Improvement of Ambulance Response Times in Karachi, Pakistan

Emergencies Clinical Trial

Official title:

Spatial Analysis Optimization of Prehospital Services in Karachi, Pakistan to Improve Ambulance Response Times

Clinical Trial Details — Status: Withdrawn

Administrative data

• NCT number: NCT02743169
• Other study ID #: IRB00085859
• Status: Withdrawn
• Start date: April 1, 2017
• Est. completion date: June 29, 2020

Study information

• Verified date: August 2020
• Source: Johns Hopkins University
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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.

Description:

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.

Recruitment information / eligibility

• Status: Withdrawn
• Enrollment: 0
• Est. completion date: June 29, 2020
• Est. primary completion date: June 29, 2020
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Aman Foundation uses The Medical Priority Dispatch System (MPDS), a commonly used five-tier triage system that includes the following categories (from least to most acute) "alpha," "bravo," "charlie," "delta," and "echo." For the analyses in Aim 2 and Aim 3, we will only examine calls for "delta" and "echo" patients.

Exclusion Criteria:

• Ambulance calls for transport of patients from one healthcare facility to another or calls in which the patient refused transport will be excluded from the analysis.

Related Conditions & MeSH terms

• Emergencies

Intervention

Other:
• Spatially-Optimized
Spatial analysis of retrospective data will be used to optimize the placement of ambulances to decrease response time from the time the call is received until the time the ambulance arrives at the patient's location.

Locations

Country	Name	City	State
Pakistan	Aman Foundation	Karachi

Sponsors (1)

Lead Sponsor	Collaborator
Johns Hopkins University

Country where clinical trial is conducted

Pakistan, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Ambulance Response Time	Time from when a call comes to the call center to the time the ambulance arrives at the patient.	18 months