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The Danish Drowning Cohort: Utstein-style data from fatal and non-fatal drowning incidents in Denmark

BMC Medical Research Methodology volume 25, Article number: 28 (2025) Cite this article

Abstract

Background

Effective interventions to reduce drowning incidents require accurate and reliable data for scientific analysis. However, the lack of high-quality evidence and the variability in drowning terminology, definitions, and outcomes present significant challenges in assessing studies to inform drowning guidelines. Many drowning reports use inappropriate classifications for drowning incidents, which significantly contributes to the underreporting of drowning. In particular, non-fatal drowning incidents are underreported because many countries do not routinely collect this data.

The Danish Drowning Cohort

The Danish Drowning Cohort was established in 2016 to facilitate research to improve preventative, rescue, and treatment interventions to reduce the incidence, mortality, and morbidity of drowning. The Danish Drowning Cohort contains nationwide data on all fatal and non-fatal drowning incidents treated by the Danish Emergency Medical Services. Data are extracted from the Danish prehospital electronic medical record using a text-search algorithm (Danish Drowning Formula) and a manual validation process. The WHO definition of drowning, supported by the clarification statement for non-fatal drowning, is used as the case definition to identify drowning. All drowning patients are included, including unwitnessed incidents, non-conveyed patients, patients declared dead prehospital, or patients with obvious clinical signs of irreversible death. This method allows syndromic surveillance and monitors a nationwide cohort of fatal and non-fatal drowning incidents in near-real time to inform future prevention strategies. The Danish Drowning Cohort complies with the Utstein style for drowning reporting guidelines. The 30-day mortality is obtained through the Civil Personal Register to differentiate between fatal and non-fatal drowning incidents. In addition to prehospital data, new data linkages with other Danish registries via the patient’s civil registration number will enable the examination of various additional factors associated with drowning risk.

Conclusion

The Danish Drowning Cohort contains nationwide prehospital data on all fatal and non-fatal drowning incidents treated by the Danish Emergency Medical Service. It is a basis for all research on drowning in Denmark and may improve preventative, rescue, and treatment interventions to reduce the incidence, mortality, and morbidity of drowning.

Graphical Abstract

Plain Language Summary

The Danish Drowning Cohort includes data on fatal and non-fatal drowning incidents treated by the Emergency Medical Services from 2016 and onwards and serves as the foundation for drowning research in Denmark. Data are extracted from the Danish Prehospital Electronic Medical Record using the Danish Drowning Formula and manual validation. The research data can advance prevention, rescue, and treatment interventions, aiming to decrease drowning incidence, mortality, and morbidity. The research data follows the Utstein style for drowning reporting guidelines linked with 30-day survival.

Peer Review reports

Introduction

Targeted preventative measures can avoid a large proportion of drowning incidents, and developing evidence-based rescue and treatment recommendations is a high priority to decrease mortality and morbidity following drowning [1, 2]. Effective preventative, rescue, and treatment interventions to reduce drowning incidents require accurate, reliable, and sufficient data to be scientifically analysed. However, the lack of high-quality evidence and the variability in drowning terminology, definitions, and outcomes pose significant challenges when assessing studies to inform drowning guidelines [1, 3, 4]. Most drowning reports use an inappropriate classification of drowning incidents, which significantly contributes to the under-reporting of drowning incidents [5, 6]. Especially non-fatal drowning incidents are under-reported, as many countries do not routinely collect this data [7].

A consensus-based advisory statement from the International Liaison Committee on Resuscitation recommending the Utstein style for drowning (USFD) was published in 2003 [8, 9]. The USFD was revised in 2015 based on a review of 14 studies [10,11,12]. However, many variables from the revised USFD are not routinely reported as they are unavailable [10]. Even in high-resource healthcare settings, the large amount of variables makes data collection time-consuming [13, 14].

Using electronic medical records is becoming increasingly common as they reduce resource utilization and improve the quality of care [15, 16]. Text-search algorithms to search the prehospital electronic medical record may provide new and improved ways of detecting drowning, as they can monitor drowning indicators (i.e. trigger words or constructs) similar to syndromic surveillance and create high-quality datasets to inform prevention strategies [17, 18].

The Danish Drowning Cohort reports prehospital data on fatal and non-fatal drowning patients treated by the Emergency Medical Services (EMS) in Denmark from 2016 and onwards. Drowning incidents are identified from the Danish prehospital electronic medical record using the Danish Drowning Formula and extensive manual validation. Data are extracted following the revised USFD [11, 12]. The Danish Drowning Cohort will facilitate research to improve preventative, rescue, and treatment interventions to reduce the burden of drowning.

This paper aims to describe the Danish Drowning Cohort, including the patient selection process and the reported variables.

Materials and methods

Setting

Denmark has approximately 5.9 million inhabitants [19]. Despite its small geographical area of 42,933 square kilometres, the country and its citizens are highly exposed to aquatic environments with 8,593 km coastline, 669 natural harbours, anchorages, marinas, and 251 public pools [20,21,22].

All Danish citizens are provided free and universal tax-supported health care by the Danish National Health Services [23]. The Danish prehospital EMS response is government-funded and divided into five regions, each with a regional Emergency Medical Dispatch Centre [24]. The Danish prehospital EMS response operates round-the-clock. It includes ambulances as the basic-level response, paramedic- or nurse-staffed cars as the intermediate-level response, and physician-staffed vehicles (mobile emergency care units) or helicopters (Helicopter Emergency Medical Services [HEMS]) as the advanced-level response [25, 26]. Since 2015, all Danish prehospital personnel have utilised the prehospital electronic medical record [25, 26]. Clinical data can be entered or directly transmitted from monitors into structured sections. Several unstructured text fields are available (e.g. a summary of the prehospital effort, treatment given prior to arrival, and previous diseases). However, data are not routinely collected or required to be entered here. Data from the prehospital electronic medical record is forwarded to in-hospital servers in real-time, providing prehospital information to the hospital staff receiving the patient.

All Danish citizens have a unique civil registration number in the Danish Civil Registration System [27]. Patients without a Danish civil registration number will receive a temporary number upon contact with the Danish health care system. In medical research, the civil registration number can be used for exact individual-level record linkage of all extensive Danish registries facilitating research [28]. Therefore, regularly updated data on 30-day survival can be collected from the Civil Personal Register and linked to the Danish Drowning Cohort [27].

Danish drowning formula

In 2023, the Danish Drowning Formula was developed as a text-search algorithm that searches the unstructured text fields of the prehospital electronic medical record to detect drowning-related out-of-hospital cardiac arrest registered in the Danish Cardiac Arrests Registry [29, 30]. The Danish Drowning Formula consists of 111 trigger words related to submersion injury and aquatic environments and is described previously [29].

Population

The study population included all fatal and non-fatal drowning patients treated by the EMS in Denmark from 2016 and onwards.

Case validation

The Danish Drowning Formula was initially used to detect all possible water-related incidents. To identify drowning-related records, a comprehensive validation of all records with potential drowning incidents was conducted (Fig. 1).

Fig. 1
figure 1

Flowchart showing the process of manual validation of drowning incidents for the Danish drowning cohort from 2016–2021

Full size image

Nineteen trigger words and constructs from the Danish Drowning Formula were considered critical, i.e. high association with drowning (Fig. 1). These consisted of (1) variations of “drowning” and “near-drowning”, the latter still being used by some EMS personnel despite being incompatible with the current drowning definition, (2) variations of “found in water”, and (3) variations of “cardiopulmonary resuscitation” and “obvious clinical signs of irreversible death”. Critical words and constructs included in numbers one and two were already present in the Danish Drowning Formula. However, as critically ill or deceased drowning patients often have shorter medical records consisting of fewer words, we decided to manually validate all those records identified by the Danish Drowning Formula containing any critical words or constructs included in number three.

Records were separated into three groups: (1) records containing a critical trigger word, (2) records containing multiple non-critical trigger words, and (3) records containing a single non-critical trigger word (Fig. 1). If the records contained a critical trigger word or more than one non-critical trigger word, they were assumed to have a high probability of being drowning-related and were manually validated. For records containing a single non-critical trigger word, we identified text constructs containing the trigger word used in a context typically not associated with drowning (e.g. “water broke” as a sign of labour). If no drowning incidents were identified within 10% of the records containing the text construct, the text construct and related records were excluded.

Four observers (two physicians and two medical students) manually validated all remaining records in three steps. In the first validation process, each record was assessed by two independent reviewers. A physician and a medical student reviewed discrepancies in the second validation process. In the third validation process, a physician reviewed any ambiguous records with prehospital vital signs indicating respiratory impairment (increased respiratory rate and decreased peripheral arterial oxygen saturation).

We used 30-day mortality to differentiate between fatal and non-fatal drowning.

Inclusion and exclusion criteria

The WHO definition of drowning, supported by the clarification statement for non-fatal drowning, was used as the case definition to identify drowning (target condition) during the three steps of manual validation [31, 32]. Drowning was defined by the WHO in 2002 as “the process of experiencing respiratory impairment from submersion or immersion in liquid” [32]. Submersion indicated that the victim’s entire body, including the airway, was below the surface of the liquid. Immersion indicated that the head was above the water, whereas the rest of the body was immersed [33, 34]. However, for drowning to occur, water must be aspirated [8, 9]. If the person died because of drowning, this was termed a fatal drowning, but if the process of respiratory impairment was stopped before death, this was termed a non-fatal drowning [31]. Patients were categorised as non-drowning if it was unclear that the incident involved submersion or immersion or if the patient did not experience respiratory impairment. If it was unclear if the patient had experienced respiratory impairment immediately after the drowning process was stopped, we selected the option that best reflected the respondent’s description of the respiratory impairment, relying on the description from the respondent and vital signs and used the best judgment according to the “Clarification and Categorisation of Non-fatal Drowning” [31]. The Danish Drowning Cohort contains all drowning patients treated by the EMS, including unwitnessed incidents, non-conveyed patients, patients declared dead prehospital, or patients with obvious clinical signs of irreversible death (decomposition, postmortem lividity, postmortem rigidity).

Variables and data collection

Table 1 contains all the Danish Drowning Cohort variables, including the variable name and definition, collection method, and how the data are coded in the Danish Drowning Cohort. Blank fields indicate unknown/missing values. Variables are collected as outlined in the USFD based on the availability in the Danish prehospital electronic medical record. A complete overview of USFD variables compared to the available variables in the Danish Drowning Cohort is provided in Supplementary Table S1.

Table 1 Variables in the Danish Drowning Cohort year 2024
Full size table

Statistical analysis

The performance metrics of the Danish Drowning Formula were statistically evaluated by calculating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). These metrics were calculated from the numbers of true positives (TP; i.e. the record was drowning, and it was detected as drowning by the Danish Drowning Formula), false positives (FP; i.e. the record was not drowning, but it was detected as drowning), true negatives (TN; i.e. the record was a non-drowning and it was detected as a non-drowning), and false negatives (FN; i.e. the record was a non-drowning but it was detected as drowning). Sensitivity [TP / (TP + FN)] and specificity [TN / (FP + TN)] were calculated to show the performance of the Danish Drowning Formula as a drowning identification tool. PPV [TP / (TP + FP)] and NPV [TN / (FN + TN)] were calculated to show the Danish Drowning Formula test result. There was no imputation of missing data. All analyses were performed using R statistical software (version 4.2.2) [35].

Results

Figure 2 provides an inclusion flowchart. The Danish Drowning Formula identified 65,771 records from 3,471,681 unique prehospital medical records in the Danish prehospital electronic medical record containing one or more trigger words from January 1st, 2016, to December 31st, 2021. In total, 1,227 records were identified as drowning patients treated by the Danish EMS from 2016 to 2021, corresponding to an annual incidence of approximately 205 patients per year and an annual incidence rate of 3.5 per 100,000 persons.

Fig. 2
figure 2

Inclusion flowchart for the Danish Drowning Cohort from 2016–2021

Full size image

Table 2 shows the performance metrics of the Danish Drowning Formula as a drowning identification tool when applied to the Danish prehospital electronic medical record on unrestricted terms. The sensitivity was 100%, the specificity was 98%, the PPV was 1.87%, and the NPV was 100%. The sensitivity and NPV of 100% were based on the assumption that using a text-search algorithm with comprehensive search criteria (e.g. the Danish Drowning Formula) followed by extensive manual validation was the gold standard for drowning identification.

Table 2 Diagram demonstrating the performance metrics of the Danish drowning formula from 2016–2021
Full size table

Of 1,227 drowning records, 817 (66.6%) records contained one or more critical trigger words, 338 (27.5%) records contained multiple non-critical trigger words, and 72 (5.9%) records contained a single non-critical trigger word (Table 3). Overall, the drowning rate increased by the number of trigger words from the Danish Drowning Formula identified in the prehospital electronic medical record (Table 3). Most drowning records contained less than four trigger words, and 200 records (16.3%) contained only one trigger word. Therefore, it would not be possible to establish a cut-off based on the number of trigger words in the prehospital electronic medical record.

Table 3 Association between drowning identification and trigger words’ type and number
Full size table

Discussion

Summary of results

The Danish Drowning Cohort is a new database under establishment containing nationwide prehospital data on all fatal and non-fatal drowning incidents treated by the Danish EMS from 2016 and onwards. Using the Danish Drowning Formula to detect fatal and non-fatal drowning incidents by searching the prehospital electronic medical record followed by extensive manual validation shows satisfying results. The Danish Drowning Cohort can monitor drowning incidents and facilitate research by providing detailed information on the exact geographical locations, time of incident, and patient characteristics (ClinicalTrials.gov: NCT06312202). These data can be used to improve preventative, rescue, and treatment interventions aimed at reducing the incidence, mortality, and morbidity of drowning. In the future, data from the Danish Drowning Cohort may be combined with other data sources of similar quality to contribute to an International Drowning Registry, as Thom et al. suggested, to facilitate multicenter and multinational sharing of drowning data [14].

Methods compared to the existing literature

Similar to other drowning reports from Sweden, Australia, and Canada, the past Danish drowning statistics identified drowning by searching the Danish Register of Causes of Death for relevant diagnosis codes in the International Classification of Diseases (ICD) 10th Edition (V90, V92, W65-74, X31, X38, X39, X71, X92, Y21, T68, and T75.1, Supplementary Table S2) [36,37,38,39,40,41,42,43]. The search results were combined with other data sources to create a triangulation method and improve data quality (e.g. reports on rescue missions, year-round media monitoring including newspapers and social media, police reports, and internet searches). For drowning persons with foreign nationality, media monitoring was the only source of information [36]. Other studies have used multiple and complex criteria for data extraction, a correction factor to report an estimate of the true incidence of drowning accidents, or the presenting problem or discharge diagnosis of drowning or immersion to enroll all drowning patients presenting to the emergency department [14, 39, 44]. These methods have several limitations regarding the identification of drowning incidents and data collection compared to searching the prehospital electronic medical record using text-search algorithms, such as the Danish Drowning Formula, followed by extensive manual validation [29]. First, using primary-cause ICD codes significantly underreport the true incidence of fatal and non-fatal drowning incidents, as the codes are not sufficiently specific [6, 39, 45, 46]. Second, collecting death certificates and confirming the cause of death may take several years, may not include drowning incidents with a delayed fatal outcome due to incorrect coding in the reports, systematically excludes non-fatal drowning, and does not include information on prehospital treatment performed by bystanders or EMS personnel [36, 44]. Third, accessing and linking data from various sources, including media, is time-consuming and increases the risk of bias and missing data. Future studies should focus on developing and validating a formula for drowning identification in different settings using the prehospital electronic health record. In Australia, the prehospital electronic health record is used to monitor mental health and self-harm, presenting an opportunity to develop a formula for drowning identification based on English-language records [47]. In the United States, drowning incidents can be identified through the National Syndromic Surveillance Program, which relies on in-hospital data [17, 18]. However, the decentralized and non-unified data systems in the United States challenge using the electronic health record to exchange health information, limiting its use for drowning identification [48]. Furthermore, many resource-limited settings need financial support to acquire the essential technology and provide staff training to implement an electronic health record and utilize data for syndromic surveillance [49, 50].

Limitations

This study has several limitations. First, the Danish Drowning Formula was designed to search the unstructured text fields in the prehospital electronic medical record on unrestricted terms with comprehensive search criteria to identify all potential water-related incidents and achieve a high sensitivity. This was important as drowning is a rare occurrence, but it resulted in a low PPV for detecting drowning incidents specifically. Ongoing studies aim to augment the PPV of the Danish Drowning Formula and reduce the temporal demands associated with manual validation (ClinicalTrials.gov: NCT06310525). The Danish Drowning Formula may still be used as the basis for future studies investigating rare water-related incidents, such as in-water traumatic spinal cord injuries, to support the development of guidelines [51]. Second, using the prehospital electronic medical record may introduce selection bias, as this source of information does not contain drowning incidents where the body is never recovered, self-referred patients in the emergency department, and incidents in the open ocean where the patient or the body is retrieved by Royal Danish Air Force’s Search and Rescue (SAR) helicopters that do not register missions in the prehospital electronic medical record (ClinicalTrials.gov: NCT06322134) [52]. Third, all manually extracted variables are retrospectively extracted from the prehospital electronic medical record, possibly introducing information bias through missing data. Fourth, uncertainty persists in unwitnessed incidents where the body is recovered from the water, as it remains challenging to conclusively differentiate drowning from other causes of death (e.g. suicide, homicide, or other medical conditions occurring while the patient was in the water) [53]. Linkage with the patients’ unique civil registration numbers may enable future access to the Danish Register of Causes of Death and their autopsy reports to specify the cause of death (ClinicalTrials.gov: NCT06310499) [37].

Conclusions

The Danish Drowning Cohort is an established and growing dataset. It contains nationwide prehospital data on all fatal and non-fatal drowning incidents treated by the Danish Emergency Medical Services.

Data availability

The data are intended for use nationally and internationally by researchers to reduce the incidence, mortality, and morbidity of drowning. The data are available from the corresponding author upon reasonable request. Access to the data requires approval by the relevant regulatory bodies to ensure compliance with ethical and legal requirements.

Abbreviations

EMS:

Emergency Medical Services

FN:

False Negative

FP:

False Positive

HEMS:

Helicopter Emergency Medical Services

ICD:

International Classification of Diseases

NPV:

Negative Predictive Value

PPV:

Positive Predictive Value

SAR:

Search and Rescue

TN:

True Negative

TP:

True Positive

USFD:

Utstein Style For Drowning

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Acknowledgements

Theo W. Jensen and Mathias G. Holgersen were part of the Danish Drowning Validation Group, responsible for continuously developing the Danish Drowning Formula used in this study, and qualified as collaborating authors. All Danish Drowning Validation Group members are affiliated with Prehospital Center Region Zealand, Næstved, Denmark.

Funding

Open access funding provided by Copenhagen University This study was supported by the Danish foundation TrygFonden. TrygFonden did not influence study design, data collection, analysis, interpretation, writing, or decision to submit the manuscript for publication.

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Authors and Affiliations

  1. Prehospital Center Region Zealand, Ringstedgade 61, 14th Floor, Naestved, 4700, Denmark

    Niklas Breindahl, Kasper Bitzer, Alexander Wildenschild, Signe A. Wolthers, Stig N. F. Blomberg & Helle C. Christensen

  2. Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark

    Niklas Breindahl, Kasper Bitzer, Signe A. Wolthers, Jacob Steinmetz, Stig N. F. Blomberg & Helle C. Christensen

  3. Department of Neonatal and Pediatric Intensive Care, Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, Copenhagen, 2100, Denmark

    Niklas Breindahl

  4. The Prehospital Research Unit, Region of Southern Denmark, Odense University Hospital, Odense, Denmark

    Oliver B. Sørensen & Alexander Wildenschild

  5. Department of Regional Health Research, University of Southern Denmark, Campusvej 55, Odense M, 5230, Denmark

    Oliver B. Sørensen

  6. Centre for Prehospital and Emergency Research, Department of Clinical Medicine, Aalborg University Hospital, Aalborg University, Selma Lagerløfs Vej 249, Gistrup, 9260, Denmark

    Tim Lindskou

  7. Danish Air Ambulance, Brendstrupgårdsvej 7, Aarhus, 8200, Denmark

    Jacob Steinmetz

  8. Department of Anaesthesia, Centre of Head and Orthopaedics, Rigshospitalet, Blegdamsvej 9, Copenhagen, 2100, Denmark

    Jacob Steinmetz

  9. Faculty of Health, Aarhus University, Aarhus, Denmark

    Jacob Steinmetz

Authors
  1. Niklas Breindahl
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  2. Kasper Bitzer
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  8. Stig N. F. Blomberg
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  9. Helle C. Christensen
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Consortia

the Danish Drowning Validation Group

  • Theo W. Jensen
  •  & Mathias G. Holgersen

Contributions

NB, SNFB, and HCC participated in the study conception and design. NB, KB, OBS, and AW were involved in data acquisition. NB analysed the data. NB, KB, SAW, TL, JS, SNFB, and HCC contributed to the interpretation of data. NB drafted the manuscript. KB, OBS, AW, SAW, TL, JS, SNFB, and HCC were involved in critically revising the manuscript. All authors have agreed to submit the manuscript. All authors read and approved the final version of the manuscript. All authors agree to take responsibility and be accountable for the contents of the article.

Corresponding author

Correspondence to Niklas Breindahl.

Ethics declarations

Ethics approval and consent to participate

According to Danish law, registry-based research projects that are based on pure data (i.e. numbers and characters) are exempted from ethical approval and do not require informed consent from the participants (assessed by the Regional Committee on Health Research Ethics for Region Zealand ID-number: EMN-2022-03474). The Danish Data Protection Agency approved data management and processing of the current dataset from 2016 to 2021 (ID-number: REG-041-2022). The Regional Council in Region Zealand approved the handover of medical records from the same period (ID-number: R-22025982).

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Not applicable.

Competing interests

The authors declare no competing interests.

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Breindahl, N., Bitzer, K., Sørensen, O.B. et al. The Danish Drowning Cohort: Utstein-style data from fatal and non-fatal drowning incidents in Denmark. BMC Med Res Methodol 25, 28 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12874-025-02483-8

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Keywords

BMC Medical Research Methodology

ISSN: 1471-2288

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