Development and Implementation of an In-Hospital Pharmacist Emergency Response Simulation Training Curriculum

BACKGROUND

Medical simulation is an effective educational tool used to increase confidence, improve knowledge, and refine skills when responding to high acuity situations. Despite established roles of the pharmacist on the hospital code team, most institutions lack formalized pharmacist training for code team responses.

OBJECTIVE

This pre-post analysis aimed to evaluate the impact of a didactic and simulation-based code response training for pharmacists on self-perceived improvement and preparedness when responding to in-hospital medical emergencies.

METHODS

An emergency response curriculum (ERC) was developed for pharmacists and pharmacy residents at our institution. The curriculum, led by four lead clinical pharmacy specialists, included a sixty-minute didactic code competency lecture followed by two medical emergency simulations and a debrief after each scenario. Following completion of the simulation portion of the ERC, participants were given a survey to complete which assessed their confidence utilizing a 5-point Likert scale (1=very unconfident to 5=very confident) in completing the course objectives prior to and post the ERC.

RESULTS

Seventy-two pharmacists completed the ERC and 60 completed the post course survey. Of those who completed the post course survey, 70% were pharmacy residents. Using a 5-point Likert scale (1=very unconfident to 5=very confident), median participant confidence rose from 3 [IQR 2-4] before the session to 4 [IQR 3-5] after the session (p <0.001). Of the participants, 95% believed the ERC training should be required annually or multiple times a year and 100% of respondents felt the ERC training was beneficial.

CONCLUSION

Development of a pharmacist ERC including didactic and simulation-based learning improved the confidence and preparedness of pharmacists when participating as members of the hospital code team. Future studies should continue to evaluate pharmacist training and curriculum development in code team responses.

Virtual Care Team Guided Management of Patients With Heart Failure During Hospitalization

BACKGROUND

Scalable and safe approaches for heart failure guideline-directed medical therapy (GDMT) optimization are needed.

OBJECTIVES

The authors assessed the safety and effectiveness of a virtual care team guided strategy on GDMT optimization in hospitalized patients with heart failure with reduced ejection fraction (HFrEF).

METHODS

In a multicenter implementation trial, we allocated 252 hospital encounters in patients with left ventricular ejection fraction ≤40% to a virtual care team guided strategy (107 encounters among 83 patients) or usual care (145 encounters among 115 patients) across 3 centers in an integrated health system. In the virtual care team group, clinicians received up to 1 daily GDMT optimization suggestion from a physician-pharmacist team. The primary effectiveness outcome was in-hospital change in GDMT optimization score (+2 initiations, +1 dose up-titrations, -1 dose down-titrations, -2 discontinuations summed across classes). In-hospital safety outcomes were adjudicated by an independent clinical events committee.

RESULTS

Among 252 encounters, the mean age was 69 ± 14 years, 85 (34%) were women, 35 (14%) were Black, and 43 (17%) were Hispanic. The virtual care team strategy significantly improved GDMT optimization scores vs usual care (adjusted difference: +1.2; 95% CI: 0.7-1.8; P < 0.001). New initiations (44% vs 23%; absolute difference: +21%; P = 0.001) and net intensifications (44% vs 24%; absolute difference: +20%; P = 0.002) during hospitalization were higher in the virtual care team group, translating to a number needed to intervene of 5 encounters. Overall, 23 (21%) in the virtual care team group and 40 (28%) in usual care experienced 1 or more adverse events (P = 0.30). Acute kidney injury, bradycardia, hypotension, hyperkalemia, and hospital length of stay were similar between groups.

CONCLUSIONS

Among patients hospitalized with HFrEF, a virtual care team guided strategy for GDMT optimization was safe and improved GDMT across multiple hospitals in an integrated health system. Virtual teams represent a centralized and scalable approach to optimize GDMT.

Virtual optimization of guideline-directed medical therapy in hospitalized patients with heart failure with reduced ejection fraction: the IMPLEMENT-HF pilot study

AIMS

Implementation of guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF) remains incomplete. Non-cardiovascular hospitalization may present opportunities for GDMT optimization. We assessed the efficacy and durability of a virtual, multidisciplinary 'GDMT Team' on medical therapy prescription for HFrEF.

METHODS AND RESULTS

Consecutive hospitalizations in patients with HFrEF (ejection fraction ≤40%) were prospectively identified from 3 February to 1 March 2020 (usual care group) and 2 March to 28 August 2020 (intervention group). Patients with critical illness, de novo heart failure, and systolic blood pressure <90 mmHg in the preceeding 24 hs prior to enrollment were excluded. In the intervention group, a pharmacist-physician GDMT Team provided optimization suggestions to treating teams based on an evidence-based algorithm. The primary outcome was a GDMT optimization score, the sum of positive (+1 for new initiations or up-titrations) and negative therapeutic changes (-1 for discontinuations or down-titrations) at hospital discharge. Serious in-hospital safety events were assessed. Among 278 consecutive encounters with HFrEF, 118 met eligibility criteria; 29 (25%) received usual care and 89 (75%) received the GDMT Team intervention. Among usual care encounters, there were no changes in GDMT prescription during hospitalization. In the intervention group, β-blocker (72% to 88%; P = 0.01), angiotensin receptor-neprilysin inhibitor (6% to 17%; P = 0.03), mineralocorticoid receptor antagonist (16% to 29%; P = 0.05), and triple therapy (9% to 26%; P < 0.01) prescriptions increased during hospitalization. After adjustment for clinically relevant covariates, the GDMT Team was associated with an increase in GDMT optimization score (+0.58; 95% confidence interval +0.09 to +1.07; P = 0.02). There were no serious in-hospital adverse events.

CONCLUSIONS

Non-cardiovascular hospitalizations are a potentially safe and effective setting for GDMT optimization. A virtual GDMT Team was associated with improved heart failure therapeutic optimization. This implementation strategy warrants testing in a prospective randomized controlled trial.

Feasibility of Virtual Optimization of Guideline Directed Medical Therapy in Hospitalized Patients with HFrEF During the Covid-19 Pandemic: The IMPLEMENT-HF Pilot Study

Introduction

Implementation of GDMT for HFrEF remains low. We assessed the feasibility of a virtual GDMT Team for optimization of GDMT during hospitalization for non-CV conditions.

Hypothesis

A GDMT Team will improve GDMT optimization compared with usual care.

Methods

Consecutive hospitalized patients with HFrEF≤40% were prospectively identified. Patients with critical illness, cardiology consult, de-novo HF, COVID-19 & SBP ≤90mmHg were excluded. February 3 to March 1, 2020 served as a pre-intervention period during which patients were screened, but did not receive GDMT Team interventions. From March 2 to June 21, 2020, a pharmacist-physician team provided up to 1 suggestion daily for GDMT optimization (evidence-based ß-blockers, ACEi/ARB/ARNI, & MRA) to treating teams based on an evidence-based algorithm.

The primary outcome of a composite GDMT optimization score, the net of positive therapeutic changes (+1 for new initiations/uptitrations) & negative therapeutic changes (-1 for discontinuations/downtitrations) during hospitalization, was compared between the pre- vs. post-intervention periods. Multivariable linear regression models were built adjusting associations for clinical factors. Safety outcomes requiring intervention or GDMT downtitration were identified.

Results

Of 187 encounters, 84 (45%) met eligibility criteria: 28 pre-intervention, 56 post-intervention. Mean age was 68±11 yrs, 70% men, and 61% White. Of 88 GDMT Team suggestions, 49 (56%) were followed by discharge. During the intervention, cumulative COVID-19 hospitalizations rose from 0 to 11085 in MA.

Mean GDMT optimization score was -0.14 (95% CI: -0.58 to +0.30) pre-intervention & +0.64 (95% CI: +0.35 to +0.93) post-intervention (P=0.004). In a model inclusive of demographics, comorbidities, vital signs, potassium levels, eGFR, & LVEF, the intervention was the only factor associated with higher GDMT optimization score (β coeff 0.89; P=0.008). Safety events included 1 instance each of AKI, hyperkalemia, bradycardia, & hypotension.

Conclusion

Admission for non-CV conditions is a feasible setting for GDMT optimization. A virtual GDMT Team was associated with improved GDMT; this implementation strategy warrants testing in a prospective RCT.