“…anesthesiology has a well-deserved reputation for pioneering approaches to improve clinical safety and quality and for innovating in times of crisis.”

Image: J. P. Rathmell.

Image: J. P. Rathmell.

ALTHOUGH the origins of anesthesiology can be traced to the operating theater, the anesthesia provider’s sphere of influence has expanded to include the continuum of perioperative care management and coordination, intensive care specialization, and simulation as a tool for training and safety. In this issue of Anesthesiology, Levy et al.1  share their experience in a nontraditional setting, developing rapid response capabilities in a COVID-19 field hospital in Boston, Massachusetts. In this special article, the authors detail their use of quality improvement approaches and in situ simulation to develop a coordinated, effective response to COVID-19 low-acuity patients who developed clinical deterioration.

The specialty of anesthesiology has a well-deserved reputation for pioneering approaches to improve clinical safety and quality and for innovating in times of crisis. Levy et al.1  carry on the tradition by demonstrating the utility in exporting quality improvement approaches for developing and testing clinical workflows in an unfamiliar environment under time-pressured, resource-constrained conditions. The authors were part of a larger team charged with creating a field hospital to help offload the Boston area’s acute care facilities, as epidemiologic projections predicted that the number of COVID-19 patients would outstrip the number of available beds. The solution was to create “Boston Hope,” a 500-bed field medical facility, within the Boston Convention and Exhibition Center. Boston Hope was meant to be a low acuity center with a level of care similar to that of a skilled nursing facility. The designers realized, however, that some of the patients would inevitably deteriorate, needing a higher level of care. Recognition of the importance of proactively preparing for both anticipated and unanticipated critical emergencies led to the creation of a rapid response team that comprised a diverse group of available, mostly outpatient-focused clinicians with a collective clinical experience that infrequently require triage and rescue of the acutely decompensating patient, supported by anesthesiologists on standby.

The Boston Hope team recognized multiple challenges that would complicate care for a patient in extremis, including unfavorable acoustics in the repurposed exhibit hall, an inability to perform aerosol-generating procedures (e.g., intubation, chest compressions) in open spaces, and staff unfamiliarity with rapid response procedures. Presciently, Levy et al.1  prospectively employed quality improvement approaches to identify problems and safety threats. These approaches—failure modes and effects analysis, process mapping with on-site walkthroughs, and in situ simulation—were crucial in proactively identifying hazards that could be remedied even before the rapid response team was needed. We explain each of these approaches below.

Failure Mode and Effects Analysis

Failure Mode and Effects Analysis is a proactive process that dissects an event of interest (in this case, responding to a deteriorating patient), allowing identification of potential problems, called “failure modes.”2  This work is ideally undertaken by a group of engaged stakeholders representing the various people who influence the process of interest directly or indirectly. The group prioritizes the failure modes according to severity, probability of occurrence, and detectability, collapsing these concepts into a single risk priority score. The typical Failure Mode and Effects Analysis requires multiple meetings and may unfold over weeks or months. Recognizing the importance of timely evaluation in healthcare settings, a Veterans Affairs team published a modification of the Failure Mode and Effects Analysis process that they called Health Care Failure Mode and Effects Analysis.3  Levy et al.1  also used an abbreviated process, motivated by the need to develop a functional rapid response process in a matter of days. With this initial work, they focused only on those failure modes deemed both high severity and immediate priority, including the presence of just one automated external defibrillator in the space and the lack of a means to alert the rapid response team.

Process Mapping with On-site Walkthroughs

Clinicians usually based in hospitals may take for granted environmental design features that facilitate patient care, including easy access to oxygen, a functional overhead paging system, and beds with adjustable height. These were among the problems discovered by Levy et al.1  on walking through the Boston Hope space. In our own experience preparing for COVID-19 patient care in novel spaces, it was only with walkthroughs that entry and egress pathways could be defined, personal protective equipment donning and doffing stations could be sited, and air and medical gas handling concerns could be discovered. The process of walking through a space with clinical leaders, frontline staff, and support staff such as environmental services thus represents, in our opinion, an essential step in clinical scenario planning.

In Situ Simulation

In situ simulation brings simulation to the bedside to allow practice in the same environment as clinical care and is an evolving, high-impact tool for interprofessional and multidisciplinary human factors training frequently led by anesthesiologists.4,5  Approaches to safety are multipronged and include Safety I (analysis of events for improvement), Safety II (enhancing existing work processes that are successful through practice), resilience engineering (resourcing teams with the skills to flex to totally unexpected and unanticipated emergencies), and antifragility (active learning and improvement during and after critical events).6  The Boston Hope team recognized the applicability of in situ simulation to enhance each of these dimensions as they related to the organizational challenges of the COVID-19 field hospital. The Boston Hope team used in situ simulation as the next step in a natural progression from theoretical hazards to those experienced when caring for a mannikin in the Boston Hope setting. These simulations, which took place while the center was open for patient care, allowed these ad hoc teams to practice communication and teamwork dynamics in the process of performing time trials demonstrating, for example, the ability to deliver an automated external defibrillator shock within the American Heart Association recommended 2-min time window. In our case, in situ simulation revealed inefficiencies in personal protective equipment donning and doffing that could increase time to intubation for patients with impending respiratory failure. Such simulation scenarios provide a realistic but low-risk strategy for team members to practice closed-loop communication, situational awareness, and team leadership while also evaluating failure modes, established algorithms, and eliciting direct feedback to improve clinical care delivery. Given the myriad unknowns in the COVID-19 environment, the substantial unfamiliarity of many of the field clinicians with COVID-19 protocols, personal protective equipment, and colleagues’ skills sets, and the need for robust adaptability, simulation is a critical tool in the armamentarium of clinical teams caring for this challenging patient population.

The Boston Hope team used these prospective quality improvement approaches with conventional retrospective review of patient cases to craft a comprehensive approach to safe patient care in a novel, challenging environment. While the scenario they faced was unique, the process they followed is relevant to any new clinical setting. The creation of new hospitals and expansion of nonoperating room anesthesia locations are two examples of settings where these approaches could be used to uncover safety hazards before any patient is exposed to risk. Indeed, the use of these proactive, flexible techniques is likely to promote team resiliency in the face of COVID-19 and other inevitable clinical challenges to be faced by anesthesiologists and other acute care providers.

Competing Interests

The authors are not supported by, nor maintain any financial interest in, any commercial activity that may be associated with the topic of this article. Dr. Lane-Fall receives grant funding from the National Institutes of Health (Bethesda, Maryland; grant Nos. 1R01HL153735, 5P30AG059302, 5UM1HL088957) and the Robert Wood Johnson Foundation (Princeton, New Jersey), is on the Board of Directors of the Anesthesia Patient Safety Foundation (Rochester, Minnesota), and has received a speaking honorarium from destinationCME, LLC (Chicago, Illinois). Dr. Atkins has received support from the Medtronic Corporation (Minneapolis, Minnesota), Becton Dickinson Corporation (Franklin Lakes, New Jersey), and Oppenheimer, Inc (New York, New York).

References

1.
Levy
N
,
Zucco
L
,
Ehrlichman
RJ
,
Hirschberg
RE
,
Johnson
SH
,
Yaffe
MB
,
Ramachandran
SK
,
Bose
S
,
Leibowitz
A
.
Development of rapid response capabilities in a large COVID-19 alternate care site using failure modes and effect analysis with in situ simulation.
Anesthesiology
.
2020
;
133
:
985
96
2.
Ashley
L
,
Armitage
G
,
Neary
M
,
Hollingsworth
G
.
A practical guide to failure mode and effects analysis in health care: Making the most of the team and its meetings.
Jt Comm J Qual Patient Saf
.
2010
;
36
:
351
8
3.
DeRosier
J
,
Stalhandske
E
,
Bagian
JP
,
Nudell
T
.
Using health care Failure Mode and Effect Analysis: The VA National Center for Patient Safety’s prospective risk analysis system.
Jt Comm J Qual Improv
.
2002
;
28
:
248
67
4.
Rosenman
ED
,
Fernandez
R
,
Wong
AH
,
Cassara
M
,
Cooper
DD
,
Kou
M
,
Laack
TA
,
Motola
I
,
Parsons
JR
,
Levine
BR
,
Grand
JA
.
Changing systems through effective teams: A role for simulation.
Acad Emerg Med
.
2018
;
25
:
128
43
5.
Gardner
AK
,
Johnston
M
,
Korndorffer
JR
Jr
,
Haque
I
,
Paige
JT
.
Using simulation to improve systems-based practices.
Jt Comm J Qual Patient Saf
.
2017
;
43
:
484
91
6.
Martinetti
A
,
Chatzimichailidou
MM
,
Maida
L
,
van Dongen
L
.
Safety I–II, resilience and antifragility engineering: A debate explained through an accident occurring on a mobile elevating work platform.
Int J Occup Saf Ergon
.
2019
;
25
:
66
75