(72) The DCC Challenge: Utilizing a Network Learning model to test implementation of the Daily Care Check-In

Background: The Daily Care Check-In (DCC) is a previously validated measure of barriers to daily CF care and can be used to facilitate conversations about patients’ self-care. Using the implementation principles germane to learning networks, the CF Learning Network (CFLN) and Success with Therapies Research Consortium (STRC) partnered to lead a two-phase 180-day challenge to surface best practices to address barriers elicited from the DCC. The aim of Phase 1 was to use QI methods and a 90-day learning cycle to test the feasibility of administering and reviewing the DCC in standard clinic workflows. Implementation and results of Phase 2, focused on defining a “successful conversation” and are reported separately in a psychosocial abstract.

Methods: Design for Phase 1 was completed by a multi-stakeholder leader team in the summer of 2021. Invitations were sent to pre-selected CF Programs. Criteria for invitations included Programs with strong QI Leaders. Teams were asked to participate in both phases and include patient and family partners. A 60-minute kick-off meeting convened in September 2021 followed by bi-weekly 30-minute team huddles through December 2021. The Model for Improvement QI methodology was applied. Challenge leads created or adapted huddle content from existing material including the DCC Toolkit and Cincinnati Children’s Anderson Center Improvement Science Problem Solving Model and QI Unit training content. Huddle agendas centered on QI teaching, and teams’ sharing of Plan Do Study Act (PDSA) experience. The number of eligible visits with completed DCCs and number of completed DCCs that were reviewed were collected weekly via REDCap and displayed in Run Charts.

Results: Four programs participated in Phase 1. Interdisciplinary teams, including patients/families from all programs, joined seven of eight huddles with an average of 20 attendees [13-34] per huddle. Teams learned and applied multiple QI tools: Process Maps, Driver Diagrams, Simplified Failure Modes Effects Analysis, and Pareto Charts. A third measure was added after huddle six to differentiate eligible visits within program-defined scope (all patients 12 years and older seen in CF clinic on specified days and/or with specified providers) from eligible visits targeted for DCC use (patients within scope specifically selected to receive and complete the DCC).

Baseline data for Phase 1 measurement included:

Percent of eligible visits within scope with completed DCCs: 72%

Percent of targeted visits within scope with completed DCCs: 86%

Percent of eligible visits with completed DCCs that were reviewed: 94%

Conclusions:

Conclusion: Participation and process measures results indicate Phase 1 was well designed and met its aim to use a learning network model of multi-site collaboration for feasibility testing. QI methods facilitated rapid implementation of the DCC in clinical care workflows and facilitated discovery in tested processes.

Acknowledgements: This study was funded, in part, by the CFLN (CFF grant SEID19ABO), CFLN site-grants, and STRC DMC grant (RIEKER15PE0) which supported the data collect and analysis.

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