Introduction: Pediatric/neonatal transport teams are highly dedicated crews who treat a broad range of pediatric diagnoses and acuity. Most pediatric hospitals cover large geographic areas due to limited resources available in the community for pediatric patients. There is a need to standardize acuity and mode of transport. The aim of this project was to find a scoring system or matrix that could consistently be used in our institution to identify which patients needed to be transported the fastest and which mode of transport to use. Methods: Initially we began using a matrix which scored neonatal and pediatric patients on a scale from 1-5. This matrix took into account the patient's diagnosis but not distance, clinical presentation or resources available at the referral center. Many times the matrix did not categorize the patient correctly. After reviewing a variety of guidelines and scoring systems, we created an acuity and mode of transport matrix for our patient population and geographical area. The matrix was created to take into account four primary categories: airway, circulation, disability, and environment. Patients were scored within each category. Patients that scored the highest in each category were considered for helicopter flight or fastest mode of transport depending on time of day and distance. Patients who did not score in the high risk column were considered for ground versus air transport based on their total score from all columns. We encouraged the transport team to use the matrix for each patient and document any difficulties with scoring or any reason that they deviated from the matrix mode. The matrix was audited by transport nurses and medical directors. Multiple small changes were made to help improve the accuracy of the scoring, efficiency of the mode of transport determined and compliance with the matrix. Results: We were able to identify a matrix that worked for most patients. Another mode was utilized during inclement weather or when the helicopter was unavailable. The crew was allowed to deviate from the matrix for unusual patient circumstances. When we began using this matrix, the helicopter we utilized was located off site. Subsequently, we have transitioned to having an aircraft on the hospital helipad. Additional evaluation and auditing of the matrix has been required with this shift. There is full support from the transport medical directors who encouraged the medical control physicians to allow the team to choose the appropriate mode based on the matrix. Conclusion: We were able to create and utilize an acuity and mode of transport matrix to categorize patients and select the mode of transport. This matrix may differ for different institutions depending on their geographic area, transport team composition, and modes of transportation readily available to them.

Evaluation of Mode of Transport Matrix

QA over last 8 months showing the percentage of transports with a completed mode of transport matrix, percentage of transports moved by a mode other than one indicated by the matrix, and reason for not following mode of transport matrix.

Evaluation of Mode of Transport Matrix

QA over last 8 months showing the percentage of transports with a completed mode of transport matrix, percentage of transports moved by a mode other than one indicated by the matrix, and reason for not following mode of transport matrix.

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