Emergencies Clinical Trial
Official title:
Spatial Analysis Optimization of Prehospital Services in Karachi, Pakistan to Improve Ambulance Response Times
The investigators hypothesize that spatial analysis of the location data of ambulance calls can improve prehospital care provided by Aman Foundation in Karachi, Pakistan by decreasing ambulance response times for high acuity patients. In Aim 1, the investigators will develop a conceptual framework for prehospital care in low- and middle-income countries (LMICs) to anchor this project in Aims 2 and 3. In Aim 2, the investigators will analyze the location of calls to identify geographic areas with delayed responses for patients with higher severity of illness. As part of their quality assurance/quality improvement practices, Aman Foundation routinely collects location data from GPS devices in their ambulances for each call. Based on the analyses in Aim 2, in Aim 3 the investigators will position ambulances where there are clusters of delayed ambulance calls for high acuity patients to improve response times. This period will be compared with a previous, control period and will be analyzed to identify possible new clusters.
The list of the top causes of death and lost disability-adjusted life-years (DALYs) globally
includes many conditions that initially present in the emergency setting. These top causes
include lower respiratory infections, ischemic heart disease, and acute injury. The morbidity
and mortality that result from these causes can be minimized with emergency treatment. A key
element to reducing morbidity and mortality from acute illnesses is the time of patient
transport to a medical facility, which has been most clearly demonstrated for acute injury.
Low- and middle-income countries (LMICs) shoulder a disproportionate burden from acute
illnesses, yet it has also been demonstrated that reduced transport times to a hospital
decrease the odds of mortality in trauma patients in LMICs. A lack of equipment, poorly
developed infrastructure, and long distances have been reported as key barriers in the
provision of emergency care. Pakistan is one such LMIC that is burdened by many of these
challenges in prehospital care. Emergency medical systems (EMS) have only recently been
established in Pakistan, and prior to the last several years, patients were routinely
transported to healthcare facilities by relatives, bystanders, or by basic patient transport.
Where formal patient transport is available, transport times are often prolonged by distance,
traffic congestion, and a lack of public cooperation.
Geographic information systems (GIS) are an analytic method that may serve as a key tool in
decreasing the time of transporting acutely ill patients to life-saving medical care. GIS,
which links geographic information to public health data, has been used in simulations to
decrease ambulance response times and been shown to decrease response times in industrialized
countries. However, this has not been replicated in other highly developed countries and has
never been demonstrated in an LMIC.
The investigators hypothesize that that spatial analysis of the location data of ambulance
calls can improve prehospital care provided by Aman Health Care Services in Karachi, Pakistan
by decreasing ambulance response times for high acuity patients.
Aim 1: Develop a conceptual framework for prehospital care in LMICs. As no such framework
currently exists in the literature, the investigators will develop a conceptual framework to
anchor this project in Aims 2 and 3. The framework will be developed after a consideration of
other related health systems frameworks in the literature. The investigators will also
consult with experts in the field and with the partners in Karachi to comment on how the
framework can be improved.
Aim 2: Analyze the location of calls to identify geographic areas with longer calls and
higher severity of illness. Using GIS and spatial analysis, the investigators will analyze
Aman Ambulance's existing data on ambulance calls to find areas of Karachi that routinely
have long response times.
Aim 3: Position ambulances where there are clusters of delayed ambulance calls for high
acuity patients to improve response times. Over a six-month period, ambulances will be
repositioned in and around clusters of delays to improve response times. This period will be
compared with the same calendar period in the previous year using a logistic regression
analysis to determine if there is a decrease in delayed ambulance responses. Spatial analyses
will also be performed on data from the intervention period to assess for the presence of
clusters of delays.
This study has the potential to use a sustainable method of analyzing routinely collected
data on ambulance calls to shorten the time that patients with acute illnesses receive
appropriate medical care in Pakistan, a setting in which there are substantial infrastructure
and human resource challenges.
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