Risk factors for cancellation after dispatch of rapid response cars for prehospital emergency care: a single-center, case-control study

Development and Validation of a Machine Learning Model to Predict Post-dispatch Cancellation of Physician-staffed Rapid Car

Objectives

This study aimed to develop and validate a machine learning prediction model for post-dispatch cancellation of physician-staffed rapid car.

Materials

Data were extracted from the physician-staffed rapid response car database at our Hospital between April 2017 and March 2019.

Methods

After obtaining 2019 cases, we divided the dataset into a training set for developing the model and a test set for validation using stratified random sampling with an 8 : 2 allocation ratio. We selected random forest as the machine-learning classifier. The outcome was the post-dispatch cancellation of a rapid car. The model was trained using predictor variables, including 18 different reasons for rapid car request, age and gender of a patient, date (month), and distance from the hospital.

Results

This machine learning model predicted the occurrence of post-dispatch cancellation of rapid cars with an accuracy of 75.5% [95% confidence interval (CI): 71.0-79.6], sensitivity of 81.5% (CI: 75.0-86.9), specificity of 70.8% (CI: 64.4-76.6), and an area under the receiver operating characteristic value of 0.83 (CI: 0.79-0.87). The important features were distance from the hospital to the scene, age, suspicion of non-witnessed cardiac arrest, farthest geographic area, and date (months).

Conclusions

We developed a favorable machine learning model to predict post-dispatch cancellation of rapid cars in a local district. This study suggests the potential of machine-learning models in improving the efficiency of dispatching physicians outside hospitals.

Fudan Zenshin, Kyumeikyukyu ; ~Now JIN again~

I graduated from Osaka University in 1982 and joined the Department of Traumatology, Osaka University Medical School. Patients with severe injuries and illnesses were brought in every day. Staff brushed up their skills on site, taught each other, and engaged in friendly competition for research. We had many frustrating moments when we could not save lives. Since then, the needs of emergency medicine have changed, and the scope of practice of emergency physicians has expanded to include pre-hospital emergency care, primary health care, intensive care, and disaster medicine. I was transferred to Juntendo University Urayasu Hospital in September 2007. Soon after my assignment, Urayasu Hospital was in the spotlight due to the emergency hospitalization of the All-Japan soccer coach and the Chinese frozen dumpling incident. It is said that emergency medicine is a mirror of society. I myself have experienced many disasters and incidents. It has been 15 years since I was assigned to this hospital, and I have 62 colleagues at Urayasu Hospital. They have all acquired various medical specialties, and some are emergency medicine specialists. In 2019, we hosted the 47th Annual Meeting of the Japanese Association for Acute Medicine. The theme of the conference is "Fudan Zenshin, Kyumeikyukyu (constant advancement, emergency medical services)". Emergency medical care is the starting point of "medicine" and is the ultimate source of life preservation for all citizens. We emergency physicians will continue to provide lifesaving medical care to patients without giving up until the very end, to keep the light of life from going out.