Evidence map›Paper›PMID 30849977›Full record

Observational studyBMC health services research2019

Collecting core data in physician-staffed pre-hospital helicopter emergency medical services using a consensus-based template: international multicentre feasibility study in Finland and Norway.

Kristin Tønsager, Marius Rehn, Kjetil G Ringdal, Hans Morten Lossius, Ilkka Virkkunen, Øyvind Østerås, Jo Røislien, Andreas J Krüger

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in BMC health services research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Database quality assessment in research in paramedicine: a scoping review.Scandinavian journal of trauma, resuscitation and emergency medicine · 2023
    Article
  4. Article
  5. Article
  6. Observational
  7. Article
  8. Template for documenting and reporting data in physician-staffed pre-hospital services: a consensus-based update.Scandinavian journal of trauma, resuscitation and emergency medicine · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Kristin TønsagerThe Norwegian Air Ambulance Foundation, Oslo, Norway. kristin.tonsager@norskluftambulanse.no.ORCID http://orcid.org/0000-0002-5289-0442
Marius RehnThe Norwegian Air Ambulance Foundation, Oslo, Norway.
Kjetil G RingdalDepartment of Anesthesiology, Vestfold Hospital Trust, Tønsberg, Norway.
Hans Morten LossiusThe Norwegian Air Ambulance Foundation, Oslo, Norway.
Ilkka VirkkunenResearch and Development Unit, FinnHEMS, Vantaa, Finland.
Øyvind ØsteråsDepartment of Anaesthesiology and Intensive Care, Haukeland University Hospital, Bergen, Norway.
Jo RøislienThe Norwegian Air Ambulance Foundation, Oslo, Norway.
Andreas J KrügerThe Norwegian Air Ambulance Foundation, Oslo, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComparison of services and identification of factors important for favourable patient outcomes in emergency medical services (EMS) is challenging due to different organization and quality of data. The purpose of the present study was to evaluate the feasibility of physician-staffed EMS (p-EMS) to collect patient and system level data by using a consensus-based template.

methodsThe study was an international multicentre observational study. Data were collected according to a template for uniform reporting of data from p-EMS using two different data collection methods; a standard and a focused data collection method. For the standard data collection, data were extracted retrospectively for one year from all FinnHEMS bases and for the focused data collection, data were collected prospectively for six weeks from four selected Norwegian p-EMS bases. Completeness rates for the two data collection methods were then compared and factors affecting completeness rates and template feasibility were evaluated. Standard Chi-Square, Fisher's Exact Test and Mann-Whitney U Test were used for group comparison of categorical and continuous data, respectively, and Kolomogorov-Smirnov test for comparison of distributional properties.

resultsAll missions with patient encounters were included, leaving 4437 Finnish and 128 Norwegian missions eligible for analysis. Variable completeness rates indicated that physiological variables were least documented. Information on pain and respiratory rate were the most frequently missing variables with a standard data collection method and systolic blood pressure was the most missing variable with a focused data collection method. Completeness rates were similar or higher when patients were considered severely ill or injured but were lower for missions with short patient encounter. When a focused data collection method was used, completeness rates were higher compared to a standard data collection method.

conclusionsWe found that a focused data collection method increased data capture compared to a standard data collection method. The concept of using a template for documentation of p-EMS data is feasible in physician-staffed services in Finland and Norway. The greatest deficiencies in completeness rates were evident for physiological parameters. Short missions were associated with lower completeness rates whereas severe illness or injury did not result in reduced data capture.

Indexed as

Emergency Medical ServicesEmergency Service, HospitalPhysiciansAircraftConsensusData CollectionFeasibility StudiesFinlandHumansNorwayPractice Guidelines as TopicCritical careData collectionDocumentationEmergency medical servicesFeasibility studiesPre-hospital emergency care

Identifiers

PMID30849977
PMCPMC6408770

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.