The effect of Computerized Physician Order Entry and decision support system on medication errors in the neonatal ward: experiences from an Iranian teaching hospital. J Med Syst. 2011;35:25-37. [PMID: 20703588 DOI: 10.1007/s10916-009-9338-x]

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.

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.

Identifying the data elements and functionalities of clinical decision support systems to administer medication for neonates and pediatrics: a systematic literature review

BACKGROUND

Patient safety is a central healthcare policy worldwide. Adverse drug events (ADE) are among the main threats to patient safety. Children are at a higher risk of ADE in each stage of medication management process. ADE rate is high in the administration stage, as the final stage of preventing medication errors in pediatrics and neonates. The most effective way to reduce ADE rate is using medication administration clinical decision support systems (MACDSSs). The present study reviewed the literature on MACDSS for neonates and pediatrics. It identified and classified the data elements that mapped onto the Fast Healthcare Interoperability Resources (FHIR) standard and the functionalities of these systems to guide future research.

METHODS

PubMed/ MEDLINE, Embase, CINAHL, and ProQuest databases were searched from 1995 to June 31, 2021. Studies that addressed developing or applying medication administration software for neonates and pediatrics were included. Two authors reviewed the titles, abstracts, and full texts. The quality of eligible studies was assessed based on the level of evidence. The extracted data elements were mapped onto the FHIR standard.

RESULTS

In the initial search, 4,856 papers were identified. After removing duplicates, 3,761 titles, and abstracts were screened. Finally, 56 full-text papers remained for evaluation. The full-text review of papers led to the retention of 10 papers which met the eligibility criteria. In addition, two papers from the reference lists were included. A total number of 12 papers were included for analysis. Six papers were categorized as high-level evidence. Only three papers evaluated their systems in a real environment. A variety of data elements and functionalities could be observed. Overall, 84 unique data elements were extracted from the included papers. The analysis of reported functionalities showed that 18 functionalities were implemented in these systems.

CONCLUSION

Identifying the data elements and functionalities as a roadmap by developers can significantly improve MACDSS performance. Though many CDSSs have been developed for different medication processes in neonates and pediatrics, few have actually evaluated MACDSSs in reality. Therefore, further research is needed on the application and evaluation of MACDSSs in the real environment.

PROTOCOL REGISTRATION

(dx.doi.org/10.17504/protocols.io.bwbwpape).

Implementation of a Regional Standardised Model for Perinatal Electronic Medical Records

Electronic recording of newborn health information contributes to improving the quality of care. Nonetheless, there is limited evidence on the implementation of perinatal electronic medical records models. We describe the development and implementation of an electronic recording model that includes data on the health care provided to both the mother and the newborn, standardised for six hospitals of a regional health care system. The implementation process was developed in 2 stages. During stage 1, the tool was introduced in hospitals to stablish first contact with the healthcare staff. The second stage consisted in designing a new strategy to stabilise the model. Technical issues were fixed, and a new version was drawn up based on multidisciplinary agreement. Indicators to monitor implementation were measured in both stages and compared using the chi-squared test. During stage 1, nearly every newborn got its electronic medical record with an appropriate connection to the mother's data. However, certain forms that were meant to be filled in by staff were frequently neglected (completion rates: 36.7%-55.3%). In stage 2, there was a statistically significant increase in the completion rates of all these forms. As a result, a standardised discharge report was provided to every newborn at the end of stage 2. The PCR model implemented in the Region of Murcia is an innovative example of how the digitalisation and standardisation of data related to the care of healthy newborns at maternity wards is feasible across an entire network of hospitals.

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

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

A Systematic Review and Meta-analysis of the Medical Error Rate in Iran: 2005-2019

BACKGROUND AND OBJECTIVES

Medical errors (MEs) are one of the main factors affecting the quality of hospital services and reducing patient safety in health care systems, especially in developing countries. The aim of this study was to determine the rate of ME in Iran.

METHODS

This is a systematic literature review and meta-analysis of extracted data. The databases MEDLINE, EMBASE, Scopus, Cochrane, SID, Magiran, and Medlib were searched in Persian and English, using a combination of medical subject heading terms ("Medical Error" [Mesh] OR "Medication error" [Mesh] OR "Hospital Error" AND ("Iran" [Mesh]) for observational and interventional studies that reported ME rate in Iran from January 1995 to April 2019. We followed the STROBE checklist for the purpose of this review.

RESULTS

The search yielded a total of 435 records, of which 74 articles were included in the systematic review. The rate of MEs in Iran was determined as 0.35%. The rates of errors among physicians and nurses were 31% and 37%, respectively. The error rates during the medication process, including prescription, recording, and administration, were 31%, 27%, and 35%, respectively. Also, incidence of MEs in night shifts was higher than in any other shift (odds ratio [OR] = 38%; 95% confidence interval [CI]: 31%-45%). Moreover, newer nurses were responsible for more errors within hospitals than other nurses (OR = 57%; 95% CI: 41%-80%). The rate of reported error after the Health Transformation Plan was higher than before the Health Transformation Plan (OR = 40%; CI: 33%-49% vs OR = 30%; CI: 25%-35%).

CONCLUSION

This systematic review has demonstrated the high ME rate in Iranian hospitals. Based on the error rate attributed solely to night shifts, more attention to the holistic treatment process is required. Errors can be decreased through a variety of strategies, such as training clinical and support staff regarding safe practices and updating and adapting systems and technologies.

Redesign of computerized decision support system to improve Non Vitamin K oral anticoagulant prescribing-A pre and post qualitative and quantitative study

BACKGROUND

Inappropriate prescribing of non-vitamin K agents (NOAC) contributes to significant economic and personal burden to our society. Studies have shown that when well designed and targeted, computerized alerts can be effective in improving prescribing without contributing to alert fatigue.

METHOD

A collaborative multidisciplinary review group was set up to review and endorse an upgrade and modification to the hospital electronic medication management system (EMS). The intervention focused on implementing tailored electronic patient specific physiological alerts (such as age, renal function weight and drug interactions) built in EMS to improve the appropriateness of NOAC prescribing at this multisite teaching Australian hospital. To assess the qualitative and quantitative impact of the intervention, a pre and post retrospective study of NOAC prescribing of 100 patients' pre and post the implementation stage was conducted in a multisite Australian 650 bed hospital. Appropriateness of NOAC prescribing was assessed by an experienced pharmacist using approved prescribing product information recommendations. Prescriber satisfaction and experience survey was assessed in both stages of the study using a standard satisfaction survey. Associated hospital acquired complications (HAC) with potential inappropriate NOAC prescribing were evaluated as well as related admission cost and average length of stay.

RESULTS

Redesign of computerised decision support in EMS improved appropriateness of NOAC prescribing from 48 % to 91 %, P < 0.05. A total of 67 prescribers accepted the invitation to participate in the qualitative satisfaction study. Half the respondents (n = 33, 50 %) answered positively to a question assessing the usefulness of implementing NOAC alerts in the EMS in improving their practice and patient safety. This rate has increased to 72 % (n = 48) in the post intervention phase. P < 0.05. Additionally, the total number of reported HAC that are likely to be associated with inappropriate NOAC prescribing was reduced by 36 % in the post intervention phase (from 29 to 22 (RR = 0.7454 95 %CI (0.4283-1.2972), P = 0.2986). The cost of associated HAC has also reduced by 29 % (from $1,282,748 to $911,117) as well as the mean length stay by 11 % (from 18 days to 16 days) post the intervention phase.

CONCLUSION

This study highlights that well-designed electronic prescribing alerts that provide context-relevant information to prescribers are likely to result in benefits to clinicians and patients as well reduction in economic burden. Moreover, they could also contribute to reducing hospital acquired complications and lessen the economic burden on our society.

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

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

Impact of Computerized Prescription on Medication Errors and Workflow Efficiency in Neonatal Intensive Care Units: A Quasi-Experimental Three-Phase Study

BACKGROUND

Neonates are highly vulnerable to preventable medication errors due to their extensive exposure to medications in the neonatal intensive care units (NICUs). These errors, which can be made by medical, nursing, or pharmacy personnel, are costly and can be life-threatening. This study aimed to investigate the newly developed computerized neonatal pharmaceutical health care system (NPHCS) in terms of its ability to (1) minimize neonatal medication prescription errors (NMPEs) and (2) improve workflow efficiency compared with the traditional manual prescribing approach.

METHODS

A computerized neonatal medication prescription system was designed, developed, and tested successfully through a pilot clinical trial for over 6 months in 100 neonates. A three phase quasi-experimental study was then conducted using standardized monitoring checklists for the assessment of NMPEs before and after utilization of the developed prescribing system.

RESULTS

The obtained result showed a high rate of NMPEs in both systems, especially for the antibiotic drug group. However, the use of newly developed NPHCS significantly improved workflow efficacy. The identified errors were significantly more common in the manual mode than in the computerized mode (158.8 vs. 55 per 100 medications). These errors were distributed among different categories, including the documentation of patient identity, birth weight, and gestational age, as well as statements of dose, unit, interval, and diagnosis. Analysis of variance across different categories showed a p-value of <0.05.

CONCLUSION

The use of the computerized NPHCS improved patient safety in NICUs by decreasing NMPEs. It also significantly reduced the time required for dose calculation, prescription generation, and electronic documentation of medical records, compared with the traditional handwritten approach.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

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 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.

Computerized Physician Order Entry in the Neonatal Intensive Care Unit: A Narrative Review

BACKGROUND

Computerized physician order entry (CPOE) has grown since the early 1990s. While many systems serve adult patients, systems for pediatric and neonatal populations have lagged. Adapting adult CPOE systems for pediatric use may require significant modifications to address complexities associated with pediatric care such as daily weight changes and small medication doses.

OBJECTIVE

This article aims to review the neonatal intensive care unit (NICU) CPOE literature to characterize trends in the introduction of this technology and to identify potential areas for further research.

METHODS

Articles pertaining to NICU CPOE were identified in MEDLINE using MeSH terms "medical order entry systems," "drug therapy," "intensive care unit, neonatal," "infant, newborn," etc. Two physician reviewers evaluated each article for inclusion and exclusion criteria. Consensus judgments were used to classify the articles into five categories: medication safety, usability/alerts, clinical practice, clinical decision Support (CDS), and implementation. Articles addressing pediatric (nonneonatal) CPOE were included if they were applicable to the NICU setting.

RESULTS

Sixty-nine articles were identified using MeSH search criteria. Twenty-two additional articles were identified by hand-searching bibliographies and 6 articles were added after the review process. Fifty-five articles met exclusion criteria, for a final set of 42 articles. Medication safety was the focus of 22 articles, followed by clinical practice (10), CDS (10), implementation (11), and usability/alerts (4). Several addressed more than one category. No study showed a decrease in medication safety post-CPOE implementation. Within clinical practice articles, CPOE implementation showed no effect on blood glucose levels or time to antibiotic administration but showed conflicting results on mortality rates. Implementation studies were largely descriptive of single-hospital experiences.

CONCLUSION

CPOE implementation within the NICU has demonstrated improvement in medication safety, with the most consistent benefit involving a reduction in medication errors and wrong-time administration errors. Additional research is needed to understand the potential limitations of CPOE systems in neonatal intensive care and how CPOE affects mortality.

The Effect of Laboratory Test-Based Clinical Decision Support Tools on Medication Errors and Adverse Drug Events: A Laboratory Medicine Best Practices Systematic Review

BACKGROUND

Laboratory and medication data in electronic health records create opportunities for clinical decision support (CDS) tools to improve medication dosing, laboratory monitoring, and detection of side effects. This systematic review evaluates the effectiveness of such tools in preventing medication-related harm.

METHODS

We followed the Laboratory Medicine Best Practice (LMBP) initiative's A-6 methodology. Searches of 6 bibliographic databases retrieved 8508 abstracts. Fifteen articles examined the effect of CDS tools on (a) appropriate dose or medication (n = 5), (b) laboratory monitoring (n = 4), (c) compliance with guidelines (n = 2), and (d) adverse drug events (n = 5). We conducted meta-analyses by using random-effects modeling.

RESULTS

We found moderate and consistent evidence that CDS tools applied at medication ordering or dispensing can increase prescriptions of appropriate medications or dosages [6 results, pooled risk ratio (RR), 1.48; 95% CI, 1.27-1.74]. CDS tools also improve receipt of recommended laboratory monitoring and appropriate treatment in response to abnormal test results (6 results, pooled RR, 1.40; 95% CI, 1.05-1.87). The evidence that CDS tools reduced adverse drug events was inconsistent (5 results, pooled RR, 0.69; 95% CI, 0.46-1.03).

CONCLUSIONS

The findings support the practice of healthcare systems with the technological capability incorporating test-based CDS tools into their computerized physician ordering systems to (a) identify and flag prescription orders of inappropriate dose or medications at the time of ordering or dispensing and (b) alert providers to missing laboratory tests for medication monitoring or results that warrant a change in treatment. More research is needed to determine the ability of these tools to prevent adverse drug events.

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.

Qualitative exploration of practices to prevent medication errors in neonatal intensive care units: a focus group study

Background

Medication errors (MEs) in neonates are frequent and associated with increased potential for harm compared with adults. The effect of learning from reported MEs is potentially lacking due to underreporting, lack of feedback and missing actions to improve medication safety. A new approach involving positive recognition of current and future strategies may facilitate greater exploration of how to improve medication safety in neonates. We aimed to explore current and potential future practices to prevent MEs in neonatal intensive care units (NICUs).

Methods

Focus group interviews of physicians and nurses were conducted at three Danish NICUs. Participants were included if they had at least 1 month of working experience and provided direct patient care. A semistructured interview guide involving three questions was used: (a) how do you feel about discussing prevention of MEs? (b) how do you currently prevent MEs from occurring? and (c) how can we become better at preventing MEs in the future? Content analysis was used to identify themes in the interviews.

Results

Participants commented that MEs still occur and that action must be taken to improve medication safety. Current practices to prevent MEs involved technology, procedures, education, skills and hospital pharmacy services. Potential future practices to prevent MEs included customizing the computerized physician order entry systems to support optimal prescribing, standardizing the double-check process, training of calculation skills and teamwork and increased use of hospital pharmacy services.

Conclusions

Several current and potential future practices to reduce MEs in NICUs were identified, highlighting the complexity of MEs. Our findings support an interdisciplinary multifaceted intervention involving both technical and nontechnical elements to improve medication safety in NICUs.

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.

Pediatricians' Understanding and Experiences of an Electronic Clinical-Decision-Support-System

Objectives

Subsequent dosing errors after implementing an Electronic Medical Record (EMR) at a pediatric hospital in Sweden led to the development, in close collaboration with the clinical profession, of a Clinical Decision Support System (CDSS) with Dose Range Check and Weight Based Dose Calculation integrated directly in the EMR. The aim of this study was to explore the understanding and experiences of the CDSS among Swedish pediatricians after one year of practice.

Methods

Semi-structured interviews with physicians at different levels of the health care system were performed with seventeen pediatricians working at three different pediatrics wards in Stockholm County Council. The interviews were analysed with a thematic analysis without pre-determined categories.

Results

Six categories and fourteen subcategories emerged from the analysis. The categories included the use, the benefit, the confidence, the situations of disregards, the misgivings/risks and finally the development potential of the implemented CDSS with Weight Based Dose Calculation and Dose Range Check.

Conclusions

A need for CDSS in the prescribing for children is evident to support the prevention of medication errors. After implementing a CDSS, organized efforts are crucial to understand the need for further development based on the practical knowledge of the clinical profession. Different contextual settings of health care organisations do affect the way how physicians think and act in work. When implementing a CDSS in practice we need to describe and analyse the context where the CDSS should be used as well as the prescribers’ needs in work.

Interventions to reduce medication errors in neonatal care: a systematic review

Background

Medication errors represent a significant but often preventable cause of morbidity and mortality in neonates. The objective of this systematic review was to determine the effectiveness of interventions to reduce neonatal medication errors.

Methods

A systematic review was undertaken of all comparative and noncomparative studies published in any language, identified from searches of PubMed and EMBASE and reference-list checking. Eligible studies were those investigating the impact of any medication safety interventions aimed at reducing medication errors in neonates in the hospital setting.

Results

A total of 102 studies were identified that met the inclusion criteria, including 86 comparative and 16 noncomparative studies. Medication safety interventions were classified into six themes: technology (n = 38; e.g. electronic prescribing), organizational (n = 16; e.g. guidelines, policies, and procedures), personnel (n = 13; e.g. staff education), pharmacy (n = 9; e.g. clinical pharmacy service), hazard and risk analysis (n = 8; e.g. error detection tools), and multifactorial (n = 18; e.g. any combination of previous interventions). Significant variability was evident across all included studies, with differences in intervention strategies, trial methods, types of medication errors evaluated, and how medication errors were identified and evaluated. Most studies demonstrated an appreciable risk of bias. The vast majority of studies (>90%) demonstrated a reduction in medication errors. A similar median reduction of 50-70% in medication errors was evident across studies included within each of the identified themes, but findings varied considerably from a 16% increase in medication errors to a 100% reduction in medication errors.

Conclusion

While neonatal medication errors can be reduced through multiple interventions aimed at improving the medication use process, no single intervention appeared clearly superior. Further research is required to evaluate the relative cost-effectiveness of the various medication safety interventions to facilitate decisions regarding uptake and implementation into clinical practice.

Redesign of computerized decision support to improve antimicrobial prescribing. A controlled before-and-after study

OBJECTIVE

To determine the impact of the introduction of new pre-written orders for antimicrobials in a computerized provider order entry (CPOE) system on 1) accuracy of documented indications for antimicrobials in the CPOE system, 2) appropriateness of antimicrobial prescribing, and 3) compliance with the hospital's antimicrobial policy. Prescriber opinions of the new decision support were also explored to determine why the redesign was effective or ineffective in altering prescribing practices.

METHODS

The study comprised two parts: a controlled pre-post study and qualitative interviews. The intervention involved the redesign of pre-written orders for half the antimicrobials so that approved indications were incorporated into pre-written orders. 555 antimicrobials prescribed before (September - October, 2013) and 534 antimicrobials prescribed after (March - April, 2015) the intervention on all general wards of a hospital were audited by study pharmacists. Eleven prescribers participated in semi-structured interviews.

RESULTS

Redesign of computerized decision support did not result in more appropriate or compliant antimicrobial prescribing, nor did it improve accuracy of indication documentation in the CPOE system (Intervention antimicrobials: appropriateness 49% vs. 50%; compliance 44% vs. 42%; accuracy 58% vs. 38%; all p>0.05). Via our interviews with prescribers we identified five main reasons for this, primarily that indications entered into the CPOE system were not monitored or followed-up, and that the antimicrobial approval process did not align well with prescriber workflow.

CONCLUSION

Redesign of pre-written orders to incorporate appropriate indications did not improve antimicrobial prescribing. Workarounds are likely when compliance with hospital policy creates additional work for prescribers or when system usability is poor. Implementation of IT, in the absence of support or follow-up, is unlikely to achieve all anticipated benefits.

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.

Strategies to enhance rational use of antibiotics in hospital: a guideline by the German Society for Infectious Diseases

Introduction

In the time of increasing resistance and paucity of new drug development there is a growing need for strategies to enhance rational use of antibiotics in German and Austrian hospitals. An evidence-based guideline on recommendations for implementation of antibiotic stewardship (ABS) programmes was developed by the German Society for Infectious Diseases in association with the following societies, associations and institutions: German Society of Hospital Pharmacists, German Society for Hygiene and Microbiology, Paul Ehrlich Society for Chemotherapy, The Austrian Association of Hospital Pharmacists, Austrian Society for Infectious Diseases and Tropical Medicine, Austrian Society for Antimicrobial Chemotherapy, Robert Koch Institute.

Materials and methods

A structured literature research was performed in the databases EMBASE, BIOSIS, MEDLINE and The Cochrane Library from January 2006 to November 2010 with an update to April 2012 (MEDLINE and The Cochrane Library). The grading of recommendations in relation to their evidence is according to the AWMF Guidance Manual and Rules for Guideline Development.

Conclusion

The guideline provides the grounds for rational use of antibiotics in hospital to counteract antimicrobial resistance and to improve the quality of care of patients with infections by maximising clinical outcomes while minimising toxicity. Requirements for a successful implementation of ABS programmes as well as core and supplemental ABS strategies are outlined. The German version of the guideline was published by the German Association of the Scientific Medical Societies (AWMF) in December 2013.

National trends in safety performance of electronic health record systems in children's hospitals

Objective

To evaluate the safety of computerized physician order entry (CPOE) and associated clinical decision support (CDS) systems in electronic health record (EHR) systems at pediatric inpatient facilities in the US using the Leapfrog Group's pediatric CPOE evaluation tool.

Methods

The Leapfrog pediatric CPOE evaluation tool, a previously validated tool to assess the ability of a CPOE system to identify orders that could potentially lead to patient harm, was used to evaluate 41 pediatric hospitals over a 2-year period. Evaluation of the last available test for each institution was performed, assessing performance overall as well as by decision support category (eg, drug-drug, dosing limits). Longitudinal analysis of test performance was also carried out to assess the impact of testing and the overall trend of CPOE performance in pediatric hospitals.

Results

Pediatric CPOE systems were able to identify 62% of potential medication errors in the test scenarios, but ranged widely from 23-91% in the institutions tested. The highest scoring categories included drug-allergy interactions, dosing limits (both daily and cumulative), and inappropriate routes of administration. We found that hospitals with longer periods since their CPOE implementation did not have better scores upon initial testing, but after initial testing there was a consistent improvement in testing scores of 4 percentage points per year.

Conclusions

Pediatric computerized physician order entry (CPOE) systems on average are able to intercept a majority of potential medication errors, but vary widely among implementations. Prospective and repeated testing using the Leapfrog Group's evaluation tool is associated with improved ability to intercept potential medication errors.

The neonatal preventable harm index: a high reliability tool

OBJECTIVE

The aim of this study is to identify, quantify and disseminate a novel set of safety indicators for monitoring the occurrence of preventable harm in the neonatal intensive care unit (NICU).

STUDY DESIGN

Literature review and experiences in an academic, level IV NICU identified prevalent, preventable safety events: hospital-acquired infections (catheter-associated bloodstream infection, ventilator-associated pneumonia), unscheduled extubations, intravenous infiltrates requiring intervention, first week readmissions, serious adverse drug events and miscellaneous events (unanticipated harm or serious near misses). Negative binominal regression evaluated the event incidence trends.

RESULTS

Of 226 preventable harm events occurring between March 2013 and January 2015, the most common were unscheduled extubations (98; 2/100 ventilator days) and intravenous infiltrates (62; 2.7/100 admissions). No trends were detected (rate ratio: 0.99; confidence limits: 0.96 to 1.01; P=0.38).

CONCLUSION

The Neonatal Preventable Harm Index represents a novel and transparent means to monitor serious safety events and direct harm prevention strategies in the NICU.

A bundle with a preformatted medical order sheet and an introductory course to reduce prescription errors in neonates

The objective of this study was to assess whether the introduction of a new preformatted medical order sheet coupled with an introductory course affected prescription quality and the frequency of errors during the prescription stage in a neonatal intensive care unit (NICU). Two-phase observational study consisting of two consecutive 4-month phases: pre-intervention (phase 0) and post-intervention (phase I) conducted in an 11-bed NICU in a Swiss university hospital. Interventions consisted of the introduction of a new preformatted medical order sheet with explicit information supplied, coupled with a staff introductory course on appropriate prescription and medication errors. The main outcomes measured were formal aspects of prescription and frequency and nature of prescription errors. Eighty-three and 81 patients were included in phase 0 and phase I, respectively. A total of 505 handwritten prescriptions in phase 0 and 525 in phase I were analysed. The rate of prescription errors decreased significantly from 28.9% in phase 0 to 13.5% in phase I (p < 0.05). Compared with phase 0, dose errors, name confusion and errors in frequency and rate of drug administration decreased in phase I, from 5.4 to 2.7% (p < 0.05), 5.9 to 0.2% (p < 0.05), 3.6 to 0.2% (p < 0.05), and 4.7 to 2.1% (p < 0.05), respectively. The rate of incomplete and ambiguous prescriptions decreased from 44.2 to 25.7 and 8.5 to 3.2% (p < 0.05), respectively.

CONCLUSION

Inexpensive and simple interventions can improve the intelligibility of prescriptions and reduce medication errors.

WHAT IS KNOWN

Medication errors are frequent in NICUs and prescription is one of the most critical steps. CPOE reduce prescription errors, but their implementation is not available everywhere.

WHAT IS NEW

Preformatted medical order sheet coupled with an introductory course decrease medication errors in a NICU. Preformatted medical order sheet is an inexpensive and readily implemented alternative to CPOE.

Intervention Component Analysis (ICA): a pragmatic approach for identifying the critical features of complex interventions

BACKGROUND

In order to enable replication of effective complex interventions, systematic reviews need to provide evidence about their critical features and clear procedural details for their implementation. Currently, few systematic reviews provide sufficient guidance of this sort.

METHODS

Through a worked example, this paper reports on a methodological approach, Intervention Component Analysis (ICA), specifically developed to bridge the gap between evidence of effectiveness and practical implementation of interventions. By (a) using an inductive approach to explore the nature of intervention features and (b) making use of trialists' informally reported experience-based evidence, the approach is designed to overcome the deficiencies of poor reporting which often hinders knowledge translation work whilst also avoiding the need to invest significant amounts of time and resources in following up details with authors.

RESULTS

A key strength of the approach is its ability to reveal hidden or overlooked intervention features and barriers and facilitators only identified in practical application of interventions. It is thus especially useful where hypothesised mechanisms in an existing programme theory have failed. A further benefit of the approach is its ability to identify potentially new configurations of components that have not yet been evaluated.

CONCLUSIONS

ICA is a formal and rigorous yet relatively streamlined approach to identify key intervention content and implementation processes. ICA addresses a critical need for knowledge translation around complex interventions to support policy decisions and evidence implementation.

Automated detection of medication administration errors in neonatal intensive care

OBJECTIVE

To improve neonatal patient safety through automated detection of medication administration errors (MAEs) in high alert medications including narcotics, vasoactive medication, intravenous fluids, parenteral nutrition, and insulin using the electronic health record (EHR); to evaluate rates of MAEs in neonatal care; and to compare the performance of computerized algorithms to traditional incident reporting for error detection.

METHODS

We developed novel computerized algorithms to identify MAEs within the EHR of all neonatal patients treated in a level four neonatal intensive care unit (NICU) in 2011 and 2012. We evaluated the rates and types of MAEs identified by the automated algorithms and compared their performance to incident reporting. Performance was evaluated by physician chart review.

RESULTS

In the combined 2011 and 2012 NICU data sets, the automated algorithms identified MAEs at the following rates: fentanyl, 0.4% (4 errors/1005 fentanyl administration records); morphine, 0.3% (11/4009); dobutamine, 0 (0/10); and milrinone, 0.3% (5/1925). We found higher MAE rates for other vasoactive medications including: dopamine, 11.6% (5/43); epinephrine, 10.0% (289/2890); and vasopressin, 12.8% (54/421). Fluid administration error rates were similar: intravenous fluids, 3.2% (273/8567); parenteral nutrition, 3.2% (649/20124); and lipid administration, 1.3% (203/15227). We also found 13 insulin administration errors with a resulting rate of 2.9% (13/456). MAE rates were higher for medications that were adjusted frequently and fluids administered concurrently. The algorithms identified many previously unidentified errors, demonstrating significantly better sensitivity (82% vs. 5%) and precision (70% vs. 50%) than incident reporting for error recognition.

CONCLUSIONS

Automated detection of medication administration errors through the EHR is feasible and performs better than currently used incident reporting systems. Automated algorithms may be useful for real-time error identification and mitigation.

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.

Prospective, controlled study of an intervention to reduce errors in neonatal antibiotic orders

OBJECTIVE

To evaluate the effectiveness of an interactive computerized order set with decision support (ICOS-DS) in preventing medication errors in neonatal late-onset sepsis (LOS).

STUDY DESIGN

Prospective, controlled comparison of error rates in antibiotic orders for neonates admitted to the Medical University of South Carolina neonatal intensive care unit with suspected LOS (after postnatal day of life 3) prior to (n=153) and after (n=146) implementation of the ICOS-DS. Antibiotic orders were independently evaluated by two pharmacists for prescribing errors, potential errors and omissions. Prescribing errors included>10% overdoses or underdoses, inappropriate route, schedule or antibiotic, drug-drug or drug-disease interactions, and incorrect patient demographics. Potential errors included misspelled drugs, leading decimals, trailing zeroes, impractical doses and error-prone abbreviations. Multiple errors and omissions in an order were counted individually.

RESULTS

Overall error rate per order decreased from 1.7 to 0.8 (P<0.001) and potential error rate from 1.0 to 0.06 (P<0.001). The reduction in omission error rate per order from 0.2 to 0.1 was not significant (P=0.17). The prescribing error rate per order increased from 0.4 to 0.7 (P=0.03) because of the use of incorrect patient weights (P<0.001). Renal dysfunction was significantly associated with an increased risk of prescribing errors (odds ratio=3.7, P=0.01) which was not significantly different for handwritten versus ICOS-DS orders (P=0.15).

CONCLUSIONS

The ICOS-DS significantly improved the quality of neonatal LOS antibiotic orders although the use of incorrect patient weights was increased. In both groups, orders for patients with renal dysfunction were at risk for prescribing errors. Further evaluation of interventions to promote medication safety for this population is needed.

Summary and frequency of barriers to adoption of CPOE in the U.S

Medical errors are common, costly, and can potentially be life threatening to patients. Recent studies have established that Computer Provider Order Entry (CPOE) systems reduce medical errors as well as improve safety, quality, and value of patient care. However, research regarding adoption factors associated with CPOE systems is limited. Therefore, the purpose of this review was to determine adoption factors by identifying the frequency of barriers through the analysis of literature and research. A systematic literature review was conducted from EBSCO Host and Google Scholar. The search criteria focused on publication date, keywords, and peer reviewed articles. The final set established for evaluation was ten articles. The authors summarized each article and then identified common barriers. Throughout the ten articles, 31 barriers were identified; 15 of which were unique. The three most frequent barriers identified were: process changes (23%), training (13%), and efficacy (10%). The results of this review identify to policy makers levers to incentivize to encourage adoption. The results also illustrate to vendors the importance of factors to include in both marketing and development. The leadership of healthcare organizations should be encouraged to see such results and know that their concerns are heard. If policy makers and vendors help healthcare organizations overcome barriers to adoption, the organization has a better chance of successful CPOE implementation. If successfully implemented, a CPOE system can improve the process of care, quality of care, and patient outcomes; all of which address issues of Meaningful Use.

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.

Preventing medication errors in neonatology: Is it a dream?

Since 1999, the problem of patient safety has drawn particular attention, becoming a priority in health care. A “medication error” (ME) is any preventable event occurring at any phase of the pharmacotherapy process (ordering, transcribing, dispensing, administering, and monitoring) that leads to, or can lead to, harm to the patient. Hence, MEs can involve every professional of the clinical team. MEs range from those with severe consequences to those with little or no impact on the patient. Although a high ME rate has been found in neonatal wards, newborn safety issues have not been adequately studied until now. Healthcare professionals working in neonatal wards are particularly susceptible to committing MEs due to the peculiarities of newborn patients and of the neonatal intensive care unit (NICU) environment. Current neonatal prevention strategies for MEs have been borrowed from adult wards, but many factors such as high costs and organizational barriers have hindered their diffusion. In general, two types of strategies have been proposed: the first strategy consists of identifying human factors that result in errors and redesigning the work in the NICU in order to minimize them; the second one suggests to design and implement effective systems for preventing errors or intercepting them before reaching the patient. In the future, prevention strategies for MEs need to be improved and tailored to the special neonatal population and the NICU environment and, at the same time, every effort will have to be made to support their clinical application.

Interventions to reduce pediatric medication errors: a systematic review

BACKGROUND AND OBJECTIVE

Medication errors cause appreciable morbidity and mortality in children. The objective was to determine the effectiveness of interventions to reduce pediatric medication errors, identify gaps in the literature, and perform meta-analyses on comparable studies.

METHODS

Relevant studies were identified from searches of PubMed, Embase, Scopus, Web of Science, the Cochrane Library, and the Cumulative Index to Nursing Allied Health Literature and previous systematic reviews. Inclusion criteria were peer-reviewed original data in any language testing an intervention to reduce medication errors in children. Abstract and full-text article review were conducted by 2 independent authors with sequential data extraction.

RESULTS

A total of 274 full-text articles were reviewed and 63 were included. Only 1% of studies were conducted at community hospitals, 11% were conducted in ambulatory populations, 10% reported preventable adverse drug events, 10% examined administering errors, 3% examined dispensing errors, and none reported cost-effectiveness data, suggesting persistent research gaps. Variation existed in the methods, definitions, outcomes, and rate denominators for all studies; and many showed an appreciable risk of bias. Although 26 studies (41%) involved computerized provider order entry, a meta-analysis was not performed because of methodologic heterogeneity. Studies of computerized provider order entry with clinical decision support compared with studies without clinical decision support reported a 36% to 87% reduction in prescribing errors; studies of preprinted order sheets revealed a 27% to 82% reduction in prescribing errors.

CONCLUSIONS

Pediatric medication errors can be reduced, although our understanding of optimal interventions remains hampered. Research should focus on understudied areas, use standardized definitions and outcomes, and evaluate cost-effectiveness.

Interventions to reduce medication errors in pediatric intensive care

OBJECTIVE

To systematically examine the research literature to identify which interventions reduce medication errors in pediatric intensive care units.

DATA SOURCES

Databases were searched from inception to April 2014.

STUDY SELECTION AND DATA EXTRACTION

Studies were included if they involved the conduct of an intervention with the intent of reducing medication errors.

DATA SYNTHESIS

In all, 34 relevant articles were identified. Apart from 1 study, all involved single-arm, before-and-after designs without a comparative, concurrent control group. A total of 6 types of interventions were utilized: computerized physician order entry (CPOE), intravenous systems (ISs), modes of education (MEs), protocols and guidelines (PGs), pharmacist involvement (PI), and support systems for clinical decision making (SSCDs). Statistically significant reductions in medication errors were achieved in 7/8 studies for CPOE, 2/5 studies for ISs, 9/11 studies for MEs, 1/2 studies for PGs, 2/3 studies for PI, and 3/5 studies for SSCDs. The test for subgroup differences showed that there was no statistically significant difference among the 6 subgroups of interventions, χ(2)(5) = 1.88, P = 0.87. The following risk ratio results for meta-analysis were obtained: CPOE: 0.47 (95% CI = 0.28, 0.79); IS: 0.37 (95% CI = 0.19, 0.73); ME: 0.36 (95% CI = 0.22, 0.58); PG: 0.82 (95% CI = 0.21, 3.25); PI: 0.39 (95% CI = 0.10, 1.51), and SSCD: 0.49 (95% CI = 0.23, 1.03).

CONCLUSIONS

Available evidence suggests some aspects of CPOE with decision support, ME, and IS may help in reducing medication errors. Good quality, prospective, observational studies are needed for institutions to determine the most effective interventions.

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

OBJECTIVES

To determine the sensitivity and specificity of a dosing alert system for dosing errors and to compare the sensitivity of a proprietary system with and without institutional customization at a pediatric hospital.

METHODS

A retrospective analysis of medication orders, orders causing dosing alerts, reported adverse drug events, and dosing errors during July, 2011 was conducted. Dosing errors with and without alerts were identified and the sensitivity of the system with and without customization was compared.

RESULTS

There were 47,181 inpatient pediatric orders during the studied period; 257 dosing errors were identified (0.54%). The sensitivity of the system for identifying dosing errors was 54.1% (95% CI 47.8% to 60.3%) if customization had not occurred and increased to 60.3% (CI 54.0% to 66.3%) with customization (p=0.02). The sensitivity of the system for underdoses was 49.6% without customization and 60.3% with customization (p=0.01). Specificity of the customized system for dosing errors was 96.2% (CI 96.0% to 96.3%) with a positive predictive value of 8.0% (CI 6.8% to 9.3). All dosing errors had an alert over-ridden by the prescriber and 40.6% of dosing errors with alerts were administered to the patient. The lack of indication-specific dose ranges was the most common reason why an alert did not occur for a dosing error.

DISCUSSION

Advances in dosing alert systems should aim to improve the sensitivity and positive predictive value of the system for dosing errors.

CONCLUSIONS

The dosing alert system had a low sensitivity and positive predictive value for dosing errors, but might have prevented dosing errors from reaching patients. Customization increased the sensitivity of the system for dosing errors.

Systematic review of clinical decision support interventions with potential for inpatient cost reduction

Background

Healthcare costs are increasing rapidly and at an unsustainable rate in many countries, and inpatient hospitalizations are a significant driver of these costs. Clinical decision support (CDS) represents a promising approach to not only improve care but to reduce costs in the inpatient setting. The purpose of this study was to systematically review trials of CDS interventions with the potential to reduce inpatient costs, so as to identify promising interventions for more widespread implementation and to inform future research in this area.

Methods

To identify relevant studies, MEDLINE was searched up to July 2013. CDS intervention studies with the potential to reduce inpatient healthcare costs were identified through titles and abstracts, and full text articles were reviewed to make a final determination on inclusion. Relevant characteristics of the studies were extracted and summarized.

Results

Following a screening of 7,663 articles, 78 manuscripts were included. 78.2% of studies were controlled before-after studies, and 15.4% were randomized controlled trials. 53.8% of the studies were focused on pharmacotherapy. The majority of manuscripts were published during or after 2008. 70.5% of the studies resulted in statistically and clinically significant improvements in an explicit financial measure or a proxy financial measure. Only 12.8% of the studies directly measured the financial impact of an intervention, whereas the financial impact was inferred in the remainder of studies. Data on cost effectiveness was available for only one study.

Conclusions

Significantly more research is required on the impact of clinical decision support on inpatient costs. In particular, there is a remarkable gap in the availability of cost effectiveness studies required by policy makers and decision makers in healthcare systems.

Computerized advice on drug dosage to improve prescribing practice

BACKGROUND

Maintaining therapeutic concentrations of drugs with a narrow therapeutic window is a complex task. Several computer systems have been designed to help doctors determine optimum drug dosage. Significant improvements in health care could be achieved if computer advice improved health outcomes and could be implemented in routine practice in a cost-effective fashion. This is an updated version of an earlier Cochrane systematic review, first published in 2001 and updated in 2008.

OBJECTIVES

To assess whether computerized advice on drug dosage has beneficial effects on patient outcomes compared with routine care (empiric dosing without computer assistance).

SEARCH METHODS

The following databases were searched from 1996 to January 2012: EPOC Group Specialized Register, Reference Manager; Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Ovid; EMBASE, Ovid; and CINAHL, EbscoHost. A "top up" search was conducted for the period January 2012 to January 2013; these results were screened by the authors and potentially relevant studies are listed in Studies Awaiting Classification. The review authors also searched reference lists of relevant studies and related reviews.

SELECTION CRITERIA

We included randomized controlled trials, non-randomized controlled trials, controlled before-and-after studies and interrupted time series analyses of computerized advice on drug dosage. The participants were healthcare professionals responsible for patient care. The outcomes were any objectively measured change in the health of patients resulting from computerized advice (such as therapeutic drug control, clinical improvement, adverse reactions).

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted data and assessed study quality. We grouped the results from the included studies by drug used and the effect aimed at for aminoglycoside antibiotics, amitriptyline, anaesthetics, insulin, anticoagulants, ovarian stimulation, anti-rejection drugs and theophylline. We combined the effect sizes to give an overall effect for each subgroup of studies, using a random-effects model. We further grouped studies by type of outcome when appropriate (i.e. no evidence of heterogeneity).

MAIN RESULTS

Forty-six comparisons (from 42 trials) were included (as compared with 26 comparisons in the last update) including a wide range of drugs in inpatient and outpatient settings. All were randomized controlled trials except two studies. Interventions usually targeted doctors, although some studies attempted to influence prescriptions by pharmacists and nurses. Drugs evaluated were anticoagulants, insulin, aminoglycoside antibiotics, theophylline, anti-rejection drugs, anaesthetic agents, antidepressants and gonadotropins. Although all studies used reliable outcome measures, their quality was generally low.This update found similar results to the previous update and managed to identify specific therapeutic areas where the computerized advice on drug dosage was beneficial compared with routine care:1. it increased target peak serum concentrations (standardized mean difference (SMD) 0.79, 95% CI 0.46 to 1.13) and the proportion of people with plasma drug concentrations within the therapeutic range after two days (pooled risk ratio (RR) 4.44, 95% CI 1.94 to 10.13) for aminoglycoside antibiotics;2. it led to a physiological parameter more often within the desired range for oral anticoagulants (SMD for percentage of time spent in target international normalized ratio +0.19, 95% CI 0.06 to 0.33) and insulin (SMD for percentage of time in target glucose range: +1.27, 95% CI 0.56 to 1.98);3. it decreased the time to achieve stabilization for oral anticoagulants (SMD -0.56, 95% CI -1.07 to -0.04);4. it decreased the thromboembolism events (rate ratio 0.68, 95% CI 0.49 to 0.94) and tended to decrease bleeding events for anticoagulants although the difference was not significant (rate ratio 0.81, 95% CI 0.60 to 1.08). It tended to decrease unwanted effects for aminoglycoside antibiotics (nephrotoxicity: RR 0.67, 95% CI 0.42 to 1.06) and anti-rejection drugs (cytomegalovirus infections: RR 0.90, 95% CI 0.58 to 1.40);5. it tended to reduce the length of time spent in the hospital although the difference was not significant (SMD -0.15, 95% CI -0.33 to 0.02) and to achieve comparable or better cost-effectiveness ratios than usual care;6. there was no evidence of differences in mortality or other clinical adverse events for insulin (hypoglycaemia), anaesthetic agents, anti-rejection drugs and antidepressants.For all outcomes, statistical heterogeneity quantified by I(2) statistics was moderate to high.

AUTHORS' CONCLUSIONS

This review update suggests that computerized advice for drug dosage has some benefits: it increases the serum concentrations for aminoglycoside antibiotics and improves the proportion of people for which the plasma drug is within the therapeutic range for aminoglycoside antibiotics.It leads to a physiological parameter more often within the desired range for oral anticoagulants and insulin. It decreases the time to achieve stabilization for oral anticoagulants. It tends to decrease unwanted effects for aminoglycoside antibiotics and anti-rejection drugs, and it significantly decreases thromboembolism events for anticoagulants. It tends to reduce the length of hospital stay compared with routine care while comparable or better cost-effectiveness ratios were achieved.However, there was no evidence that decision support had an effect on mortality or other clinical adverse events for insulin (hypoglycaemia), anaesthetic agents, anti-rejection drugs and antidepressants. In addition, there was no evidence to suggest that some decision support technical features (such as its integration into a computer physician order entry system) or aspects of organization of care (such as the setting) could optimize the effect of computerized advice.Taking into account the high risk of bias of, and high heterogeneity between, studies, these results must be interpreted with caution.

Appropriateness of commercially available and partially customized medication dosing alerts among pediatric patients

OBJECTIVES

To evaluate dosing alert appropriateness, categorize orders with alerts, and compare the appropriateness of alerts due to customized and non-customized dose ranges at a pediatric hospital.

METHODS

This was a retrospective analysis of medication orders causing dosing alerts. Orders for outpatient prescriptions, patients ≥18 years of age, and research protocols were excluded. Patient medical records were reviewed and ordered doses compared with a widely used pediatric reference (Lexi-Comp) and institutional recommendations. The alerted orders were categorized and the occurrence of appropriate alerts was compared.

RESULTS

There were 47 181 inpatient orders during the studied period; 1935 orders caused 3774 dosing alerts for 369 medications in 573 patients (median age 6.1 years). All alerted orders had an alert overridden by the prescriber. The majority (86.2%) of alerted orders inappropriately caused alerts; 58.0% were justifiable doses and 28.2% were within Lexi-Comp. However, 13.8% of alerted orders appropriately caused alerts; 8.0% were incorrect doses and 5.8% had no dosing recommendations available. Appropriately alerted orders occurred in 19.7% of alerted orders due to customized ranges compared to 12.8% due to non-customized ranges (p=0.002). Preterm and term neonates, infants, and children (2-5 years) had higher proportions of inappropriate alerts compared to appropriate alerts (all p<0.01).

CONCLUSIONS

The vast majority of dosing alerts were presented to practitioners inappropriately, potentially contributing to alert fatigue. Appropriate alerts occurred more often when alerts were due to customized ranges. Advances in dosing alerts should aim to provide accurate and clinically relevant alerts that minimize excessive inappropriate alerting. Medications requiring dosing adjustments based on clinical parameters must be taken into account when designing and evaluating dosing alerts.

Evaluation of medication dose alerts in pediatric inpatients

OBJECTIVE

This study evaluates the impact of 12,093 consecutive dose alerts generated by a computerized provider order entry system on pediatric medication ordering.

PATIENTS AND METHODS

All medication orders entered and all resulting medication dose alerts at the Johns Hopkins Children's Medical and Surgical Center in 2010, were retrospectively evaluated. Inclusion criteria were hospitalized patients less than 21 years old. There were no exclusion criteria.

RESULTS

During 2010, there were 7738 admissions for 5553 unique patients. A total of 182,308 medication orders for 1092 unique medications were submitted by providers. Six percent (11,155) of orders or order attempts generated alerts for 2046 patients and 524 medications. Two categories of alerts were analyzed: dose range alerts and informational alerts. 73.4% (8187) of all alerts were dose range alerts, with a compliance rate of 8.5% (694); 26.6% (2968) were informational alerts, with a compliance rate of 5.5% (163).

CONCLUSIONS

We found that underdosing alerts provide less value to providers than overdosing alerts. However, the low compliance with the alerts should trigger the evaluation of clinical practice behavior and the existing alert thresholds. Informational alerts noting the absence of established dosing guidelines had little effect on provider behavior and should be avoided when building a dose range alert system.

Computerized clinical decision support for medication prescribing and utilization in pediatrics

BACKGROUND AND OBJECTIVE

Accurate and informed prescribing is essential to ensure the safe and effective use of medications in pediatric patients. Computerized clinical decision support (CCDS) functionalities have been embedded into computerized physician order entry systems with the aim of ensuring accurate and informed medication prescribing. Owing to a lack of comprehensive analysis of the existing literature, this review was undertaken to analyze the effect of CCDS implementation on medication prescribing and use in pediatrics.

MATERIALS AND METHODS

A literature search was performed using keywords in PubMed to identify research studies with outcomes related to the implementation of medication-related CCDS functionalities.

RESULTS AND DISCUSSION

Various CCDS functionalities have been implemented in pediatric patients leading to different results. Medication dosing calculators have decreased calculation errors. Alert-based CCDS functionalities, such as duplicate therapy and medication allergy checking, may generate excessive alerts. Medication interaction CCDS has been minimally studied in pediatrics. Medication dosing support has decreased adverse drug events, but has also been associated with high override rates. Use of medication order sets have improved guideline adherence. Guideline-based treatment recommendations generated by CCDS functionalities have had variable influence on appropriate medication use, with few studies available demonstrating improved patient outcomes due to CCDS use.

CONCLUSION

Although certain medication-related CCDS functionalities have shown benefit in medication prescribing for pediatric patients, others have resulted in high override rates and inconsistent or unknown impact on patient care. Further studies analyzing the effect of individual CCDS functionalities on safe and effective prescribing and medication use are required.