<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03235388</url>
  </required_header>
  <id_info>
    <org_study_id>4-1982/2017</org_study_id>
    <nct_id>NCT03235388</nct_id>
  </id_info>
  <brief_title>The Trauma Audit Filters Trial</brief_title>
  <acronym>TAFT</acronym>
  <official_title>The Trauma Audit Filters Trial: Does Institutional Implementation of Audit Filters Reduce Mortality in Adult Trauma Patients?</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Karolinska Institutet</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>Doctors For You</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>St Johns Medical College Hospital, Bangalore, India</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Seth Sukhlal Karnani Memorial Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Grant Government Medical College &amp; Sir J J Group of Hospitals</agency>
      <agency_class>Other</agency_class>
    </collaborator>
    <collaborator>
      <agency>Maulana Azad Medical College and Lok Nayak Hospital</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Karolinska Institutet</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Audit filters for monitoring trauma care quality are regarded as one of the most essential&#xD;
      components of trauma quality improvement programmes; however, there is a paucity of evidence&#xD;
      that shows that audit filters are associated with improved outcomes. Therefore, our aim is to&#xD;
      assess if institutional implementation of audit filters reduce mortality in adult trauma&#xD;
      patients.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Survey of the field&#xD;
&#xD;
      Trauma, defined as the clinical entity composed of physical injury and the body's associated&#xD;
      response, kills almost five million people each year. This is more than the total number of&#xD;
      annual deaths from malaria, tuberculosis, HIV/AIDS, and maternal conditions combined. More&#xD;
      than 90% of trauma deaths occur in low and middle income countries (LMIC), and about 30-50%&#xD;
      of these deaths have been reported to occur in hospital. Research show that almost 11% of the&#xD;
      global burden of disease estimated using disability adjusted life years are due to trauma,&#xD;
      and that disability adjusted life years from road traffic trauma has increased by 35% in the&#xD;
      last 25 years.&#xD;
&#xD;
      The United Nation now vows to reduce the number of road traffic deaths by 50% by 2020.&#xD;
      Although primary prevention will play a major role in achieving this, several international&#xD;
      actors, including the World Health Organization (WHO), emphasise the importance of&#xD;
      strengthened trauma care. A considerable body of research on the strengthening of trauma care&#xD;
      attributes improvements in trauma patient outcomes to the implementation of quality&#xD;
      improvement programmes, defined as programmes to improve &quot;health care through monitoring the&#xD;
      process of care and measuring outcomes&quot;.&#xD;
&#xD;
      For example, a recent single centre study from Australia showed a reduction in in-hospital&#xD;
      mortality from 16 to 10% after the implementation of a quality improvement programme. This&#xD;
      programme included interventions such as a protocol for trauma team activation, massive&#xD;
      transfusion protocols, case reviews and the recording and follow up audit filters. Similarly,&#xD;
      research from Thailand and Pakistan show reduced mortality after the implementation of such&#xD;
      programmes. Unfortunately the heterogeneity of interventions included in most quality&#xD;
      improvement programmes makes it hard to draw conclusions about the impact of individual&#xD;
      components.&#xD;
&#xD;
      Despite this heterogeneity, audit filters constitute a common denominator across different&#xD;
      quality improvement programmes. Such filters can be defined as &quot;pre-identified variables that&#xD;
      are routinely tracked to identify whether accepted standards of care are being met&quot;. Hence,&#xD;
      audit filters are also referred to as quality indicators or key performance indicators. The&#xD;
      concept of audit filters in trauma care originates from the American College of Surgeons&#xD;
      guidelines on trauma care . They defined 22 filters and the basic idea was that each filter&#xD;
      should represent a &quot;sentinel event&quot; associated with poor patient outcome.&#xD;
&#xD;
      In theory, audit filters may catalyse improvements in care and therefore the use of such&#xD;
      filters is now widespread in trauma care organisations. Research on the impact of&#xD;
      implementing audit filters on patient outcomes is however scarce. One widely cited study from&#xD;
      Thailand demonstrated a reduction in preventable mortality after the revision of audit&#xD;
      filters; however, this study was not deemed to be of high enough quality to merit inclusion&#xD;
      in the only Cochrane review conducted on the subject. In fact, the authors of that review&#xD;
      were not able to identify a single study of high enough quality.&#xD;
&#xD;
      The push to include audit filters in efforts to strengthen trauma care is strong, despite the&#xD;
      remarkable lack of evidence that such filters improve patient outcomes. The WHO even includes&#xD;
      audit filters as a core technique in their guidelines for trauma quality improvement&#xD;
      programmes . Considering the often extremely limited resources in the contexts of their&#xD;
      intended audience, primarily decision and policy makers in LMIC, it is crucial that the&#xD;
      recommendations of potentially costly interventions are evidence based. Therefore, the&#xD;
      research question is, does institutional implementation of audit filters reduce mortality in&#xD;
      adult trauma patients?&#xD;
&#xD;
      Hypothesis&#xD;
&#xD;
      The implementation of audit filters will lead to: 1) identification of potentially&#xD;
      correctable deficiencies; 2) subsequent correction of identified deficiencies; and 3)&#xD;
      ultimate improved clinical care and reduced mortality.&#xD;
&#xD;
      Study design&#xD;
&#xD;
      A controlled interrupted time series trial. This design is generally considered to be the&#xD;
      strongest quasi experimental design when a randomised controlled trial is not feasible. In&#xD;
      brief, the trial will be composed of three phases. First there will be an observation phase&#xD;
      spanning one year, during which outcome baselines will be established. Then there will be an&#xD;
      implementation phase during which locally relevant and appropriate audit filters will be&#xD;
      developed and implemented and an audit filter review board will be elected. This phase will&#xD;
      be six months. Finally, there will be an intervention phase for two years when the audit&#xD;
      filters will be reviewed at monthly meetings.&#xD;
&#xD;
      Setting&#xD;
&#xD;
      This trial will be conducted in four university hospitals in India. There are several reasons&#xD;
      why India will be used as a model. First, India accounts for 20-25% of all trauma mortality&#xD;
      globally and efforts to strengthen trauma care in the country are urgently needed. The&#xD;
      results of this trial will thus be highly relevant to its participants as well as the&#xD;
      community at the large. Second, none of the centres that will participate use audit filters&#xD;
      today. Hence, the time of implementation will be precisely controlled and thereby one source&#xD;
      of bias will be substantially reduced. All four centres are public university hospitals with&#xD;
      demonstrated research capacity. Each centre has approximately 1500 beds and all clinical&#xD;
      specialities relevant for trauma care available in house. The trial will start in 2017 and&#xD;
      continue for four years after ethical approval from participating centres.&#xD;
&#xD;
      Source and method of participant selection&#xD;
&#xD;
      One project officer at each centre will be employed to enrol participants and collect data.&#xD;
      The project officer will be posted in the emergency department and enrol consecutive patients&#xD;
      that fit the eligibility criteria. She or he will work day, evening, and night duties&#xD;
      according to a rotating random schedule so that all possible shifts are covered during the&#xD;
      course of each month. Each shift will be eight hours, out of which the project officer will&#xD;
      spend six in the emergency department and two conducting follow up of admitted and discharged&#xD;
      patients. The project officer will work five shifts per week. The aim of this model for&#xD;
      participant selection and data collection is to enrol a representative sample of each&#xD;
      centre's population of eligible participants, maximising data quality by having the project&#xD;
      officers record outcomes and covariates, while at the same time minimising data collection&#xD;
      costs and potential observer bias.&#xD;
&#xD;
      Study setup&#xD;
&#xD;
      As alluded to previously, the trial will have three distinct phases:&#xD;
&#xD;
      observation, implementation, and intervention.&#xD;
&#xD;
      Observation phase The observation phase will be used to establish a baseline for primary&#xD;
      outcome and secondary outcome. The data collection procedures outlined in section &quot;Source and&#xD;
      method of participant selection&quot; will be applied in all four centres.&#xD;
&#xD;
      Implementation phase (Month 12-18)&#xD;
&#xD;
      Two centres will randomly be chosen as control centres and the remaining two will be chosen&#xD;
      as intervention centres. Data collection continues as during the observation phase in both&#xD;
      groups.&#xD;
&#xD;
      Control centres: No change compared to the observation phase.&#xD;
&#xD;
      Intervention centres: The goal of the implementation phase in the intervention centres will&#xD;
      be to develop and implement locally relevant and appropriate audit filers, as well as a&#xD;
      system to identify and implement solutions to identified deficiencies. To achieve this goal a&#xD;
      participatory and multidisciplinary approach will be used. First a meeting and two day course&#xD;
      will be hosted at each intervention centre to present the background and rationale for using&#xD;
      audit filters to improve trauma care. Representation by all disciplines and specialities&#xD;
      involved in trauma care, including clinical specialities, nursing, rehabilitation and&#xD;
      administration will be strived for.&#xD;
&#xD;
      The two day course on trauma quality improvement processes (TQIP) including audit filters&#xD;
      will include the following objectives: 1) Gaining an understanding of TQIP and a familiarity&#xD;
      with the evidence supporting it; 2) Gaining an understanding of implementation options for&#xD;
      different clinical contexts; 3) Gaining an understanding of the application of audit filters&#xD;
      in TQIP; 4) Training on the implementation of targeted corrective action plans; 5)&#xD;
      Explanation of the utility of ongoing data collection to evaluate interventions (&quot;closing the&#xD;
      loop&quot;). This course will provide an overview of techniques used for hospital-based TQIP,&#xD;
      focusing on the concepts of audit filter application, and processes of flagged event review.&#xD;
&#xD;
      After the course participants on professor, associate professor, and assistant professor&#xD;
      level, i.e. 10-15 people, will be invited to take part in an anonymous online Delphi survey.&#xD;
      The Delphi approach means that the survey will be delivered in multiple rounds, and that&#xD;
      participants receive feedback on the previous round's results before a new round is&#xD;
      initiated. In each round the participants will be provided with a set of audit filters and&#xD;
      will be asked to rate each filter on a scale from 1 to 10 (where 1 represent useless and 10&#xD;
      very useful), provide written comments on suggested filters, and finally suggest new audit&#xD;
      filters, and provide a written rationale for each.&#xD;
&#xD;
      In the first round participants will be provided with a set of audit filters used in other&#xD;
      contexts. All audit filters that get a median rank of ≥7 as well as all filters provided by&#xD;
      participants will be included in subsequent rounds. The Delphi survey will be terminated when&#xD;
      either consensus or stability of group responses is reached. Consensus is defined as the&#xD;
      situation when all included audit filters have a median rank of ≥9. Stability is defined as&#xD;
      the situation when no significant change in audit filter ranks occurs between two rounds. If&#xD;
      stability is reached then all audit filters with a median rank of ≥9, or the five audit&#xD;
      filters with the highest ranks, will be implemented.&#xD;
&#xD;
      The results of the Delphi survey will be presented in each intervention centre at a second&#xD;
      meeting. This first post-survey meeting will only host the survey participants. After this&#xD;
      meeting each centre will be asked to elect an audit filter review board. This board will&#xD;
      review audit filter data, identify potentially correctable deficiencies and solutions. The&#xD;
      board will also have the mandate to implement potential these solutions. Once an audit filter&#xD;
      review board has been elected it will inform the relevant staff cadres of the audit filter&#xD;
      implementation and review mechanisms.&#xD;
&#xD;
      The audit filters will then be implemented. Data on audit filters will be collected and&#xD;
      collated by a second project officer, employed by us, in each of the intervention centres.&#xD;
      Project management will participate in the three first audit filter review meetings. At these&#xD;
      meetings each flag will be assessed by reviewing the patient's record. The plan, do, study,&#xD;
      act (PDSA) cycle typically employed to implement and evaluate interventions to improve&#xD;
      processes of care will be taught.&#xD;
&#xD;
      Intervention phase (Month 18-42)&#xD;
&#xD;
      Control centres: No change compared to the observation and implementation phase.&#xD;
&#xD;
      Intervention centres: The audit filter review board will conduct monthly review meetings.&#xD;
      Project management will not participate in these meetings. The audit filter review board will&#xD;
      be free to add or remove audit filters and implement and evaluate interventions as they&#xD;
      choose. The meetings will be documented in standardised protocols.&#xD;
&#xD;
      Covariates&#xD;
&#xD;
      Throughout the trial data on the following covariates will be collected to allow describing&#xD;
      participants as well as adjust analyses for potential differences in case mix between centres&#xD;
      and over time:&#xD;
&#xD;
        -  Age in years. Recorded by project officers.&#xD;
&#xD;
        -  Sex, coded as male or female. Recorded by project officers.&#xD;
&#xD;
        -  Systolic blood pressure. Recorded by project officers using dedicated equipment.&#xD;
&#xD;
        -  Diastolic blood pressure. Recorded by project officers using dedicated equipment.&#xD;
&#xD;
        -  Heart rate. Recorded by project officers using dedicated equipment.&#xD;
&#xD;
        -  Blood oxygen saturation. Recorded by project officers using dedicated equipment.&#xD;
&#xD;
        -  Respiratory rate. Recorded by project officers by manual counting during one minute.&#xD;
&#xD;
        -  Level of consciousness using the Glasgow coma scale and Alert, Voice, Pain or&#xD;
           Unresponsive scale (AVPU). Recorded by project officers.&#xD;
&#xD;
        -  Mechanism of injury according to chapter XX of ICD-10. Recorded by project officers.&#xD;
&#xD;
        -  Injuries sustained, extracted from patient records by project officers to enable&#xD;
           anatomical injury severity scoring using the injury severity score (ISS).&#xD;
&#xD;
        -  Transferred from another health facility. Recorded by project officer by asking&#xD;
           participant or participant's relative.&#xD;
&#xD;
        -  Mode of transport. Recorded by project officer by asking participant or participant's&#xD;
           relative.&#xD;
&#xD;
        -  Date and time of injury, to calculate delay between injury and presentation to&#xD;
           participating centre. Recorded by project officer by asking participant or participant's&#xD;
           relative.&#xD;
&#xD;
        -  Date and time of computed tomography investigation. Recorded by project officer from the&#xD;
           participant's hospital record or by direct observation.&#xD;
&#xD;
        -  Date of ultrasonography investigation. Recorded by project officer from the&#xD;
           participant's hospital record or by direct observation.&#xD;
&#xD;
        -  Date when mechanical ventilation was started and stopped. Recorded by project officer&#xD;
           from the participant's hospital record or by direct observation.&#xD;
&#xD;
        -  Date, time and type of surgery, defined as any surgical intervention performed under&#xD;
           general or regional anesthesia. Recorded by project officers from the participant's&#xD;
           hospital record or by direct observation.&#xD;
&#xD;
      Statistical methods and analyses&#xD;
&#xD;
      A segmented general additive model (GAM) will be used to assess the impact of institutional&#xD;
      implementation of audit filters on outcomes. The GAM approach will allow accommodation of&#xD;
      potential nonlinearity in intervention effect while adjusting for autocorrelation,&#xD;
      seasonality and case mix differences. Data from intervention and control centres will be&#xD;
      pooled separately. Each observation will represent averaged data for all patients enrolled&#xD;
      during one month instead of data for an individual patient.&#xD;
&#xD;
      A second analysis will be conducted using patient level data. In both analyses the primary&#xD;
      interest is detecting a change in trend between the observation and intervention phases, as&#xD;
      well as between control and intervention centres, for each of the outcomes. Furthermore,&#xD;
      estimation of intervention effect on both mortality and quality of life will be possible by&#xD;
      calculating the difference between predicted outcomes assuming no intervention effect and the&#xD;
      observed outcomes with intervention. R will be used for statistical analyses, adopting a 95%&#xD;
      confidence level and 5% significance level. The Holm procedure will be used to adjust for&#xD;
      multiple tests.&#xD;
&#xD;
      Subgroup analyses&#xD;
&#xD;
        -  Patients with major trauma, defined as any patient who is admitted for more than three&#xD;
           days with an ISS of &gt;15, or who dies within three days of admission, or who dies between&#xD;
           arrival and admission.&#xD;
&#xD;
        -  Patients with life-threatening, but potentially salvageable trauma, defined as any&#xD;
           patient with 15&lt;ISS&lt;24.&#xD;
&#xD;
      Sensitivity analyses&#xD;
&#xD;
        -  Exclusion of the implementation phase from the analysis model.&#xD;
&#xD;
        -  Data will be pooled for the observation and intervention phase and analysed using a&#xD;
           pre-post design.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Enrolling by invitation</overall_status>
  <start_date type="Actual">October 16, 2017</start_date>
  <completion_date type="Anticipated">December 2023</completion_date>
  <primary_completion_date type="Anticipated">December 2023</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Health Services Research</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>All cause mortality within 30 days of arrival to participating hospital.</measure>
    <time_frame>30 days</time_frame>
    <description>This outcome will be extracted by the project officer from the patient's record as date and time of death or discharge. If the patient is discharged alive before 30 days of arrival the project officer will call the patient or patient relative 30 days after arrival to hospital to establish the patient's status.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>All cause in-hospital mortality</measure>
    <time_frame>From arrival to emergency department to discharge from hospital, assessed up to 42 months</time_frame>
    <description>This outcome will be extracted by the project officer from the patient's record as date and time of death or discharge.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>All cause mortality within 24 hours of arrival to participating hospital.</measure>
    <time_frame>24 hours</time_frame>
    <description>This outcome will be extracted by the project officer from the patient's record as date and time of death or discharge. If the patient is discharged alive before 24 hours of arrival the project officer will call the patient or patient relative 24 hours after arrival to hospital to establish the patient's status.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>All cause mortality within 90 days of arrival to participating hospital.</measure>
    <time_frame>90 days</time_frame>
    <description>This outcome will be extracted by the project officer from the patient's record as date and time of death or discharge. If the patient is discharged alive before 90 days of arrival the project officer will call the patient or patient relative 90 days after arrival to hospital to establish the patient's status.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Quality of life measured using validated translations of the EQ-5D-3L instrument</measure>
    <time_frame>90 days</time_frame>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Number of hospital free days to day 30</measure>
    <time_frame>30 days</time_frame>
    <description>Defined as 30 days minus the number of days between arrival to discharge. Date of arrival is observed by the project officer and date of discharge or death is extracted from the patient record. A participant who dies will be assigned 0 as number of hospital free days.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Number of intensive care unit (ICU) free days to day 30</measure>
    <time_frame>30 days</time_frame>
    <description>Defined as 30 days minus the number of days a participant is admitted to an ICU, measured in days from date of ICU admission to date of ICU discharge. Both dates are extracted by the project officer from the patient record. A participant who dies will be assigned 0 as number of ICU free days.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Number of items adhered to in the WHO trauma care checklist</measure>
    <time_frame>At the time the participant arrives to emergency department, assessed up to six hours</time_frame>
    <description>Recorded by project officers by direct observation</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Anticipated">8400</enrollment>
  <condition>Trauma</condition>
  <arm_group>
    <arm_group_label>Intervention</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Audit filter implementation in hospital</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Control</arm_group_label>
    <arm_group_type>No Intervention</arm_group_type>
    <description>Routine care</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Audit filters</intervention_name>
    <description>Institutional implementation of audit filters</description>
    <arm_group_label>Intervention</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Admitted to participating centres with history of trauma. History of trauma is here&#xD;
             defined as having any of the external causes of morbidity and mortality listed in&#xD;
             block V01-Y36, chapter XX of the International Classification of Disease version 10&#xD;
             (ICD-10) codebook as reason for admission.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <location>
    <facility>
      <name>St John's Medical College Hospital</name>
      <address>
        <city>Bengaluru</city>
        <country>India</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Maulana Azad Medical College and Lok Nayak Hospital</name>
      <address>
        <city>Delhi</city>
        <country>India</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Institute of Post-Graduate Medical Education and Research and Seth Sukhlal Karnani Memorial Hospital</name>
      <address>
        <city>Kolkata</city>
        <country>India</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Institute is Grant Government Medical College &amp; Sir J J Group of Hospitals</name>
      <address>
        <city>Mumbai</city>
        <country>India</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>India</country>
  </location_countries>
  <verification_date>September 2021</verification_date>
  <study_first_submitted>July 25, 2017</study_first_submitted>
  <study_first_submitted_qc>July 28, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">August 1, 2017</study_first_posted>
  <last_update_submitted>September 1, 2021</last_update_submitted>
  <last_update_submitted_qc>September 1, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">September 2, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Karolinska Institutet</investigator_affiliation>
    <investigator_full_name>Martin Gerdin</investigator_full_name>
    <investigator_title>Researcher</investigator_title>
  </responsible_party>
  <keyword>Trauma</keyword>
  <keyword>Injury</keyword>
  <keyword>Audit filter</keyword>
  <keyword>Quality improvement</keyword>
  <keyword>India</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Wounds and Injuries</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>The collated data will be de-identified adhering to recognised standards, e.g. applicable parts of the Safe Harbor standard defined in the US Health Insurance Portability and Accountability Act. The de-identified data, from which it will not be reasonable possible to identify individual hospitals or patients, will be uploaded to a public data repository to be used by other researchers. Further, such use will be preceded by the signing of a data sharing agreement, which will include the prohibition of any attempts at re-identification of centres or patients.</ipd_description>
    <ipd_info_type>Study Protocol</ipd_info_type>
    <ipd_access_criteria>Signing of data sharing agreement</ipd_access_criteria>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03235388
org study id: 4-1982/2017
nct id: NCT03235388
lead sponsor: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
collaborator: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Audit filters for monitoring trauma care quality are regarded as one of the most essential
      components of trauma quality improvement programmes; however, there is a paucity of evidence
      that shows that audit filters are associated with improved outcomes. Therefore, our aim is to
      assess if institutional implementation of audit filters reduce mortality in adult trauma
      patients.
Survey of the field

      Trauma, defined as the clinical entity composed of physical injury and the body's associated
      response, kills almost five million people each year. This is more than the total number of
      annual deaths from malaria, tuberculosis, HIV/AIDS, and maternal conditions combined. More
      than 90% of trauma deaths occur in low and middle income countries (LMIC), and about 30-50%
      of these deaths have been reported to occur in hospital. Research show that almost 11% of the
      global burden of disease estimated using disability adjusted life years are due to trauma,
      and that disability adjusted life years from road traffic trauma has increased by 35% in the
      last 25 years.

      The United Nation now vows to reduce the number of road traffic deaths by 50% by 2020.
      Although primary prevention will play a major role in achieving this, several international
      actors, including the World Health Organization (WHO), emphasise the importance of
      strengthened trauma care. A considerable body of research on the strengthening of trauma care
      attributes improvements in trauma patient outcomes to the implementation of quality
      improvement programmes, defined as programmes to improve "health care through monitoring the
      process of care and measuring outcomes".

      For example, a recent single centre study from Australia showed a reduction in in-hospital
      mortality from 16 to 10% after the implementation of a quality improvement programme. This
      programme included interventions such as a protocol for trauma team activation, massive
      transfusion protocols, case reviews and the recording and follow up audit filters. Similarly,
      research from Thailand and Pakistan show reduced mortality after the implementation of such
      programmes. Unfortunately the heterogeneity of interventions included in most quality
      improvement programmes makes it hard to draw conclusions about the impact of individual
      components.

      Despite this heterogeneity, audit filters constitute a common denominator across different
      quality improvement programmes. Such filters can be defined as "pre-identified variables that
      are routinely tracked to identify whether accepted standards of care are being met". Hence,
      audit filters are also referred to as quality indicators or key performance indicators. The
      concept of audit filters in trauma care originates from the American College of Surgeons
      guidelines on trauma care . They defined 22 filters and the basic idea was that each filter
      should represent a "sentinel event" associated with poor patient outcome.

      In theory, audit filters may catalyse improvements in care and therefore the use of such
      filters is now widespread in trauma care organisations. Research on the impact of
      implementing audit filters on patient outcomes is however scarce. One widely cited study from
      Thailand demonstrated a reduction in preventable mortality after the revision of audit
      filters; however, this study was not deemed to be of high enough quality to merit inclusion
      in the only Cochrane review conducted on the subject. In fact, the authors of that review
      were not able to identify a single study of high enough quality.

      The push to include audit filters in efforts to strengthen trauma care is strong, despite the
      remarkable lack of evidence that such filters improve patient outcomes. The WHO even includes
      audit filters as a core technique in their guidelines for trauma quality improvement
      programmes . Considering the often extremely limited resources in the contexts of their
      intended audience, primarily decision and policy makers in LMIC, it is crucial that the
      recommendations of potentially costly interventions are evidence based. Therefore, the
      research question is, does institutional implementation of audit filters reduce mortality in
      adult trauma patients?

      Hypothesis

      The implementation of audit filters will lead to: 1) identification of potentially
      correctable deficiencies; 2) subsequent correction of identified deficiencies; and 3)
      ultimate improved clinical care and reduced mortality.

      Study design

      A controlled interrupted time series trial. This design is generally considered to be the
      strongest quasi experimental design when a randomised controlled trial is not feasible. In
      brief, the trial will be composed of three phases. First there will be an observation phase
      spanning one year, during which outcome baselines will be established. Then there will be an
      implementation phase during which locally relevant and appropriate audit filters will be
      developed and implemented and an audit filter review board will be elected. This phase will
      be six months. Finally, there will be an intervention phase for two years when the audit
      filters will be reviewed at monthly meetings.

      Setting

      This trial will be conducted in four university hospitals in India. There are several reasons
      why India will be used as a model. First, India accounts for 20-25% of all trauma mortality
      globally and efforts to strengthen trauma care in the country are urgently needed. The
      results of this trial will thus be highly relevant to its participants as well as the
      community at the large. Second, none of the centres that will participate use audit filters
      today. Hence, the time of implementation will be precisely controlled and thereby one source
      of bias will be substantially reduced. All four centres are public university hospitals with
      demonstrated research capacity. Each centre has approximately 1500 beds and all clinical
      specialities relevant for trauma care available in house. The trial will start in 2017 and
      continue for four years after ethical approval from participating centres.

      Source and method of participant selection

      One project officer at each centre will be employed to enrol participants and collect data.
      The project officer will be posted in the emergency department and enrol consecutive patients
      that fit the eligibility criteria. She or he will work day, evening, and night duties
      according to a rotating random schedule so that all possible shifts are covered during the
      course of each month. Each shift will be eight hours, out of which the project officer will
      spend six in the emergency department and two conducting follow up of admitted and discharged
      patients. The project officer will work five shifts per week. The aim of this model for
      participant selection and data collection is to enrol a representative sample of each
      centre's population of eligible participants, maximising data quality by having the project
      officers record outcomes and covariates, while at the same time minimising data collection
      costs and potential observer bias.

      Study setup

      As alluded to previously, the trial will have three distinct phases:

      observation, implementation, and intervention.

      Observation phase The observation phase will be used to establish a baseline for primary
      outcome and secondary outcome. The data collection procedures outlined in section "Source and
      method of participant selection" will be applied in all four centres.

      Implementation phase (Month 12-18)

      Two centres will randomly be chosen as control centres and the remaining two will be chosen
      as intervention centres. Data collection continues as during the observation phase in both
      groups.

      Control centres: No change compared to the observation phase.

      Intervention centres: The goal of the implementation phase in the intervention centres will
      be to develop and implement locally relevant and appropriate audit filers, as well as a
      system to identify and implement solutions to identified deficiencies. To achieve this goal a
      participatory and multidisciplinary approach will be used. First a meeting and two day course
      will be hosted at each intervention centre to present the background and rationale for using
      audit filters to improve trauma care. Representation by all disciplines and specialities
      involved in trauma care, including clinical specialities, nursing, rehabilitation and
      administration will be strived for.

      The two day course on trauma quality improvement processes (TQIP) including audit filters
      will include the following objectives: 1) Gaining an understanding of TQIP and a familiarity
      with the evidence supporting it; 2) Gaining an understanding of implementation options for
      different clinical contexts; 3) Gaining an understanding of the application of audit filters
      in TQIP; 4) Training on the implementation of targeted corrective action plans; 5)
      Explanation of the utility of ongoing data collection to evaluate interventions ("closing the
      loop"). This course will provide an overview of techniques used for hospital-based TQIP,
      focusing on the concepts of audit filter application, and processes of flagged event review.

      After the course participants on professor, associate professor, and assistant professor
      level, i.e. 10-15 people, will be invited to take part in an anonymous online Delphi survey.
      The Delphi approach means that the survey will be delivered in multiple rounds, and that
      participants receive feedback on the previous round's results before a new round is
      initiated. In each round the participants will be provided with a set of audit filters and
      will be asked to rate each filter on a scale from 1 to 10 (where 1 represent useless and 10
      very useful), provide written comments on suggested filters, and finally suggest new audit
      filters, and provide a written rationale for each.

      In the first round participants will be provided with a set of audit filters used in other
      contexts. All audit filters that get a median rank of ≥7 as well as all filters provided by
      participants will be included in subsequent rounds. The Delphi survey will be terminated when
      either consensus or stability of group responses is reached. Consensus is defined as the
      situation when all included audit filters have a median rank of ≥9. Stability is defined as
      the situation when no significant change in audit filter ranks occurs between two rounds. If
      stability is reached then all audit filters with a median rank of ≥9, or the five audit
      filters with the highest ranks, will be implemented.

      The results of the Delphi survey will be presented in each intervention centre at a second
      meeting. This first post-survey meeting will only host the survey participants. After this
      meeting each centre will be asked to elect an audit filter review board. This board will
      review audit filter data, identify potentially correctable deficiencies and solutions. The
      board will also have the mandate to implement potential these solutions. Once an audit filter
      review board has been elected it will inform the relevant staff cadres of the audit filter
      implementation and review mechanisms.

      The audit filters will then be implemented. Data on audit filters will be collected and
      collated by a second project officer, employed by us, in each of the intervention centres.
      Project management will participate in the three first audit filter review meetings. At these
      meetings each flag will be assessed by reviewing the patient's record. The plan, do, study,
      act (PDSA) cycle typically employed to implement and evaluate interventions to improve
      processes of care will be taught.

      Intervention phase (Month 18-42)

      Control centres: No change compared to the observation and implementation phase.

      Intervention centres: The audit filter review board will conduct monthly review meetings.
      Project management will not participate in these meetings. The audit filter review board will
      be free to add or remove audit filters and implement and evaluate interventions as they
      choose. The meetings will be documented in standardised protocols.

      Covariates

      Throughout the trial data on the following covariates will be collected to allow describing
      participants as well as adjust analyses for potential differences in case mix between centres
      and over time:

        -  Age in years. Recorded by project officers.

        -  Sex, coded as male or female. Recorded by project officers.

        -  Systolic blood pressure. Recorded by project officers using dedicated equipment.

        -  Diastolic blood pressure. Recorded by project officers using dedicated equipment.

        -  Heart rate. Recorded by project officers using dedicated equipment.

        -  Blood oxygen saturation. Recorded by project officers using dedicated equipment.

        -  Respiratory rate. Recorded by project officers by manual counting during one minute.

        -  Level of consciousness using the Glasgow coma scale and Alert, Voice, Pain or
           Unresponsive scale (AVPU). Recorded by project officers.

        -  Mechanism of injury according to chapter XX of ICD-10. Recorded by project officers.

        -  Injuries sustained, extracted from patient records by project officers to enable
           anatomical injury severity scoring using the injury severity score (ISS).

        -  Transferred from another health facility. Recorded by project officer by asking
           participant or participant's relative.

        -  Mode of transport. Recorded by project officer by asking participant or participant's
           relative.

        -  Date and time of injury, to calculate delay between injury and presentation to
           participating centre. Recorded by project officer by asking participant or participant's
           relative.

        -  Date and time of computed tomography investigation. Recorded by project officer from the
           participant's hospital record or by direct observation.

        -  Date of ultrasonography investigation. Recorded by project officer from the
           participant's hospital record or by direct observation.

        -  Date when mechanical ventilation was started and stopped. Recorded by project officer
           from the participant's hospital record or by direct observation.

        -  Date, time and type of surgery, defined as any surgical intervention performed under
           general or regional anesthesia. Recorded by project officers from the participant's
           hospital record or by direct observation.

      Statistical methods and analyses

      A segmented general additive model (GAM) will be used to assess the impact of institutional
      implementation of audit filters on outcomes. The GAM approach will allow accommodation of
      potential nonlinearity in intervention effect while adjusting for autocorrelation,
      seasonality and case mix differences. Data from intervention and control centres will be
      pooled separately. Each observation will represent averaged data for all patients enrolled
      during one month instead of data for an individual patient.

      A second analysis will be conducted using patient level data. In both analyses the primary
      interest is detecting a change in trend between the observation and intervention phases, as
      well as between control and intervention centres, for each of the outcomes. Furthermore,
      estimation of intervention effect on both mortality and quality of life will be possible by
      calculating the difference between predicted outcomes assuming no intervention effect and the
      observed outcomes with intervention. R will be used for statistical analyses, adopting a 95%
      confidence level and 5% significance level. The Holm procedure will be used to adjust for
      multiple tests.

      Subgroup analyses

        -  Patients with major trauma, defined as any patient who is admitted for more than three
           days with an ISS of >15, or who dies within three days of admission, or who dies between
           arrival and admission.

        -  Patients with life-threatening, but potentially salvageable trauma, defined as any
           patient with 15<ISS<24.

      Sensitivity analyses

        -  Exclusion of the implementation phase from the analysis model.

        -  Data will be pooled for the observation and intervention phase and analysed using a
           pre-post design.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Health Services Research
masking: None (Open Label)
measure: All cause mortality within 30 days of arrival to participating hospital.
time frame: 30 days
description: This outcome will be extracted by the project officer from the patient's record as date and time of death or discharge. If the patient is discharged alive before 30 days of arrival the project officer will call the patient or patient relative 30 days after arrival to hospital to establish the patient's status.
measure: All cause in-hospital mortality
time frame: From arrival to emergency department to discharge from hospital, assessed up to 42 months
description: This outcome will be extracted by the project officer from the patient's record as date and time of death or discharge.
measure: All cause mortality within 24 hours of arrival to participating hospital.
time frame: 24 hours
description: This outcome will be extracted by the project officer from the patient's record as date and time of death or discharge. If the patient is discharged alive before 24 hours of arrival the project officer will call the patient or patient relative 24 hours after arrival to hospital to establish the patient's status.
measure: All cause mortality within 90 days of arrival to participating hospital.
time frame: 90 days
description: This outcome will be extracted by the project officer from the patient's record as date and time of death or discharge. If the patient is discharged alive before 90 days of arrival the project officer will call the patient or patient relative 90 days after arrival to hospital to establish the patient's status.
measure: Quality of life measured using validated translations of the EQ-5D-3L instrument
time frame: 90 days
measure: Number of hospital free days to day 30
time frame: 30 days
description: Defined as 30 days minus the number of days between arrival to discharge. Date of arrival is observed by the project officer and date of discharge or death is extracted from the patient record. A participant who dies will be assigned 0 as number of hospital free days.
measure: Number of intensive care unit (ICU) free days to day 30
time frame: 30 days
description: Defined as 30 days minus the number of days a participant is admitted to an ICU, measured in days from date of ICU admission to date of ICU discharge. Both dates are extracted by the project officer from the patient record. A participant who dies will be assigned 0 as number of ICU free days.
measure: Number of items adhered to in the WHO trauma care checklist
time frame: At the time the participant arrives to emergency department, assessed up to six hours
description: Recorded by project officers by direct observation
arm group label: Intervention
arm group type: Experimental
description: Audit filter implementation in hospital
arm group label: Control
arm group type: No Intervention
description: Routine care
intervention type: Other
intervention name: Audit filters
description: Institutional implementation of audit filters
arm group label: Intervention
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
facility: 
facility: 
facility: 
facility: 
country: India
responsible party type: Principal Investigator
investigator affiliation: Karolinska Institutet
investigator full name: Martin Gerdin
investigator title: Researcher
mesh term: Wounds and Injuries
sharing ipd: Yes
ipd description: The collated data will be de-identified adhering to recognised standards, e.g. applicable parts of the Safe Harbor standard defined in the US Health Insurance Portability and Accountability Act. The de-identified data, from which it will not be reasonable possible to identify individual hospitals or patients, will be uploaded to a public data repository to be used by other researchers. Further, such use will be preceded by the signing of a data sharing agreement, which will include the prohibition of any attempts at re-identification of centres or patients.
ipd info type: Study Protocol
ipd access criteria: Signing of data sharing agreement