Abstract
Background Nurses are at the frontline of detecting patient deterioration. We developed Communicating
Narrative Concerns Entered by Registered Nurses (CONCERN), an early warning system
for clinical deterioration that generates a risk prediction score utilizing nursing
data. CONCERN was implemented as a randomized clinical trial at two health systems
in the Northeastern United States. Following the implementation of CONCERN, our team
sought to develop the CONCERN Implementation Toolkit to enable other hospital systems
to adopt CONCERN.
Objective The aim of this study was to identify the optimal resources needed to implement CONCERN
and package these resources into the CONCERN Implementation Toolkit to enable the
spread of CONCERN to other hospital sites.
Methods To accomplish this aim, we conducted qualitative interviews with nurses, prescribing
providers, and information technology experts in two health systems. We recruited
participants from July 2022 to January 2023. We conducted thematic analysis guided
by the Donabedian model. Based on the results of the thematic analysis, we updated
the α version of the CONCERN Implementation Toolkit.
Results There was a total of 32 participants included in our study. In total, 12 themes were
identified, with four themes mapping to each domain in Donabedian's model (i.e., structure,
process, and outcome). Eight new resources were added to the CONCERN Implementation
Toolkit.
Conclusions This study validated the α version of the CONCERN Implementation Toolkit. Future
studies will focus on returning the results of the Toolkit to the hospital sites to
validate the β version of the CONCERN Implementation Toolkit. As the development of
early warning systems continues to increase and clinician workflows evolve, the results
of this study will provide considerations for research teams interested in implementing
early warning systems in the acute care setting.
Keywords
qualitative - nursing informatics - toolkit - implementation - early warning system
