Errors associated with applying decision support by suggesting default doses for aminoglycosides

A Provider-Focused Intervention to Promote Optimal Care of Pediatric Patients With Suspected Elbow Fracture

OBJECTIVE

Emergency department (ED) and urgent care (UC) physicians' accurate assessment of the neurovascular and musculoskeletal (NV/MSK) examination in pediatric patients with suspected elbow fracture is crucial to the early recognition of neurovascular compromise. Our objective was to determine the impact of computer-based simulation (CBS) and computerized clinical decision support systems (CCDSS) on ED and UC physicians' assessment of the NV/MSK examination of pediatric patients with elbow fracture as noted in their documentation.

METHODS

All ED UC physician participants received CBS training about management of pediatric patients with suspected elbow fracture. Participants were then randomized to receive CCDSS (intervention arm) when an eligible patient was seen or no further intervention (comparison arm.) Participants received feedback on the proportion of patients with discharge diagnosis of elbow fracturewith proper examination elements documented.

RESULTS

Twenty-eight ED and UC physicians were enrolled - 14 in each arm. Over the span of 16 weeks, 50 patients with a discharge diagnosis of elbow fracture were seen - 25 in each arm. Twenty-two of 25 (88%) patients seen by intervention arm participants had a complete NV/MSK examination documented. Six of 25 (24%) patients seen by comparison arm participants had a complete NV/MSK examination documented. Elements most commonly missed in the comparison arm included documentation of ulnar pulse as well as radial, median, and ulnar nerve motor functions.

CONCLUSIONS

Compared with single CBS training alone, repeated exposure to CCDSS after CBS training resulted in improved documentation of the NV/MSK status of pediatric patients with elbow fracture.

Medication Safety in Two Intensive Care Units of a Community Teaching Hospital After Electronic Health Record Implementation: Sociotechnical and Human Factors Engineering Considerations

OBJECTIVE

The aim of the study was to assess the impact of Electronic Health Record (EHR) implementation on medication safety in two intensive care units (ICUs).

METHODS

Using a prospective pre-post design, we assessed 1254 consecutive admissions to two ICUs before and after an EHR implementation. Each medication event was evaluated with regard to medication error (error type, medication-management stage) and impact on patient (severity of potential or actual harm).

RESULTS

We identified 4063 medication-related events either pre-implementation (2074 events) or post-implementation (1989 events). Although the overall potential for harm due to medication errors decreased post-implementation only 2 of the 3 error rates were significantly lower post-implementation. After EHR implementation, we observed reductions in rates of medication errors per admission at the stages of transcription (0.13-0, P < 0.001), dispensing (0.49-0.16, P < 0.001), and administration (0.83-0.56, P = 0.011). Within the ordering stage, 4 error types decreased post-implementation (orders with omitted information, error-prone abbreviations, illegible orders, failure to renew orders) and 4 error types increased post-implementation (orders of wrong drug, orders containing a wrong start or stop time, duplicate orders, orders with inappropriate or wrong information). Within the administration stage, we observed a reduction of late administrations and increases in omitted administrations and incorrect documentation.

CONCLUSIONS

Electronic Health Record implementation in two ICUs was associated with both improvement and worsening in rates of specific error types. Further safety improvements require a nuanced understanding of how various error types are influenced by the technology and the sociotechnical work system of the technology implementation. Recommendations based on human factors engineering principles are provided for reducing medication errors.

Design, development, and deployment of an indication- and kidney function-based decision support tool to optimize treatment and reduce medication dosing errors

Delivering clinical decision support (CDS) at the point of care has long been considered a major advantage of computerized physician order entry (CPOE). Despite the widespread implementation of CPOE, medication ordering errors and associated adverse events still occur at an unacceptable level. Previous attempts at indication- and kidney function-based dosing have mostly employed intrusive CDS, including interruptive alerts with poor usability. This descriptive work describes the design, development, and deployment of the Adult Dosing Methodology (ADM) module, a novel CDS tool that provides indication- and kidney-based dosing at the time of order entry. Inclusion of several antimicrobials in the initial set of medications allowed for the additional goal of optimizing therapy duration for appropriate antimicrobial stewardship. The CDS aims to decrease order entry errors and burden on providers by offering automatic dose and frequency recommendations, integration within the native electronic health record, and reasonable knowledge maintenance requirements. Following implementation, early utilization demonstrated high acceptance of automated recommendations, with up to 96% of provided automated recommendations accepted by users.

Incident reports versus direct observation to identify medication errors and risk factors in hospitalised newborns

Newborns are often exposed to medication errors in hospitals. Identification and understanding the causes and risk factors associated with medication errors will help to improve the effectiveness of medication. We sought to compare voluntary incident reports and direct observation in the identification of medication errors. We also identified corresponding risk factors in order to establish measures to prevent medication errors. Medication errors identified by a clinical pharmacist and those recorded in our incident reporting system by caregivers were analysed. Main outcomes were rates, type and severity of medication error, and other variables related to medication errors. Ultimately, 383 medication errors were identified by the clinical pharmacist, and two medication errors were declared by caregivers. Prescription errors accounted for 38.4%, preparation errors for 16.2%, and administration errors for 45.4%. The two variables significantly related to the occurrence of medication errors were gestational age < 32.0 weeks (p = 0.04) and the number of drugs prescribed (p < 0.01).Conclusion: Caregivers underreported the true rate of medication errors. Most medication errors were caused by inattention and could have been limited by simplifying the medication process. Risk of medication errors is increased in newborns < 32.0 weeks and increases with the number of drugs prescribed to each patient. What is Known: • Newborns in hospitals are particularly susceptible to medication errors. • Identification and understanding the reasons for medication errors should help us to establish preventive measures to reduce the occurrence of such errors. What is New: • Direct observation of the medication process, though time consuming, is essential to accurately assess the frequency of medication errors, which are underreported by caregivers. Most medication errors are caused by inattention and could be limited by simplifying the medication process. • The risk of medication errors was significantly increased in very preterm newborns (< 32 weeks) and when the number of prescription per patient increased.

Provider-Focused Intervention to Promote Comprehensive Screening for Adolescent Idiopathic Scoliosis by Primary Care Pediatricians

Screening can detect adolescent idiopathic scoliosis (AIS). The objective was to determine if computer-based simulation (CBS) and computerized clinical decision-support systems (CCDSS) would improve primary care providers' AIS screening exams as noted in their documentation. All participants received AIS screening CBS training. Participants were then randomized to receive either CCDSS when an eligible patient was seen (intervention arm) or no further intervention (comparison arm). Eligible patients' documentation was analyzed looking for a complete AIS screening exam. Over the span of 17 weeks, 1051 eligible patients were seen; 468 by providers in the intervention arm, 583 in the comparison arm. In all, 292/468 (62%) of eligible patients seen in the intervention arm and 0/583 (0%) in the comparison arm had a complete AIS screening exam documented. Compared with single CBS training alone, repeated exposure to CCDSS after CBS training resulted in improved documentation of the screening exam for AIS.

Evidence-based Health Informatics: How Do We Know What We Know?

Background: Health IT is expected to have a positive impact on the quality and efficiency of health care. But reports on negative impact and patient harm continue to emerge. The obligation of health informatics is to make sure that health IT solutions provide as much benefit with as few negative side effects as possible. To achieve this, health informatics as a discipline must be able to learn, both from its successes as well as from its failures.

Objectives: To present motivation, vision, and history of evidence-based health informatics, and to discuss achievements, challenges, and needs for action.

Methods: Reflections on scientific literature and on own experiences.

Results: Eight challenges on the way towards evidence-based health informatics are identified and discussed: quality of studies; publication bias; reporting quality; availability of publications; systematic reviews and meta-analysis; training of health IT evaluation experts; translation of evidence into health practice; and post-market surveil-lance. Identified needs for action comprise: establish health IT study registers; increase the quality of publications; develop a taxonomy for health IT systems; improve indexing of published health IT evaluation papers; move from meta-analysis to meta-summaries; include health IT evaluation competencies in curricula; develop evidence-based implementation frameworks; and establish post-marketing surveillance for health IT.

Conclusions: There has been some progress, but evidence-based health informatics is still in its infancy. Building evidence in health informatics is our obligation if we consider medical informatics a scientific discipline.

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

OBJECTIVE

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

MATERIALS AND METHODS

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

RESULTS

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

DISCUSSION

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

CONCLUSIONS

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

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.

A systematic review of the types and causes of prescribing errors generated from using computerized provider order entry systems in primary and secondary care

OBJECTIVE

To understand the different types and causes of prescribing errors associated with computerized provider order entry (CPOE) systems, and recommend improvements in these systems.

MATERIALS AND METHODS

We conducted a systematic review of the literature published between January 2004 and June 2015 using three large databases: the Cumulative Index to Nursing and Allied Health Literature, Embase, and Medline. Studies that reported qualitative data about the types and causes of these errors were included. A narrative synthesis of all eligible studies was undertaken.

RESULTS

A total of 1185 publications were identified, of which 34 were included in the review. We identified 8 key themes associated with CPOE-related prescribing errors: computer screen display, drop-down menus and auto-population, wording, default settings, nonintuitive or inflexible ordering, repeat prescriptions and automated processes, users' work processes, and clinical decision support systems. Displaying an incomplete list of a patient's medications on the computer screen often contributed to prescribing errors. Lack of system flexibility resulted in users employing error-prone workarounds, such as the addition of contradictory free-text comments. Users' misinterpretations of how text was presented in CPOE systems were also linked with the occurrence of prescribing errors.

DISCUSSION AND CONCLUSIONS

Human factors design is important to reduce error rates. Drop-down menus should be designed with safeguards to decrease the likelihood of selection errors. Development of more sophisticated clinical decision support, which can perform checks on free-text, may also prevent errors. Further research is needed to ensure that systems minimize error likelihood and meet users' workflow expectations.

EHR-related medication errors in two ICUs

The objective of this study was to describe the frequency, potential harm, and nature of electronic health record (EHR)-related medication errors in intensive care units (ICUs). Using a secondary data analysis of a large database of medication safety events collected in a study on EHR technology in ICUs, we assessed the EHR relatedness of a total of 1622 potential preventable adverse drug events (ADEs) identified in a sample of 624 patients in 2 ICUs of a medical center. Thirty-four percent of the medication events were found to be EHR related. The EHR-related medication events had greater potential for more serious patient harm and occurred more frequently at the ordering stage as compared to non-EHR-related events. Examples of EHR-related events included orders with omitted information and duplicate orders. The list of EHR-related medication errors can be used by health care delivery organizations to monitor implementation and use of the technology and its impact on patient safety. Health information technology (IT) vendors can use the list to examine whether their technology can mitigate or reduce EHR-related medication errors.

Computerized Decision Support Improves Medication Review Effectiveness: An Experiment Evaluating the STRIP Assistant's Usability

Background

Polypharmacy poses threats to patients’ health. The Systematic Tool to Reduce Inappropriate Prescribing (STRIP) is a drug optimization process for conducting medication reviews in primary care. To effectively and efficiently incorporate this method into daily practice, the STRIP Assistant—a decision support system that aims to assist physicians with the pharmacotherapeutic analysis of patients’ medical records—has been developed. It generates context-specific advice based on clinical guidelines.

Objective

The aim of this study was to validate the STRIP Assistant’s usability as a tool for physicians to optimize medical records for polypharmacy patients.

Methods

In an online experiment, 42 physicians were asked to optimize medical records for two comparable polypharmacy patients, one in their usual manner and one using the STRIP Assistant. Changes in effectiveness were measured by comparing respondents’ optimized medicine prescriptions with medication prepared by an expert panel of two geriatrician-pharmacologists. Efficiency was operationalized by recording the time the respondents took to optimize the two cases. User satisfaction was measured with the System Usability Scale (SUS). Independent and paired t tests were used for analysis.

Results

Medication optimization significantly improved with the STRIP Assistant. Appropriate decisions increased from 58 % without the STRIP Assistant to 76 % with it (p < 0.0001). Inappropriate decisions decreased from 42 % without the STRIP Assistant to 24 % with it (p < 0.0001). Participants spent significantly more time optimizing medication with the STRIP Assistant (24 min) than without it (13 min; p < 0.0001). They assigned it a below-average SUS score of 63.25.

Conclusion

The STRIP Assistant improves the effectiveness of medication reviews for polypharmacy patients.

A pre-postintervention study to evaluate the impact of dose calculators on the accuracy of gentamicin and vancomycin initial doses

OBJECTIVES

Gentamicin and vancomycin are narrow-therapeutic-index antibiotics with potential for high toxicity requiring dose individualisation and continuous monitoring. Clinical decision support (CDS) tools have been effective in reducing gentamicin and vancomycin dosing errors. Online dose calculators for these drugs were implemented in a London National Health Service hospital. This study aimed to evaluate the impact of these calculators on the accuracy of gentamicin and vancomycin initial doses.

METHODS

The study used a pre-postintervention design. Data were collected using electronic patient records and paper notes. Random samples of gentamicin and vancomycin initial doses administered during the 8 months before implementation of the calculators were assessed retrospectively against hospital guidelines. Following implementation of the calculators, doses were assessed prospectively. Any gentamicin dose not within ± 10% and any vancomycin dose not within ± 20% of the guideline-recommended dose were considered incorrect.

RESULTS

The intranet calculator pages were visited 721 times (gentamicin=333; vancomycin=388) during the 2-month period following the calculators' implementation. Gentamicin dose errors fell from 61.5% (120/195) to 44.2% (95/215), p<0.001. Incorrect vancomycin loading doses fell from 58.1% (90/155) to 32.4% (46/142), p<0.001. Incorrect vancomycin first maintenance doses fell from 55.5% (86/155) to 33.1% (47/142), p<0.001. Loading and first maintenance vancomycin doses were both incorrect in 37.4% (58/155) of patients before and 13.4% (19/142) after calculator implementation, p<0.001.

CONCLUSIONS

This study suggests that gentamicin and vancomycin dose calculators significantly improved the prescribing of initial doses of these agents. Therefore, healthcare organisations should consider using such CDS tools to support the prescribing of these high-risk drugs.

Memorandum on the use of information technology to improve medication safety

BACKGROUND

Information technology in health care has a clear potential to improve the quality and efficiency of health care, especially in the area of medication processes. On the other hand, existing studies show possible adverse effects on patient safety when IT for medication-related processes is developed, introduced or used inappropriately.

OBJECTIVES

To summarize definitions and observations on IT usage in pharmacotherapy and to derive recommendations and future research priorities for decision makers and domain experts.

METHODS

This memorandum was developed in a consensus-based iterative process that included workshops and e-mail discussions among 21 experts coordinated by the Drug Information Systems Working Group of the German Society for Medical Informatics, Biometry and Epidemiology (GMDS).

RESULTS

The recommendations address, among other things, a stepwise and comprehensive strategy for IT usage in medication processes, the integration of contextual information for alert generation, the involvement of patients, the semantic integration of information resources, usability and adaptability of IT solutions, and the need for their continuous evaluation.

CONCLUSION

Information technology can help to improve medication safety. However, challenges remain regarding access to information, quality of information, and measurable benefits.

Medication safety and knowledge-based functions: a stepwise approach against information overload

AIMS

The aim was to improve medication safety in an emergency department (ED) by enhancing the integration and presentation of safety information for drug therapy.

METHODS

Based on an evaluation of safety of drug therapy issues in the ED and a review of computer-assisted intervention technologies we redesigned an electronic case sheet and implemented computer-assisted interventions into the routine work flow. We devised a four step system of alerts, and facilitated access to different levels of drug information. System use was analyzed over a period of 6 months. In addition, physicians answered a survey based on the technology acceptance model TAM2.

RESULTS

The new application was implemented in an informal manner to avoid work flow disruption. Log files demonstrated that step I, 'valid indication' was utilized for 3% of the recorded drugs and step II 'tooltip for well-known drug risks' for 48% of the drugs. In the questionnaire, the computer-assisted interventions were rated better than previous paper based measures (checklists, posters) with regard to usefulness, support of work and information quality.

CONCLUSION

A stepwise assisting intervention received positive user acceptance. Some intervention steps have been seldom used, others quite often. We think that we were able to avoid over-alerting and work flow intrusion in a critical ED environment.

Assessing cardiovascular drug safety for clinical decision-making

Optimal therapeutic decision-making requires integration of patient-specific and therapy-specific information at the point of care, particularly when treating patients with complex cardiovascular conditions. The formidable task for the prescriber is to synthesize information about all therapeutic options and match the best treatment with the characteristics of the individual patient. Computerized decision support systems have been developed with the goal of integrating such information and presenting the acceptable therapeutic options on the basis of their effectiveness, often with limited consideration of their safety for a specific patient. Assessing the safety of therapies relative to each patient is difficult, and sometimes impossible, because the evidence required to make such an assessment is either imperfect or does not exist. In addition, many of the alerts sent to prescribers by decision-support systems are not perceived as credible, and 'alert fatigue' causes warnings to be ignored putting patients at risk of harm. The CredibleMeds.org and BrugadaDrugs.org websites are prototypes for evidence-based sources of safety information that rank drugs for their risk of a specific form of drug toxicity-in these cases, drug-induced arrhythmias. Broad incorporation of this type of information in electronic prescribing algorithms and clinical decision support could speed the evolution of safe personalized medicine.

Design of decision support interventions for medication prescribing

OBJECTIVE

Describe optimal design attributes of clinical decision support (CDS) interventions for medication prescribing, emphasizing perceptual, cognitive and functional characteristics that improve human-computer interaction (HCI) and patient safety.

METHODS

Findings from published reports on success, failures and lessons learned during implementation of CDS systems were reviewed and interpreted with regard to HCI and software usability principles. We then formulated design recommendations for CDS alerts that would reduce unnecessary workflow interruptions and allow clinicians to make informed decisions quickly, accurately and without extraneous cognitive and interactive effort.

RESULTS

Excessive alerting that tends to distract clinicians rather than provide effective CDS can be reduced by designing only high severity alerts as interruptive dialog boxes and less severe warnings without explicit response requirement, by curating system knowledge bases to suppress warnings with low clinical utility and by integrating contextual patient data into the decision logic. Recommended design principles include parsimonious and consistent use of color and language, minimalist approach to the layout of information and controls, the use of font attributes to convey hierarchy and visual prominence of important data over supporting information, the inclusion of relevant patient data in the context of the alert and allowing clinicians to respond with one or two clicks.

CONCLUSION

Although HCI and usability principles are well established and robust, CDS and EHR system interfaces rarely conform to the best known design conventions and are seldom conceived and designed well enough to be truly versatile and dependable tools. These relatively novel interventions still require careful monitoring, research and analysis of its track record to mature. Clarity and specificity of alert content and optimal perceptual and cognitive attributes, for example, are essential for providing effective decision support to clinicians.

Interface design principles for usable decision support: a targeted review of best practices for clinical prescribing interventions

Developing effective clinical decision support (CDS) systems for the highly complex and dynamic domain of clinical medicine is a serious challenge for designers. Poor usability is one of the core barriers to adoption and a deterrent to its routine use. We reviewed reports describing system implementation efforts and collected best available design conventions, procedures, practices and lessons learned in order to provide developers a short compendium of design goals and recommended principles. This targeted review is focused on CDS related to medication prescribing. Published reports suggest that important principles include consistency of design concepts across networked systems, use of appropriate visual representation of clinical data, use of controlled terminology, presenting advice at the time and place of decision making and matching the most appropriate CDS interventions to clinical goals. Specificity and contextual relevance can be increased by periodic review of trigger rules, analysis of performance logs and maintenance of accurate allergy, problem and medication lists in health records in order to help avoid excessive alerting. Developers need to adopt design practices that include user-centered, iterative design and common standards based on human-computer interaction (HCI) research methods rooted in ethnography and cognitive science. Suggestions outlined in this report may help clarify the goals of optimal CDS design but larger national initiatives are needed for systematic application of human factors in health information technology (HIT) development. Appropriate design strategies are essential for developing meaningful decision support systems that meet the grand challenges of high-quality healthcare.

Cognitive analysis of decision support for antibiotic ordering in a neonatal intensive care unit

BACKGROUND

Clinical decision support systems (CDSS) are a method used to support prescribing accuracy when deployed within a computerized provider order entry system (CPOE). Divergence from using CDSS is exemplified by high alert override rates. Excessive cognitive load imposed by the CDSS may help to explain such high rates.

OBJECTIVES

The aim of this study was to describe the cognitive impact of a CPOE-integrated CDSS by categorizing system use problems according to the type of mental processing required to resolve them.

METHODS

A qualitative, descriptive design was used employing two methods; a cognitive walkthrough and a think-aloud protocol. Data analysis was guided by Norman's Theory of Action and a theory of cognitive distances which is an extension to Norman's theory.

RESULTS

The most frequently occurring source of excess cognitive effort was poor information timing. Information presented by the CDSS was often presented after clinicians required the information for decision making. Additional sources of effort included use of language that was not clear to the user, vague icons, and lack of cues to guide users through tasks.

CONCLUSIONS

Lack of coordination between clinician's task-related thought processes and those presented by a CDSS results in excessive cognitive work required to use the system. This can lead to alert overrides and user errors. Close attention to user's cognitive processes as they carry out clinical tasks prior to CDSS development may provide key information for system design that supports clinical tasks and reduces cognitive effort.

How should medication errors be defined? Development and test of a definition

Aims: Definitions of medication errors vary widely in the literature, and prevalence from 2–75% in part because of this lack of consensus. Thus, clarification of the concept is urgently needed. The objective was to develop a clear-cut definition of medication errors and specify relevant error types in the medication process. Methods: Based on existing taxonomy and through a modified Delphi-process consensus of definition and error types were reached among Danish experts appointed by 13 healthcare organisations and the project group. The experts prioritised five definitions of medication errors and score the relevance of 76 error types. Based on explicit criteria, the project group settled non-consensus cases. Results: The panel consisted of 12 physicians, seven pharmacists, and six nurses. Consensus was reached for the definition “An error in the stages of the medication process – ordering, dispensing, administering and monitoring the effect – causing harm or implying a risk of harming the patient”. Moreover, consensus for 60 of 76 error types was achieved. Applied to a historic dataset the definition reduced the number of medication errors from 34% to 7%. Conclusions: Experts deemed a definition using harm or risk of harm as cut-off point as the most appropriate in Danish hospital settings. In addition, they agreed on a list of 60 error types covering the medication process. Interestingly, a substantial lower occurrence of medication errors was found when applied to historic data. The definition is in accordance with international taxonomy, thus is assumed to be applicable to modern healthcare settings abroad.

Effects of clinical decision support on initial dosing and monitoring of tobramycin and amikacin

PURPOSE

The impact of clinical decision support (CDS) on initial doses and intervals and pharmacokinetic outcomes of amikacin and tobramycin therapy was evaluated.

METHODS

A complex CDS advisor to provide guidance on initial dosing and monitoring of aminoglycoside orders, using both traditional-dosing and extended-interval-dosing strategies, was integrated into a computerized prescriber-order-entry (CPOE) system and compared with a control group whose aminoglycoside orders were closely monitored by pharmacists. The primary outcome measured was an initial dose within 10% of a dose calculated to be adherent to published dose guidelines. Secondary outcomes included a guideline-adherent interval, trough and peak concentrations in goal range, and rate of nephrotoxicity.

RESULTS

Of 216 patients studied, 97 were prescribed amikacin and 119 were prescribed tobramycin. The number of orders with initial doses consistent with reference standards increased from 40% in the preadvisor group to 80% in the postadvisor group (p < 0.001). Selection of the correct initial interval based on renal function increased from 63% to 87% (p < 0.001). The changes in the initial dosing and interval resulted in an increase of trough concentrations at goal (59% in the preadvisor group versus 89% in the postadvisor group, p = 0.0004). There was no significant difference in peak concentrations in the goal range or rate of nephrotoxicity.

CONCLUSION

An advisor for aminoglycoside dosing and monitoring integrated into a CPOE system significantly improved selection of initial doses and intervals and resulted in an improvement in the rate of trough serum drug concentrations at goal compared with standard provider dosing.

Detecting pregnancy use of non-hormonal category X medications in electronic medical records

OBJECTIVES

To determine whether a rule-based algorithm applied to an outpatient electronic medical record (EMR) can identify patients who are pregnant and prescribed medications proved to cause birth defects.

DESIGN

A descriptive study using the University of Pennsylvania Health System outpatient EMR to simulate a prospective algorithm to identify exposures during pregnancy to category X medications, soon enough to intervene and potentially prevent the exposure. A subsequent post-hoc algorithm was also tested, working backwards from pregnancy endpoints, to search for possible exposures that should have been detected.

MEASUREMENTS

Category X medications prescribed to pregnant patients.

RESULTS

The alert simulation identified 2201 pregnancies with 16,969 pregnancy months (excluding abortions and ectopic pregnancies). Of these, 30 appeared to have an order for a non-hormone category X medication during pregnancy. However, none of the 30 'exposed pregnancies' were confirmed as true exposures in medical records review. The post-hoc algorithm identified 5841 pregnancies with 64 exposed pregnancies in 52,569 risk months, only one of which was a confirmed case.

CONCLUSIONS

Category X medications may indeed be used in pregnancy, although rarely. However, most patients identified by the algorithm as exposed in pregnancy were not truly exposed. Therefore, implementing an electronic warning without evaluation would have inconvenienced prescribers, possibly hurting some patients (leading to non-use of needed drugs), with no benefit. These data demonstrate that computerized physician order entry interventions should be selected and evaluated carefully even before their use, using alert simulations such as that performed here, rather than just taken off the shelf and accepted as credible without formal evaluation.

Health information technology and quality of health care: strategies for reducing disparities in underresourced settings

Health information technology (health IT) has potential for facilitating quality improvement and reducing quality disparities found in underresourced settings (URSs). With this systematic literature review, complemented by key informant interviews, the authors sought to identify evidence regarding health IT and quality outcomes in URSs. The review included 105 peer-reviewed studies (2004-2009) in all settings. Only 15 studies included URSs, and 8 focused on URSs. Based on literature across settings, most evidence was available for quality impact of order entry, clinical decision support systems, and computerized reminders. Study designs were predominantly quasi-experimental (37%) or descriptive (35%); 90% of the studies focused on the microsystem level of quality improvement, indicating a need for expanding research into patient experience and organizational and environmental levels. Key informants highlighted organizational partnerships and health IT champions and emphasized that for health IT to have an impact on quality, there must be an organizational culture of quality improvement.

Substantial reduction of inappropriate tablet splitting with computerised decision support: a prospective intervention study assessing potential benefit and harm

Background

Currently ambulatory patients break one in four tablets before ingestion. Roughly 10% of them are not suitable for splitting because they lack score lines or because enteric or modified release coating is destroyed impairing safety and effectiveness of the medication. We assessed impact and safety of computerised decision support on the inappropriate prescription of split tablets.

Methods

We performed a prospective intervention study in a 1680-bed university hospital. Over a 15-week period we evaluated all electronically composed medication regimens and determined the fraction of tablets and capsules that demanded inappropriate splitting. In a subsequent intervention phase of 15 weeks duration for 10553 oral drugs divisibility characteristics were indicated in the system. In addition, an alert was generated and displayed during the prescription process whenever the entered dosage regimen demanded inappropriate splitting (splitting of capsules, unscored tablets, or scored tablets unsuitable for the intended fragmentation).

Results

During the baseline period 12.5% of all drugs required splitting and 2.7% of all drugs (257/9545) required inappropriate splitting. During the intervention period the frequency of inappropriate splitting was significantly reduced (1.4% of all drugs (146/10486); p = 0.0008). In response to half of the alerts (69/136) physicians adjusted the medication regimen. In the other half (67/136) no corrections were made although a switch to more suitable drugs (scored tablets, tablets with lower strength, liquid formulation) was possible in 82% (55/67).

Conclusion

This study revealed that computerised decision support can immediately reduce the frequency of inappropriate splitting without introducing new safety hazards.

The effect of electronic prescribing on medication errors and adverse drug events: a systematic review

The objective of this systematic review is to analyse the relative risk reduction on medication error and adverse drug events (ADE) by computerized physician order entry systems (CPOE). We included controlled field studies and pretest-posttest studies, evaluating all types of CPOE systems, drugs and clinical settings. We present the results in evidence tables, calculate the risk ratio with 95% confidence interval and perform subgroup analyses for categorical factors, such as the level of care, patient group, type of drug, type of system, functionality of the system, comparison group type, study design, and the method for detecting errors. Of the 25 studies that analysed the effects on the medication error rate, 23 showed a significant relative risk reduction of 13% to 99%. Six of the nine studies that analysed the effects on potential ADEs showed a significant relative risk reduction of 35% to 98%. Four of the seven studies that analysed the effect on ADEs showed a significant relative risk reduction of 30% to 84%. Reporting quality and study quality was often insufficient to exclude major sources of bias. Studies on home-grown systems, studies comparing electronic prescribing to handwriting prescribing, and studies using manual chart review to detect errors seem to show a higher relative risk reduction than other studies. Concluding, it seems that electronic prescribing can reduce the risk for medication errors and ADE. However, studies differ substantially in their setting, design, quality, and results. To further improve the evidence-base of health informatics, more randomized controlled trials (RCTs) are needed, especially to cover a wider range of clinical and geographic settings. In addition, reporting quality of health informatics evaluation studies has to be substantially improved.

Clinical review: medication errors in critical care

Medication errors in critical care are frequent, serious, and predictable. Critically ill patients are prescribed twice as many medications as patients outside of the intensive care unit (ICU) and nearly all will suffer a potentially life-threatening error at some point during their stay. The aim of this article is to provide a basic review of medication errors in the ICU, identify risk factors for medication errors, and suggest strategies to prevent errors and manage their consequences.

Evaluation of outpatient computerized physician medication order entry systems: a systematic review

This paper provides a systematic literature review of CPOE evaluation studies in the outpatient setting on: safety; cost and efficiency; adherence to guideline; alerts; time; and satisfaction, usage, and usability. Thirty articles with original data (randomized clinical trial, non-randomized clinical trial, or observational study designs) met the inclusion criteria. Only four studies assessed the effect of CPOE on safety. The effect was not significant on the number of adverse drug events. Only one study showed a significant reduction of the number of medication errors. Three studies showed significant reductions in medication costs; five other studies could not support this. Most studies on adherence to guidelines showed a significant positive effect. The relatively small number of evaluation studies published to date do not provide adequate evidence that CPOE systems enhance safety and reduce cost in the outpatient settings. There is however evidence for (a) increasing adherence to guidelines, (b) increasing total prescribing time, and (c) high frequency of ignored alerts.