Performance Analysis for the
Emergency Medical Service Dhulikhel, Nepal
The rescue service in the catchment area of Dhulikhel Hospital is still in its infancy. A network of meanwhile 8 rescue stations is based on the vision of a committed Nepalese doctor who wanted to do the same as the emergency medical care in Germany and implemented a control center at Dhulikhel Hospital. For seven years now, the control centre has been coordinating 8 rescue stations, some of which are operated with the support of the Nepalese Red Cross.
A prehospital emergency system created by a handful of dedicated individuals.
What the Dhulikhel Rescue Service lacks, despite its overwhelming commitment, is a quality check of the current system. For seven years now, emergency data has been collected at the Dhulikhel control center, but has not been subjected to standardized evaluation due to a lack of know-how. The actual performance of the system is not known and potential process optimizations are also hidden.
In Germany, the standardized evaluation of control center data is part of day-to-day business in order to ensure compliance with legal requirements in emergency medical services. In Nepal there are no such requirements because the rescue service in Nepal is not centrally organised.
Due to the lack of knowledge about their own performance, it is difficult to expand the system in a targeted manner and close potential gaps in supply.
In addition, there is no way to attract potential supporters as long as the performance of the system cannot be demonstrated.
What did we do?
In February 2020 we travelled to Nepal to see the control centre and the ambulance service of Dhulikhel Hospital. Special attention was paid to the data input, which at that time was still done in a rather uncoordinated way by untrained people. Correspondingly, the data quality showed signs of improvement. In February, the creation of an input mask was already in progress, so we neglected to optimize the data input.
We merged and cleaned up the loose Excel files at that time.
Currently we are working on the creation of several MS Power BI Dashboards, which show the rescue service supply in detail. Supply bottlenecks as well as optimizations in medical care are to be uncovered so that they can be attacked specifically.
The Nepalese rescue service team is thus to receive a tool that can be presented to potential donors and from which it can be seen how many people have actually been cared for by the Dhulikhel rescue service. An overview of the complaints and the overall state of health of the emergency patients should show the necessity of the rescue service. The deployment development over the years and per province should make visible if the capacity of the rescue service network should be expanded in favour of an even larger number of patients.
The analyses are to be adapted to the new database as soon as the standardized data input is operational.
Threshold values should then show where the capacity needs to be increased or where it makes sense to keep rescue service personnel at other rescue stations. The performance of the system should thus be made visible and weak points can be eliminated in a targeted manner.