Purpose

Lung transplantation in children remains challenging, requiring extensive infrastructure and expertise. At our institution, we have performed 191 pediatric lung transplants since 2002. We hypothesized that the ability to mine data from multiple electronic medical records in real time would be a great facilitator of patient care. We endeavored to build a data analytics platform that would allow us to daily review our current pediatric lung transplant outcomes across multiple clinical settings.

Methods

A team that includes surgeons, pediatric pulmonologists, nursing, outcomes researchers and information technology specialists was created and variables to be included in the data analytics platform defined. Variable sources were located in our enterprise data warehouse and consisted of data from multiple electronic medical records. Structure query language (SQL) was written for each data point, which was then validated by multiple team members. Visualization software was then used to display graphics that would facilitate patient care. The platform updates every morning and is available to the members of the pediatric lung transplant team through our institution's website.

Results

Patient characteristics were separated by volume, operative variables, hospital course, survival, and follow up. Filters were created that when selected filter data throughout the data analytics platform by year, age, gender, race, surgeon, organ type, UNOS diagnosis, retransplant, and deceased patients. This platform is used by our entire transplant team and has now been integrated into many of our care pathways. It is used for a wide range of clinical activities, including for our quality conferences, in our pediatric pulmonology and congenital heart surgery clinics when counseling patients and families, and to answer clinical questions that arise.

Conclusions

Building a data analytics platform for our lung transplant patients has enabled us to talk to families in real time about what to expect from transplantation using up-to-date data. It allows us to quickly answer clinical questions and has improved our care of a challenging patient population. We anticipate continuing to expand applications for real-time data integration.

CITATION INFORMATION: Scully B., Hosek K., Dash D., Carberry K., Melicoff E., Gazzaneo M., Mallory G., Heinle J. Using a Data Analytics Platform to Improve Patient Care in Pediatric Lung Transplantation Am J Transplant. 2017;17 (suppl 3).

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