High-alert Medications Research Articles

A Pharmacy Quality and Internal Audit Program Promoting Continuous Survey Readiness with Medication Management Standards.

Showcasing compliance with Joint Commission Medication Management (MM) standards during accreditation visits is important, but it is equally vital to maintain a state of continuous survey readiness. This article describes a Pharmacy Quality and Internal Audit Program to promote continuous survey readiness and sustained compliance with MM standards. A comprehensive MM audit was developed to assess for compliance in all inpatient, ambulatory, and procedural areas that use medications, with each area undergoing the internal auditing process at least twice per calendar year. The audit is performed by an MM subject matter expert from the Department of Pharmacy and incorporates electronic chart review, clinical staff interviews, and observations of area-specific medication practices. Notable findings and recommendations are communicated to area-specific leadership. Institutionwide scorecards are compiled to track performance with MM standards, identify opportunities, and determine future focus areas to improve and sustain compliance. Results revealed consistent compliance (≥ 90%) with a majority of MM standards. These included hazardous medication management, controlled substances compliance, look-alike/sound-alike drugs, medication storage/security, and labeling of medication syringes. Several areas of opportunity were identified: awareness of high-alert medications and risk-reduction safety strategies, compliance with pill cutter standards, and therapeutic duplication of "as needed" medication orders. Subsequent implementation of corrective actions and mitigation strategies resulted in improved compliance rates from < 50% to ≥ 90% for awareness of high-alert medications and risk-reduction strategies, from < 60% to ≥ 80% for compliance with pill cutter standards, and from < 90% to ≥ 90% for therapeutic duplication of "as needed" orders. Establishment of a Pharmacy Quality and Internal Audit Program allowed for performance tracking, identification of compliance deficiencies, implementation of focused corrective actions, and promotion of continuous survey readiness with MM standards.

Medical students' confidence and competence with prescribing in ST-elevation myocardial infarction: a mixed-methods study.

To explore factors associated with prescribing confidence and competence of final-year medical students for prescribing antiplatelet and fibrinolytic agents in ST-segment elevation myocardial infarction (STEMI). The study was conducted among final-year medical students with a triangular convergent mixed-methods approach. First, an online survey was conducted using a voluntary sampling method with concurrent in-depth interviews performed. The survey data was analysed using descriptive statistics and paired t-tests, while survey factors were compared using the chi-squared or Fisher's exact test. The interview data were coded and analysed thematically. The relations between the qualitative and quantitative findings were finally described. Totally 92 validly replied to the questionnaire, and 20 participated in the interviews. The quantitative analysis indicated that they had high competence in the diagnosis of STEMI and prescribing antiplatelet and fibrinolytic agents. The mean confidence score of prescribing for both was medium and was significantly lower in fibrinolytic agents. (M=3.3, SD=1.1 vs. M=2.8, SD=1.0, t(91)=5.39, p<0.01). Their experience, knowledge, and mentoring were accounted for, considering the prescribing confidence factors in both approaches. Besides, providing guidelines and standing orders were derived from the interview data. This study has demonstrated that final-year medical students have a high ability to diagnose and prescribe essential medications in STEMI but tend to have low confidence in prescribing fibrinolytic agents. Experiential learning, mentorship and providing guidelines can help them, especially in emergency settings to prescribe confidently and safely. Further multicenter studies on undergraduate and graduate medical students' confidence and perspective of prescribing are required, especially for high-alert medications.

Analyzing an Implementation of Patient Safety Targets Standards at Ja'far Medika Hospital Based on Hospital Accreditation National Standards (SNARS) Issue 1.1

Background : The complexity of hospital operations has the errors’ potential. Patient safety will have an impact on the patient's medical condition as well as increasing health costs. Ja'far Medika Hospital scored 82.4 in the KARS accreditation survey using SNARS edition 1.1 in 2019. This study analyzes the implementation of patient safety target standards at Ja'far Medika Hospital Karanganyar based on SNARS edition 1.1. Methods : This study is a quantitative descriptive study by document review, observation of infrastructure facilities, and observation of the implementation of patient safety at Ja'far Medika Hospital. Results and discussion : The accomplishment of the implementation of patient safety goals that meet the passing grade are the accuracy of identifying patient by 85%, reducing the risk of infection related to health services/healthcare-acquired infections (HAIs) by 82.3%, and reducing the risk of injury due to falls by 87.5%. Whereas the targets below the passing grade are improve effective communication by 78.5%, Increased safety of high alert medication (HAM) by 75%, and the confirmation of the exact location, procedure, and patient of the operation by 50%. Conclusion : The implementation of patient safety targets at Ja'far Medika Hospital has not been carried out optimally with the target of Effective Communication improvement, the safety enhancement of high alert drugs/drugs that need to watched out and the confirmation of the exact location, procedure, and patient of the operation

Factors associated with pharmacists’ knowledge regarding high-alert medications: a convenience sample survey in China

The consequences of medication errors are more severe for high-alert medications than general drugs. Improving pharmacists’ knowledge regarding high-alert medications is important to increase drug safety and maintain patient health. This study was aimed at understanding Chinese hospital pharmacists’ knowledge regarding high-alert medications and exploring associated factors, to provide suggestions for management of high-alert medications. A total of 380 pharmacists from four hospitals in southern, northern and central China were selected through a convenience sampling method. Through a questionnaire survey, the pharmacists’ demographic sociology characteristics and knowledge regarding high-alert medications were investigated. Chi-square tests and binary logistic regression were used to analyze the factors associated with pharmacists’ knowledge regarding high-alert medications. A total of 336 valid questionnaires were returned, with an effective recovery rate of 88.4%. Among the respondents, 79.2% had high knowledge regarding high-alert medications. The analysis results show that the main factors significantly associated with pharmacists’ knowledge levels of high-alert medication were work experience and professional title, whether high alert-medication knowledge was obtained through the network channel, whether high-alert-medication knowledge was obtained through daily work practice and whether high-alert medications were double independent checked before use. Increase the sharing of work cases and knowledge cooperation among different pharmacists and departments in high-alert medications, rationally adjust and arrange the responsibilities of pharmacists, and improve the internal circulation of hospital high-alert medications are helpful to improve pharmacists’ cognitive level of high-alert medication and improve the hospital’s ability to control the risk of high-alert medication.

Call for Decision Support for High-Alert Medication Administration Among Pediatric Nurses: Findings From a Large, Multicenter, Cross-Sectional Survey in China

Background: Children have a higher risk of medication errors (MEs) than adults. The Institute for Safe Medication Practice (ISMP) defined high-alert medications (HAMs) as a group of medications that could cause significant patient harm or even death when they are used in error. Nurses are actively involved in and responsible for patient care, especially in medication administration. This study aimed to estimate the knowledge, decision-making basis and confidence and decision support needs related to HAMs among pediatric nurses in China. Methods: A web-based, cross-sectional survey was conducted among pediatric nurses who were recruited from 14 member hospitals of the Pediatric Nursing Alliance of National Children’s Medical Center in China using a convenient sampling technique. Data were collected using a self-administered instrument composed of four parts: the demographic characteristics of participants, participants’ knowledge about HAMs, participants’ self-evaluation of the basis of and confidence in decision-making, and decision support needs regarding HAMs. Among the participants, the maximum score for HAM knowledge was 100. All data were entered and analyzed using SPSS 20.0. Results: A total of 966 nurses participated in this study. Nurses were found to have insufficient knowledge about HAMs, with a median (IQR) of 75.0 (70.0, 80.0), out of a maximum score of 100. Knowledge about HAM administration was significantly higher than that about HAM regulation, with a p value < 0.001. The three lowest-scoring items concerned HAM regulation, and the “Treat fentanyl skin patches as a regulated narcotic” item obtained the lowest score, with only 1/5 of respondents answering it correctly. Most participants reported that their basis for decision-making about HAMs was drug instructions (90.0%) or drug handbooks (81.9%) and evaluated their confidence in decision-making about HAMs as high or relatively high (84.6%). The decision-making difficulties when encountering HAMs focused on most stages of HAM administration, especially the appropriateness of prescriptions, checks, preparation and administration. The vast majority of participants assessed decision support as necessary or very necessary (92.0%), and the most popular options for decision support were computerized clinical decision support systems (46.4%) and real-time online communication with pharmacists (23.9%). Conclusion: Our study demonstrated the inadequacies in HAM knowledge, the basis and difficulty of decision-making, and decision support needs regarding HAMs in Chinese pediatric nurses. Nurses need greater support in HAM administration, including not only training but also adequate technology, mutually beneficial interprofessional collaboration, and a positive institutional culture.

Critical Thinking Disposition, Medication Error Risk Level of High-alert Medication and Medication Safety Competency among Intensive Care Unit Nurses

Purpose : The study aimed to identify relationship among intensive care unit (ICU) nurses’ critical thinking disposition, medication error risk level of high-alert medication, and medication safety competency, as well as the factors affecting medication safety competency.Methods : The participants were 266 ICU nurses of one higher-tier general hospital and one general hospital in Province. The data were collected using structured self-administered questionnaire from August 10 to August 31, 2021. Measurements included the critical thinking disposition questionnaire, nurses’s knowledge of high-alert medication questionnaire, the medication safety competency scale. Data were analyzed using hierarchical multiple regressions using SPSS/WIN 28.0.Results : In the multiple regression analysis, the medication safety competence has a statistically significant correlation with the working department, the critical thinking disposition, and medication error risk level of high-alert medication.Conclusion : Based on the results of this study, it is suggested to develop and apply an educational strategy that can strengthen the knowledge and skills of critical thinking disposition and medication error risk level of high-alert medication to improve the ICU nurse’s medication safety competency.

High-alert medications for hospitalised paediatric patients - a two-step survey among paediatric clinical expert pharmacists in Germany.

Paediatric patients are more vulnerable to be harmed by medication errors compared to adults due to pharmacokinetic and pharmacodynamic changes in their development, individual dosing calculations, and manipulation of ready to-use products intended for adult patients. According to the Institute of Safe Medication Practices, there are some "drugs that bear a heightened risk of causing significant patient harm when they are used in error"; these drugs are called high-alert medications (HAM). The two-step survey among paediatric clinical expert pharmacists presented here aimed to compile a nation-wide HAM list. To provide detailed guidance, this survey followed a drugbased approach, resulting in specific potential drug related problems (DRPs) and associated recommendations for prevention. In contrast to this approach, in the first round of the survey two drug classes were included that both were rated as HAM (i.e.chemotherapy and parenteral nutrition). Twenty single drugs were identified as HAM, 65% of which were cardiovascular or neurological drugs. The paediatric expert pharmacists mentioned in total 216 potential DRPs; in particular, they identified potential administration-related problems (28% of all DRPs), dosing-related problems (26%), and drug-choice-related problems (18%, e.g.drug confusion and drug monitoring). Moreover, they suggested 275 potential interventions to address these DRPs. Two thirds of all interventions dealt with the preparation by the hospital pharmacy, standardisation of processes (e.g.labelling), and education or training. In conclusion, this survey provided a German paediatric high-alert medication list from a paediatric pharmacist point of view. Moreover, the experts mentioned for the first time specific potential DRPs and associated interventions to guide a local multidisciplinary approach for preventing medication-related harm in children.

Mobile Health Apps Providing Information on Drugs for Adult Emergency Care: Systematic Search on App Stores and Content Analysis.

BackgroundDrug-referencing apps are among the most frequently used by emergency health professionals. To date, no study has analyzed the quantity and quality of apps that provide information on emergency drugs.ObjectiveThis study aimed to identify apps designed to assist emergency professionals in managing drugs and to describe and analyze their characteristics.MethodsWe performed an observational, cross-sectional, descriptive study of apps that provide information on drugs for adult emergency care. The iOS and Android platforms were searched in February 2021. The apps were independently evaluated by 2 hospital clinical pharmacists. We analyzed developer affiliation, cost, updates, user ratings, and number of downloads. We also evaluated the main topic (emergency drugs or emergency medicine), the number of drugs described, the inclusion of bibliographic references, and the presence of the following drug information: commercial presentations, usual dosage, dose adjustment for renal failure, mechanism of action, therapeutic indications, contraindications, interactions with other medicinal products, use in pregnancy and breastfeeding, adverse reactions, method of preparation and administration, stability data, incompatibilities, identification of high-alert medications, positioning in treatment algorithms, information about medication reconciliation, and cost.ResultsOverall, 49 apps were identified. Of these 49 apps, 32 (65%) were found on both digital platforms; 11 (22%) were available only for Android, and 6 (12%) were available only for iOS. In total, 41% (20/49) of the apps required payment (ranging from €0.59 [US $0.64] to €179.99 [US $196.10]) and 22% (11/49) of the apps were developed by non–health care professionals. The mean weighted user rating was 4.023 of 5 (SD 0.71). Overall, 45% (22/49) of the apps focused on emergency drugs, and 55% (27/49) focused on emergency medicine. More than half (29/47, 62%) did not include bibliographic references or had not been updated for more than a year (29/49, 59%). The median number of drugs was 66 (range 4 to >5000). Contraindications (26/47, 55%) and adverse reactions (24/47, 51%) were found in only half of the apps. Less than half of the apps addressed dose adjustment for renal failure (15/47, 32%), interactions (10/47, 21%), and use during pregnancy and breastfeeding (15/47, 32%). Only 6% (3/47) identified high-alert medications, and 2% (1/47) included information about medication reconciliation. Health-related developer, main topic, and greater amount of drug information were not statistically associated with higher user ratings (P=.99, P=.09, and P=.31, respectively).ConclusionsWe provide a comprehensive review of apps with information on emergency drugs for adults. Information on authorship, drug characteristics, and bibliographic references is frequently scarce; therefore, we propose recommendations to consider when developing an app of these characteristics. Future efforts should be made to increase the regulation of drug-referencing apps and to conduct a more frequent and documented review of their clinical content.

Effectiveness of Nursing Guidelines on Nurses’ Performance Regarding High Alert Medications at Neonatal Intensive Care Units

Context: A high alert medication (HAM) is a medication that causes serious harm if it is used in error. Neonatal nurses are responsible for administering HAMs; incorrect administration can significantly affect clinical outcomes.&#x0D; Aim: The study aimed to evaluate the effectiveness of nursing guidelines on nurses' performance regarding HAMs at neonatal intensive care units (NICUs).&#x0D; Methods: A quasi-experimental design (pre/post-test) was utilized. The study was conducted at NICUs in Children's Hospital and Maternity and Gynecological Hospital affiliated to Ain Shams University. A convenience sample of 80 nurses caring for high-risk neonates was included in the current study from the previous setting for six months. Two tools were used to collect data. They are a structured interview questionnaire and nurses’ performance observational checklist.&#x0D; Results: The nurse's mean age was 27.79±6.83. 35% of them have worked part-time jobs. A highly statistically significant improvement was shown post-test compared to the pre-test regarding the nurses' knowledge and practices about HAMs at 0.001.&#x0D; Conclusion: The present study concludes that applying nursing guidelines interventions improved the neonatal nurses' knowledge and practice related to HAMs. The study recommended emphasizing the importance of using nursing guidelines of HAMs interventions for improving neonatal nurses' knowledge and practices at NICUs.

Effect of an Educational Program for nurses about High Alert Medications on their Competence

Effect of an Educational Program for nurses about High Alert Medications on their Competence

Detecting Unusual Intravenous Infusion Alerting Patterns with Machine Learning Algorithms

Abstract Objective To detect unusual infusion alerting patterns using machine learning (ML) algorithms as a first step to advance safer inpatient intravenous administration of high-alert medications. Materials and Methods We used one year of detailed propofol infusion data from a hospital. Interpretable and clinically relevant variables were feature engineered, and data points were aggregated per calendar day. A univariate (maximum times-limit) moving range (mr) control chart was used to simulate clinicians' common approach to identifying unusual infusion alerting patterns. Three different unsupervised multivariate ML-based anomaly detection algorithms (Local Outlier Factor, Isolation Forest, and k-Nearest Neighbors) were used for the same purpose. Results from the control chart and ML algorithms were compared. Results The propofol data had 3,300 infusion alerts, 92% of which were generated during the day shift and seven of which had a times-limit greater than 10. The mr-chart identified 15 alert pattern anomalies. Different thresholds were set to include the top 15 anomalies from each ML algorithm. A total of 31 unique ML anomalies were grouped and ranked by agreeability. All algorithms agreed on 10% of the anomalies, and at least two algorithms agreed on 36%. Each algorithm detected one specific anomaly that the mr-chart did not detect. The anomaly represented a day with 71 propofol alerts (half of which were overridden) generated at an average rate of 1.06 per infusion, whereas the moving alert rate for the week was 0.35 per infusion. Discussion These findings show that ML-based algorithms are more robust than control charts in detecting unusual alerting patterns. However, we recommend using a combination of algorithms, as multiple algorithms serve a benchmarking function and allow researchers to focus on data points with the highest algorithm agreeability. Conclusion Unsupervised ML algorithms can assist clinicians in identifying unusual alert patterns as a first step toward achieving safer infusion practices.

Exploring Pakistani Physicians' Knowledge and Practices Regarding High Alert Medications: Findings and Implications.

Introduction: While many low-middle income countries (LMICs), including Pakistan, try and ensure patient safety within available resources, there are considerable concerns with medication use. Unsafe and inappropriate medication use, especially high alert medications (HAMs), is one of the important factors compromising patient safety and quality of care. Besides economic loss, HAMs contribute to greater morbidity, hospitalization, and mortality. Physicians as key members of the provision of healthcare are expected to be well aware of the administration and regulations surrounding HAMs. However, the current status is unknown in Pakistan. Consequently, the objectives of this study were to evaluate the knowledge of Pakistani physicians about the administration, regulation, and practices related to HAMs. This builds on our recently published study with nurses. Methods: An online cross-sectional study design was used, and data were gathered from the physicians throughout Pakistan using previously used self-administered questionnaires during a period of 5 months (January 1 to May 30, 2021). All data were entered and analyzed using SPSS 22 for Windows. Results: Physicians (847) who provided consent were enrolled in the study. Most physicians (62.2%) were male, aged between 25 and 30 years (75.2%) and had 2- to 5-year work experience (50.9%). About 27% were working in the emergency departments. The median (IQR) knowledge score for HAMs administration and regulation was 5 (3) and 5 (2), respectively. About 46.4% of respondents were found to have moderate knowledge about HAMs; increasing age, work experience, and higher qualifications were significantly associated (p < 0.05) with better HAMs knowledge. Around 58% had good practices relating to HAMs during their routine work. Median practice scores increased significantly (p < 0.05) with age, work experience, and postgraduate qualification. Conclusion: Most Pakistani physicians possess moderate knowledge about HAMs administration and regulations. However, their practices relating to the HAMs administration and regulations are typically sub-optimal. Consequently, HAMs awareness needs to be improved by including course content in the current curriculum, provision of hospital-based continuous training programs about patient safety and care, and establishment of multi-disciplinary health care teams, including board-certified pharmacists and specialized nurses, for the effective execution of medication use process in Pakistani hospitals in the future.

Pharmaceutical algorithms set in a real time clinical decision support targeting high-alert medications applied to pharmaceutical analysis

BackgroundPharmaceutical analysis of the prescription has to prop up the quality of patients' medication management in a context of medication’s risk acculturation. But this activity remains highly variable. Medication-related clinical decision support may succeed in reducing adverse drug events and healthcare costs. PurposeThis study aims to present AVICENNE as a real time medication-related clinical decision support (rt-CDS) applied to pharmaceutical analysis and its ability to detect Drug related problems (DRP) consecutively resolved by pharmacists.Basic proceduresA Medication-related rt-CDS is created by integrating the software PharmaClass® (Keenturtle), 5 health data streams on the patient and Pharmaceutical algorithms (PA). PA are created by modeling the pharmaceutical experiment about DRP and the thread of their criticality. They are partially encoded as computerized rules in Pharmaclass® allowing alerts’ issue.An observational prospective study is conducted during 9-months among 1000 beds in 2 health facilities. The first step is to identify alerts as DRP; their resolution follows with clear guidelines worked out for the pharmaceutical analysis. A basis on predictive positive values (PPV) of the PA is being built today helping to know the performance of DRP detection and resolution.Main findings71 PA are encoded as rules into Pharmaclass®: 40 targeted serious adverse drug events. 1508 alerts are analyzed by pharmacists. Among them 921 DRPs were characterized and 540 pharmaceutical interventions transmitted of which 219 were accepted by prescribers. Three PPV are defined depending on software, pharmacist and patient.Principal conclusionClinical pharmacy societies should host, share and update a national corpus of PA and exploit its educational interest.

Reliability of High-Alert Medications Questionnaire in Turkish Healthcare Professionals

Reliability of High-Alert Medications Questionnaire in Turkish Healthcare Professionals

Management of high-alert medications by clinical pharmacological approaches

Management of high-alert medications by clinical pharmacological approaches

Detecting Unusual Intravenous Infusion Alerting Patterns with Machine Learning Algorithms.

To detect unusual infusion alerting patterns using machine learning (ML) algorithms as a first step to advance safer inpatient intravenous administration of high-alert medications. We used one year of detailed propofol infusion data from a hospital. Interpretable and clinically relevant variables were feature engineered, and data points were aggregated per calendar day. A univariate (maximum times-limit) moving range (mr) control chart was used to simulate clinicians' common approach to identifying unusual infusion alerting patterns. Three different unsupervised multivariate ML-based anomaly detection algorithms (Local Outlier Factor, Isolation Forest, and k-Nearest Neighbors) were used for the same purpose. Results from the control chart and ML algorithms were compared. The propofol data had 3,300 infusion alerts, 92% of which were generated during the day shift and seven of which had a times-limit greater than 10. The mr-chart identified 15 alert pattern anomalies. Different thresholds were set to include the top 15 anomalies from each ML algorithm. A total of 31 unique ML anomalies were grouped and ranked by agreeability. All algorithms agreed on 10% of the anomalies, and at least two algorithms agreed on 36%. Each algorithm detected one specific anomaly that the mr-chart did not detect. The anomaly represented a day with 71 propofol alerts (half of which were overridden) generated at an average rate of 1.06 per infusion, whereas the moving alert rate for the week was 0.35 per infusion. These findings show that ML-based algorithms are more robust than control charts in detecting unusual alerting patterns. However, we recommend using a combination of algorithms, as multiple algorithms serve a benchmarking function and allow researchers to focus on data points with the highest algorithm agreeability. Unsupervised ML algorithms can assist clinicians in identifying unusual alert patterns as a first step toward achieving safer infusion practices.

Parenteral Nutrition: Review of Recent American Society for Parenteral and Enteral Nutrition Publications

Parenteral nutrition (PN) is a complex medication administered to adult, pediatric, and neonatal patients. PN is recognized as a high-alert medication by the Institute for Safe Medication Practices (ISMP). The American Society for Parenteral and Enteral Nutrition (ASPEN) has published several key recommendations regarding safe use of PN. This manuscript will review several of the important PN papers published in 2020-2021 by ASPEN.

Analysis of standard concentrations of continuous infusions in nine Spanish neonatal intensive care units

ObjectivesThe aim of this study was to describe the use of standard concentrations for continuous infusion drugs in Spanish neonatal intensive care units (NICUs).MethodsWe conducted an observational multicentre study based...

An interactive consensus reaching model with updated weights of clusters in large-scale group decision making

Consensus reaching process generates a group decision approved by all experts despite their possible divergent preferences. To circumvent a calculated and nominal consensus without exchanges of views, an interactive consensus reaching strategy is necessary even though it may bring costs, especially for large-scale group decision making problems. To allow experts to make cost-effective preference modifications to reach consensus in large-scale group decision making, this study proposes a dynamic interactive consensus reaching model. Firstly, a minimum-cost-consensus model that focuses on clusters in a large-scale context is introduced, in which the unit preference adjustment cost can be determined objectively. Then, we apply the minimum-cost-consensus solution to develop a feedback mechanism to activate discussions between experts and support preference modifications. The modification degree is defined towards each expert cluster to measure the cost performance of a cluster pertaining to the modifications. On this basis, we update the weights of clusters so as to improve the cost performance. An illustrative example about the grading management of high-alert medication is presented. By comparison, the interactive consensus model only costs 10.1 percent more than an automatic consensus model but gets group consensus with the exchanges of expert views.

Identification and safe storage of look-alike, sound-alike medicines in automated dispensing cabinets

ObjectivesAutomated dispensing cabinets (ADCs) are used in hospitals to improve medication safety and decrease costs. However, ADCs do not completely eliminate the risk of mistakes between look-alike, sound-alike (LASA) medicines....