Setting up Chain-of-Survival Model trauma systems we should feel obliged to control the quality of treatment. Especially so when you break new ground and delegate life-saving skills to non-surgeons and non-doctors.
Quality control cannot be done by case studies; it takes a systematic effort where you analyze risk descriptors against outcome indicators for whole sets of patients treated. For that you have to gather the essential data on all patients, validate the data, and load them in a PC registry. This is a brief how-to-do guide. For details, please contact us (PEKER).
Essential data: Risk descriptors (explanatory variables)
Let us list the explanatory variables that affect the probability of trauma survival/death.
Age
The physiological response to trauma is different in Infants and children. Also “old” people can take less. Consequently we have to register years-of-age as a continuous variable.
Time factors
The injured starts dying and the post-injury stress reactions develops by hours after injury. Consequently two time variables are important:
Time 1: minutes and hours from the time of injury to in-field life support starts.
Time 2: the total prehospital transit time from injury to hospital admission.
Physiological severity: Revised Trauma Score
The “golden standard” for physiological severity scoring is the Revised Trauma Score/RTS (PEKER). It builds on three clinical signs of oxygen starvation: respiratory rate/RR, systolic blood pressure/BP, and central nervous system function as rated by Glasgow Coma Scale/GCS (PEKER).
GCS score | BP | RR | Coded value |
13 – 15 | > 90 | 10 – 30 | 4 |
9 – 12 | 76 – 89 | > 30 | 3 |
6 – 8 | 50 – 75 | 6 – 9 | 2 |
4 – 5 | 1 – 49 | 1 – 5 | 1 |
3 | No carotic pulse | No breathing | 0 |
The RTS for any patient can thus take on values from 0 (death) to 12 (no physiological derangement).