Evaluation of Critical Care Pharmacist Evening Services at an Academic Medical Center.

Purpose: Critical care pharmacists are considered essential members of the healthcare team; however, justification and recruitment of new positions, especially in the evening or weekend shifts, remains a significant challenge. The purpose of this study was to investigate the number of interventions, type of interventions, and associated cost savings with the addition of 1 board certified critical care clinical pharmacist to evening shift. Methods: This was a prospective collection and characterization of 1 evening shift critical care pharmacist's clinical interventions over a 12-week period. Interventions were collected and categorized daily from 13:00 to 22:00 Monday through Friday. After collection was complete, cost savings estimates were calculated using pharmacy wholesaler acquisition cost. Results: Interventions were collected on 52 of 60 weekdays. A total of 510 interventions were collected with an average of 9.8 interventions accepted per day. The most common interventions included transitions of care, medication dose adjustment, and antibiotic de-escalation and the highest proportion of interventions occurred in the medical intensive care unit. An estimated associated cost avoidance of $66 537.80 was calculated for an average of $1279.57 saved per day. Additionally, 22 (4.1%) of interventions were considered high yield interventions upon independent review by 2 pharmacists. Conclusion: The addition of 1 board-certified critical care pharmacist to evening shift resulted in multiple interventions across several categories and a significant cost avoidance when calculated using conservative measures.

Use of Methadone Versus Oxycodone to Facilitate Weaning of Parenteral Opioids in Critically Ill Adult Patients.

BACKGROUND: No previous literature has compared methadone with oxycodone for intravenous (IV) opioid weaning. OBJECTIVE: To determine if a weaning strategy using enteral methadone or oxycodone results in faster time to IV opioid discontinuation. METHODS: This was a single-center, retrospective, cohort medical record review of mechanically ventilated adults in an intensive care unit (ICU) who received a continuous IV infusion of fentanyl or hydromorphone for ≥72 hours and an enteral weaning strategy using either methadone or oxycodone from January 1, 2020, through December 31, 2021. Differences between groups were controlled for using Cox proportional hazards models. The primary outcome was time to continuous IV opioid discontinuation from the initiation of enteral opioids. Secondary outcomes included the primary endpoint stratified for COVID-19, duration of mechanical ventilation, ICU and hospital length of stay, and safety measures. RESULTS: Ninety-three patients were included, with 36 (38.7%) patients receiving methadone and 57 (61.3%) receiving oxycodone. Patients weaned using methadone received IV opioids significantly longer before the start of weaning (P = 0.04). However, those on methadone had a significantly faster time to discontinuation of IV opioids than those on oxycodone, mean (standard deviation) 104.7 (79.4) versus 158.3 hours (171.2), P = 0.04, and, at any time, were 1.89 times as likely to be weaned from IV opioids (hazard ratio, HR 1.89, 95% confidence interval, CI 1.16-3.07, P = 0.01). CONCLUSION AND RELEVANCE: This was the first study showing enteral methadone was associated with a shorter duration of IV opioids without differences in secondary outcomes compared with oxycodone. Prospective research is necessary to confirm this finding.

Pharmacophenotype identification of intensive care unit medications using unsupervised cluster analysis of the ICURx common data model.

BACKGROUND: Identifying patterns within ICU medication regimens may help artificial intelligence algorithms to better predict patient outcomes; however, machine learning methods incorporating medications require further development, including standardized terminology. The Common Data Model for Intensive Care Unit (ICU) Medications (CDM-ICURx) may provide important infrastructure to clinicians and researchers to support artificial intelligence analysis of medication-related outcomes and healthcare costs. Using an unsupervised cluster analysis approach in combination with this common data model, the objective of this evaluation was to identify novel patterns of medication clusters (termed 'pharmacophenotypes') correlated with ICU adverse events (e.g., fluid overload) and patient-centered outcomes (e.g., mortality). METHODS: This was a retrospective, observational cohort study of 991 critically ill adults. To identify pharmacophenotypes, unsupervised machine learning analysis with automated feature learning using restricted Boltzmann machine and hierarchical clustering was performed on the medication administration records of each patient during the first 24 h of their ICU stay. Hierarchical agglomerative clustering was applied to identify unique patient clusters. Distributions of medications across pharmacophenotypes were described, and differences among patient clusters were compared using signed rank tests and Fisher's exact tests, as appropriate. RESULTS: A total of 30,550 medication orders for the 991 patients were analyzed; five unique patient clusters and six unique pharmacophenotypes were identified. For patient outcomes, compared to patients in Clusters 1 and 3, patients in Cluster 5 had a significantly shorter duration of mechanical ventilation and ICU length of stay (p < 0.05); for medications, Cluster 5 had a higher distribution of Pharmacophenotype 1 and a smaller distribution of Pharmacophenotype 2, compared to Clusters 1 and 3. For outcomes, patients in Cluster 2, despite having the highest severity of illness and greatest medication regimen complexity, had the lowest overall mortality; for medications, Cluster 2 also had a comparably higher distribution of Pharmacophenotype 6. CONCLUSION: The results of this evaluation suggest that patterns among patient clusters and medication regimens may be observed using empiric methods of unsupervised machine learning in combination with a common data model. These results have potential because while phenotyping approaches have been used to classify heterogenous syndromes in critical illness to better define treatment response, the entire medication administration record has not been incorporated in those analyses. Applying knowledge of these patterns at the bedside requires further algorithm development and clinical application but may have the future potential to be leveraged in guiding medication-related decision making to improve treatment outcomes.

An Evaluation of the Relationship Between Medication Regimen Complexity as Measured by the MRC-ICU to Medication Errors in Critically Ill Patients.

Purpose: The purpose of this study was to determine the relationship between medication regimen complexity-intensive care unit (MRC-ICU) score at 24 hours and medication errors identified throughout the ICU. Methods: A single-center, observational study was conducted from August to October 2021. The primary outcome was the association between MRC-ICU at 24 hours and total medication errors identified. During the prospective component, ICU pharmacists recorded medication errors identified over an 8-week period. During the retrospective component, the electronic medical record was reviewed to collect patient demographics, outcomes, and MRC-ICU score at 24 hours. The primary outcome of the relationship of MRC-ICU at 24 hours to medication errors was assessed using Pearson correlation. Results: A total of 150 patients were included. There were 2 pharmacists who recorded 634 errors during the 8-week study period. No significant relationship between MRC-ICU and medication errors was observed (r2 = .13, P = .11). Exploratory analyses of MRC-ICU relationship to major interventions and harm scores showed that MRC-ICU scores >10 had more major interventions (27 vs 14, P = .27) and higher harm scores (15 vs 7, P = .33), although these values were not statistically significant. Conclusion: Medication errors appear to occur independently of medication regimen complexity. Critical care pharmacists were responsible for mitigating a large number of medication errors.

Evaluation of phenytoin loading doses in overweight patients using actual versus adjusted body weight.

BACKGROUND AND OBJECTIVES: The appropriate loading dose strategy for phenytoin/fosphenytoin in overweight patients is unknown. A small pharmacokinetic study indicated that overweight patients have a higher volume of distribution and potentially would benefit from using adjusted body weight (AdjBW) instead of actual body weight (ABW) to calculate the loading dose. The purpose of this study was to determine the optimal loading dose strategy of phenytoin in patients whose ABW is greater than 120% of their ideal body weight (IBW) using either ABW or AdjBW for calculation of the loading dose. METHODS: This was a single center, retrospective study which included patients who received a loading dose of phenytoin of at least 10 mg/kg based on ABW, had a phenytoin level drawn <6 h after the end of the dose, and weighed ≥120% of their IBW. Patients were excluded if they received intramuscular phenytoin or fosphenytoin or were prescribed phenytoin prior to the loading dose. Patients were divided into two groups, those who were dosed using their AdjBW versus those dosed using ABW. The primary outcome was achievement of therapeutic phenytoin level of 10-20 mcg/mL. Secondary outcomes included achievement of a subtherapeutic or supratherapeutic level. RESULTS: A total of 195 patients (128 in AdjBW group and 67 in ABW group) met criteria for inclusion. Patients in the AdjBW group weighed more (96.2 kg vs. 91.2 kg, p = 0.04) and received a lower dose in milligrams (1364 vs. 1760, p < 0.0001) and in mg/kg of ABW (14.2 vs. 19.3, p < 0.0001). The primary outcome was achieved in 74% of patients in the AdjBW group and 57% of patients in the ABW group (p = 0.02). Patients in the ABW group were more likely to have a supratherapeutic level (43% vs. 22%, p = 0.003), although adverse reactions did not differ between the groups. DISCUSSION: Patients weighing >120% of their IBW (average body mass index 33.5 kg/m2) who received a 20 mg/kg loading dose based on AdjBW were more likely to achieve a therapeutic phenytoin concentration compared to those dosed based on ABW. Further research is needed to correlate this finding with clinical outcomes, such as resolution of status epilepticus.

Evaluating Clostridioides difficile infection (CDI) treatment duration in hematology/oncology patients receiving concurrent non-CDI antibiotics.

PURPOSE: To determine the impact of Clostridioides difficile infection (CDI) treatment duration on CDI recurrence in hematology/oncology patients receiving concurrent non-CDI antibiotics. PATIENTS AND METHODS: This multi-site, retrospective study examined hematology/oncology patients age ≥18 years hospitalized with active CDI who received ≥1 dose of concurrent non-CDI antibiotics between September 2013 and June 2019. All patients were classified by two definitions for statistical analysis: standard (10-14 days) versus prolonged (>14 days) duration of CDI treatment and non-extended (≤24 hours after stopping non-CDI antibiotics) versus extended (>24 hours after stopping non-CDI antibiotics) CDI treatment. Primary outcome was CDI recurrence within 180 days of completing CDI treatment. Secondary outcomes included hospital length of stay (LOS) as well as mortality and incidence of vancomycin-resistant enterococcus (VRE) infections at 180 days. RESULTS: Of the 198 patients included, 112 were classified as prolonged versus 86 standard duration and 138 were classified as extended versus 60 non-extended duration. After accounting for demographic differences, no difference existed in the primary outcome of CDI recurrence in either prolonged versus standard or extended versus non-extended analysis (all p > 0.05). Patients who received prolonged versus standard CDI treatment had longer LOS (p < 0.0001) while no difference existed in extended versus non-extended (p > 0.05). No difference in mortality existed in prolonged versus standard (p > 0.05) while those who received extended versus non-extended CDI treatment had significantly lower mortality (p = 0.0008). CONCLUSIONS: Neither prolonging CDI treatment beyond standard duration nor extending duration beyond end of non-CDI antibiotics was associated with decreased CDI recurrence rate.

Productivity Tracking: A Survey of Critical Care Pharmacist Practices and Satisfaction.

Introduction: The position paper on critical care pharmacy services describes two tiers of responsibilities: essential and desirable activities. Activities are categorized into five domains: patient care, quality improvement, research and scholarship, training and education, and professional development. Documentation of these activities can be important for justifying pharmacist positions, comparing pharmacy practice models, conducting performance evaluations, and tracking individual workload; however, limited recommendations are provided for standardized productivity tracking, and national practices remain largely uncharacterized. Objectives: The purpose of this survey was to describe documentation practices of critical care pharmacist activities. Methods: A cross-sectional survey was distributed via email to 1694 members of the ACCP critical care practice research network. The survey asked respondents to describe the methods used to document productivity as it relates to the 5 domains. Results: Seventy-nine (4.7%) critical care pharmacists from 63 institutions completed the survey. Intervention documentation was used for position justification and annual reviews among 54.4% and 44.1% of pharmacists, respectively. Pharmacists were routinely expected to perform additional responsibilities beyond patient care that contribute to overall productivity, but the percentage of institutions that track these activities as a measure of pharmacist productivity was relatively low: quality improvement (46%), research/scholarship (29%), training/education (38%), and professional development (27%). Documentation of these additional responsibilities and activities was primarily used for annual evaluations, but the majority of respondents answered that no standardized method for tracking activities existed. In multivariate regression, dedicated ICU pharmacists was a significant predictor for increased satisfaction (Exp(ß) 4.498, 95% CI 1.054-19.187, P = .042). Conclusion: Practice variation exists in how and for what intent critical care pharmacists track productivity. Further evaluation and standardization of productivity tracking may aid in position justification and practice model evaluation for dedicated ICU pharmacists in today's value-based era.

Queue the quarter life crisis: The value of mentorship for early-career pharmacists.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

Unsupervised machine learning analysis to identify patterns of ICU medication use for fluid overload prediction.

INTRODUCTION: Intravenous (IV) medications are a fundamental cause of fluid overload (FO) in the intensive care unit (ICU); however, the association between IV medication use (including volume), administration timing, and FO occurrence remains unclear. METHODS: This retrospective cohort study included consecutive adults admitted to an ICU ≥72 hours with available fluid balance data. FO was defined as a positive fluid balance ≥7% of admission body weight within 72 hours of ICU admission. After reviewing medication administration record (MAR) data in three-hour periods, IV medication exposure was categorized into clusters using principal component analysis (PCA) and Restricted Boltzmann Machine (RBM). Medication regimens of patients with and without FO were compared within clusters to assess for temporal clusters associated with FO using the Wilcoxon rank sum test. Exploratory analyses of the medication cluster most associated with FO for medications frequently appearing and used in the first 24 hours was conducted. RESULTS: FO occurred in 127/927 (13.7%) of the patients enrolled. Patients received a median (IQR) of 31 (13-65) discrete IV medication administrations over the 72-hour period. Across all 47,803 IV medication administrations, ten unique IV medication clusters were identified with 121-130 medications in each cluster. Among the ten clusters, cluster 7 had the greatest association with FO; the mean number of cluster 7 medications received was significantly greater in patients in the FO cohort compared to patients who did not experience FO (25.6 vs.10.9. p<0.0001). 51 of the 127 medications in cluster 7 (40.2%) appeared in > 5 separate 3-hour periods during the 72-hour study window. The most common cluster 7 medications included continuous infusions, antibiotics, and sedatives/analgesics. Addition of cluster 7 medications to a prediction model with APACHE II score and receipt of diuretics improved the ability for the model to predict fluid overload (AUROC 5.65, p =0.0004). CONCLUSIONS: Using ML approaches, a unique IV medication cluster was strongly associated with FO. Incorporation of this cluster improved the ability to predict development of fluid overload in ICU patients compared with traditional prediction models. This method may be further developed into real-time clinical applications to improve early detection of adverse outcomes.

Critical care pharmacist perspectives on optimal practice models and prioritization of professional activities: A cross-sectional survey.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: Critical care pharmacists (CCPs) are essential members of the multidisciplinary critical care team. Professional activities of the CCP are outlined in a 2020 position paper on critical care pharmacy services. This study looks to characterize CCP perspectives for priorities in optimizing pharmacy practice models and professional activities. METHODS: This was a cross-sectional survey conducted from July 24 to September 20, 2023. A 41-question survey instrument was developed to assess 7 domains: demographics, CCP resource utilization, patient care, quality improvement, research and scholarship, training and education, and professional development. This voluntary survey was sent to members of the American College of Clinical Pharmacy's Critical Care Practice and Research Network. The survey was open for a total of 6 weeks. RESULTS: There was a response rate of 20.7% (332 of 1,605 invitees), with 66.6% of respondents (n = 221) completing at least 90% of the survey questions. Most respondents were clinical specialists (58.2%) and/or practiced at an academic medical center (58.5%). Direct patient care, quality improvement and medication safety, and teaching and precepting were identified as the CCP activities of highest importance to CCPs. The CCP-to-patient ratios considered ideal were 1:11-15 (selected by 49.8% of respondents) and 1:16-20 (33.9% of respondents). The ideal percentage of time dedicated to direct patient care activities, as identified by survey respondents, was 50% (interquartile range, 40-50). CONCLUSION: These findings highlight the professional activities viewed as having the highest priority by CCPs. Future research is needed to define optimal CCP practice models for the delivery of patient care in real-world settings.

A common data model for the standardization of intensive care unit medication features.

Objective: Common data models provide a standard means of describing data for artificial intelligence (AI) applications, but this process has never been undertaken for medications used in the intensive care unit (ICU). We sought to develop a common data model (CDM) for ICU medications to standardize the medication features needed to support future ICU AI efforts. Materials and Methods: A 9-member, multi-professional team of ICU clinicians and AI experts conducted a 5-round modified Delphi process employing conference calls, web-based communication, and electronic surveys to define the most important medication features for AI efforts. Candidate ICU medication features were generated through group discussion and then independently scored by each team member based on relevance to ICU clinical decision-making and feasibility for collection and coding. A key consideration was to ensure the final ontology both distinguished unique medications and met Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles. Results: Using a list of 889 ICU medications, the team initially generated 106 different medication features, and 71 were ranked as being core features for the CDM. Through this process, 106 medication features were assigned to 2 key feature domains: drug product-related (n = 43) and clinical practice-related (n = 63). Each feature included a standardized definition and suggested response values housed in the electronic data library. This CDM for ICU medications is available online. Conclusion: The CDM for ICU medications represents an important first step for the research community focused on exploring how AI can improve patient outcomes and will require ongoing engagement and refinement.

Optimizing Pharmacist Team-Integration for ICU Patient Management: Rationale, Study Design, and Methods for a Multicentered Exploration of Pharmacist-to-Patient Ratio.

BACKGROUND: The workload of healthcare professionals including physicians and nurses in the ICU has an established relationship to patient outcomes, including mortality, length of stay, and other quality indicators; however, the relationship of critical care pharmacist workload to outcomes has not been rigorously evaluated and determined. The objective of our study is to characterize the relationship of critical care pharmacist workload in the ICU as it relates to patient-centered outcomes of critically ill patients. METHODS: Optimizing Pharmacist Team-Integration for ICU patient Management is a multicenter, observational cohort study with a target enrollment of 20,000 critically ill patients. Participating critical care pharmacists will enroll patients managed in the ICU. Data collection will consist of two observational phases: prospective and retrospective. During the prospective phase, critical care pharmacists will record daily workload data (e.g., census, number of rounding teams). During the retrospective phase, patient demographics, severity of illness, medication regimen complexity, and outcomes will be recorded. The primary outcome is mortality. Multiple methods will be used to explore the primary outcome including multilevel multiple logistic regression with stepwise variable selection to exclude nonsignificant covariates from the final model, supervised and unsupervised machine learning techniques, and Bayesian analysis. RESULTS: Our protocol describes the processes and methods for an observational study in the ICU. CONCLUSIONS: This study seeks to determine the relationship between pharmacist workload, as measured by pharmacist-to-patient ratio and the pharmacist clinical burden index, and patient-centered outcomes, including mortality and length of stay.

Ascorbic Acid for Methemoglobinemia Treatment: A Case Report and Literature Review.

PURPOSE: Ascorbic acid has been proposed as an alternative treatment for methemoglobinemia in patients with glucose-6-phosphate dehydrogenase (G6PD) deficiency. However, its efficacy has never been compared to that of methylene blue given the inability of patients with G6PD deficiency to receive methylene blue. We present a case of methemoglobinemia treated with ascorbic acid in a patient without G6PD deficiency who had previously received methylene blue. SUMMARY: A 66-year-old male was treated for methemoglobinemia deemed to be secondary to benzocaine throat spray. He received intravenous (IV) methylene blue but had a severe reaction: diaphoresis, lightheadedness, and hypotension. The infusion was stopped prior to completion. Approximately 6 days later he presented with methemoglobinemia following an additional overconsumption of benzocaine and was treated with ascorbic acid. In both instances his methemoglobin levels were >30% on arterial blood gas on admission and decreased to 6.5% and 7.8%, respectively, after administration of methylene blue and ascorbic acid. CONCLUSION: Ascorbic acid had a similar effect on decreasing the concentration of methemoglobin compared to methylene blue. Further research into use of ascorbic acid as a recommended agent for treatment of methemoglobinemia is warranted.

Implementation of a unique mass casualty and emergency preparedness longitudinal learning experience for postgraduate year 2 pharmacy residents.

BACKGROUND AND PURPOSE: The American Society of Health-System Pharmacists (ASHP) postgraduate year 2 (PGY2) critical care pharmacy residency program offers an elective competency area, E3: Mass Casualty. Similar elective competencies are also available for PGY2 emergency medicine and postgraduate year 1/2 pharmacotherapy programs. Because of the COVID-19 pandemic, pharmacist proficiency in the management of disasters is even more urgent. However, few residency programs require or include a specific learning experience to achieve this competency. This article provides examples of opportunities that residency programs can implement to offer an Emergency Preparedness/Mass Casualty (EP/MC) learning experience. EDUCATIONAL ACTIVITY AND SETTING: A longitudinal EP/MC learning experience was integrated into a PGY2 critical care program. FINDINGS: A longitudinal EP/MC learning experience within the PGY2 critical care, emergency medicine, and pharmacotherapy residency program curricula is achievable and promotes resident development. Learning experience components included topic discussions, participation on local and state-level emergency preparedness (EP) committees, completion of certification programs, projects, and participation on statewide emergency response teams. SUMMARY: Implementation of a longitudinal EP/MC learning experience formalizes topics and activities that support achievement of the ASHP elective competency area of Mass Casualty for PGY2 residency programs. EP/MC goals and objectives should be a requirement for critical care, emergency medicine, pharmacotherapy, and health-system pharmacy administration and leadership PGY2 programs. By formalizing training, pharmacists can be better prepared for EP and more integrated into multidisciplinary disaster response teams.

Reverse Triggering: An Introduction to Diagnosis, Management, and Pharmacologic Implications.

Reverse triggering is an underdiagnosed form of patient-ventilator asynchrony in which a passive ventilator-delivered breath triggers a neural response resulting in involuntary patient effort and diaphragmatic contraction. Reverse triggering may significantly impact patient outcomes, and the unique physiology underscores critical potential implications for drug-device-patient interactions. The purpose of this review is to summarize what is known of reverse triggering and its pharmacotherapeutic consequences, with a particular focus on describing reported cases, physiology, historical context, epidemiology, and management. The PubMed database was searched for publications that reported patients presenting with reverse triggering. The current body of evidence suggests that deep sedation may predispose patients to episodes of reverse triggering; as such, providers may consider decreasing sedation or modifying ventilator settings in patients exhibiting ventilator asynchrony as an initial measure. Increased clinician awareness and research focus are necessary to understand appropriate management of reverse triggering and its association with patient outcomes.