders entered into a CPOE system.

Management of warfarin-associated intracerebral hemorrhage before and after implementation of an order set and prospective pharmacist order verification.

Management of warfarin-associated intracerebral hemorrhage (ICH) necessitates rapid reversal of anticoagulation. Guideline-based management of warfarin-associated ICH includes timely administration of prothrombin complex concentrate (PCC) and intravenous (IV) vitamin K. In 2017, our hospital implemented an order set for warfarin reversal to facilitate computerized provider order entry (CPOE), and the pharmacy department began prospective verification and dispensing of all PCC orders for anticoagulant reversal. We sought to compare the proportion of patients who received timely, guideline-based therapy for warfarin-associated ICH before and after these changes. We conducted a single-center, retrospective cohort study of all warfarin-associated ICH patients who had an order for PCC. A total of 66 patients were included; 32 patients (pre-intervention cohort) were evaluated in the 2 year period prior to the process improvement changes, while 34 patients (post-intervention cohort) were evaluated in the 2 year period following these changes. Baseline characteristics were similar between groups. The proportion of patients receiving timely guideline-based therapy was significantly higher in the post-intervention cohort compared to the pre-intervention cohort (76.5% vs 34.4%, p < 0.001), primarily driven by increased ordering of vitamin K 10 mg IV in conjunction with PCC in the post-intervention cohort. Our results indicate that implementation of an order set to assist with CPOE, in addition to prospective pharmacist verification of PCC orders, leads to increased adherence to guideline-based management of warfarin-associated ICH.

Impact of Computer Calculation Program on Quality of Individualized Parenteral Nutrition and Selected Clinical Parameters of Extremely Low-Birth-Weight Infants.

BACKGROUND: The aim of the study was to assess the effects of computerized provider order entry (CPOE) for parenteral nutrition (PN) on selected clinical parameters of extremely low-birth-weight (ELBW) neonates in a tertiary neonatal intensive care unit. METHODS: This study was a retrospective data analysis of preterm infants born over a 1-year period before and after introduction of CPOE. PN composition during the first 2 weeks of life, change in weight, head circumference and body length z-scores were assessed. Duration of PN and selected neonatal complications were compared. Logistic regression was used to adjust for confounding variables (sex, birth weight, and birth-gestational age). RESULTS: Ninety-four patients in 2 equal groups were analyzed. Birth weight (median 810 vs 825 g) and gestational age (27 vs 27 weeks) were comparable. After adjustment for confounding variables, on the first and seventh day of life, significantly more energy (P < .001), protein (P < .001), lipid (P < .03), and carbohydrate (P < .02) were administered in the CPOE group than in the manually calculated (MC) prescriptions group. The CPOE group had lower weight loss (P < .001), a significant improvement in linear growth, and faster regain of birth weight (P < .01) compared with the MC group. CONCLUSION: The CPOE positively influences the quality of PN in ELBW infants. It also significantly reduced initial weight loss, time to regain birth weight, and linear growth. It may also have beneficial effects on selected clinical outcomes, which requires further study.

Medication errors related to computerized provider order entry systems in hospitals and how they change over time: A narrative review.

BACKGROUND: Evaluations of computerized provider order entry (CPOE) systems have revealed that reductions in certain types of medication errors occur simultaneously with the emergence of system-related errors - errors that are unlikely or not possible to occur with the use of paper-based medication charts. System-related errors appear to persist many years post-implementation of CPOE, although little is known about whether the types and rates of system-related errors that occur immediately following CPOE implementation are similar to those that endure or emerge after years of system use. OBJECTIVE: To analyze and synthesize the literature on system-related errors, specifically in relation to the length of time that CPOE systems have been in use, to determine what is currently known about how system-related errors change over time. METHODS: A literature search was undertaken using the PubMed database to identify English language articles published between January 2005 and March 2020 that provided original data on system-related errors resulting from CPOE system use. Studies were included if they provided results on system-related errors and information relating to the length of time that CPOE had been in use. RESULTS: Thirty-one studies met the inclusion criteria for this narrative review. System-related errors were identified and described during short, medium and long-term use of CPOE systems, but no single study examined how errors changed over time. In comparing findings across studies, results suggest that system-related errors persist with long-term use of CPOE systems, although likely to occur at a reduced rate. CONCLUSIONS: This review has highlighted a significant gap in knowledge on how system-related errors change over time. Determining what and when system-related errors occur and the system factors that contribute to their occurrence at different time points after CPOE implementation is necessary for the future prevention and mitigation of these errors.

Trends in the use of computerized physician order entry by health-system affiliated ambulatory clinics in the United States, 2014-2016.

BACKGROUND: Computerized provider order entry (CPOE) can help providers deliver better quality care. We aimed to understand recent trends in use of CPOE by health system-affiliated ambulatory clinics. METHODS: We analyzed longitudinal data (2014-2016) for 19,109 ambulatory clinics that participated in all 3 years of the Healthcare Information and Management Systems Society Analytics survey to assess use of CPOE and identify characteristics of clinics associated with CPOE use. We calculated descriptive statistics to examine overall trends in use, location of order entry (bedside vs. clinical station), and system-level use CPOE across all clinics. We used linear probability models to explore the association between clinic characteristics (practice size, practice type, and health system type) and two outcomes of interest: CPOE use at any point between 2014 and 2016, and CPOE use beginning in 2015 or 2016. RESULTS: Between 2014 and 2016, use of CPOE increased more than 9 percentage points from 58 to 67%. Larger clinics and those affiliated with multi-hospital health systems were more likely to have reported use of CPOE. We found no difference in CPOE use by primary care versus specialty care clinics. When used, most clinics reported using CPOE for most or all of their orders. Health systems that used CPOE usually did so for all system-affiliated clinics. CONCLUSIONS: Small practice size or not being part of a multi-hospital system are associated with lower use of CPOE between 2014 and 2016. Less than optimal use in these environments may be harming patient outcomes.

Barriers and Facilitators to Implementation of Medication Decision Support Systems in Electronic Medical Records: Mixed Methods Approach Based on Structural Equation Modeling and Qualitative Analysis.

BACKGROUND: Adverse drug events (ADEs) resulting from medication error are some of the most common causes of iatrogenic injuries in hospitals. With the appropriate use of medication, ADEs can be prevented and ameliorated. Efforts to reduce medication errors and prevent ADEs have been made by implementing a medication decision support system (MDSS) in electronic health records (EHRs). However, physicians tend to override most MDSS alerts. OBJECTIVE: In order to improve MDSS functionality, we must understand what factors users consider essential for the successful implementation of an MDSS into their clinical setting. This study followed the implementation process for an MDSS within a comprehensive EHR system and analyzed the relevant barriers and facilitators. METHODS: A mixed research methodology was adopted. Data from a structured survey and 15 in-depth interviews were integrated. Structural equation modeling was conducted for quantitative analysis of factors related to user adoption of MDSS. Qualitative analysis based on semistructured interviews with physicians was conducted to collect various opinions on MDSS implementation. RESULTS: Quantitative analysis revealed that physicians' expectations regarding ease of use and performance improvement are crucial. Qualitative analysis identified four significant barriers to MDSS implementation: alert fatigue, lack of accuracy, poor user interface design, and lack of customizability. CONCLUSIONS: This study revealed barriers and facilitators to the implementation of MDSS. The findings can be applied to upgrade MDSS in the future.