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Objective: Investigation of drug administration problems, respective causes, and needs for assistance., Methods: Focus group discussions with patients, family caregivers, and nurses were conducted using a semi-structured interview guideline for a focused exploration of the participants' drug administration experiences and perceived needs for assistance. All discussions were audio-recorded and video-recorded, verbatim transcribed, and analyzed according to Mayring's qualitative content analysis., Results: In total, 6 focus group discussions were conducted. The qualitative content analysis revealed that patients and family caregivers frequently trivialized drug administration, were unaware of errors, and primarily blamed the dosage form of causing administration problems. Nurses also considered health-care system-related conditions and patient factors as potential causes of administration problems., Conclusions: The administration problems and perceived causes were multifaceted and often directed toward inappropriate dosage forms or health-care system-related conditions rather than critically questioning the medicine user's administration skills. To increase medicine users' motivation to scrutinize wrong administration practices, health-care professionals should consider individual perspectives on administration problems and perceived causes, assist medicine users' to identify the true cause of a distinct problem, and provide individualized support.

Purpose: Complexity of drug treatment is known to be a risk factor for administration errors and nonadherence promoting higher healthcare costs, hospital admissions and increased mortality. Number of drugs and dose frequency are parameters often used to assess complexity related to the medication regimen. However, factors resulting from complex processes of care or arising from patient characteristics are only sporadically analyzed. Hence, the objective of this review is to give a comprehensive overview of relevant, patient-centered factors influencing complexity of drug treatment., Methods: A purposeful literature search was performed in MEDLINE to identify potential complexity factors relating to the prescribed drug (i.e. dosage forms or other product characteristics), the specific medication regimen (i.e. dosage schemes or additional instructions), specific patient characteristics and process characteristics. Factors were included if they were associated to administration errors, nonadherence and related adverse drug events detected in community dwelling adult patients., Results: Ninety-one influencing factors were identified: fourteen in "dosage forms", five in "product characteristics", twelve in "dosage schemes", nine in "additional instructions", thirty-one in "patient characteristics" and twenty in "process characteristics"., Conclusions: Although the findings are limited by the non-systematic search process and the heterogeneous results, the search shows the influence of many factors on the complexity of drug treatment. However, to evaluate their relevance for individual patients, prospective studies are necessary.

With advancing age there is an increase in the disease burden and thus in the number of drugs prescribed to this patient group. It is often assumed that an increase in pill count is associated per se with an increase in the number of medication errors (e.g., potentially inappropriate prescribing, PIP) and the frequency of adverse drug events (ADE). However, prescribing more drugs can also mean more successful treatment, making it important to critically assess the benefit/risk balance of the medications prescribed in each patient. Whether a prescribed medication is appropriate depends on the clinical state of the patient (diagnoses), treatment goals, comedication/drug interactions, patient preferences, whether the patient tolerates the drug, a measure of how frail the patient is, etc. It is often argued that the number of prescribed drugs should be restricted, but we hold the view that this should only be done after careful consideration of the factors mentioned above. In our study, we remodeled the findings of two large cohort studies investigating the association between the number of drugs prescribed and clinical endpoints. The graphic illustrations obtained confirmed that targeting pill count, as a measure to reduce ADEs and mortality, fails to impact patient well-being because the number of drugs prescribed is likely determined by patient characteristics affecting drug response, namely, disease burden, patient functionality, and specific patient needs, all of which must be taken into account in order to reduce the risk of PIMs and the occurrence ADEs.
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Because of its inherent complexity, it is a considerable challenge to tailor drug treatment to a prevalent disease and its subgroups, which are increasingly defined by genomic variability (personalized medicine) and require consideration of context information such as co-morbidity, co-medication, patient preferences, and the specific characteristics of the healthcare sector. Thus, optimum treatment decisions might not be taken intuitively any longer, because decisions must be made both rapidly and increasingly based on analyses of complex relations of numerous variables that exceed the processing performance of a human brain. Hence, computer support is indispensable to ensure error-free high-performance medicine. A key step in computer-supported medication safety is to implement a computerized physician order entry (CPOE) system that compiles a patient's medication in a structured and coded format enabling the link to clinical decision support (CDS) systems. Implementing a CPOE is hence a strategic step for a hospital, which is crucial to exhaustingly and consistently prevent medication errors. Thereby, the best performance of a CPOE is achieved if it is deeply integrated into an electronic patient record thus enabling access to relevant patient information, which again has to be structured to allow processing. To efficiently support drug treatment, CDS systems must fulfill high-quality standards with regard to underlying data, integration, and user-interaction to ensure that they support but do not impede the provision of care.

Background: While evidence on implementation of medication safety strategies is increasing, reasons for selecting and relinquishing distinct strategies and details on implementation are typically not shared in published literature., Objective: We aimed to collect and structure expert information resulting from implementing medication safety strategies to provide advice for decision-makers., Setting: Medication safety experts with clinical expertise from thirteen hospitals throughout twelve European and North American countries shared their experience in workshop meetings, on-site-visits and remote structured interviews., Methods: We performed an expert-based, in-depth assessment of implementation of best-practice strategies to improve drug prescribing and drug administration., Main Outcome Measures: Workflow, variability and recommended medication safety strategies in drug prescribing and drug administration processes., Results: According to the experts, institutions chose strategies that targeted process steps known to be particularly error-prone in the respective setting. Often, the selection was channeled by local constraints such as the e-health equipment and critically modulated by national context factors. In our study, the experts favored electronic prescribing with clinical decision support and medication reconciliation as most promising interventions. They agreed that self-assessment and introduction of medication safety boards were crucial to satisfy the setting-specific differences and foster successful implementation., Conclusion: While general evidence for implementation of strategies to improve medication safety exists, successful selection and adaptation of a distinct strategy requires a thorough knowledge of the institute-specific constraints and an ongoing monitoring and adjustment of the implemented measures.

Aims: The aim of the present study was to conduct a meta-analysis of controlled trials assessing the impact of pharmaceutical care interventions (e.g. medication reviews) on medication underuse in older patients (≥65 years)., Methods: The databases MEDLINE and EMBASE were searched for controlled studies, and data on interventions, patient characteristics and exposure, and outcome assessment were extracted. Risk of bias was assessed using the Cochrane Collaboration's 'risk of bias' table. Results from reported outcomes were synthesized in multivariate random effects meta-analysis, subgroup meta-analysis and meta-regression., Results: From 954 identified articles, nine controlled studies, mainly comprising a medication review, were included (2542 patients). These interventions were associated with significant reductions in the mean number of omitted drugs per patient (estimate from six studies with 1469 patients: - 0.44; 95% confidence interval -0.61, -0.26) and the proportion of patients with ≥1 omitted drugs (odds ratio from eight studies with 1833 patients: 0.29; 95% confidence interval 0.13, 0.63). The only significant influential factor for improving success was the utilization of explicit screening instruments when conducting a medication review (P = 0.033)., Conclusion: Pharmaceutical care interventions, including medication reviews, can significantly reduce medication underuse in older people. The use of explicit screening instruments alone or in combination with implicit reasoning is strongly recommendable for clinical practice., (© 2015 The British Pharmacological Society.)

Aims and Objectives: To prevent medication errors in drug handling in a paediatric ward., Background: One in five preventable adverse drug events in hospitalised children is caused by medication errors. Errors in drug prescription have been studied frequently, but data regarding drug handling, including drug preparation and administration, are scarce., Design: A three-step intervention study including monitoring procedure was used to detect and prevent medication errors in drug handling., Methods: After approval by the ethics committee, pharmacists monitored drug handling by nurses on an 18-bed paediatric ward in a university hospital prior to and following each intervention step. They also conducted a questionnaire survey aimed at identifying knowledge deficits. Each intervention step targeted different causes of errors. The handout mainly addressed knowledge deficits, the training course addressed errors caused by rule violations and slips, and the reference book addressed knowledge-, memory- and rule-based errors., Results: The number of patients who were subjected to at least one medication error in drug handling decreased from 38/43 (88%) to 25/51 (49%) following the third intervention, and the overall frequency of errors decreased from 527 errors in 581 processes (91%) to 116/441 (26%). The issue of the handout reduced medication errors caused by knowledge deficits regarding, for instance, the correct 'volume of solvent for IV drugs' from 49-25%., Conclusion: Paediatric drug handling is prone to errors. A three-step intervention effectively decreased the high frequency of medication errors by addressing the diversity of their causes., Relevance to Clinical Practice: Worldwide, nurses are in charge of drug handling, which constitutes an error-prone but often-neglected step in drug therapy. Detection and prevention of errors in daily routine is necessary for a safe and effective drug therapy. Our three-step intervention reduced errors and is suitable to be tested in other wards and settings., (© 2014 John Wiley & Sons Ltd.)

Introduction: Transdermal patches provide an attractive route of drug delivery with considerable advantages over other routes of administration, for example maintenance of constant plasma drug levels and convenient usage. However, medication administration errors abound with this dosage form and frequently result in harm or treatment failure., Areas Covered: A systematic literature search was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines using appropriate keywords to identify articles reporting faulty transdermal patch administration. Common pitfalls and errors that were identified through the systematic literature search were discussed alongside individual steps of the transdermal patch administration process., Expert Opinion: The systematic investigation of published errors illustrated that every step in the transdermal patch administration process is prone to errors. Thereby, the lack of knowledge and awareness of the importance of a correct administration practice were a major source of risk. Based on the identified errors and causes of errors prevention strategies were developed as a first step in avoiding transdermal patch administration errors.

Purpose: Clinical decision support systems (CDSS) may potentially improve prescribing quality, but are subject to poor user acceptance. Reasons for alert overriding have been identified and counterstrategies have been suggested; however, poor alert specificity, a prominent reason of alert overriding, has not been well addressed. This paper aims at structuring modulators that determine alert specificity and estimating their quantitative impact on alert burden., Methods: We developed and summarized optimizing strategies to guarantee the specificity of alerts and applied them to a set of 100 critical and frequent drug interaction (DDI) alerts. Hence, DDI alerts were classified as dynamic, i.e. potentially sensitive to prescription-, co-medication-, or patient-related factors that would change alert severity or render the alert inappropriate compared to static, i.e. always applicable alerts not modulated by cofactors., Results: Within the subset of 100 critical DDI alerts, only 10 alerts were considered as static and for 7 alerts, relevant factors are not generally available in today's patient charts or their consideration would not impact alert severity. The vast majority, i.e. 83 alerts, might require a decrease in alert severity due to factors related to the prescription (N=13), the co-medication (N=11), individual patient data (N=36), or combinations of them (N=23). Patient-related factors consisted mainly of three lab values, i.e. renal function, potassium, and therapeutic drug monitoring results., Conclusion: This paper outlines how promising the refinement of knowledge bases is in order to increase specificity and decrease alert burden and suggests how to structure knowledge bases to refine DDI alerting., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Aims: The aim of this work is to understand the process of drug administration and identify points in the workflow that resulted in interventions by clinical information systems in order to improve patient safety., Methods: To identify a generic way to structure the drug administration process we performed peer-group discussions and supplemented these discussions with a literature search for studies reporting errors in drug administration and strategies for their prevention., Results: We concluded that the drug administration process might consist of up to 11 sub-steps, which can be grouped into the four sub-processes of preparation, personalization, application and follow-up. Errors in drug handling and administration are diverse and frequent and in many cases not caused by the patient him/herself, but by family members or nurses. Accordingly, different prevention strategies have been set in place with relatively few approaches involving e-health technology., Conclusions: A generic structuring of the administration process and particular error-prone sub-steps may facilitate the allocation of prevention strategies and help to identify research gaps., (© 2013 The Authors. British Journal of Clinical Pharmacology © 2013 The British Pharmacological Society.)

Background: Upon admission to a hospital patients' medications are frequently switched to alternative drugs compiled in so called hospital drug formularies. This substitution process is a laborious and error-prone task which should be supported by sophisticated electronic tools. We developed a computerised decision support system and evaluated benefit and potential harm associated with its use., Methods: Based on a multi-step algorithm we identified drug classes suitable for exchange, defined conversion factors for therapeutic interchange, built a web-based decision support system, and implemented it into the computerised physician order entry of a large university hospital. For evaluation we compared medications manually switched by clinical pharmacists with the results of automated switching by the newly developed computer system and optimised the system in an iterative process. Thereafter the final system was tested in an independent set of prescriptions., Results: After iterative optimisation of the logical framework the tool was able to switch drugs to pharmaceutical equivalents and alternatives; in addition, it contained 21 different drug classes for therapeutic substitution. In this final version it switched 91.6% of 202 documented medication consultations (containing 1,333 drugs) automatically, leaving 8.4% for manual processing by clinical professionals. No incorrect drug switches were found., Conclusion: A large majority (>90%) of drug switches performed at the interface between primary and tertiary care can be handled automatically using electronic decision support systems, indicating that medication errors and workload of healthcare professionals can be considerably reduced.

Purpose: The intake of medications (drugs) without the knowledge of the treating physician (unknown co-medication) and nonadherence strongly influence drug safety. The aim of our study was to objectively assess unknown co-medication and nonadherence in hospitalized patients by screening urine for a large number of drugs using highly sensitive full scan gas chromatograpy/mass spectrometry (GC/MS). Secondary objectives were to determine the relationship of co-medication and nonadherence to the number of drugs prescribed and to compare history-taking by a pharmacist versus a physician., Methods: In 152 patients, the drug histories taken by physicians, patients' self-reported adherence, and information compiled during as many as three structured interviews conducted by a trained pharmacist on days 1-2, 3-4, and 7-11 of the hospital stay were compared with the GC/MS results from urine samples collected after each interview., Results: In the interviews performed by the pharmacist, 235 additional drugs were identified that were not documented in the chart. Of all the drugs indicated in any interview, 16.9% were identified only by the physician, 24.1% only by the pharmacist, and 59% by both. Overall, in 78% of the patients at least one additional drug was identified by urine screening. The findings suggest overall nonadherence to at least one drug in 13.0% of patients on admission and in 23.3% of patients at any time during hospitalization. Nonadherence was less frequent for critical dose drugs and correlated with the number of prescribed drugs., Conclusions: The drug history among hospitalized patients is often incomplete, and nonadherence and unknown co-medication are alarmingly frequent. This lack of knowledge might impact the overall success of drug therapies in the hospital setting.

Introduction: Efficient search for and finding drugs is essential for electronic drug information systems which, for their part, are prerequisites for computerized physician order entry systems and clinical decision support with the potential to prevent medication errors. Search failures would be critical: they may delay or even prohibit prescription processes or timely retrieval of vital drug information. We analyzed spelling-correction and error characteristics in drug searches and the suitability of auto-completion as prevention strategy., Methods: A blank entry field was presented to the user for unbiased queries in a web-based drug information system containing >105,000 brand names and active ingredients accessible from all 5500 computers of the Heidelberg University Hospital. The system was equipped with an error-tolerant search. Misspelled but found drug names confirmed by users were aligned by dynamic programming algorithms, opposing misspelled and correct names letter by letter. We analyzed the ratios of correctly and incorrectly spelled but found drugs, frequencies of characters, and their position in misspelled search words., Results: Without error-tolerant search, no results were found in 17.5% of all queries. Users confirmed 31% of all results found with phonetic error-correction support. Sixteen percent of all spelling errors were letters in close proximity to the correct letter on keyboards. On average, 7% of the initial letters in misspelled words contained errors., Conclusion: Drug information systems should be equipped with error-tolerant algorithms to reduce search failures. Drug initial letters are also error-prone, thus auto-completion is not a sufficient error-prevention strategy and needs additional support by error-tolerant algorithms., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

Purpose: A key trade-off in computerized clinical documentation exists between collecting coded data versus free-text. Coded data are more readily computer-readable and easier to reuse in different contexts. However, clinical information often exceeds the scope of commonly available terminologies, and coding may be resisted by providers. Alert override reasons are one domain for which agreed-upon terminologies are rarely used. Few data are available on how the collection of information affects the responses of providers., Methods: We took advantage of a natural experiment and compared coded and uncoded reasons for drug-drug interaction (DDI) alert overrides entered in two inpatient prescribing systems with an identical DDI database but with one system offering coded reasons and the other free-text entry. We only included alerts which were issued in both sites and which physicians had to acknowledge., Results: Over a one-year study period, 15,636 alerts were issued. The reasons for override entered in the coded approach matched the free-text site in only 46%. When using free-text, physicians provided many reasons not among the coded options, and often reported that they considered the alert inappropriate, including their rationale regarding this. However, the information entered as free-text included many typing and spelling errors, and the same concept was often represented in different ways, e.g. 209 different ways in which "will monitor as recommended" was noted., Conclusions: The reasons for alert override vary substantially according to the data entry type, which implies that data entry choice may lead to substantial distortion of the underlying data., (Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.)

Introduction: Allergies to drugs are a major cause for hospitalisation and inappropriate prescriptions to patients. However, allergies can be prevented if the patient's history of drug allergy is known and coded., Objective of the Study: Assessment of the value of the widely used ICD-10 codes for drug-allergies (e.g. Z88, L27) as triggers for decision support in an electronic prescription system and evaluation of the potential impact of such an alert system. We also evaluated the usefulness of manual drug allergy notes recorded in patients' charts in the prevention of prescribing errors due to drug allergies., Setting: University hospital providing primary and tertiary care., Methods: Using Anatomical Therapeutic Chemical (ATC) classification codes we allocated to drug specifying ICD-10 codes (i.e. Z88) all drugs belonging to the same group of compounds or those known to induce cross-allergy. In a randomly selected cohort of 200 in-patients we then assessed documentation and coding of drug allergies and incident prescribing errors ignoring patients' drug allergies., Results: Eighteen of the 200 patients had an allergy-related ICD code in the chart, 51 had a written note, and 13 had both. About 21% of patients with documented drug allergies were prescribed a drug potentially triggering the allergy. There was no difference in prescribing errors due to drugs potentially inducing allergies when the allergy was only documented as an ICD-10 code or the information was available in the paper record (P > 0.05)., Conclusion: The findings of this study emphasise the necessity of a more precise and efficient documentation system of drug allergies along with the implementation of an electronic CDS for drug allergies that makes physicians aware of patients' drug allergies during the prescribing process.

Objective: Medication errors are frequent in a hospital setting and often caused by inappropriate drug handling. Systematic strategies for their prevention however are still lacking. We developed and applied a classification model to categorise medication handling errors and defined the urgency of correction on the basis of these findings., Setting: Nurses on medical wards (including intensive and intermediate care units) of a 1,680-bed teaching hospital., Method: In a prospective observational study we evaluated the prevalence of 20 predefined medication handling errors on the ward. In a concurrent questionnaire survey, we assessed the knowledge of the nurses on medication handling. The severity of errors observed in individual areas was scored considering prevalence, potential risk of an error, and the involved drug. These scores and the prevalence of corresponding knowledge deficits were used to define the urgency of preventive strategies according to a four-field decision matrix., Main Outcome Measure: Prevalence and potential risk of medication handling errors, corresponding knowledge deficits in nurses committing the errors, and priority of quality improvement., Results: In 1,376 observed processes 833 medication handling errors were detected. Errors concerning preparation (mean 0.88 errors per observed process [95% CI: 0.81-0.96], N = 645) were more frequent than administration errors (0.36 [0.32-0.41], N = 701, P < 0.001). Parenteral drugs (1.10 [1.00-1.19], N = 492) were more often involved in errors than enteral drugs (0.32 [0.28-0.36], N = 794, P < 0.001). Of the 833 observed medication errors 30.9% concerned processes of high risk, 19.0% of moderate risk, and 50.1% of low risk. Of these errors 11.4% were caused by critical dose drugs, 81.6% by uncomplicated drugs, and 6.9% by nutritional supplements or diluents without active ingredient. According to the decision matrix that also considered knowledge deficits two error types concerning enteral drugs (flaws in light protection and prescribing information) were given maximum priority for quality improvement. For parenteral drugs five errors (incompatibilities, flaws in hygiene, duration of administration, check for visible abnormalities, and again prescribing information) appeared most important., Conclusion: We successfully applied a newly developed classification model to prioritise medication handling errors for prevention strategies.

Purpose: The development and testing of key questions suitable to identify patients' difficulties with medication administration. Materials and Methods: We used a consecutive five-step process to draft key questions regarding 43 aspects of medication administration that can be difficult for patients who manage a complex drug treatment: Step 1) Identification of potentially error-prone characteristics of drug treatment (such as certain dosage forms) and initial draft of key questions. Step 2) Assessment of how comprehensible the questions are for patients. Step 3) Pre-testing of exemplary key questions with patients and monitoring of patient's actual medication administration behavior. Step 4) Evaluation by general practitioners of how well the questions may be integrated into actual patient visits. Step 5) Final approval of the questions in an expert panel. Thereafter, we pilot-tested exemplary questions with 36 patients (43 tests). In the course of this pilot-testing, the patients' answers to the key questions were tested against both their actual behavior during medication administration and against their answers to more general questions regarding potential difficulties with medication administration. Results: More than half of the key questions (N = 24/43) were revised at least once during the development process. During the pilot-testing, 55.8% of the pilot-tests (N = 24/43) revealed medication administration difficulties. It was observed that the key questions identified significantly more difficulties (N = 17) than the general questions (N = 8; P = 0.021, positive predictive value = 94.4% vs 88.9%). In one case, both a key question and a general question identified difficulties, which, however, was not confirmed during the drug administration demonstration, indicating a false positive rate of 5.3% in both cases. Conclusion: We developed key questions aimed at detecting administration errors with a high specificity and a significantly higher sensitivity than general questions, suggesting that the resource-intensive demonstration of medication administration can be reserved for the detection of rarer and uncommon administration errors. [ABSTRACT FROM AUTHOR]

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Purpose A comprehensive medication history can contribute to safe therapy. Many approaches aiming to improve medication history taking require significant human resources. To design an efficient process that delivers high-quality medication histories, the individual requirements and resources of a given setting need to be considered. We aimed to provide an overview of existing approaches to medication history taking and their performance in different settings to potentially support the selection of an appropriate procedure. Methods We searched 3 literature databases (PubMed/MEDLINE, CINAHL, PsycINFO) for publications on approaches to medication history taking and analyzed them with regard to their key components as well as the setting, patient population, assessed outcomes, and efficacy. Results In total, 65 publications were included and analyzed. The majority of the reported approaches relied on involvement of dedicated staff (n = 43), followed by process-oriented interventions (eg, checklists; n = 15) and information technology (IT)–guided interventions (n = 11). A mean (SD) of 6 (2.9) outcomes were described in each study. Medication discrepancies were reported in 89% of all studies, yet about 75 different descriptions of this outcome were used, making it difficult to compare study results. Only 11 studies applied a sample size calculation and statistical tests. Of those, 10 reported a positive effect of their respective intervention on the quality of medication histories. Conclusion Most approaches focused on pharmacy staff, which are associated with considerable cost and resources. Therefore, IT-based approaches and patient engagement should be investigated as cost-effective alternatives and tested for superiority in the same setting. Reporting guidelines and standardized methodology are needed to improve the comparability of such studies. [ABSTRACT FROM AUTHOR]

Abstract: Adverse drug events (ADEs) are a major limitation of drug safety. They are often caused by inappropriate selection of dose and the concurrent use of drugs modulating each other (drug interaction). Risk assessment and prevention strategies must therefore consider co-administered drugs, individual doses, and their timing. In a new approach we evaluated the performance of cross correlation, commonly used in signal processing, to determine similarities in patient treatments. To achieve this, patient treatments were modeled as groups of vectors representing discrete time intervals. These vectors were cross-correlated and the results evaluated to find clusters in time courses indicating similarity in treatment of different patients. To evaluate our algorithm, we then created a number of test cases. The focus of this article is on each treatment, and its pattern in time and dosage. The algorithm successfully produces a relatively low similarity score for cases that are completely different with respect to their pattern of time and dosage but high scores when they are equal (score of 0.699) or similar (score of 0.528) in their therapies, and thus succeeds in having a relatively high specificity (27/30). Such an approach might help to considerably reduce the problem of false alarms which hampers most existing alerting systems for medication errors or impending ADEs. [Copyright &y& Elsevier]