Abstract 14453: Multi-institutional Implementation of a Novel Tablet-Based Platform for Home Monitoring Infants With Single Ventricle Cardiac Disease: Cardiac High Acuity Monitoring Program (CHAMP)
Introduction: Infants with single ventricle cardiac disease require a series of palliative surgeries culminating in Fontan circulation. The “interstage period” between the first and second surgeries is characterized by medical fragility with mortality rates of 2-20%. Most programs use paper-based home monitoring to improve survival and growth, and to alert families and care teams to physiologic compromise. However, paper-based monitoring places the burden on families to report their child’s clinical status.
Hypothesis: We hypothesized that mobile technology could alert the care team more rapidly, and that short videos would provide additive clinical data. After CHAMP was implemented locally, we hypothesized that multi-institutional implementation of CHAMP would require significant restructuring of the care teams to ensure appropriate responsiveness to instant alerts, videos and clinical concerns.
Methods: The CHAMP platform was constructed for multi-center deployment using the Microsoft Azure cloud in a HIPAA-compliant manner. CHAMP was deployed at Children’s Mercy Kansas City in May 2014 and at Seattle Children’s in January 2016. We performed a descriptive study of the experience across both centers.
Results: Interstage characteristics recorded through CHAMP are displayed in Table 1. Multi-institutional implementation required a learning curve, adjustment of nursing resources, recognition of regional differences, and practice changes at both institutions. The response from families regarding the utility of CHAMP has been overwhelmingly positive.
Conclusions: Multi-institutional implementation of a tablet-based interstage monitoring program is a feasible and effective method to collect critical patient information to make timely care decisions. This experience proves the feasibility of moving CHAMP to a nationwide platform, with the potential for predictive analytics and machine learning to enhance the accuracy of alerting methods.
- Single ventricle
- Mobile technology
- Hypoplastic left heart
- Congenital heart surgery, pediatric
- Healthcare innovation
Author Disclosures: M.D. Files: None. K. Waldburger: None. L. Erickson: None. J. Apperson: None. R. Stroup: None. A. Ricketts: None. B. Beaven: None. S. Goudar: None. A.S. Lay: None. G. Shirali: None.
- © 2016 by American Heart Association, Inc.