Computerised physician order entry-related medication errors: analysis of reported errors and vulnerability testing of current systems

An Analysis of Incident Reports Related to Electronic Medication Management: How They Change Over Time

OBJECTIVE

Electronic medication management (EMM) systems have been shown to introduce new patient safety risks that were not possible, or unlikely to occur, with the use of paper charts. Our aim was to examine the factors that contribute to EMM-related incidents and how these incidents change over time with ongoing EMM use.

METHODS

Incidents reported at 3 hospitals between January 1, 2010, and December 31, 2019, were extracted using a keyword search and then screened to identify EMM-related reports. Data contained in EMM-related incident reports were then classified as unsafe acts made by users and the latent conditions contributing to each incident.

RESULTS

In our sample, 444 incident reports were determined to be EMM related. Commission errors were the most frequent unsafe act reported by users (n = 298), whereas workarounds were reported in only 13 reports. User latent conditions (n = 207) were described in the highest number of incident reports, followed by conditions related to the organization (n = 200) and EMM design (n = 184). Over time, user unfamiliarity with the system remained a key contributor to reported incidents. Although fewer articles to electronic transfer errors were reported over time, incident reports related to the transfer of information between different computerized systems increased as hospitals adopted more clinical information systems.

CONCLUSIONS

Electronic medication management-related incidents continue to occur years after EMM implementation and are driven by design, user, and organizational conditions. Although factors contribute to reported incidents in varying degrees over time, some factors are persistent and highlight the importance of continuously improving the EMM system and its use.

Ability of machine-learning based clinical decision support system to reduce alert fatigue, wrong-drug errors, and alert users about look alike, sound alike medication

BACKGROUND AND OBJECTIVE

The overall benefits of using clinical decision support systems (CDSSs) can be restrained if physicians inadvertently ignore clinically useful alerts due to "alert fatigue" caused by an excessive number of clinically irrelevant warnings. Moreover, inappropriate drug errors, look-alike/sound-alike (LASA) drug errors, and problem list documentation are common, costly, and potentially harmful. This study sought to evaluate the overall performance of a machine learning-based CDSS (MedGuard) for triggering clinically relevant alerts, acceptance rate, and to intercept inappropriate drug errors as well as LASA drug errors.

METHODS

We conducted a retrospective study that evaluated MedGuard alerts, the alert acceptance rate, and the rate of LASA alerts between July 1, 2019, and June 31, 2021, from outpatient settings at an academic hospital. An expert pharmacist checked the suitability of the alerts, rate of acceptance, wrong-drug errors, and confusing drug pairs.

RESULTS

Over the two-year study period, 1,206,895 prescriptions were ordered and a total of 28,536 alerts were triggered (alert rate: 2.36 %). Of the 28,536 alerts presented to physicians, 13,947 (48.88 %) were accepted. A total of 8,014 prescriptions were changed/modified (28.08 %, 8,014/28,534) with the most common reasons being adding and/or deleting diseases (52.04 %, 4,171/8,014), adding and/or deleting drugs (21.89 %, 1,755/8,014) and others (35.48 %, 2,844/ 8,014). However, the rate of drug error interception was 1.64 % (470 intercepted errors out of 28,536 alerts), which equates to 16.4 intercepted errors per 1000 alerted orders.

CONCLUSION

This study shows that machine learning based CDSS, MedGuard, has an ability to improve patients' safety by triggering clinically valid alerts. This system can also help improve problem list documentation and intercept inappropriate drug errors and LASA drug errors, which can improve medication safety. Moreover, high acceptance of alert rates can help reduce clinician burnout and adverse events.

[Translation and adaptation of a tool prescribing errors related to computerized physician order entry coding to the French hospital background]

Prescribing errors related to computerized physician order entry are current and may have serious consequences for patients. They can be detected by pharmacists during prescriptions analysis and lead to pharmacist's interventions. In France, few monocentric studies have studied Pharmacist Interventions triggered by prescribing errors identified as System-Related Errors (PISREs) in French hospitals. However, their respective analysis method prevent any comparison between computerized physician order entry systems in order to identify the safest and rule out the most dangerous. A computerized physician prescribing error related to the software is characterized by its causes, consequences and mechanism of occurrence. US researchers have developed and validated a tool to classify and illustrate these three characteristics. The objectives of this article are to present this tool, to propose a French adaptation and to describe the perspectives analyze and understand prescription errors related to computerized physician order entry based on data of Act-IP©. The adaptation was performed using PISREs extracted from the Act-IP© observatory of the French Society of Clinical Pharmacy. Each item of the codification is illustrated with an example of PI. We are considering a training plan in order to allow wide use of this tool. Once adopted this tool, the next step will be to organize a prospective multicenter study including as many computerized prescription order entry systems as possible. The aim of this study will be identifying the safest systems. Consequently, it will then be possible to have arguments to qualify the most dangerous and thus propose their withdrawal from the market.

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.

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.

Medical and nursing clinician perspectives on the usability of the hospital electronic medical record: A qualitative analysis

BACKGROUND

Electronic medical records (EMRs) have been widely implemented in Australian hospitals. Their usability and design to support clinicians to effectively deliver and document care is essential, as is their impact on clinical workflow, safety and quality, communication, and collaboration across health systems. Perceptions of, and data about, usability of EMRs implemented in Australian hospitals are key to successful adoption.

OBJECTIVE

To explore perspectives of medical and nursing clinicians on EMR usability utilising free-text data collected in a survey.

METHOD

Qualitative analysis of one free-text optional question included in a web-based survey. Respondents included medical and nursing/midwifery professionals in Australian hospitals (85 doctors and 27 nurses), who commented on the usability of the main EMR used.

RESULTS

Themes identified related to the status of EMR implementation, system design, human factors, safety and risk, system response time, and stability, alerts, and supporting the collaboration between healthcare sectors. Positive factors included ability to view information from any location; ease of medication documentation; and capacity to access diagnostic test results. Usability concerns included lack of intuitiveness; complexity; difficulties communicating with primary and other care sectors; and time taken to perform clinical tasks.

CONCLUSION

If the benefits of EMRs are to be realised, there are good reasons to address the usability challenges identified by clinicians. Easy solutions that could improve the usability experience of hospital-based clinicians include resolving sign-on issues, use of templates, and more intelligent alerts and warnings to avoid errors.

IMPLICATIONS

These essential improvements to the usability of the EMR, which are the foundation of the digital health system, will enable hospital clinicians to deliver safer and more effective health care.

Shape Matters: A Neglected Feature of Medication Safety : Why Regulating the Shape of Medication Containers Can Improve Medication Safety

This paper aims to highlight how to reduce medication errors through the implementation of human factors science to the design features of medication containers. Despite efforts to employ automation for increased safety and decreased workload, medication administration in hospital wards is still heavily dependent on human operators (pharmacists, nurses, physicians, etc.). Improving this multi-step process requires its being studied and designed as an interface in a complex socio-technical system. Human factors engineering, also known as ergonomics, involves designing socio-technical systems to improve overall system performance, and reduces the risk of system, and in particular, operator, failures. The incorporation of human factors principles into the design of the work environment and tools that are in use during medication administration could improve this process. During periods of high workload, the cognitive effort necessary to work through a very demanding process may overwhelm even expert operators. In such conditions, the entire system should facilitate the human operator's high level of performance. Regarding medications, clinicians should be provided with as many perceptual cues as possible to facilitate medication identification. Neglecting the shape of the container as one of the features that differentiates between classes of medications is a lost opportunity to use a helpful characteristic, and medication administration failures that happen in the absence of such intentional design arise from "designer error" rather than "user error". Guidelines that define a container's shape for each class of medication would compel pharmaceutical manufacturers to be compatible and would eliminate the confusion that arises when a hospital changes the supplier of a given medication.

Workarounds in Electronic Health Record Systems and the Revised Sociotechnical Electronic Health Record Workaround Analysis Framework: Scoping Review

BACKGROUND

Electronic health record (EHR) system users devise workarounds to cope with mismatches between workflows designed in the EHR and preferred workflows in practice. Although workarounds appear beneficial at first sight, they frequently jeopardize patient safety, the quality of care, and the efficiency of care.

OBJECTIVE

This review aims to aid in identifying, analyzing, and resolving EHR workarounds; the Sociotechnical EHR Workaround Analysis (SEWA) framework was published in 2019. Although the framework was based on a large case study, the framework still required theoretical validation, refinement, and enrichment.

METHODS

A scoping literature review was performed on studies related to EHR workarounds published between 2010 and 2021 in the MEDLINE, Embase, CINAHL, Cochrane, or IEEE databases. A total of 737 studies were retrieved, of which 62 (8.4%) were included in the final analysis. Using an analytic framework, the included studies were investigated to uncover the rationales that EHR users have for workarounds, attributes characterizing workarounds, possible scopes, and types of perceived impacts of workarounds.

RESULTS

The SEWA framework was theoretically validated and extended based on the scoping review. Extensive support for the pre-existing rationales, attributes, possible scopes, and types of impact was found in the included studies. Moreover, 7 new rationales, 4 new attributes, and 3 new types of impact were incorporated. Similarly, the descriptions of multiple pre-existing rationales for workarounds were refined to describe each rationale more accurately.

CONCLUSIONS

SEWA is now grounded in the existing body of peer-reviewed empirical evidence on EHR workarounds and, as such, provides a theoretically validated and more complete synthesis of EHR workaround rationales, attributes, possible scopes, and types of impact. The revised SEWA framework can aid researchers and practitioners in a wider range of health care settings to identify, analyze, and resolve workarounds. This will improve user-centered EHR design and redesign, ultimately leading to improved patient safety, quality of care, and efficiency of care.

Electronic Medication Management Systems: Analysis of Enhancements to Reduce Errors and Improve Workflow

BACKGROUND

Electronic medication management (eMM) has been shown to reduce medication errors; however, new safety risks have also been introduced that are associated with system use. No research has specifically examined the changes made to eMM systems to mitigate these risks.

OBJECTIVES

To (1) identify system-related medication errors or workflow blocks that were the target of eMM system updates, including the types of medications involved, and (2) describe and classify the system enhancements made to target these risks.

METHODS

In this retrospective qualitative study, documents detailing updates made from November 2014 to December 2019 to an eMM system were reviewed. Medication-related updates were classified according to "rationale for changes" and "changes made to the system."

RESULTS

One hundred and seventeen updates, totaling 147 individual changes, were made to the eMM system over the 4-year period. The most frequent reasons for changes being made to the eMM were to prevent medication errors (24% of reasons), optimize workflow (22%), and support "work as done" on paper (16%). The most frequent changes made to the eMM were options added to lists (14% of all changes), extra information made available on the screen (8%), and the wording or phrasing of text modified (8%). Approximately a third of the updates (37%) related to high-risk medications. The reasons for system changes appeared to vary over time, as eMM functionality and use expanded.

CONCLUSION

To our knowledge, this is the first study to systematically review and categorize system updates made to overcome new safety risks associated with eMM use. Optimization of eMM is an ongoing process, which changes over time as users become more familiar with the system and use is expanded to more sites. Continuous monitoring of the system is necessary to detect areas for improvement and capitalize on the benefits an electronic system can provide.

Characteristics of pharmacist's interventions triggered by prescribing errors related to computerised physician order entry in French hospitals: a cross-sectional observational study

OBJECTIVES

Computerised physician order entry (CPOE) systems facilitate the review of medication orders by pharmacists. Reports have emerged that show conception flaws or the misuse of CPOE systems generate prescribing errors. We aimed to characterise pharmacist interventions (PIs) triggered by prescribing errors identified as system-related errors (PISREs) in French hospitals.

DESIGN

This was a cross-sectional observational study based on PIs prospectively documented in the Act-IP observatory database from January 2014 to December 2018.

SETTING

PISREs from 319 French computerised healthcare facilities were analysed.

PARTICIPANTS

Among the 319 French hospitals, 232 (72.7%) performed SRE interventions, involving 652 (51%) pharmacists.

RESULTS

Among the 331 678 PIs recorded, 27 058 were qualified as due to SREs (8.2%). The main drug-related problems associated with PISREs were supratherapeutic (27.5%) and subtherapeutic dosage (17.2%), non-conformity with guidelines/contraindications (22.4%) and improper administration (17.9%). The PI prescriber acceptation rate was 78.9% for SREs vs 67.6% for other types of errors. The PISRE ratio was estimated relative to the total number of PIs. Concerning the certification status of CPOE systems, the PISRE ratio was 9.4% for non-certified systems vs 5.5% for certified systems (p<0.001). The PISRE ratio for senior pharmacists was 9.2% and that for pharmacy residents 5.4% (p<0.001). Concerning prescriptions made by graduate prescribers and those made by residents, the PISRE ratio was 8.4% and 7.8%, respectively (p<0.001).

CONCLUSION

Computer-related prescribing errors are common. The PI acceptance rate by prescribers was higher than that observed for PIs that were not CPOE related. This suggests that physicians consider the potential clinical consequences of SREs for patients to be more frequently serious than interventions unrelated to CPOE. CPOE medication review requires continual pharmacist diligence to catch these errors. The significantly lower PISRE ratio for certified software should prompt patient safety agencies to undertake studies to identify the safest software and discard software that is potentially dangerous.

Predicting inpatient pharmacy order interventions using provider action data

Objective

The widespread deployment of electronic health records (EHRs) has introduced new sources of error and inefficiencies to the process of ordering medications in the hospital setting. Existing work identifies orders that require pharmacy intervention by comparing them to a patient’s medical records. In this work, we develop a machine learning model for identifying medication orders requiring intervention using only provider behavior and other contextual features that may reflect these new sources of inefficiencies.

Materials and Methods

Data on providers’ actions in the EHR system and pharmacy orders were collected over a 2-week period in a major metropolitan hospital system. A classification model was then built to identify orders requiring pharmacist intervention. We tune the model to the context in which it would be deployed and evaluate global and local feature importance.

Results

The resultant model had an area under the receiver-operator characteristic curve of 0.91 and an area under the precision-recall curve of 0.44.

Conclusions

Providers’ actions can serve as useful predictors in identifying medication orders that require pharmacy intervention. Careful model tuning for the clinical context in which the model is deployed can help to create an effective tool for improving health outcomes without using sensitive patient data.

The use of narrative electronic prescribing instructions in pharmacoepidemiology: A scoping review for the International Society for Pharmacoepidemiology

Narrative electronic prescribing instructions (NEPIs) are text that convey information on the administration or co‐administration of a drug as directed by a prescriber. For researchers, NEPIs have the potential to advance our understanding of the risks and benefits of medications in populations; however, due to their unstructured nature, they are not often utilized. The goal of this scoping review was to evaluate how NEPIs are currently employed in research, identify opportunities and challenges for their broader application, and provide recommendations on their future use. The scoping review comprised a comprehensive literature review and a survey of key stakeholders. From the literature review, we identified 33 primary articles that described the use of NEPIs. The majority of articles (n = 19) identified issues with the quality of information in NEPIs compared with structured prescribing information; nine articles described the development of novel algorithms that performed well in extracting information from NEPIs, and five described the used of manual or simpler algorithms to extract prescribing information from NEPIs. A survey of 19 stakeholders indicated concerns for the quality of information in NEPIs and called for standardization of NEPIs to reduce data variability/errors. Nevertheless, stakeholders believed NEPIs present an opportunity to identify prescriber's intent for the prescription and to study temporal treatment patterns. In summary, NEPIs hold much promise for advancing the field of pharmacoepidemiology. Researchers should take advantage of addressing important questions that can be uniquely answered with NEPIs, but exercise caution when using this information and carefully consider the quality of the data.

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.

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.

The Effect of Regimen Frequency Simplification on Provider Order Generation: A Quasi-Experimental Study in a Korean Hospital

The multiplicity of dosing frequencies that are attached to medication orders poses a challenge to patients regarding adhering to their medication regimens and healthcare professionals in maximizing the efficiencies of health care service delivery. A multidisciplinary team project was performed to simplify medication regimens to improve the computerized physician order entry (CPOE) system to reduce the dosing frequencies for patients who were discharged from the hospital. A 36-month pre-test–post-test study was performed, including 12-month pre-intervention, 12-month intervention, and 12-month post-intervention periods. Two-pronged strategies, including regimen standardization and prioritization, were devised to evaluate the dosing frequencies and prescribing efficiency. The results showed that the standardized menu reduced the dosing frequencies from 4.3 ± 2.2 per day in the pre-intervention period to 3.5 ± 1.8 per day in the post-intervention period (p < 0.001). In addition, the proportion of patients taking medications five or more times per day decreased from 40.8% to 20.7% (p < 0.001). After prioritizing the CPOE dosing regimen, the number of pull-down options that were available reflected an improvement in the prescribing efficiency. Our findings indicate that concerted efforts in improving even a simple change on the CPOE screen via standardization and prioritization simplified the dosing frequencies for patients and improved the physicians’ prescribing process.

The tradeoffs between safety and alert fatigue: Data from a national evaluation of hospital medication-related clinical decision support

OBJECTIVE

The study sought to evaluate the overall performance of hospitals that used the Computerized Physician Order Entry Evaluation Tool in both 2017 and 2018, along with their performance against fatal orders and nuisance orders.

MATERIALS AND METHODS

We evaluated 1599 hospitals that took the test in both 2017 and 2018 by using their overall percentage scores on the test, along with the percentage of fatal orders appropriately alerted on, and the percentage of nuisance orders incorrectly alerted on.

RESULTS

Hospitals showed overall improvement; the mean score in 2017 was 58.1%, and this increased to 66.2% in 2018. Fatal order performance improved slightly from 78.8% to 83.0% (P < .001), though there was almost no change in nuisance order performance (89.0% to 89.7%; P = .43). Hospitals alerting on one or more nuisance orders had a 3-percentage-point increase in their overall score.

DISCUSSION

Despite the improvement of overall scores in 2017 and 2018, there was little improvement in fatal order performance, suggesting that hospitals are not targeting the deadliest orders first. Nuisance order performance showed almost no improvement, and some hospitals may be achieving higher scores by overalerting, suggesting that the thresholds for which alerts are fired from are too low.

CONCLUSIONS

Although hospitals improved overall from 2017 to 2018, there is still important room for improvement for both fatal and nuisance orders. Hospitals that incorrectly alerted on one or more nuisance orders had slightly higher overall performance, suggesting that some hospitals may be achieving higher scores at the cost of overalerting, which has the potential to cause clinician burnout and even worsen safety.

Comparison of Accuracy and Speed in Computer-Assisted Versus Conventional Methods for Pediatric Drug Dose Calculation: A Scenario-Based Randomized Controlled Trial

Pediatric emergency care is prone to medication errors in many aspects including prescriptions, administrations, and monitoring. This study was designed to assess the effects of computer-assisted calculation on reducing error rates and time to prescription of specific emergency drugs. We conducted a randomized crossover experimental study involving emergency medicine residents and paramedics in the Department of Emergency Medicine at Ramathibodi Hospital. Participants calculated and prescribed medications using both the conventional method and a computer-assisted method. Medication names, dosages, routes of administration, and time to prescription were collected and analyzed using logistic and quantile regression analysis. Of 562 prescriptions, we found significant differences between computer-assisted calculation and the conventional method in the calculation accuracy of overall medications, pediatric advanced life support (PALS) drugs, and sedative drugs (91.17% vs 67.26%, 86.54% vs 46.15%, and 89.29% vs 57.86%, respectively, P < .001). Moreover, there were significant differences in calculation time for overall medications, PALS drugs and sedative drugs (25 vs 47 seconds, P < .001), and computer-assisted calculation significantly decreased the gap in medication errors between doctors and paramedics (P < .001). We conclude that computer-assisted prescription calculation provides benefits over the conventional method in accuracy of all medication dosages and in time required for calculation, while enhancing the drug prescription ability of paramedics.

Categorization of Medication Safety Errors in Ambulatory Electronic Health Records

Preventable medication errors continue to affect the quality and consistency in the delivery of care. While numerous studies on medication safety have been performed in the inpatient setting, a review of ambulatory patient safety by the American Medical Association found that medication safety errors were the most frequent safety problems in the outpatient arena. The leading cause of ambulatory safety problems, adverse drug events (ADEs), are common, with estimates of more than 2 million ADEs each year in the ambulatory Medicare population alone, and these events are frequently preventable. We conducted an environmental scan that allowed us to create our own categorization schema of medication safety errors in electronic healthcare records (EHRs) found in the outpatient setting and observed which of these were additionally supported in the literature. This study combines data from the California Hospital Patient Safety Organization (CHPSO), with several key articles in the area of medication errors in the EHR era. Method: To best utilize the various EHR ambulatory medication events submitted into CHPSO’s database, we chose to create a framework to bucket the near misses or adverse events (AEs) submitted to the database. This newly created categorization scheme was based on our own drafted categorization labels of events, after a high-level review, and from two leading articles on physician order entry. Additionally, we conducted a literature review of computerized provider order entry (CPOE) medication errors in the ambulatory setting. Within the newly created categorization scheme, we organized the articles based on issues addressed so we could see areas that were supported by the literature and what still needed to be researched. Results: We initially screened the CHPSO database for ambulatory safety events and found 25,417 events. Based on those events, an initial review was completed, and 19,242 events were found in the “Medication or Other Substance” and “Other” categories, in which the EHR appeared to have been a potential contributing factor. This review identified a subset of 2,236 events that were then reviewed. One hundred events were randomly selected for further review to identify common categories. The most common categories in which errors occurred were orders in order sets and plans (n=12) and orders crossing or not crossing encounters (n=12), incorrect order placed on correct patient (n=10), orders missing (n=8), standing orders (n=8), manual data entry errors (n=6), and future orders (n=6). Conclusion: There were several common themes seen in this analysis of ambulatory medication safety errors related to the EHR. Common among them were incorrect orders consisting of examples such as dose errors or ordering the wrong medication. The manual data entry errors consisted of height or weight being entered incorrectly or entering the wrong diagnostic codes. Lastly, different sources of medication safety information demonstrate a diversity of errors in ambulatory medication safety. This confirms the importance of considering more than one source when attempting to comprehensively describe ambulatory medication safety errors.

Online Supplement to “Categorization of Medication Safety Errors in Ambulatory Electronic Health Records”

This supplementary material has been provided by the authors to give readers additional information about their work.

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.

Categorizing and understanding medication errors in hospital pharmacy in relation to human factors

BACKGROUND

Medication errors (MEs) in hospital settings are attributed to various factors including the human factors. Human factors researches are aiming to implement the knowledge regarding human nature and their interaction with surrounding equipment and environment to design efficient and safe systems. Human Factors Frameworks (HFF) developed awareness regarding main system's components that influence healthcare system and patients' safety. An in-depth evaluation of human factors contributing to medication errors in the hospital pharmacy is crucial to prevent such errors.

OBJECTIVE

This study, therefore, aims to identify and categorize the human factors of MEs in hospital pharmacy using the Human Factors Framework (HFF).

METHOD

A qualitative study conducted in King Saud Medical City, Riyadh, Kingdom of Saudi Arabia. Data collection was carried out in two stages; the first stage was the semi-structured interview with the pharmacist or technician involved in the medication error. Then, occupational burnout and personal fatigue scores of participants were assessed. Data analysis was done using thematic analysis.

RESULTS

A total of 19 interviews were done with pharmacists and technicians. Themes were categorized using HFF into five categories; individual, organization and management, task, work, and team factors. Examples of these themes are poor staff competency, insufficient staff support, Lack of standardization, workload, and prescriber behaviour respectively. Scores of fatigue, work disengagement, and emotional exhaustion are correlating with medium fatigue, high work disengagement, and high emotional exhaustion, respectively.

CONCLUSIONS

The study provided a unique insight into the contributing factors to MEs in the hospital pharmacy. Emotional stress, lack of motivation, high workload, poor communication, and missed patient information on the information system, are examples of the human factors contributing to medication errors. Our study found that among those factors, organizational factors had a major contribution to medication safety and staff wellbeing.

Computerized provider order entry-related medication errors among hospitalized patients: An integrative review

The Institute of Medicine estimates that 7,000 lives are lost yearly as a result of medication errors. Computerized physician and/or provider order entry was one of the proposed solutions to overcome this tragic issue. Despite some promising data about its effectiveness, it has been found that computerized provider order entry may facilitate medication errors.The purpose of this review is to summarize current evidence of computerized provider order entry -related medication errors and address the sociotechnical factors impacting the safe use of computerized provider order entry. By using PubMed and Google Scholar databases, a systematic search was conducted for articles published in English between 2007 and 2019 regarding the unintended consequences of computerized provider order entry and its related medication errors. A total of 288 articles were screened and categorized based on their use within the review. One hundred six articles met our pre-defined inclusion criteria and were read in full, in addition to another 27 articles obtained from references. All included articles were classified into the following categories: rates and statistics on computerized provider order entry -related medication errors, types of computerized provider order entry -related unintended consequences, factors contributing to computerized provider order entry failure, and recommendations based on addressing sociotechnical factors. Identifying major types of computerized provider order entry -related unintended consequences and addressing their causes can help in developing appropriate strategies for safe and effective computerized provider order entry. The interplay between social and technical factors can largely affect its safe implementation and use. This review discusses several factors associated with the unintended consequences of this technology in healthcare settings and presents recommendations for enhancing its effectiveness and safety within the context of sociotechnical factors.

Electronic Health Record-Related Events in Medical Malpractice Claims

Background

There is widespread agreement that the full potential of health information technology (health IT) has not yet been realized and of particular concern are the examples of unintended consequences of health IT that detract from the safety of health care or from the use of health IT itself. The goal of this project was to obtain additional information on these health IT–related problems, using a mixed methods (qualitative and quantitative) analysis of electronic health record–related harm in cases submitted to a large database of malpractice suits and claims.

Methods

Cases submitted to the CRICO claims database and coded during 2012 and 2013 were analyzed. A total of 248 cases (<1%) involving health IT were identified and coded using a proprietary taxonomy that identifies user- and system-related sociotechnical factors. Ambulatory care accounted for most of the cases (146 cases). Cases were most typically filed as a result of an error involving medications (31%), diagnosis (28%), or a complication of treatment (31%). More than 80% of cases involved moderate or severe harm, although lethal cases were less likely in cases from ambulatory settings. Etiologic factors spanned all of the sociotechnical dimensions, and many recurring patterns of error were identified.

Conclusions

Adverse events associated with health IT vulnerabilities can cause extensive harm and are encountered across the continuum of health care settings and sociotechnical factors. The recurring patterns provide valuable lessons that both practicing clinicians and health IT developers could use to reduce the risk of harm in the future. The likelihood of harm seems to relate more to a patient's particular situation than to any one class of error.

Veterans Health Administration Primary Care Provider Adherence to Prescribing Guidelines for Systemic Hormone Therapy in Menopausal Women

BACKGROUND

Systemic hormone therapy (HT) is effective for treating menopausal symptoms but also confers risks. Therefore, experts have developed clinical guidelines for its use.

PURPOSE

We assessed primary care guideline adherence in prescribing systemic HT, and associations between adherence and provider characteristics, in four Veterans Health Administration (VA) facilities.

METHODS

We abstracted medical records associated with new and renewal systemic HT prescriptions examining adherence to guidelines for documenting indications and contraindications; prescribing appropriate dosages; and prescribing progesterone.

RESULTS

Average guideline adherence was 58%. Among new prescriptions, 74% documented a guideline-adherent indication and 28% documented absence of contraindications. Among renewals, 39% documented a guideline-adherent indication. In prescribing an appropriate dose, 45% of new prescriptions were guideline-adherent. Among renewal prescriptions with conjugated equine estrogen doses ≥0.625 mg or equivalent, 16% documented the dosing rationale. Among 116 prescriptions for systemic estrogen in women with a uterus, progesterone was not prescribed in 8.

CONCLUSIONS

Guideline adherence in prescribing systemic HT was low among VA primary care providers. Failures to coprescribe progesterone put women at increased risk for endometrial cancer.

IMPLICATIONS

Intervention development is urgently needed to improve guideline adherence among primary care prescribers of systemic HT for menopause. Similar assessments should be conducted in community settings.

Interventions designed to improve the safety and quality of therapeutic anticoagulation in an inpatient electronic medical record

IMPORTANCE

Anticoagulants are high-risk medications with the potential to cause significant patient harm or death. Digital transformation is occurring in hospital practice and it is essential to implement effective, evidence-based strategies for these medications in an electronic medical record (EMR).

OBJECTIVE

To systematically appraise the literature to determine which EMR interventions have improved the safety and quality of therapeutic anticoagulation in an inpatient hospital setting.

METHODS

PubMed, Embase, CINAHL, and the International Pharmaceutical Database were searched for suitable publications. Articles that met eligibility criteria up to September 2018 were included. The review was registered with PROSPERO (CRD42018104899). The web-based software platform Covidence® was used for screening and data extraction. Studies were grouped according to the type of intervention and the outcomes measured. Where relevant, a bias assessment was performed.

RESULTS

We found 2624 candidate articles and 27 met inclusion criteria. They included 3 randomised controlled trials, 4 cohort studies and 20 pre/post observational studies. There were four major interventions; computerised physician order entry (CPOE) (n = 4 studies), clinical decision support system (CDSS) methods (n = 21), dashboard utilisation (n = 1) and EMR implementation in general (n = 1). Seven outcomes were used to summarise the study results. Most research focused on prescribing or documentation compliance (n = 18). The remaining study outcome measures were: medication errors (n = 9), adverse drug events (n = 5), patient outcomes (morbidity/mortality/length of hospital stay/re-hospitalisation) (n = 5), quality use of anticoagulant (n = 4), end-user acceptance (n = 4), cost effectiveness (n = 1).

CONCLUSION

Despite the research cited, limited benefits have been demonstrated to date. It appears healthcare organisations are yet to determine optimal, evidence-based-methods to improve EMR utilisation. Further evaluation, collaboration and work are necessary to measure and leverage the potential benefits of digital health systems. Most research evaluating therapeutic anticoagulation management within an EMR focused on prescribing or documentation compliance, with less focus on clinical impact to the patient or cost effectiveness. Evidence suggests that CPOE in conjunction with CDSS is needed to effectively manage therapeutic anticoagulation. Targets for robust research include the integration of 'stealth' alerts, nomograms into digital systems and the use of dashboards within clinical practice.

Electronic prescription: frequency and severity of medication errors

OBJECTIVE

To assess the frequency and severity of prescriptions errors with potentially dangerous drugs (heparin and potassium chloride for injection concentrate) before and after the introduction of a computerized provider order entry (CPOE) system.

METHODS

This is a retrospective study that compared errors in manual/pre-typed prescriptions in 2007 (Stage 1) with CPOE prescriptions in 2014 (Stage 2) (Total = 1,028 prescriptions), in two high-complexity hospitals of Belo Horizonte, Brasil.

RESULTS

An increase of 25% in the frequency of errors in Hospital 1 was observed after the intervention (p<0.001). In contrast, a decreased error frequency of 85% was observed in Hospital 2 (p<0.001). Regarding potassium chloride, the error rate remained unchanged in Hospital 1 (p>0.05). In Hospital 2, a significant decrease was recorded in Stage 2 (p<0.001). A reduced error severity with heparin (p<0.001) was noted, while potassium chloride-related prescription severity remain unchanged (p> 0.05).

CONCLUSIONS

The frequency and severity of medication errors after the introduction of CPOE was affected differently in the two hospitals, which shows a need for thorough observation when the prescription system is modified. Control of new potential errors introduced and their causes for the adoption of measures to prevent these events must be in place during and after the implementation of this technology.

University of California Technology Wellness Index: A Physician-Centered Framework to Assess Technologies' Impact on Physician Well-Being

Technology is increasingly being incorporated into the everyday workflows of physicians. There are concerns that electronic medical records and other digital technologies will contribute to the growing epidemic of physician burnout. However, some technologies, such as telemedicine, have demonstrated positive effects on physician health by saving time, enhancing work-life balance, improving quality, and restoring more control and flexibility to their practices. Organizations often lack data to evaluate the impact of technologies on physician health. The University of California Technology Wellness Index is a framework that provides a fast, systematic, physician-centered method to assess the impact of technology on physician well-being.

Electronic prescribing in paediatric secondary care: are harmful errors prevented?

OBJECTIVE

The aim of this research was to ascertain the effectiveness of current electronic prescribing (EP) systems to prevent a standardised set of paediatric prescribing errors likely to cause harm if they reach the patient.

DESIGN

Semistructured survey.

SETTING

UK hospitals using EP in the paediatric setting.

OUTCOME MEASURES

Number and type of erroneous orders able to be prescribed, and the level of clinical decision support (CDS) provided during the prescribing process.

RESULTS

90.7% of the erroneous orders were able to be prescribed across the seven different EP systems tested. Levels of CDS varied between systems and between sites using the same system.

CONCLUSIONS

EP systems vary in their ability to prevent harmful prescribing errors in the hospital paediatric setting. Differences also occur between sites using the same system, highlighting the importance of how a system is set up and optimised.

Patient-Generated Health Data in Surgical Site Infection: Changing Clinical Workflow and Care Delivery

Background: The patient's history of present illness provides an important part of the data with which clinicians diagnose and treat. Once surgical patients are discharged, the ability to incorporate direct observation requires coordinating patient and provider for a clinical visit. Mobile technologies offer the ability to gather and organize the patient's history, supplement that history with photographs and other clinical observations, and convey those data accurately and rapidly to the entire clinical team. Methods: We review our experience with patient-generated health data in surgical site infection, draw parallels with similar work in other domains, and identify principles we have found useful. Results: Health information system implementations require substantial changes in provider workflow. Shared expectations between the patient and the surgical team, an incremental approach to change in clinical processes, and an emphasis on clinical utility all support successful implementation. Conclusions: The data collection and rapid information exchange afforded by monitoring post-operative, post-discharge patients using mobile technologies can support the expectations of both patients and providers and may provide a novel data source for public health surveillance of surgical site infection. Both uses of these data require careful attention to introducing changes in clinical workflow.

Automated detection of wrong-drug prescribing errors

BACKGROUND

To assess the specificity of an algorithm designed to detect look-alike/sound-alike (LASA) medication prescribing errors in electronic health record (EHR) data.

SETTING

Urban, academic medical centre, comprising a 495-bed hospital and outpatient clinic running on the Cerner EHR. We extracted 8 years of medication orders and diagnostic claims. We licensed a database of medication indications, refined it and merged it with the medication data. We developed an algorithm that triggered for LASA errors based on name similarity, the frequency with which a patient received a medication and whether the medication was justified by a diagnostic claim. We stratified triggers by similarity. Two clinicians reviewed a sample of charts for the presence of a true error, with disagreements resolved by a third reviewer. We computed specificity, positive predictive value (PPV) and yield.

RESULTS

The algorithm analysed 488 481 orders and generated 2404 triggers (0.5% rate). Clinicians reviewed 506 cases and confirmed the presence of 61 errors, for an overall PPV of 12.1% (95% CI 10.7% to 13.5%). It was not possible to measure sensitivity or the false-negative rate. The specificity of the algorithm varied as a function of name similarity and whether the intended and dispensed drugs shared the same route of administration.

CONCLUSION

Automated detection of LASA medication errors is feasible and can reveal errors not currently detected by other means. Real-time error detection is not possible with the current system, the main barrier being the real-time availability of accurate diagnostic information. Further development should replicate this analysis in other health systems and on a larger set of medications and should decrease clinician time spent reviewing false-positive triggers by increasing specificity.

Assessing the safety of electronic health records: a national longitudinal study of medication-related decision support

BACKGROUND

Electronic health records (EHR) can improve safety via computerised physician order entry with clinical decision support, designed in part to alert providers and prevent potential adverse drug events at entry and before they reach the patient. However, early evidence suggested performance at preventing adverse drug events was mixed.

METHODS

We used data from a national, longitudinal sample of 1527 hospitals in the USA from 2009 to 2016 who took a safety performance assessment test using simulated medication orders to test how well their EHR prevented medication errors with potential for patient harm. We calculated the descriptive statistics on performance on the assessment over time, by years of hospital experience with the test and across hospital characteristics. Finally, we used ordinary least squares regression to identify hospital characteristics associated with higher test performance.

RESULTS

The average hospital EHR system correctly prevented only 54.0% of potential adverse drug events tested on the 44-order safety performance assessment in 2009; this rose to 61.6% in 2016. Hospitals that took the assessment multiple times performed better in subsequent years than those taking the test the first time, from 55.2% in the first year of test experience to 70.3% in the eighth, suggesting efforts to participate in voluntary self-assessment and improvement may be helpful in improving medication safety performance.

CONCLUSION

Hospital medication order safety performance has improved over time but is far from perfect. The specifics of EHR medication safety implementation and improvement play a key role in realising the benefits of computerising prescribing, as organisations have substantial latitude in terms of what they implement. Intentional quality improvement efforts appear to be a critical part of high safety performance and may indicate the importance of a culture of safety.

Some Multidimensional Unintended Consequences of Telehealth Utilization: A Multi-Project Evaluation Synthesis

Background: Telehealth initiatives have bloomed around the globe, but their integration and diffusion remain challenging because of the complex issues they raise. Available evidence around telehealth usually deals with its expected effects and benefits, but its unintended consequences (UCs) and influencing factors are little documented. This study aims to explore, describe and analyze multidimensional UCs that have been associated with the use of telehealth.

Methods: We performed a secondary analysis of the evaluations of 10 telehealth projects conducted over a 22-year period in the province of Quebec (Canada). All material was subjected to a qualitative thematic-pragmatic content analysis with triangulation of methodologies and data sources. We used the conceptual model of the UCs of health information technologies proposed by Bloomrosen et al to structure our analysis.

Results: Four major findings emerged from our analysis. First, telehealth utilization requires many adjustments, changes and negotiations often underestimated in the planning and initial phases of the projects. Second, telehealth may result in the emergence of new services corridors that disturb existing ones and involve several adjustments for organizations, such as additional investments and resources, but also the risk of fragmentation of services and the need to balance between standardization of practices and local innovation. Third, telehealth may accentuate power relations between stakeholders. Fourth, it may lead to significant changes in the responsibilities of each actor in the supply chain of services. Finally, current legislative and regulatory frameworks appear ill-adapted to many of the new realities brought by telehealth.

Conclusion: This study provides a first attempt for an overview of the UCs associated with the use of telehealth. Future research-evaluation studies should be more sensitive to the multidimensional and interdependent factors that influence telehealth implementation and utilization as well as its impacts, intended or unintended, at all levels. Thus, a consideration of potential UCs should inform telehealth projects, from their planning until their scaling-up.

Understanding CancelRx: Results of End-to-End Functional Testing, Proactive Risk Assessment, and Pilot Implementation

BACKGROUND

CancelRx allows prescribers to send electronic cancellation messages to pharmacies when medications are discontinued. Little is known about its functionality and impact on clinical workflows.

OBJECTIVES

To understand CancelRx functionality, its potential impact on workflows and medication safety risks, and to develop mitigating strategies for risks introduced by implementation.

METHODS

We conducted direct observations and semi-structured interviews to develop CancelRx use cases and assessed CancelRx in an end-to-end test environment, proactive risk assessment, and pilot implementation from April 16 to July 15, 2018.

RESULTS

E-cancellations were sent upon discontinuation of e-prescriptions written within the electronic health record (EHR), but not other medications (e.g., printed prescriptions) and could be initiated by nonprescribers. In our proactive risk assessment, CancelRx implementation eliminated five of seven failure modes in outpatient prescribing to Johns Hopkins pharmacies, but introduced new risks, including (1) failure to act if an e-cancellation was not sent or was unsuccessful; (2) failure to cancel all prescriptions for a medication; (3) errors in manual matching; and (4) erroneous medication cancellations. We identified potential mitigation strategies for these risks. During pilot implementation, 92.4% (428/463) of e-cancellations had confirmed approval by the receiving pharmacy, while 4.5% (21/463) were denied, and 3.0% (14/463) had no e-cancellation response. Among e-cancellations received by the pilot pharmacy, 1.7% (7/408) required manual matching by pharmacy staff. Based on performance in testing, 73.4% (340/463) of completed e-cancellations would be expected to generate an in-basket message, including 21 (6.2%) denials and 319/340 (93.8%) approvals with a note from the pharmacy.

CONCLUSION

CancelRx is an important functionality with the potential to decrease adverse events due to medication errors. However, changes in implementation in our EHR and pharmacy software and enhancements in the CancelRx standard are needed to maximize safety and usability. Further studies are needed to evaluate the impact of e-cancellation on medication safety.

Assessing EHR use during hospital morning rounds: A multi-faceted study

Background

The majority of U.S hospitals have implemented electronic health records (EHRs). While the benefits of EHRs have been widely touted, little is known about their effects on inpatient care, including how well they meet workflow needs and support care.

Objective

Assess the extent to which EHRs support care team workflow during hospital morning rounds.

Design

We applied a mixed-method approach including observations of care teams during morning rounds, semi-structured interviews and an electronic survey of hospital inpatient clinicians. Structured field notes taken during observations were used to identify workflow patterns for analysis. We applied a grounded theory approach to extract emerging themes from interview transcripts and used SPSS Statistics 24 to analyze survey responses.

Setting

Medical units at a major teaching hospital in New England.

Results

Data triangulation across the three analyses yielded four main findings: (1) a high degree of variance in the ways care teams use EHRs during morning rounds. (2) Pervasive use of workarounds at critical points of care (3) EHRs are not used for information sharing and frequently impede intra-care team communication. (4) System design and hospital room settings do not adequately support care team workflow.

Conclusions

Gaps between EHR design and the functionality needed in the complex inpatient environment result in lack of standardized workflows, extensive use of workarounds and team communication issues. These issues pose a threat to patient safety and quality of care. Possible solutions need to include improvements in EHR design, care team training and changes to the hospital room setting.

Protocol for a scoping review to understand how interorganisational electronic health records affect hospital physician and pharmacist decisions

INTRODUCTION

Patient records are often fragmented across organisations and departments in UK health and care services, often due to substandard information technology. However, although government policy in the UK and internationally is strongly pushing 'digital transformation', the evidence for the positive impact of electronic information systems on cost, quality and safety of healthcare is far from clear. In particular, the mechanisms by which information availability is translated into better decision-making are not well understood. We do not know when a full interorganisational record is more useful than a key information summary or an institutional record. In this paper, we describe our scoping review of how interorganisational electronic health records affect decision-making by hospital physicians and pharmacists.

METHODS AND ANALYSIS

This scoping review will follow the Arksey and O'Malley (2005) methodology. The review has adopted sociotechnical systems thinking and the notion of distributed cognition as its guiding conceptual models. The UK National Institute for Health and Care Excellence Healthcare Databases Advanced Search will be used, as it incorporates key sources including PubMed, Medline, Embase, HMIC and Health Business Elite. A hand search will be conducted using the reference lists of included studies to identify additional relevant articles. A two-part study selection process will be used: (1) a title and abstract review and (2) full text review. During the first step, two researchers separately will review the citations yielded from the search to determine eligibility based on the defined inclusion and exclusion criteria. Related articles will be included if they are empirical studies that address how interorganisational records affect decision-making by hospital physicians and pharmacists.

ETHICS AND DISSEMINATION

The results will be disseminated through stakeholder meetings, conference presentations and peer-reviewed publication. The data used are from publicly available secondary sources, so this study does not require ethical review.

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.

Defining electronic-prescribing and infusion-related medication errors in paediatric intensive care - a Delphi study

Background

The use of health information technology (HIT) to improve patient safety is widely advocated by governmental and safety agencies. Electronic-prescribing and smart-pump technology are examples of HIT medication error reduction strategies. The introduction of new errors on HIT implementation is, however, also recognised. To determine the impact of HIT interventions, clear medication error definitions are required. This study aims to achieve consensus on defining as medication errors a range of either technology-generated, or previously unaddressed infusion-related scenarios, common in the paediatric intensive care setting.

Methods

This study was conducted in a 23-bed paediatric intensive care unit (PICU) of an Irish tertiary paediatric hospital. A modified Delphi technique was employed: previously undefined medication-incidents were identified by retrospective review of voluntary incident reports and clinical pharmacist interventions; a multidisciplinary expert panel scored each incident using a 9-point Likert scale over a number of iterative rounds; levels of agreement were assessed to produce a list of medication errors. Differences in scoring between healthcare professionals were assessed.

Results

Seventeen potential errors or ‘scenarios’ requiring consensus were identified, 13 of which related to technology recently implemented into the PICU. These were presented to a panel of 37 participants, comprising of doctors, nurses and pharmacists. Consensus was reached to define as errors all reported smart-pump scenarios (n = 6) and those pertaining to the pre-electronic process of prescribing weight-based paediatric infusions (n = 4). Of 7 electronic-prescribing scenarios, 4 were defined as errors, 2 were deemed not to be and consensus could not be achieved for the last. Some differences in scoring between healthcare professionals were found, but were only significant (p < 0.05) for two and three scenarios in consensus rounds 1 and 2 respectively.

Conclusion

The list of medication errors produced using the Delphi technique highlights the diversity of previously undefined medication errors in PICU. The increased complexity of electronic-prescribing processes is evident from the difficulty in achieving consensus on those scenarios. Reducing ambiguity in defining medication errors should assist future research on the impact of HIT medication safety initiatives in critical care. The increasing use of HIT and associated new errors will necessitate further similar studies.

The impact of electronic health records on diagnosis

Diagnostic error may be the largest unaddressed patient safety concern in the United States, responsible for an estimated 40,000-80,000 deaths annually. With the electronic health record (EHR) now in near universal use, the goal of this narrative review is to synthesize evidence and opinion regarding the impact of the EHR and health care information technology (health IT) on the diagnostic process and its outcomes. We consider the many ways in which the EHR and health IT facilitate diagnosis and improve the diagnostic process, and conversely the major ways in which it is problematic, including the unintended consequences that contribute to diagnostic error and sometimes patient deaths. We conclude with a summary of suggestions for improving the safety and safe use of these resources for diagnosis in the future.

Improving medication-related clinical decision support

PURPOSE

Current uses of medication-related clinical decision support (CDS) and recommendations for improving these systems are reviewed.

SUMMARY

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

CONCLUSION

Standardization, integration of patient-specific parameters, and consideration of human factors design principles are central to realizing the potential benefits of medication-related CDS.

[Problems encountered by hospital pharmacists with information systems: Analysis of exchanges within social networks]

OBJECTIVE

The development of information systems in French hospitals is mandatory. The aim of this work was to analyze the content of exchanges carried out within social networks, dealing with problems encountered with hospital pharmacies information systems.

METHODS

Messages exchanged via the mailing list of the Association pour le Digital et l'Information en Pharmacie and abstracts of communications presented at hospital pharmacists trade union congresses were analyzed. Those referring to information systems used in hospital pharmacies were selected.

RESULTS

From March 2015 to June 2016, 122 e-mails sent by 80 pharmacists concerned information systems. From 2002 to 2016, 45 abstracts dealt with this topic. Problems most often addressed in these 167 documents were "parameterization and/or functionalities" (n=116), interfaces and complexity of the hospital information systems (n=52), relationship with health information technologies vendors and poor reactivity (n=32), additional workload (n=32), ergonomics (n=30), insufficient user training (n=22). These problems are interdependent, lead to errors and in order to mitigate their consequences, they compel pharmacy professionals to divert a significant amount of working hours to the detriment of pharmaceutical care and dispensing and preparing drugs.

CONCLUSION

Hospital pharmacists are faced with many problems of insecurity and inefficiency generated by information systems. Researches are warranted to determine their cost, specify their deleterious effects on care and identify the safest information systems.

Going Mobile: Resident Physicians' Assessment of the Impact of Tablet Computers on Clinical Tasks, Job Satisfaction, and Quality of Care

BACKGROUND

There are few published studies of the use of portable or handheld computers in health care, but these devices have the potential to transform multiple aspects of clinical teaching and practice.

OBJECTIVE

This article assesses resident physicians' perceptions and experiences with tablet computers before and after the introduction of these devices.

METHODS

We surveyed 49 resident physicians from 8 neurology, surgery, and internal medicine clinical services before and after the introduction of tablet computers at a 415-bed Boston teaching hospital. The surveys queried respondents about their assessment of tablet computers, including the perceived impact of tablets on clinical tasks, job satisfaction, time spent at work, and quality of patient care.

RESULTS

Respondents reported that it was easier (73%) and faster (70%) to use a tablet computer than to search for an available desktop. Tablets were useful for reviewing data, writing notes, and entering orders. Respondents indicated that tablet computers increased their job satisfaction (84%), reduced the amount of time spent in the hospital (51%), and improved the quality of care (65%).

CONCLUSION

The introduction of tablet computers enhanced resident physicians' perceptions of efficiency, effectiveness, and job satisfaction. Investments in this technology are warranted.