---
title: The Trauma Audit Filters Trial
subtitle: An Interrupted Time Series Trial on the Effect of Implementing Trauma Audit Filters on Outcomes of Patients Admitted with Trauma in Urban India
status: Ongoing
start: 2017
pageName: TAFT
aim: To assess if institutional implementation of audit filters reduce mortality in adult trauma patients
centres:
  - name: SSKM
    latitude: 22.539791106134892
    longitude: 88.34254487862368
  - name: JJ
    latitude: 18.963743250393183 
    longitude: 72.83354874003894
  - name: MAMC
    latitude: 28.638291630960076 
    longitude: 77.23877270880529
  - name: St Johns
    latitude: 12.929517952436166 
    longitude: 77.62001626696319
cities: 4
sampleSize: "8,400"
links:
  - name: ClinicalTrials.gov
    href: https://clinicaltrials.gov/ct2/show/NCT03235388
---

# Summary

## Introduction
Trauma is emerging as a major threat to population health globally. In addition
to prevention, strengthening trauma care is now recognised as imperative to the
global health agenda. Substantial research attributes improved trauma outcomes
in high income countries to quality improvement programmes. Audit filters,
defined as ``pre-identified variables that are routinely tracked to identify
whether accepted standards of care are being met'', for monitoring trauma care
quality are regarded as one of the most essential components of such programmes;
however, there is a paucity of evidence that shows that audit filters are
associated with improved outcomes. Therefore, our primary aim is to assess if
institutional implementation of audit filters reduce mortality in adult trauma
patients. Our secondary aim is to assess if such implementation improve other in
and out of hospital outcomes in adult trauma patients.

## Design
Controlled interrupted time series trial.

## Setting
Four university hospitals in India.

## Participants
Adult patients admitted with history of trauma.

## Primary outcome
All cause mortality within 30 days of arrival to
participating hospital.

## Secondary outcomes
All cause mortality in hospital, within 24 hours
and 90 days, quality of life at 90 days, number of hospital free days to day 30,
number of intensive care unit free days until day 30, and number of items
adhered to in the World Health Organisation's trauma care checklist.

## Covariates
Demographics, vital signs and injury data.

## Statistical methods
Segmented generalized additive model.




---
title: The Trauma Life Support Training Effectiveness Network Pilot Trial
subtitle: A pilot multicentre cluster randomised trial to compare the effect of trauma life support training programmes on patient and provider outcomes
status: Ongoing
start: 2022
pageName: TERN
aim: To assess the feasibility of conducting a cluster randomised controlled trial comparing advanced trauma life support (ATLS) and primary trauma care (PTC) with standard care.
centres:
  - name: LTMGH
    latitude: 19.03677576262065 
    longitude: 72.85990966081276
  - name: KEM
    latitude: 19.002568320059286 
    longitude: 72.84188182527217
  - name: Cooper
    latitude: 19.107940128317104 
    longitude: 72.83628059984359
  - name: NRS
    latitude: 22.563951824706272 
    longitude: 88.36894110202326
  - name: Medical College Kolkata
    latitude: 22.573778529331076 
    longitude: 88.36188378454496
  - name: Medica Superspeciality Hospital
    latitude: 22.4942271975299 
    longitude: 88.40064659433372
  - name: PGIMER
    latitude: 30.764943631596683 
    longitude: 76.77571548463719
cities: 3
sampleSize: "306"
links:
  - name: ClinicalTrials.gov
    href: https://clinicaltrials.gov/ct2/show/NCT05417243
  - name: Project Website
    href: https://tern.network
  - name: Published Protocol
    href: https://bmjopen.bmj.com/content/12/4/e057504.full
---

# Summary

## Introduction 
Trauma accounts for nearly 10% of the global burden of disease. Several trauma life support programmes aim to improve trauma outcomes. There is no evidence from controlled trials to show the effect of these programmes on patient outcomes. We describe the protocol of a pilot study that aims to assess the feasibility of conducting a cluster randomised controlled trial comparing advanced trauma life support (ATLS) and primary trauma care (PTC) with standard care.

## Methods and analysis
We will pilot a pragmatic three-armed parallel, cluster randomised controlled trial in India, where neither of these programmes are routinely taught. We will recruit tertiary hospitals and include trauma patients and residents managing these patients. Two hospitals will be randomised to ATLS, two to PTC and two to standard care. The primary outcome will be all-cause mortality at 30 days from the time of arrival to the emergency department. Our secondary outcomes will include patient, provider and process measures. All outcomes except time-to-event outcomes will be measured both as final values as well as change from baseline. We will compare outcomes in three combinations of trial arms: ATLS versus PTC, ATLS versus standard care and PTC versus standard care using absolute and relative differences along with associated CIs. We will conduct subgroup analyses across the clinical subgroups men, women, blunt multisystem trauma, penetrating trauma, shock, severe traumatic brain injury and elderly. In parallel to the pilot study, we will conduct community consultations to inform the planning of the full-scale trial.

## Ethics and dissemination
We will apply for ethics approvals to the local institutional review board in each hospital. The protocol will be published to Clinical Trials Registry—India and ClinicalTrials.gov. The results will be published and the anonymised data and code for analysis will be released publicly.


---
title: Towards Improved Trauma Care Outcomes
subtitle: The Original Cohort of Trauma Patients Admitted to Public University Hospitals in Urban India
status: Completed
start: 2013
end: 2015
dataset: https://github.com/titco/titco-I
pageName: TITCO
aim: To describe trauma patients admitted to public university hospitals in urban India
centres:
  - name: SSKM
    latitude: 22.539791106134892
    longitude: 88.34254487862368
  - name: LTMGH
    latitude: 19.0369518174664 
    longitude: 72.8581057056997
  - name: KEM
    latitude: 19.002785835076537 
    longitude: 72.84177683253944
  - name: JPNATC
    latitude: 28.568274285675535 
    longitude: 77.2012565266127
cities: 4
sampleSize: "16,000"
links:
  - name: GitHub
    href: https://github.com/titco/titco-I
---

# Summary

## Setting

The original TITCO cohort includes data on 16 000 patients admitted to
four public university hospitals in urban India.  At the time of the
research Jai Prakash Narayan Apex Trauma Center (JPNATC), All India
Institute of Medical Sciences, New Delhi, was a dedicated trauma
centre with almost 180 beds. King Edward Memorial hospital (KEM),
Mumbai, was a tertiary level hospital with no dedicated trauma
ward. Lokmanya Tilak Municipal General Hospital (LTMGH), Mumbai was a
tertiary level public university hospital with a dedicated trauma ward
with 14 beds. The Institute of Post-Graduate Medical Education and
Research and Seth Sukhlal Karnani Memorial Hospital (SSKM), Kolkata
was a tertiary level public university hospital, but without a
dedicated trauma ward. The cost of care in these hospitals was nominal
and the patients admitted represented mainly a lower socioeconomic
stratum of the population. The first patient was enrolled in July 2013
and the last patient in December 2015. The exact enrollment period
varied across participating hospitals.

## Design and participant selection

One dedicated project officer collected data on site for approximately
eight hours, five days per week. The shifts were rotated, so that the
project officers worked morning, evening, and night shifts, and then had
a day off. This way all possible shifts were covered during the course
of a month. Data for patients arriving during the project officers
shifts were collected by direct observation in the area where trauma
patients were received, and the project officers were allowed to ask the
health care staff for values of parameters not entered into the
patient\'s records. For example, if the systolic blood pressure was
measured (the project officer could see it being measured) but was not
documented in the patient record, the project officer was allowed to ask
for its value. Data for patients arriving to hospital outside the
project officers\' shifts were recorded from patient records. These
patients were identified from the nurses\' log books in the emergency
department.

## Eligibility criteria

Patients of all ages were included if they presented with history of
trauma and were admitted or died between arrival and admission. Patients
with isolated limb injury and patients who were dead on arrival were not
included.

## Ethical considerations

We obtained ethical approval for the collection of data for the original
research from each of the participating hospitals. The names of the
ethical bodies and reference numbers were Institute Ethics Committee All
India Institute of Medical Sciences (EC/NP-279/2013 RP-Ol/2013),
Institutional Ethics Committee (IEC(I)/OUT/222/14), Ethics Committee of
the Staff and Research Society (IEC/11/13), and IPGME&R Research
Oversight Committee (IEC/279) for JPNATC, KEM, LTMGH, and SSKM
respectively. We applied for a waiver of informed consent, which was
granted by all review boards. The patients included in this study were
all admitted after trauma, often arriving with an altered level of
consciousness and in severe physical and psychological distress. As the
original research involved only collection of routine data and did not
alter the care provided in any way, we and the ethics committees felt
that obtaining informed consent would be to burden the patients or their
relatives unnecessarily. Names, addresses, telephone, social security or
insurance numbers were never collected.




---
title: The Trauma Triage Study
subtitle: A Comparison of Prediction Models for Triage of Adult Trauma Patients Presenting to Emergency Departments in Urban India
status: Ongoing
start: 2016
pageName: TTRIS
aim: To validate and compare published prediction models for use in early trauma care
centres:
  - name: SSKM
    latitude: 22.539791106134892
    longitude: 88.34254487862368
  - name: KBBH
    latitude: 19.058265662484267 
    longitude: 72.83355916931863
  - name: MAMC
    latitude: 28.638291630960076 
    longitude: 77.23877270880529
cities: 3
sampleSize: "16,400"
links:
  - name: GitHub
    href: https://github.com/titco/trauma-triage-study
---

# Summary

## Introduction
In India a substantial share of trauma deaths happens in urban
areas. Here, prehospital care is largely lacking or poorly
organised. Ambulances are mainly used for transfer of patients between
hospitals. Hence, even the most severe patients arrive to hospital
without being assessed in the prehospital setting and then mix with
the general patient population that presents to the emergency
department. In such scenarios, one of the key challenges in trauma
care is how to prioritise patients so that the patients in greatest
need of care are seen first, i.e. triage. Our aim is to validate and
compare published prediction models for use in early trauma care.

## Design
Prospective multicentre cohort

## Setting
Three hospitals in urban India

## Participants
Any person aged > 18 years presenting to the emergency department (ED)
of participating sites with history of trauma.

## Primary outcome
Mortality within 30 days of arrival to hospital. Extracted by project
officer from patient record as date and time of death or discharge. If
the patient is discharged alive before 30 days of arrival the research
officer will call the patient or patient relative 30 days after
arrival to hospital to establish the patient’s status.

## Secondary outcomes

- Mortality within 24 hours of presentation to hospital. Extracted by
  project officer from patient record as date and time of death or
  discharge. If the patient is discharged alive before 24 hours of
  arrival the research officer will call the patient or patient
  relatives 24 hours after arrival to hospital to establish the
  patient’s status.
- Mortality within six months of presentation to hospital. Extracted
  by project officer from patient record as date and time of death or
  discharge. If the patient is discharged alive before six months of
  arrival the research officer will call the patient or patient
  relatives six months after arrival to hospital to establish the
  patient’s status.
- Mortality in participating hospital. Extracted by project officer
  from patient record as date and time of death or discharge.
- Admission to ward/hospital admission. Extracted by project officer
  from patient record and/or ascertained during follow up calls with
  patient or relative.
- Admission to intensive care unit. Extracted by project officer from
  patient record and/or ascertained during follow up calls with
  patient or relative.

## Covariates
Demographics, vital signs and injury data.

## Statistical methods
We will compare models using measures of discrimination, calibration, and net benefit. 


Projects

Our Ongoing and Completed Projects

The Trauma Life Support Training Effectiveness Network Pilot Trial

A pilot multicentre cluster randomised trial to compare the effect of trauma life support training programmes on patient and provider outcomes

The Trauma Audit Filters Trial

An Interrupted Time Series Trial on the Effect of Implementing Trauma Audit Filters on Outcomes of Patients Admitted with Trauma in Urban India

The Trauma Triage Study

A Comparison of Prediction Models for Triage of Adult Trauma Patients Presenting to Emergency Departments in Urban India

Towards Improved Trauma Care Outcomes

The Original Cohort of Trauma Patients Admitted to Public University Hospitals in Urban India