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Objective: To provide ICU clinicians with evidence-based guidance on safe medication use practices for the critically ill., Data Sources: PubMed, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, CINAHL, Scopus, and ISI Web of Science for relevant material to December 2015., Study Selection: Based on three key components: 1) environment and patients, 2) the medication use process, and 3) the patient safety surveillance system. The committee collectively developed Population, Intervention, Comparator, Outcome questions and quality of evidence statements pertaining to medication errors and adverse drug events addressing the key components. A total of 34 Population, Intervention, Comparator, Outcome questions, five quality of evidence statements, and one commentary on disclosure was developed., Data Extraction: Subcommittee members were assigned selected Population, Intervention, Comparator, Outcome questions or quality of evidence statements. Subcommittee members completed their Grading of Recommendations Assessment, Development, and Evaluation of the question with his/her quality of evidence assessment and proposed strength of recommendation, then the draft was reviewed by the relevant subcommittee. The subcommittee collectively reviewed the evidence profiles for each question they developed. After the draft was discussed and approved by the entire committee, then the document was circulated among all members for voting on the quality of evidence and strength of recommendation., Data Synthesis: The committee followed the principles of the Grading of Recommendations Assessment, Development, and Evaluation system to determine quality of evidence and strength of recommendations., Conclusions: This guideline evaluates the ICU environment as a risk for medication-related events and the environmental changes that are possible to improve safe medication use. Prevention strategies for medication-related events are reviewed by medication use process node (prescribing, distribution, administration, monitoring). Detailed considerations to an active surveillance system that includes reporting, identification, and evaluation are discussed. Also, highlighted is the need for future research for safe medication practices that is specific to critically ill patients.

Introduction: Adverse events in the intensive care unit (ICU) may be associated with several possible causes, so determining a drug-related causal assessment is more challenging than in general ward patients. Therefore, the hypothesis was that automated trigger alerts may perform differently in various patient care settings. The purpose of this study was to compare the frequency and type of clinically significant automated trigger alerts in critically ill and general ward patients as well as evaluate the performance of alerts for drug-related hazardous conditions (DRHCs)., Methods: A retrospective cohort study was conducted in adult ICU and general ward patients at three institutions (academic, community, and rural hospital) in a health system. Automated trigger alerts generated during two nonconsecutive months were obtained from a centralized database. Pharmacist responses to alerts and prescriber response to recommendations were evaluated for all alerts. A clinical significant event was defined as an actionable intervention requiring drug therapy changes that the pharmacist determined to be appropriate for patient safety and where the physician accepted the pharmacist's recommendation. The positive predictive value (PPV) was calculated for each trigger alert considered a DRHC (i.e., abnormal laboratory values and suspected drug causes)., Results: A total of 751 alerts were generated in 623 patients during the study period. Pharmacists intervened on 39.8 and 44.8 % alerts generated in the ICU and general ward, respectively. Overall, the physician acceptance rate of approximately 90 % was comparable irrespective of patient care setting. Therefore, the number of clinically significant alerts was 88.9 and 83.4 % for the ICU and non-ICU, respectively. The types of drug therapy changes were similar between settings. The PPV of alerts identifying a DRHC was 0.66 in the ICU and 0.76 in general ward patients., Conclusions: The number and type of clinically significant alerts were similar irrespective of patient population, suggesting that the alerts may be equally as beneficial in the ICU population, despite the challenges in drug-related event adjudication. An opportunity exists to improve the performance of alerts in both settings, so quality improvement programs for measuring alert performance and making refinements is needed.

Background: Medication errors are common upon hospital admission. Clinical pharmacist involvement in medication reconciliation is effective in identifying and rectifying medication errors. However, data is lacking on the economic impact, time requirements, and severity of errors resolved by clinical pharmacists., Objective: To determine the incidence of unintended admission medication discrepancies resolved by clinical pharmacists. Secondary objectives were to determine the type of discrepancies, potential severity, proximal cause, and economic impact of this clinical pharmacy program., Methods: This was a single-center, prospective, observational study conducted at a major teaching medical institution. Following institutional review board approval, data collection was conducted over a 4-week period (August 22, 2011, to September 16, 2011). Descriptive statistical methods were performed for all data analyses., Results: A total of 517 patients involving 5006 medications were included in this study. More than 25% (n = 132) of patients had at least 1 error associated with a medication ordered on hospital admission. Pharmacists resolved a total of 467 admission medication errors (3.5 ± 2.3 errors/patient). The most common type of medication error resolved was medication omission (79.6%). In regard to severity, 46% of medication errors were considered significant or serious. Overall, the mean total time was 44.4 ± 21.8 minutes per medication reconciliation. This clinical pharmacy program was estimated to carry a net present value of $5.7 million over 5 years., Conclusion: Clinical pharmacist involvement within a multidisciplinary health care team during the admission medication reconciliation process demonstrated a significant improvement in patient safety and an economic benefit.

Purpose: Evaluate the rate, type and severity of medication errors occurring during Medical Emergency Team (MET) care at a large, tertiary-care, academic medical center., Methods: A prospective, observational evaluation of 50 patients that required MET care was conducted. Data on medication use were collected using a direct-observation method whereby an observer documented drug information such as drug, dose, frequency, rate of administration and administration technique. Subsequently, a team of three clinicians assessed rate, type and severity of medication errors using definitions consistent with United States Pharmacopeia MEDMARX system. Severity was assessed on a scale of minor, moderate and severe., Results: One hundred eighty six doses were observed for 36 different medications. A total of 296 errors were identified; of these 196 errors (66%) were inappropriate aseptic technique. Of the remaining 100 errors, 46% were prescribing errors, 28% administration technique errors, 14% mislabeling errors, 10% drug preparation errors and 2% improper dose prescribing. Examples included: (1) prescribing errors, (2) administering wrong doses, (3) mislabeling, and (4) wrong administration technique such as not flushing intravenous medication through intravenous access. The rate of medication administration errors was 1.6 errors/dose including aseptic technique and 0.5 errors/dose excluding aseptic technique. A notable portion (14%) of errors was considered at least moderate in severity., Conclusions: One out of 2 doses was administered in error after errors of using inappropriate aseptic technique were excluded. There is a need for education and systematic changes to prevent medication errors during medical emergencies as an effort to avoid harm., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

Background: Computerized provider order entry with decision support software offers an opportunity to identify and prevent medication-related errors, including drug-drug interactions (DDIs), through alerting mechanisms. However, the number of alerts generated can overwhelm and lead to "alert fatigue." A DDI alert system based on severity rankings has been shown to reduce alert fatigue; however, the best method to populate this type of database is unclear., Objective: To compare the severity ranking of proprietary databases to clinician assessment for DDIs occurring in critically ill patients., Methods: This observational, prospective study was conducted over 8 weeks in the cardiac and cardiothoracic intensive care unit. Medication profiles of patients were screened for the presence of DDIs and a severity evaluation was conducted using rankings of proprietary databases and clinician opinion using a DDI severity assessment tool. The primary outcome measure was the number of DDIs considered severe by both evaluation methods., Results: A total of 1150 DDIs were identified after 400 patient medication profiles were evaluated. Of these, 458 were unique drug pairs. Overall, 7.4% (34/458) were considered a severe interaction based upon proprietary database ratings. The assessment by clinicians ranked 6.6% (30/458) of the unique DDIs as severe. Only 3 interactions, atazanavir-simvastatin, atazanavir-tenofovir, and aspirin-warfarin, were considered severe by both evaluation methods., Conclusions: Since proprietary databases and clinician assessment of severe DDIs do not agree, developing a knowledge base for a DDI alert system likely requires proprietary database information in conjunction with clinical opinion.

Purpose: To compare medication administration error rates before and after the provision of educational sessions using either traditional didactic lecture or simulation-based training., Methods: A single-center, parallel, controlled, prospective study conducted in adult coronary critical care (CCU) and medical intensive care units (MICU). Twenty-four nurses were observed administering medications. Documentation included drug name, dose, route, time and technique during observation and active medication orders in the patient's chart. A direct observation method was completed at baseline and repeated twice after the interventions. Data obtained during observation were analyzed for medication administration error rates. Interventions were two types of educational sessions with content developed from baseline medication administration error data: simulation-based training for CCU nurses and a didactic lecture for MICU nurses. Quizzes completed before and after the interventions were used to assess knowledge., Results: A total of 880 doses (402 CCU, 478 MICU) were observed. After the simulation-based educational intervention in the CCU, medication administration error rates decreased from 30.8 to 4.0% (p < 0.001) in the initial post-intervention observation and were sustained in the final post-intervention observation (30.8 to 6.2%; p < 0.001). The error rate in the MICU after the didactic lecture intervention was not significantly different from the baseline and increased in the final post-intervention observation from 20.8 to 36.7% (p = 0.002). Mean quiz scores were significantly improved after education sessions in both ICUs., Conclusions: Simulation-based learning provides a significant advantage to patient care through the reduction of medication administration errors compared to lecture style education.

Advances in diagnostic tests, technological interventions, and pharmacotherapy have resulted in spectacular results for many intensive care unit (ICU) patients who, in earlier generations, would have succumbed to their critical illness. At the same time, the complexity and intensity of care required for ICU patients is also associated with greater risks for harm resulting from care. As in other inpatient areas, medications are the most common type of therapy in ICUs and are also associated with the most frequent type of ICU adverse events. Critically ill patients are at high risk for adverse drug events for many reasons, including the complexity of their disease that creates challenges in drug dosing, their vulnerability to rapid changes in pharmacotherapy, the intensive care environment providing ample distractions and opportunity for error, the administration of complex drug regimens, the numerous high-alert medications that they receive, and the mode of drug administration. The clinical outcomes of adverse drug events can result in end-organ damage and even death. The costs of an adverse drug event can be substantial to healthcare systems with an additional $6,000-$9,000 for each event. The multiprofessional patient care team is one approach to promoting patient safety in the ICU.

Aggregation of adverse drug event data has evolved in the last decade. Several approaches are available to augment the standard voluntary incident reporting system. Most of these methods are applicable to nonmedication adverse events as well. To identify appropriately system trends as well as process failures, intensive care units should participate in various collection methods. Several different methods are available for robust adverse drug event data collection, such as target chart review, nontargeted chart review, and direct observation. As the various methods usually capture different types of events, employing more than one technique will improve the assessment of intensive care unit care. Some of these surveillance methods offer real-time or near real-time identification of adverse drug events and potentially afford the practitioner time for intervention. Continued development of adverse drug event detection will allow for further quality improvement efforts and preventive strategies to be utilized.

Medication errors are a common unfortunate occurrence in hospitals. One population that is particularly vulnerable are patients admitted to the Intensive Care Unit (ICU). ICU patients have a combination of rapidly changing medical conditions, laboratory values, and medications, which present a particular challenge for clinicians in practice in every aspect of patient care. Medication errors can occur in different phases (prescribing, distribution, administration, and monitoring) of the medication process and have a significant impact on morbidity and mortality. Medication error analysis requires a structured approach including: detection, reporting, and analysis, in order to provide the most efficient and practical information to the ICU team. In addition, a particular focus is made on the implementation of medication error prevention strategies such as evidenced-based protocols, team education, and technology. In an effort to reduce medication error rates in the ICU requires a collaborative, multi-disciplinary approach in order to be effective and consistent through time. Further research efforts are currently taking place in this challenging aspect of patient care to further provide more strategies for medication error detection, analysis, and prevention.

Background/Objectives: Federally‐mandated consultant pharmacist‐conducted retrospective medication regimen reviews (MRRs) are designed to improve medication safety in nursing homes (NH). However, MRRs are potentially ineffective. A new model of care that improves access to and efficiency of consultant pharmacists is needed. The objective of this study was to determine the impact of pharmacist‐led telemedicine services on reducing high‐risk medication adverse drug events (ADEs) for NH residents using medication reconciliation and prospective MRR on admission plus ongoing clinical decision support alerts throughout the residents' stay. Design: Quality improvement study using a stepped‐wedge design comparing the novel service to usual care in a one‐year evaluation from November 2016 to October 2017. Setting: Four NHs (two urban, two suburban) in Southwestern Pennsylvania. Participants: All residents in the four NHs were screened. There were 2,127 residents admitted having 652 alerts in the active period. Intervention: Upon admission, pharmacists conducted medication reconciliation and prospective MRR for residents and also used telemedicine for communication with cognitively‐intact residents. Post‐admission, pharmacists received clinical decision support alerts to conduct targeted concurrent MRRs and telemedicine. Measurement: Main outcome was incidence of high‐risk medication, alert‐specific ADEs. Secondary outcomes included all‐cause hospitalization, 30‐day readmission rates, and consultant pharmacists' recommendations. Results: Consultant pharmacists provided 769 recommendations. The intervention group had a 92% lower incidence of alert‐specific ADEs than usual care (9 vs 31; 0.14 vs 0.61/1,000‐resident‐days; adjusted incident rate ratio (AIRR) = 0.08 (95% confidence interval (CI) = 0.01–0.40]; P =.002). All‐cause hospitalization was similar between groups (149 vs 138; 2.33 vs 2.70/1,000‐resident‐days; AIRR = 1.06 (95% CI = 0.72–1.58); P =.75), as were 30‐day readmissions (110 vs 102; 1.72 vs 2.00/1,000‐resident‐days; AIRR = 1.21 (95% CI = 0.76–1.93); P =.42). Conclusions: This is the first evaluation of the impact of pharmacist‐led patient‐centered telemedicine services to manage high‐risk medications during transitional care and throughout the resident's NH stay, supporting a new model of patient care. [ABSTRACT FROM AUTHOR]