Sensitivity and specificity of dosing alerts for dosing errors among hospitalized pediatric patients

Use of Computerized Physician Order Entry with Clinical Decision Support to Prevent Dose Errors in Pediatric Medication Orders: A Systematic Review

BACKGROUND

Prescribing is a high-risk task within the pediatric medication-use process and requires defenses to prevent errors. Such system-centric defenses include electronic health record systems with computerized physician order entry (CPOE) and clinical decision support (CDS) tools that assist safe prescribing. The objective of this study was to examine the effects of CPOE systems with CDS functions in preventing dose errors in pediatric medication orders.

MATERIAL AND METHODS

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 criteria and Synthesis Without Meta-Analysis (SWiM) items. The study protocol was registered in PROSPERO (CRD42021277413). The final literature search on MEDLINE (Ovid), Scopus, Web of Science, and EMB Reviews was conducted on 10 September 2023. Only peer-reviewed studies considering both CPOE and CDS systems in pediatric inpatient or outpatient settings were included. Study selection, data extraction, and evidence quality assessment (JBI critical appraisal tool assessment and GRADE approach) were carried out by two individual reviewers. Vote counting method was used to evaluate the effects of CPOE-CDS systems on dose errors rates.

RESULTS

A total of 17 studies published in 2007-2021 met the inclusion criteria. The most used CDS tools were dose range check (n = 14), dose calculator (n = 8), and dosing frequency check (n = 8). Alerts were recorded in 15 studies. A statistically significant reduction in dose errors was found in eight studies, whereas an increase of dose errors was not reported.

CONCLUSIONS

The CPOE-CDS systems have the potential to reduce pediatric dose errors. Most beneficial interventions seem to be system customization, implementing CDS alerts, and the use of dose range check. While human factors are still present within the medication use process, further studies and development activities are needed to optimize the usability of CPOE-CDS systems.

Improvement in Pharmacy Student Responses to Medication-Related Problems with and without Clinical Decision Support Alerts

OBJECTIVE

To assess pharmacy student responses to medication problems with and without clinical decision support (CDS) alerts during simulated order verification.

METHODS

Three classes of students completed an order verification simulation. The simulation randomized students to a different series of 10 orders with varying CDS alert frequency. Two of the orders contained medication-related problems. The appropriateness of the students' interventions and responses to the CDS alerts were evaluated. In the following semester for 2 classes, 2 similar simulations were completed. All 3 simulations contained 1 problem with and 1 without an alert.

RESULTS

During the first simulation, 384 students reviewed an order with a problem and an alert. Students exposed to prior inappropriate alerts within the simulation had less appropriate responses (66% vs 75%). Of 321 students who viewed a second order with a problem, those reviewing an order lacking an alert recommended an appropriate change less often (45% vs 87%). Among 351 students completing the second simulation, those who participated in the first simulation appropriately responded to the alert for a problem more often than those who only received a didactic debrief (95% vs 87%). Among those completing all 3 simulations, appropriate responses increased between simulations for problems with (n = 238, 72-95-93%) and without alerts (n = 49, 53-71-90%).

CONCLUSIONS

Some pharmacy students displayed baseline alert fatigue and overreliance on CDS alerts for medication problem detection during order verification simulations. Exposure to the simulations improved CDS alert response appropriateness and detection of problems.

Dose Verification Errors in Hospitals: Literature Review of the eMAR-based Systems Used by Nurses

BACKGROUND

The effectiveness of the dose verification features of the electronic medication administration record (eMAR) and complementary systems in the hospital setting is not well understood.

PURPOSE

The authors completed a narrative synthesis of literature findings on the effectiveness of eMAR-based systems in the hospital setting.

METHODS

A literature review was carried out across 5 bibliographic databases to evaluate the safety features of current eMAR-based systems in preventing dosing errors and design issues that impede their usability.

RESULTS

While eMAR-based systems are beneficial to reducing order and drug cross-checking errors, safe dose verification features are sporadically available for targeted tasks. Overall, the eMAR had little impact on preventing low to moderate dosing errors. Dosing errors may occur because of error-prone activities that result from system design and work process issues during medication administration.

The appropriateness of clinical decision support systems alerts in supporting clinical workflows: A systematic review

A CDSS generates a high number of inappropriate alerts that interrupt the clinical workflow. As a result, clinicians silence, disable, or ignore alerts, thereby undermining patient safety. Therefore, the effectiveness and appropriateness of CDSS alerts need to be evaluated. A systematic review was carried out to identify the factors that affect CDSS alert appropriateness in supporting clinical workflow. Seven electronic databases (PubMed, Scopus, ACM, Science Direct, IEEE, Ovid Medline, and Ebscohost) were searched for English language articles published between 1997 and 2018. Seventy six papers met the inclusion criteria, of which 26, 24, 15, and 11 papers are retrospective cohort, qualitative, quantitative, and mixed-method studies, respectively. The review highlights various factors influencing the appropriateness and efficiencies of CDSS alerts. These factors are categorized into technology, human, organization, and process aspects using a combination of approaches, including socio-technical framework, five rights of CDSS, and Lean. Most CDSS alerts were not properly designed based on human factor methods and principles, explaining high alert overrides in clinical practices. The identified factors and recommendations from the review may offer valuable insights into how CDSS alerts can be designed appropriately to support clinical workflow.

Evaluating the appropriateness of clinical decision support alerts: A case study

RATIONALE, AIMS, AND OBJECTIVES

Clinical decision support (CDS) generates excessive alerts that disrupt the workflow of clinicians. Therefore, inefficient clinical processes that contribute to the misfit between CDS alert and workflow must be evaluated. This study evaluates the appropriateness of CDS alerts in supporting clinical workflow from a socio-technical perspective.

METHOD

A qualitative case study evaluation was conducted at a 620-bed public teaching hospital in Malaysia using interview, observation, and document analysis to investigate the features and functions of alert appropriateness and workflow-related issues in cardiological and dermatological settings. The current state map for medication prescribing process was also modelled to identify problems pertinent to CDS alert appropriateness.

RESULTS

The main findings showed that CDS was not well designed to fit into a clinician's workflow due to influencing factors such as technology (usability, alert content, and alert timing), human (training, perception, knowledge, and skills), organizational (rules and regulations, privacy, and security), and processes (documenting patient information, overriding default option, waste, and delay) impeding the use of CDS with its alert function. We illustrated how alert affect workflow in clinical processes using a Lean tool known as value stream mapping. This study also proposes how CDS alerts should be integrated into clinical workflows to optimize their potential to enhance patient safety.

CONCLUSION

The design and implementation of CDS alerts should be aligned with and incorporate socio-technical factors. Process improvement methods such as Lean can be used to enhance the appropriateness of CDS alerts by identifying inefficient clinical processes that impede the fit of these alerts into clinical workflow.

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.

Feedback at the Point of Care to Decrease Medication Alert Rates in an Electronic Health Record

Frequently overridden alerts in the electronic health record can highlight alerts that may need revision. This method is a way of fine-tuning clinical decision support. We evaluated the feasibility of a complementary, yet different method that directly involved pediatric emergency department (PED) providers in identifying additional medication alerts that were potentially incorrect or intrusive. We then evaluated the effect subsequent resulting modifications had on alert salience.

METHODS

We performed a prospective, interventional study over 34 months (March 6, 2014, to December 31, 2016) in the PED. We implemented a passive alert feedback mechanism by enhancing the native electronic health record functionality on alert reviews. End-users flagged potentially incorrect/bothersome alerts for review by the study's team. The alerts were updated when clinically appropriate and trends of the impact were evaluated.

RESULTS

More than 200 alerts were reported from both inside and outside the PED, suggesting an intuitive approach. On average, we processed 4 reviews per week from the PED, with attending physicians as major contributors. The general trend of the impact of these changes seems favorable.

DISCUSSION

The implementation of the review mechanism for user-selected alerts was intuitive and sustainable and seems to be able to detect alerts that are bothersome to the end-users. The method should be run in parallel with the traditional data-driven approach to support capturing of inaccurate alerts.

CONCLUSIONS

User-centered, context-specific alert feedback can be used for selecting suboptimal, interruptive medication alerts.

Evaluating the alert appropriateness of clinical decision support systems in supporting clinical workflow

The overwhelming number of medication alerts generated by clinical decision support systems (CDSS) has led to inappropriate alert overrides, which may lead to unintended patient harm. This review highlights the factors affecting the alert appropriateness of CDSS and barriers to the fit of CDSS alert with clinical workflow. A literature review was conducted to identify features and functions pertinent to CDSS alert appropriateness using the five rights of CDSS. Moreover, a process improvement method, namely, Lean, was used as a tool to optimise clinical workflows, and the appropriate design for CDSS alert using a human automation interaction (HAI) model was recommended. Evaluating the appropriateness of CDSS alert and its impact on workflow provided insights into how alerts can be designed and triggered effectively to support clinical workflow. The application of Lean methods and tools to analyse alert efficiencies in supporting workflow in this study provides an in-depth understanding of alert-workflow fit problems and their root cause, which is required for improving CDSS design. The application of the HAI model is recommended in the design of CDSS alerts to support various levels and stages of alert automations, namely, information acquisition and analysis, decision action and action implementation.

The Prevalence of Dose Errors Among Paediatric Patients in Hospital Wards with and without Health Information Technology: A Systematic Review and Meta-Analysis

INTRODUCTION

The risk of dose errors is high in paediatric inpatient settings. Computerized provider order entry (CPOE) systems with clinical decision support (CDS) may assist in reducing the risk of dosing errors. Although a frequent type of medication error, the prevalence of dose errors is not well described. Dosing error rates in hospitals with or without CPOE have not been compared.

OBJECTIVE

Our aim was to conduct a systematic review assessing the prevalence and impact of dose errors in paediatric wards with and without CPOE and/or CDS.

METHODS

We systematically searched five databases to identify studies published between January 2000 and December 2017 that assessed dose error rates by medication chart audit or direct observation.

RESULTS

We identified 39 studies, nine of which involved paediatric wards using CPOE with or without CDS. Studies of paediatric wards using paper medication charts reported approximately 8-25% of patients experiencing a dose error, and approximately 2-6% of medication orders and approximately 3-8% of dose administrations contained a dose error, with estimates varying by ward type. The nine studies of paediatric wards using CPOE reported approximately 22% of patients experiencing a dose error, and approximately 1-6% of medication orders and approximately 3-8% of dose administrations contained a dose error. Few studies provided data for individual wards. The severity and prevalence of harm associated with dose errors was rarely assessed and showed inconsistent results.

CONCLUSIONS

Dose errors occur in approximately 1 in 20 medication orders. Hospitals using CPOE with or without CDS had a lower rate of dose errors compared with those using paper charts. However, few pre/post studies have been conducted and none reported a significant reduction in dose error rates associated with the introduction of CPOE. Future research employing controlled designs is needed to determine the true impact of CPOE on dosing errors among children, and any associated patient harm.

Nature and frequency of dosing instructions on prescription labels in primary care

PURPOSE

To investigate the nature and frequency of dosing instructions and auxiliary labels on prescription labels in primary care.

METHODS

A retrospective analysis of data on prescription labels of dispensed drugs extracted from the pharmacy information system of community pharmacies in the Netherlands. Dosing instructions were categorized into four types.

RESULTS

Data were extracted from 123 community pharmacies. All drugs dispensed for a random sample of 10% of patients were selected. In the sample of 938 479 prescriptions, 96% had a predefined dosing instruction and 2995 different coded instructions were used. Ninety-five percent of all instructions were covered by 354 coded instructions. Most prescriptions were coded with an instruction indicating once daily use (48.4%) or twice or more times daily use (23.8%) without specification of the time (eg, "1 tablet 1 time a day"). A general instruction ("use as directed") was given for 7.0% of all prescriptions, and for 6.0%, the instruction was to use "as needed." For most prescriptions (80.6%), one or more auxiliary labels were generated with the warning "may cause drowsiness" (17.9%) being the most frequent one.

CONCLUSIONS

A limited set of instructions covered the majority of the prescriptions. About a quarter of the prescription labels contained nonspecific dosing instructions for use multiple times a day, and 13.0% were general or "use as needed" instructions. These instructions can potentially be made more comprehensible by rewording and specification of the time of day.

Assessment of Different Methods for Pediatric Meningitis Dosing Clinical Decision Support

Background: Indication-specific medication dosing support is needed to improve pediatric dosing support. Objective: To compare the sensitivity and positive predictive value (PPV) of different meningitis dosing alert triggers and dosing error rates between antimicrobials with and without meningitis order sentences. Methods: We retrospectively analyzed 4-months of pediatric orders for antimicrobials with meningitis-specific dosing. At the time of the order, it was determined if the antimicrobial was for meningitis management, if a cerebrospinal fluid (CSF) culture was ordered, and if a natural language processing (NLP) system could detect “meningitis” in clinical notes. Results: Of 1383 orders, 243 were for the management of meningitis. A CSF culture or NLP combination trigger searching the electronic health record since admission yielded the greatest sensitivity for detecting meningitis management (67.5%, P < 0.01 vs others), but dosing error detection was similar if the trigger only searched 48 hours preceding the order (68.8% vs 62.5%, P = 0.125). Using a CSF culture alone and a 48-hour time frame had a higher PPV versus a combination with a 48-hour time frame (97.1% vs 80.9%, P < 0.001), and both triggers had a higher PPV than others ( P < 0.001). Antimicrobials with meningitis order sentences had fewer dosing errors (19.8% vs 43.2%, P < 0.01). Conclusion and Relevance: A meningitis dosing alert triggered by a combination of a CSF culture or NLP system and a 48-hour triggering time frame could provide reasonable sensitivity and PPV for meningitis dosing errors. Order sentences with indication-specific recommendations may provide additional dosing support, but additional studies are needed.

Too many medication alerts: How alarm frequency affects providers

NPs see many medication alerts on a daily basis. The dilemma is finding a balance between having enough alerts to prevent harm and too many inappropriate alerts, causing alert fatigue. Technical and human factors affect how alerts impact NPs, and consequently, NPs should play a role in ensuring only appropriate alerts are used.

Preventable Adverse Drug Events Among Inpatients: A Systematic Review

: media-1vid110.1542/5799876436001PEDS-VA_2018-0805Video Abstract CONTEXT: Patient harm resulting from medication errors drives prevention efforts, yet harm associated with medication errors in children has not been systematically reviewed.

OBJECTIVE

To review the incidence and severity of preventable adverse drug events (pADEs) resulting from medication errors in pediatric inpatient settings.

DATA SOURCES

Data sources included Cumulative Index of Nursing and Allied Health Literature, Medline, Scopus, the Cochrane Library, and Embase.

STUDY SELECTION

Selected studies were published between January 2000 and December 2017, written in the English language, and measured pADEs among pediatric hospital inpatients by chart review or direct observation.

DATA EXTRACTION

Data extracted were medication error and harm definitions, pADE incidence and severity rates, items required for quality assessment, and sample details.

RESULTS

Twenty-two studies were included. For children in general pediatric wards, incidence was at 0 to 17 pADEs per 1000 patient days or 1.3% of medication errors (of any type) compared with 0 to 29 pADEs per 1000 patient days or 1.5% of medication errors in ICUs. Hospital-wide studies contained reports of up to 74 pADEs per 1000 patient days or 2.6% of medication errors. The severity of pADEs was mainly minor.

LIMITATIONS

Limited literature on the severity of pADEs is available. Additional study will better illuminate differences among hospital wards and among those with or without health information technology.

CONCLUSIONS

Medication errors in pediatric settings seldom result in patient harm, and if they do, harm is predominantly of minor severity. Implementing health information technologies was associated with reduced incidence of harm.

Factors contributing to medication errors made when using computerized order entry in pediatrics: a systematic review

Objective

To identify and understand the factors that contribute to medication errors associated with the use of computerized provider order entry (CPOE) in pediatrics and provide recommendations on how CPOE systems could be improved.

Materials and Methods

We conducted a systematic literature review across 3 large databases: the Cumulative Index to Nursing and Allied Health Literature, Embase, and Medline. Three independent reviewers screened the titles, and 2 authors then independently reviewed all abstracts and full texts, with 1 author acting as a constant across all publications. Data were extracted onto a customized data extraction sheet, and a narrative synthesis of all eligible studies was undertaken.

Results

A total of 47 articles were included in this review. We identified 5 factors that contributed to errors with the use of a CPOE system: (1) lack of drug dosing alerts, which failed to detect calculation errors; (2) generation of inappropriate dosing alerts, such as warnings based on incorrect drug indications; (3) inappropriate drug duplication alerts, as a result of the system failing to consider factors such as the route of administration; (4) dropdown menu selection errors; and (5) system design issues, such as a lack of suitable dosing options for a particular drug.

Discussion and Conclusions

This review highlights 5 key factors that contributed to the occurrence of CPOE-related medication errors in pediatrics. Dosing support is the most important. More advanced clinical decision support that can suggest doses based on the drug indication is needed.

Quality of Decision Support in Computerized Provider Order Entry: Systematic Literature Review

Background

Computerized decision support systems have raised a lot of hopes and expectations in the field of order entry. Although there are numerous studies reporting positive impacts, concerns are increasingly high about alert fatigue and effective impacts of these systems. One of the root causes of fatigue alert reported is the low clinical relevance of these alerts.

Objective

The objective of this systematic review was to assess the reported positive predictive value (PPV), as a proxy to clinical relevance, of decision support systems in computerized provider order entry (CPOE).

Methods

A systematic search of the scientific literature published between February 2009 and March 2015 on CPOE, clinical decision support systems, and the predictive value associated with alert fatigue was conducted using PubMed database. Inclusion criteria were as follows: English language, full text available (free or pay for access), assessed medication, direct or indirect level of predictive value, sensitivity, or specificity. When possible with the information provided, PPV was calculated or evaluated.

Results

Additive queries on PubMed retrieved 928 candidate papers. Of these, 376 were eligible based on abstract. Finally, 26 studies qualified for a full-text review, and 17 provided enough information for the study objectives. An additional 4 papers were added from the references of the reviewed papers. The results demonstrate massive variations in PPVs ranging from 8% to 83% according to the object of the decision support, with most results between 20% and 40%. The best results were observed when patients’ characteristics, such as comorbidity or laboratory test results, were taken into account. There was also an important variation in sensitivity, ranging from 38% to 91%.

Conclusions

There is increasing reporting of alerts override in CPOE decision support. Several causes are discussed in the literature, the most important one being the clinical relevance of alerts. In this paper, we tried to assess formally the clinical relevance of alerts, using a near-strong proxy, which is the PPV of alerts, or any way to express it such as the rate of true and false positive alerts. In doing this literature review, three inferences were drawn. First, very few papers report direct or enough indirect elements that support the use or the computation of PPV, which is a gold standard for all diagnostic tools in medicine and should be systematically reported for decision support. Second, the PPV varies a lot according to the typology of decision support, so that overall rates are not useful, but must be reported by the type of alert. Finally, in general, the PPVs are below or near 50%, which can be considered as very low.

Systematic Review of Medical Informatics-Supported Medication Decision Making

This systematic review sought to assess the applications and implications of current medical informatics-based decision support systems related to medication prescribing and use. Studies published between January 2006 and July 2016 which were indexed in PubMed and written in English were reviewed, and 39 studies were ultimately included. Most of the studies looked at computerized provider order entry or clinical decision support systems. Most studies examined decision support systems as a means of reducing errors or risk, particularly associated with medication prescribing, whereas a few studies evaluated the impact medical informatics-based decision support systems have on workflow or operations efficiency. Most studies identified benefits associated with decision support systems, but some indicate there is room for improvement.

Preventability of Voluntarily Reported or Trigger Tool-Identified Medication Errors in a Pediatric Institution by Information Technology: A Retrospective Cohort Study

INTRODUCTION

Information technology (IT) has the potential to prevent medication errors. While many studies have analyzed specific IT technologies and preventable adverse drug events, no studies have identified risk factors for errors still occurring that are not preventable by IT.

OBJECTIVES

The objective of this study was to categorize reported or trigger tool-identified errors and adverse events (AEs) at a pediatric tertiary care institution. Also, we sought to identify medication errors preventable by IT, determine why IT-preventable errors occurred, and to identify risk factors for errors that were not preventable by IT.

METHODS

This was a retrospective analysis of voluntarily reported or trigger tool-identified errors and AEs occurring from 1 July 2011 to 30 June 2012. Medication errors reaching the patients were categorized based on the origin, severity, and location of the error, the month in which they occurred, and the age of the patient involved. Error characteristics were included in a multivariable logistic regression model to determine independent risk factors for errors occurring that were not preventable by IT. A medication error was defined as a medication-related failure of a planned action to be completed as intended or the use of a wrong plan to achieve an aim. An IT-preventable error was defined as having an IT system in place to aid in prevention of the error at the phase and location of its origin.

RESULTS

There were 936 medication errors (identified by voluntarily reporting or a trigger tool system) included and analyzed. Drug administration errors were identified most frequently (53.4% ), but prescribing errors most frequently caused harm (47.2 % of harmful errors). There were 470 (50.2 %) errors that were IT preventable at their origin, including 155 due to IT system bypasses, 103 due to insensitivity of IT alerting systems, and 47 with IT alert overrides. Dispensing, administration, and documentation errors had higher odds than prescribing errors for being not preventable by IT [odds ratio (OR) 8.0, 95 % CI 4.4-14.6; OR 2.4, 95 % CI 1.7-3.7; and OR 6.7, 95 % CI 3.3-14.5, respectively; all p < 0.001). Errors occurring in the operating room and in the outpatient setting had higher odds than intensive care units for being not preventable by IT (OR 10.4, 95 % CI 4.0-27.2, and OR 2.6, 95 % CI 1.3-5.0, respectively; all p ≤ 0.004).

CONCLUSIONS

Despite extensive IT implementation at the studied institution, approximately one-half of the medication errors identified by voluntarily reporting or a trigger tool system were not preventable by the utilized IT systems. Inappropriate use of IT systems was a common cause of errors. The identified risk factors represent areas where IT safety features were lacking.

Complexities of Clinical Decision Support Illustrated by Pediatric Dosing Alerts

Health information technologies, such as computerized clinical decision support (CDS) systems, are being utilized increasingly in pediatric health care institutions as a means of medication error prevention. Most studies have suggested a positive impact of CDS on medication safety, but others have identified complexities that have prevented full optimization of these systems. Recent studies regarding the implementation of pediatric dosing alerts have illustrated the complexities that can be associated with the design, implementation, and refinement of CDS systems. Although CDS dosing alerts have likely improved the safety of medication use in pediatric patients, it is important to be aware of certain limitations of the dosing alert systems. A collaborative effort is required to optimize the effectiveness of CDS dosing alerts.

Prescription order risk factors for pediatric dosing alerts

OBJECTIVES

To determine dosing alert rates based on prescription order characteristics and identify prescription order risk factors for the occurrence of dosing alerts.

METHODS

A retrospective analysis of inpatient medication orders and dosing alerts occurring during October 2011 and January, April, and July 2012 at a pediatric institution. Prescription orders and alerts were categorized by: medication class, patient age, route of administration, and month of the year.

RESULTS

There were 228,259 orders during the studied period, with 11,072 alerted orders (4.9%). The most frequently alerted medication class was the non-analgesic central nervous system agent class (14% of alerts). Age, route, medication class, and month all independently affected dosing alert rates. The alert rate was highest for immunosuppressive agents (54%), neonates (6.7%), and orders for rectal administration (9.5%). The alert rate was higher in adult patients receiving their care at a pediatric institution (5.7%) compared to children (4.7%), but after multivariate analysis, pediatric orders had higher odds for an alert (OR 1.1, 95% CI 1.05-1.16). Mercaptopurine had the highest alert rate when categorized by active ingredient (73.9%). Albuterol 2.5mg/mL continuous aerosol and heparin 1000 units in 0.9% sodium chloride injection solution were the unique medications with the highest alert rates (100.0% and 97.7%, respectively).

CONCLUSIONS

Certain types of prescription orders have a higher risk for causing dosing alerts than others. Patient age, medication class, route of administration, and the month of year can affect dosing alert rates. Design and customization efforts should focus on these medications and prescription order characteristics that increase the risk for dosing alerts.