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Emergency Medical ServicesAHRTEMISNCT06666647

Response Times in Danish Emergency Medical Services

An observational study of Emergency Medical Services and Response, run by Peter Martin Hansen at 1 site in Denmark.

Active, not recruiting

Under way, not looking for participants. Everyone needed has enrolled. The study is still running.

Official record
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Trial summary

The overall aim of this retrospective observational study is to investigate the association of emergency medical services response time with patient survival and treatment outcomes. Read more about this study

Who is it for?
Any age
Conditions the study is for
Emergency Medical Services, Response, Triage
What is being tested?
Treatment by ambulance or helicopter services with response times
Type of treatment
Surgery or procedure
How many people
2,500,000 participants
Where
1 siteDenmark
Study dates
1 May 2025to 31 Dec 2026
Phase
Observational
Are there results?
Not yet: the study is under way

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages Any age
  • All sexes
  • No healthy volunteers
  • Child, Adult, Older adult

Study population: Every patient in Denmark in need of ambulance and/or helicopter services treatment from 2016 to 2022 with one year follow-up

Who may be able to join

  • Every patient in Denmark in need of ambulance and/or helicopter services treatment in Denmark from 2016-2022 with outgoing response mode A (with lights and sirens) and B (without lights and sirens) is eligible for inclusion in the study.

Who cannot join

  • No civil personal registration number available
  • Patient not identified
  • Patient not entered in the prehospital electronic patient journal
  • invalid data entered
  • No linkage between substitue personal register number and actual personal register number for patients identified later;

Trial locations and contacts

1 site in 1 country.

Denmark1 site
  • Odense University Hospital

    Odense, 5000

Other trials in Denmark

About this study

Official title: Ambulance and Helicopter Response Times in Danish Emergency Medical Services: Protocol for an Epidemiological Study. The AHRTEMIS Study

The overall aim of this retrospective observational study is to investigate the association of emergency medical services response time with patient survival and treatment outcomes.

The main question it aims to answer is:

What is the association between response time and patient survival?

The investigators will collect data for all patients who were treated by ambulance and/or helicopter services in Denmark and follow the patient's path from illness or injury to discharge from hospital with a focus on the significance of ambulance and helicopter response time.

Read the detailed description

INTRODUCTION Background and rationale Response time, defined as the time from dispatch to arrival of the vehicle at the patient´s address for emergency medical services (EMS) units, may be essential in critical situations such as e.g., cardiac arrest and serious injury. Apart from these conditions, there is currently only limited or even contradictory evidence to support that a short response time is associated with improved patient survival and other treatment parameters. There are other significant factors that affect mortality in the acute phase, such as competence on prehospital care provider level, emergency department patient load and staffing shortages, that have been shown to affect mortality. Confounders such as bidirectional causality and confounding by indication may hinder scientific interpretation of response time importance and significance for patient outcomes in observational studies.

Importance of the study The results of the research project may contribute to establishing a scientific background for when response time matters for the patient and when it does not matter. Thereby, the investigators expect that the results can enable an evidence-based differentiation of ambulance response and degree of urgency and purvey the use of alternate key performance indicators and benchmarking in EMS systems.

Aims of the study This project aims to increase the knowledge about the possible association between response time and survival and treatment outcomes.

The overall aim is to investigate the association of response time with treatment outcomes, including patient survival.

Research questions in the study

  1. Is there an association between ambulance/helicopter response time and patient survival?
  2. Is there an association between ambulance/helicopter response time and intensive care treatment characteristics?

METHODS Ethics committee and other approvals required Approvals for the study were obtained from the Regional Secretariat and Legal Matters, Region Southern Denmark, Journal no. 23/30574 and from the Executive Secretariat, Odense University Hospital, Journal number 23/31007. From the Danish Clinical Quality Program - National Clinical Registries, the investigators obtained permissions as well (DAH-2024-02-16 and DID-2024-02-16). The investigators will store data in accordance with current Danish Data Protection Agency regulations via a license agreement with OPEN, Odense Patient data Exploratory Network.

Patient consent According to the Act on Processing of Personal Data, register-based studies approved by the Danish Patient Safety Authorities do not require consent to use data already entered into the registry.

Setting Danish EMS is free of charge for everyone. It is a three-tiered system, comprising emergency medical technician ambulances, paramedic ambulances and anesthesiologist-staffed mobile emergency care units. Further, a nationwide anesthesiologist-staffed helicopter EMS can be dispatched by all five health care regions. In total, approximately 300 ambulances, twenty-six mobile emergency care units and four helicopters are available in Denmark. The Danish EMS has been described in detail previously.

The Danish national distress number 1-1-2 provides one point of entry for citizens requiring emergency assistance from police, fire brigade or EMS. The 1-1-2 calls are received by three national command centers: two operated by the police and one by the Copenhagen fire brigade, relaying medical emergencies to the relevant health care regional Emergency Medical Dispatch Center. The dispatch center is responsible for the EMS response from receiving the call until the patient is handed over to a hospital or patient contact is finalized on scene or during the call. Each health region has its own dispatch center that operates prehospital units, using criteria-based dispatch.

Criteria-based dispatch In Denmark, criteria-based dispatch is the method of triaging in EMS. Based on the interview with the caller making the 1-1-2 call, the dispatch call-taker, usually a nurse or a paramedic, selects one of the 37 main symptom chapters with specific sub-chapters in the Danish Index support tool (See Table 1). Once entered into the computer-aided dispatch software, the criterion selected automatically triggers a response, which can either be an ambulance, a rapid response vehicle, a physician-manned unit, or a combination of those. Non-conveyance may also be the response plan. Every mission must have an assigned Danish Index criterion to be dispatched.

The prehospital personnel document and record all interventions and measurements in a wireless digital tablet named the Electronic Prehospital Patient Record System. Data are encrypted and stored on mainframe computers. When an ambulance crew is dispatched on a mission, all details such as address, time stamps, patient identification, vital parameters, medications used, and treatment details are collected during the patient contact. Data consistency is predominant as all EMS personnel are obliged to document their activities.

Data sources and collection The project will collect data from the Electronic Prehospital Patient Record System in the period from 1 January 2016 to 31 December 2022 on all patients in Denmark, who have been treated by ambulance and/or helicopter services, with response modes A (with lights and sirens) and B (without lights and sirens). Other forms of missions are not covered by the project. Further, data from Danish Intensive Care Database and Danish Database for Acute Hospital Contacts will be extracted as per the predefined data variable.

Data linkage The investigators will link data from Electronic Prehospital Patient Record with Danish Intensive Care Database and the Danish Database for Acute Hospital Contacts from 2016 to 2022 with one year follow-up. The purpose is to chart the patient path in the Danish healthcare system from illness or injury to discharge from hospital, death or e.g., emigration. Data will be linked via the patient's unique civil personal register number.

Data variables To answer the research questions in the planned study, the investigators will extract variables from the databases Electronic Prehospital Patient Record, Danish Intensive Care database and Danish database for Acute Hospital Contacts.

Guidelines The investigators will adhere to The Strengthening the Reporting of Observational studies in Epidemiology (STROBE) guidelines in the reporting of the study findings.

Missing data Missing data will be accounted for, and the investigators will use validated methods to mitigate the effects of missing data.

Measures Nominal results are expressed as medians with interquartile ranges or means with standard deviations. Odds and risk ratios are expressed with standard error and 95% confidence intervals.

Tables The investigators will produce tables to demonstrate the findings of the study in a tabular format, presenting all data of the included participants from the database searches.

Figures The investigators will construct a study flow-chart to illustrate the pathway of the study. Further, the investigators will develop a Directed Acyclic Graph to demonstrate the study pathway between exposure/treatment and outcome with confounders, expected study causalities and associations, and for a graphic overview of the study.

Analyses In the statistical analyses, the investigators will adjust for age, sex, acute illness, and chronic illness. Further, the investigators will use regression analysis, Kaplan-Meyer plots and linear regression models to assess and evaluate the association between response time and the primary and secondary outcomes. The investigators will use advanced statistical and epidemiological methods to assess confounders and biases and conduct a stratified analysis for each of the 37 dispatch categories.

In the analyses, the investigators will address causality, explained by way of the Bradford-Hill criteria, and the Sufficient-component cause model. The investigators will use Directed Acyclic Graphs to illustrate and identify measurable and unmeasurable confounders. The investigators will also apply causal mediation analysis as warranted, and address time-varying covariates and immortal time bias, if applicable.

Further, the investigators will use validated statistical methods to control for confounding including multivariable regression, stratification and inverse probability of treatment weighting and use this concept to mitigate and address time-dependent confounding.

Publications and dissemination The investigators plan to publish the results from the two studies in peer-reviewed scientific journals. Results will also be presented at relevant scientific congresses and meetings and on the project website, www.ahrtemis.dk.

In addition, the results will be presented in relevant publications, newspapers, digital media, television, social media, etc. Further, the AHRTEMIS project has planned a meeting in Q4 2024 with patients and relatives to formulate a layman's resume of the AHRTEMIS project synopsis and to define important aspects to EMS dispatch from the patient and relative perspective.

DISCUSSION In presenting the protocol for this substantive epidemiological assessment study, the investigators seek to pave the way for a comprehensive exploration of the association between EMS units' response time and patient survival and relevant outcomes in Denmark. The investigators will seek to scientifically quantify the importance and significance of response time association with patient outcomes, stratified as per selected Danish Index symptom-based criterion.

Through the adherence to validated guidelines such as the STROBE, the investigators aim to ensure consistent methodology and transparency in the reporting of the study findings. In the discussion of the findings, the investigators anticipate valuable insights to enhance clinical practice, guide future research in the field, and ultimately optimize the delivery of care for patient in need om emergency medical services treatment.

The use of advanced epidemiological and statistical methods will aide to mitigate major limitations that include confounding by indication and bidirectional causality, which are inherent in observational studies. The investigators will systematically address and quantify additional limitations, such as observation, classification, or measurement bias.

CONCLUSION In this epidemiological study, the investigators aim to describe the associations, if any, between EMS response time and patient survival and important outcome measures. The investigators will scientifically quantify the importance and significance of response time association with patient outcomes in a large material of Danish patients treated by ambulance and helicopter services from 2016-2022 with one year follow-up, using advanced epidemiological and statistical methodologies.

Table 1. Danish Index. Main symptom groups

Chapter Main symptoms

  1. Unconscious adult
  2. Unconscious child
  3. Foreign body in airway
  4. Disaster, major incident
  5. Ordered task
  6. Unclear problem
  7. Allergic reaction
  8. Bleeding, non-traumatic
  9. Fire or electrical injury
  10. Chest pain, heart disease
  11. Diabetes
  12. Drowning
  13. Diving accident
  14. Animal or insect bite
  15. Fever
  16. Poisoning in children
  17. Childbirth
  18. Gynecology, pregnancy
  19. Headache
  20. Skin and rashes
  21. Hypothermia, hyperthermia
  22. Chemicals, gasses
  23. Seizures
  24. Abdominal or back pain
  25. Possible death or sudden infant death
  26. Impaired consciousness, paralysis
  27. Psychiatry, suicidal
  28. Breathing difficulties
  29. Intoxication, medications, alcohol, drug overdose
  30. Sick child
  31. Minor wound, fracture, injury
  32. Traffic accident
  33. Accident, not related to traffic
  34. Urinary tract
  35. Violence, abuse
  36. Ear, nose, throat
  37. Eye
Being tested
Treatment by ambulance or helicopter services with response times
Keywords
emergency medical services, response time, intensive care unit treatment, ventilator days

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • Treatment by ambulance or helicopter services with response timesProcedure or surgery

    Prehospital treatment by ambulance and/or helicopter services personnel of patients in acute conditions

Study groups in NCT06666647
Study groupRoleWhat they receive
Patients in need of treatment by emergency medical servicesAll patients in Denmark to whom an ambulance or helicopter has been disapatched
Receives: Procedure: Treatment by ambulance or helicopter services with response times

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. 30-day survival

    Patient is alive 30 days after hospital admission

    Measured: Status at 30 days after hospital admission

Secondary outcomes (5)
  1. 24 hour survival

    The patient is alive 24 hours after hospital admission

    Measured: Status at 24 hours after hospital admission

  2. 48 hour survival

    The patient is alive 48 hours after hospital admission

    Measured: Status at 48 hours after hospital admission

  3. 7-day survival

    The patient is alive seven days after hospital admission

    Measured: Status at seven days after hospital admission

  4. 90-day survival

    The patient is alive 90 days after hospital admission

    Measured: Status at 90 days after hospital admission

  5. Survival to hospital discharge

    Patient is alive on hospital discharge

    Measured: Status at hospital discharge, assessed up to 5 days

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted30 Oct 2024
  2. Study start1 May 2025
  3. Primary completion30 Mar 2026 (estimated)
  4. Study completion31 Dec 2026 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Retrospective
Enrolment
2,500,000 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT06666647
Sponsor's protocol ID
AHRTEMIS.PROTOCOL.PMH
Acronym
AHRTEMIS
Status last verified
Dec 2025
First submitted
22 Oct 2024
Last updated
30 Dec 2025
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No: There is no sharing of IPD as this is a retrospective cohort study without disclosure of individual patient details

Publications

  • Austin PC, Stuart EA. Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies. Stat Med. 2015 Dec 10;34(28):3661-79. doi: 10.1002/sim.6607. Epub 2015 Aug 3.

    PubMed 26238958
  • Chesnaye NC, Stel VS, Tripepi G, Dekker FW, Fu EL, Zoccali C, Jager KJ. An introduction to inverse probability of treatment weighting in observational research. Clin Kidney J. 2021 Aug 26;15(1):14-20. doi: 10.1093/ckj/sfab158. eCollection 2022 Jan.

    PubMed 35035932
  • Levesque LE, Hanley JA, Kezouh A, Suissa S. Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes. BMJ. 2010 Mar 12;340:b5087. doi: 10.1136/bmj.b5087. No abstract available.

    PubMed 20228141
  • Hu X, Zhao J, Lin Z, Wang Y, Peng H, Zhao H, Wan X, Yang C. Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics. Proc Natl Acad Sci U S A. 2022 Jul 12;119(28):e2106858119. doi: 10.1073/pnas.2106858119. Epub 2022 Jul 5.

    PubMed 35787050
  • Carter AR, Sanderson E, Hammerton G, Richmond RC, Davey Smith G, Heron J, Taylor AE, Davies NM, Howe LD. Mendelian randomisation for mediation analysis: current methods and challenges for implementation. Eur J Epidemiol. 2021 May;36(5):465-478. doi: 10.1007/s10654-021-00757-1. Epub 2021 May 7.

    PubMed 33961203
  • VanderWeele TJ, Hernan MA. Results on differential and dependent measurement error of the exposure and the outcome using signed directed acyclic graphs. Am J Epidemiol. 2012 Jun 15;175(12):1303-10. doi: 10.1093/aje/kwr458. Epub 2012 May 8.

    PubMed 22569106
  • Rijnhart JJM, Valente MJ, Smyth HL, MacKinnon DP. Statistical Mediation Analysis for Models with a Binary Mediator and a Binary Outcome: the Differences Between Causal and Traditional Mediation Analysis. Prev Sci. 2023 Apr;24(3):408-418. doi: 10.1007/s11121-021-01308-6. Epub 2021 Nov 16.

    PubMed 34782926
  • Suzuki E, Yamamoto E. Strength in causality: discerning causal mechanisms in the sufficient cause model. Eur J Epidemiol. 2021 Sep;36(9):899-908. doi: 10.1007/s10654-021-00798-6. Epub 2021 Sep 26.

    PubMed 34564795
  • Schober P, Vetter TR. Linear Regression in Medical Research. Anesth Analg. 2021 Jan;132(1):108-109. doi: 10.1213/ANE.0000000000005206. No abstract available.

    PubMed 33315608
  • Hess AS, Hess JR. Kaplan-Meier survival curves. Transfusion. 2020 Apr;60(4):670-672. doi: 10.1111/trf.15725. Epub 2020 Feb 20. No abstract available.

    PubMed 32077507
  • Hsu CH, Yu M. Cox regression analysis with missing covariates via nonparametric multiple imputation. Stat Methods Med Res. 2019 Jun;28(6):1676-1688. doi: 10.1177/0962280218772592. Epub 2018 May 2.

    PubMed 29717943
  • Zhang Z, Reinikainen J, Adeleke KA, Pieterse ME, Groothuis-Oudshoorn CGM. Time-varying covariates and coefficients in Cox regression models. Ann Transl Med. 2018 Apr;6(7):121. doi: 10.21037/atm.2018.02.12.

    PubMed 29955581
  • Broderick JP, Adeoye O, Elm J. Evolution of the Modified Rankin Scale and Its Use in Future Stroke Trials. Stroke. 2017 Jul;48(7):2007-2012. doi: 10.1161/STROKEAHA.117.017866. Epub 2017 Jun 16. No abstract available.

    PubMed 28626052
  • Jahn M, Rekowski J, Gerken G, Kribben A, Canbay A, Katsounas A. The predictive performance of SAPS 2 and SAPS 3 in an intermediate care unit for internal medicine at a German university transplant center; A retrospective analysis. PLoS One. 2019 Sep 25;14(9):e0222164. doi: 10.1371/journal.pone.0222164. eCollection 2019.

    PubMed 31553738
  • Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83. doi: 10.1016/0021-9681(87)90171-8.

    PubMed 3558716

Questions about this trial

What is this clinical trial studying?

An observational study of Emergency Medical Services and Response, run by Peter Martin Hansen at 1 site in Denmark.

The full registered description is in the About this study section and the official record.

Who may be eligible to take part?

The sponsor lists 1 inclusion and 5 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.

Is this clinical trial currently recruiting?

The record says: under way, not looking for participants, as of the sponsor's last update on 30 Dec 2025. Status can change between updates, so confirm with the study contact before making plans.

Where is the study taking place?

The record lists 1 site in Denmark. Whether a site is taking part right now should be confirmed with that site. See every site.

What are the possible benefits and risks?

They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.

Are results available for this study?

This study is still under way. Results are not available in the source record yet.

How can a doctor refer a patient or contact the research team?

The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.

What does the primary outcome measure?

30-day survival (time frame: Status at 30 days after hospital admission). It is what the study was designed to measure, not a finding.

Where can I read the original study information?

On the ClinicalTrials.gov record for NCT06666647, which also lists 39 linked publications.

Does a listing mean the treatment is approved or proven to work?

No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.

How often is this information updated?

AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 30 Dec 2025.

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