Characteristics and mortality of patients categorised with non-specific symptoms when dialling the emergency medical number: A register-based cohort study

doi:10.21203/rs.3.rs-4809779/v1

Download PDF

Research Article

Characteristics and mortality of patients categorised with non-specific symptoms when dialling the emergency medical number: A register-based cohort study

https://doi.org/10.21203/rs.3.rs-4809779/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Background

When calling medical emergency number 1-1-3 in Norway, operators in emergency medical communication centres use the decision support tool, the Norwegian Index for Medical Emergency, to categorise the problem and determine the correct handling and urgency level of the situation. The index holds 42 chapters, of which, one is the ‘Non-specific problem’. Studies in Denmark frequently use this chapter; however, there are no published Norwegian studies on the demographics of this patient group. We investigated the characteristics of the patients assigned to this chapter and their outcomes of 1- and 30-day mortality.

Methods

This was a registry-based, retrospective cohort study. Descriptive statistics were used to compare the two groups; t-tests were performed for continuous variables, and data were presented with corresponding 95% confidence intervals. Categorical data were compared using the chi-square test. Statistical significance was set at p < 0.05.

Results

Overall, out of the 25.474 included calls to the emergency medical communication centre in 2022, 1.860 (7.3%) were categorised as ‘Non-specific problem’. Patients in this group had a higher mean age, were more often men, had a shorter hospital stay, and showed more comorbidities than the control group. The use of this chapter was associated with the allocation of a higher urgency level and a reduction in the use of these criteria was observed during the nighttime. Significantly higher 1- and 30-day mortality rates were observed in patients with non-specific symptoms (1.40% and 6.94%, respectively; p < 0.05).

Conclusions

The group presenting symptoms categorised as non-specific comprised older patients, more men, and more patients showing comorbidities than the control group. They typically perceived a high level of urgency. A majority of these patients had a non-specific main diagnosis after hospital admission and a significantly higher mortality rate than those presenting with symptoms categorised as specific.

Non-specific problem

non-specific symptoms

prehospital emergency medicine

emergency medical communication center

health services

Early diagnosis, correct treatment, and fast transportation to the right level of healthcare are the foundations of prehospital treatment. These aspects increase the probability of a good outcome for the patient [1–3]. Operators in emergency medical communication centres (EMCC) serve an important role in ensuring correct care is provided at the right time [4]. EMCC operators use a criterion-based decision support tool called the Norwegian Index for Medical Emergency (Index) to define the health problems of patients who call in [5–8]. This tool identifies the medical problem, aids the operator in determining the correct response, and indicates the level of urgency of the situation [5, 8].

A majority of the listed chapters in the Index are symptom-specific, except for the chapter listed as number 07, namely ‘Non-specific problem’ [8]. Studies in Denmark frequently use this chapter; however, there are no published Norwegian studies on the demographics of this patient group [9–11]. Throughout this article, patients presenting symptoms categorised as non-specific by the EMCC personnel will be referred to as the ‘NSP group’. Due to challenges related to defining the problem among patients in the NSP group, this group may be at risk of delayed diagnostics and, therefore, the time until the correct treatment is initiated may be prolonged. Patients in the NSP group are older and have a higher mortality rate than those in the control group presenting with specific problems [9–12]. A higher incidence of over- and under-triage has been reported among patients in the NSP group than in the control group [13].

Based on this knowledge, we investigated patients with non-specific symptoms in our Emergency Medical System (EMS). We aimed to compare patient mortality between the two groups, that is, the NSP group and patients presenting symptoms categorised as specific.

Study design and data sources

We conducted a register-based retrospective cohort study to describe a patient group with symptoms categorised as non-specific when calling the EMCC. The data included routinely collected patient information from all medical emergency calls made to the Bergen EMCC in Norway over 1 year (2022). Data were collected from two different registers: the EMCCs patient records (AMIS) and the hospital’s electronic patient record (EPJ) system (DIPS).

Setting

A person in need of pre-hospital medical assistance in Norway may contact the nearest EMCC by dialling 1-1-3. In contrast to several European countries, where the generic emergency number is 1-1-2 for all emergencies, Norway has three different emergency numbers; here, 1-1-3 is the designated, free-of-charge medical emergency number. There are 16 EMCCs spread across the country, usually corresponding to the local health trust (HT), with some exceptions. The EMCCs are staffed by specially trained ambulance personnel and nurses. When receiving a call, the EMCC operator uses the index to identify the medical problems [5, 7]. The Index is a criteria-based decision support tool comprising 42 chapters, with each chapter containing a specified list of signs, symptoms, and situational descriptions to guide the operator in determining the correct level of urgency (Table 1), and dispatching the appropriate resources needed for the situation at hand [5, 8].

Table 1

Urgency levels used in the Norwegian Index for Medical Emergency [8]
Code	Urgency level	Description
Red	Acute	Time critical and potentially life-threatening situation in need of immediate medical assistance
Yellow	Urgent	Non-life-threatening situation but in need of medical assistance without delay
Green	Non-urgent	Scheduled patient transport; contact directed to general practitioner or Emergency Primary Care Centre

Helse Bergen HT is located in the western part of Southern Norway and provides specialised healthcare, including EMCC and ambulance services, to approximately 470.000 inhabitants [5, 14]. The trust covers a total land area of approximately 10.000 km², including cities, islands, fjords, and mountains. The 18 municipalities comprising the trust have a population density varying from 1 to 650 inhabitants per km² [14, 15]. The region has three hospitals; only one has a trauma centre and a PCI centre [16, 17].

Participants

Patients aged under 18 years, with unknown age or ID, as well as those with missing information on the level of urgency or ‘non-urgent’ cases, were excluded (Fig. 1). Patients who could not be linked to a subsequent hospital admission, and thus had no ICD-10 diagnoses, were excluded. The remaining calls were subsequently split into two groups: emergency calls categorised as ‘non-specific problem’ according to the Index, and a control group containing all chapters other than ‘non-specific problem’.

Variables and outcomes

Patient data on age, sex, length of hospital stay, diagnosis at discharge, and number of days until death were extracted from the EPJ. Information on the urgency level, time of contact, criterion number, and delivery location were collected from the EMCC’s digital system.

Analysis of age and length of hospital stay included range, mean, and interquartile range, and the proportions of males and females in the groups were determined. Differences in the occurrence of calls throughout the day were analysed by comparing the total number of calls during the day, evening, and night; the time intervals 07.00 am to 02.59 pm, 03.00 pm to 09.59 pm and 10.00 pm to 06.59 am were used, respectively, as they represent the typical hours of a three-part rotation often used in the Norwegian health care system [18]. We investigated the number of calls every weekday, compared between weekdays (Monday to Friday) and weekends (Saturday to Sunday), and the monthly variation in calls throughout the year.

Mortality rates were calculated as deaths within 1 and 30 days of the call. As Norwegian hospitals use the World Health Organization (WHO) International Classification of Diseases 10th Revision (ICD-10) when discharging patients, we used the main chapters of ICD-10 in our analysis of diagnoses [19, 20]. The first listed diagnosis was used as the patient's main diagnosis, and the total number of diagnoses at discharge was used to measure comorbidity, assessing those with 1, 2–3, or 4 or more diagnoses.

Statistical analysis

The data extracted from the two registers were aligned using national individual identification numbers, de-identified, and stored on a secure hospital server. The data were stratified into two groups as shown in Fig. 1, and descriptive statistics were used for their comparison between the groups. T-tests were performed for continuous variables, and data were presented with corresponding 95% confidence intervals (95% CIs). Categorical data were compared using the chi-square test. Statistical significance was set at p < 0.05.

Ethics

In Norway, no formal application to the Regional Committee for Medical and Health Research Ethics (REK) is required for quality control studies. This was a quality-control study (2023/606320/REK vest). The study was approved by the hospital’s data protection officer and relevant departments.

In 2022, the Bergen EMCC received 103.938 emergency calls, of which, 25.747 calls met our inclusion criteria (Fig. 1). The included calls were divided into two groups: NSP (7.3%) and control with symptoms categorised as specific by the EMCC (92.7%).

Patient characteristics and dispatch information for the two groups are shown in Table 2. Notably, significantly higher mean age was observed in the NSP group (66.0 years) than in the control group (61.7 years) and the proportion of men was a significantly higher in the NSP group. A shorter length of hospital stay was observed in the NSP group (3.49 days) than that in the group with specific problems (3.99 days). A higher level of comorbidity was found among patients in the NSP group, where a majority of them received four or more diagnoses at discharge (38.1%), compared with the control group, with the majority of cases had two to three diagnoses (39.0%).

A significantly larger proportion of calls in the NSP group were triaged as ‘acute’, compared with the calls categorised with a specific problem, at 52% and 43%, respectively. Analysis of the distribution of calls throughout the day revealed a lower occurrence of the chapter ‘non-specific problem’ during nighttime, compared with the symptom-specific chapters. However, no significant differences were found in the occurrence of calls throughout the week when comparing weekdays with weekends, and there was no significant variation in the monthly distribution of calls throughout the year.

Furthermore, significantly enhanced mortality was observed in the NSP group than in the control group, after 1 and 30 days (Table 2). There was no significant difference in 1-day mortality rates between the ‘acute’ and ‘urgent’ urgency levels. However, significantly increased 30-day mortality was observed in the NSP group at both urgency levels. The largest differences in mortality were found among patients triaged with the urgency level ‘acute’, with a 30-day mortality in the two groups being 8.26% and 5.76%.

Table 2. Variables describing patients contacting the medical emergency number, categorised with a non-specific problem or specific problem.

Variables		Non-specific	Specific	P-value
		N = 1860	N = 23614
Age in years	Range (IQR)	18–103 (53–82)	18–108 (44–80)
	Mean (95% CI)	66.0 (65.11–66.98)	61.7 (61.38–61.94)	<0.05*
Sex	Female	841 (45.2%)	11283 (47.8%)	< 0.05*
	Male	1019 (54.8%)	12331 (52.2%)
Length of stay	Range (IQR)	0–150 (1–4)	0–388 (0–4)
	Mean (95% CI)	3.49 (3.17–3.80)	3.99 (3.885–4.12)	<0.05*
Comorbidity	1 diagnose	451 (24.3%)	7146 (30.3%)	< 0.05*
	2–3 diagnoses	701 (37.7%)	9219 (39.0%)
	4+ diagnoses	708 (38.1%)	7249 (30.7%)
Time of day	Daytime	853 (45.9%)	9677 (41.0%)	< 0.05*
	Evening	671 (36.1%)	8345 (35.3%)
	Night	336 (18.1%)	5592 (23.7%)

Day of the week	Monday	248 (13.3%)	3404 (14.4%)	0.38
	Tuesday	292 (15.7%)	3336 (14.1%)
	Wednesday	269 (14.5%)	3296 (14.0%)
	Thursday	240 (12.9%)	3287 (13.9%)
	Friday	263 (14.1%)	3346 (14.2%)
	Saturday	269 (14.5%)	3509 (14.9%)
	Sunday	279 (15.0%)	3436 (14.6%)
	Weekdays	1312 (70.5%)	16669 (70.6%)	0.96
	Weekend	548 (29.5%)	6945 (29.4%)
Month	January	142 (7.63%)	1821 (7.71%)	0.13
	February	139 (7.47%)	1733 (7.34%)
	March	153 (8.23%)	1886 (7.99%)
	April	138 (7.42%)	1897 (8.03%)
	May	185 (9.95%)	1988 (8.42%)
	June	163 (8.76%)	2003 (8.48%)
	July	133 (7.15%)	2050 (8.68%)
	August	183 (9.84%)	2021 (8.56%)
	September	149 (8.01%)	2132 (9.03%)
	October	161 (8.66%)	2144 (9.08%)
	November	162 (8.71%)	1984 (8.40%)
	December	152 (8.17%)	1955 (8.28%)
Urgency level	Acute	968 (52.0%)	10156 (43.0%)	< 0.05*
	Urgent	892 (48.0%)	13458 (57.0%)
1-day mortality	Acute	21 (2.17%)	157 (1.55%)	0.14
	Urgent	5 (0.56%)	47 (0.35%)	0.31
	Total	26 (1.40%)	204 (0.86%)	<0.05*
30-day mortality	Acute	80 (8.26%)	585 (5.76%)	< 0.05*
	Urgent	49 (5.49%)	552 (4.10%)	< 0.05*
	Total	129 (6.94%)	1137 (4.81%)	< 0.05*

*Statistically significant, p <0.05

[Table 2 here]

Diagnosis at discharge from hospital

The main diagnoses at discharge from the hospital were grouped by the ICD-10 chapters, and all 21 chapters except chapter 16, ‘Certain conditions originating in the perinatal period’, and chapter 20 ‘External causes of morbidity’, were present in both groups. As shown in Table 3, Chapter 18 was the most frequently used chapter by patients in the NSP group, followed by Chapters 9, 19, 10, and 5. The same five chapters were most commonly used in the control group, although they were presented in different sequences.

Table 3. Five most frequently used ICD-10 chapters at discharge from the hospital and their distribution among patients categorised with non-specific problems and any other criteria, referred to as a specific problem.

Chapter	Title	Non-specific	Specific
5	Mental, Behavioural and Neurodevelopmental disorders	9.8%	12.4%
9	Diseases of the circulatory system	14.2%	13.1%
10	Diseases of the respiratory system	10.7%	10.7%
18	Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified	17.3%	12.8%
19	Injury, poison and certain other consequences of external causes	12.5%	21.7%

Characteristics of patients categorised with a non-specific problem

The aim of this study was to describe the demography of patients with NSP and investigate their outcomes measured based on 1- and 30-day mortality rates. We found that the NSP group had a higher mean age, comprised more men, showed a shorter length of hospital stay, and had higher comorbidities than did patients with a specific problem. The NSP group was triaged to a higher urgency level, and fewer calls were categorised as NSP at night, compared with the control group. No significant differences were found in the distribution throughout the week, between weekdays and weekends, or across months. However, higher 1- and 30-day mortality rates were observed in the NSP group than in the control group.

A total of 7.3% of the calls made to the EMCC in 2022 were categorised as NSP, lower than similar reports from Denmark, where the proportions ranged from 8–18% [9–11]. Our finding of higher mean age in the NSP group correlated well with those of previous studies. We found significantly higher comorbidity in the NSP group. Increased comorbidities could be a complicating factor in the medical assessment of patients. It could also be assumed that older adult patients have higher frailty and thus are at a higher risk of morbidity and mortality. As reported in a study of older adult patients visiting the emergency room by Wachelder et al., several factors, such as comorbidities, communication problems, and cognitive impairment, affect the compilation of history, making assessing and triaging patients more difficult [21].

Patients in the NSP group were triaged to a higher level of urgency than were those in the control group (Table 2; Fig. 2).

Our findings of a higher level of triage and a higher mortality rate in the NSP group may indicate that these patients could present with more severe disease than the control group. This could also reflect that patients with diffuse or uncertain symptoms are over-triaged.

Mortality

Our study revealed significantly increased mortality among patients in the NSP group than among those in the control group, both in 1- (1.40%) and 30-day mortality (6.94%) rates (Table 2). Stratification of the number of deaths within the two urgency levels revealed that only the urgency level and 30-day mortality were associated. Within the NSP group, a significantly increased 30-day mortality was observed among patients triaged as ‘acute’ and ‘urgent’.

The finding of increased mortality in the NSP group correlates well with findings in other studies, where 1-day mortality was reported to be between 2.2 and 2.3%, and 30-day mortality ranged from 6.0 to 7.1% [10, 12]. A study from the Netherlands on older adult patients admitted and categorised with non-specific problems found an increased 30-day mortality rate compared with patients categorised with specific complaints [21]. Møller et al. analysed mortality rates within different urgency levels and found an association between increased mortality and a lower emergency priority level only, the so-called priority level B-calls [11].

Diagnoses at discharge

When analysing the patients’ main diagnosis at discharge from the hospital, we found the same five ICD-10 chapters to be the most frequently used, both in the NSP and control groups, although in different orders. Four of these chapters represent specific diagnoses, whereas Chap. 18 ‘Symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified’, lists more abnormal symptoms not associated with a specified diagnosis [19]. This chapter was most frequently used among patients categorised as having an NSP (17.1%). In contrast, it was only the third most used chapter among patients categorised as having a specific problem (12.8%).

Our findings also suggest that almost one out of five patients with an NSP prehospitalisation were discharged from the hospital with a non-specific diagnosis. Patients with an unclear problem after a thorough examination at the hospital might understandably constitute a difficult patient group to categorise prehospitalisation. The rest of the group received more specific diagnoses when examined at the hospital, and these patients could potentially be better categorised at first contact. The difficulties in categorising the problem of this patient group may be related to communication problems, weaknesses in the decision support tool used by the EMCC, or an atypical presentation of the symptoms or disease at the time of contacting the EMCC. However, further research is required to confirm these reasons.

Strengths and limitations

Every Norwegian has a personal identification number, which makes linking data across different record systems easier and more reliable. As a result of the digitalisation of the prehospital journal system in 2021, the linkage between registries is more reliable than the prehospital paper-based patient records utilised previously by the EMS. The improved linkage between prehospital and hospital records strengthens accuracy and lowers information and selection bias. As the study was based on register-based data, information and selection biases were low.

However, our study has some limitations. As this was a retrospective registry-based study, it was susceptible to known and unknown confounding factors. Despite reliable records, several patients had missing data and, consequently, had to be excluded (n = 16.639, 16%). These exclusions may have confounded the results [22]. However, when reviewing the patient data, a frequent explanation listed in the registry column describing the caller's presenting problem was ‘Misdialled’ or ‘No answer’, which may explain a large number of calls being excluded. As Norway has a universal healthcare system, the findings may be limited to countries with similar healthcare systems, thus reducing generalizability of the results. However, the universal healthcare system reduces the risk of selection bias.

Furthermore, there were limitations to the analysis of diagnoses at discharge. As hospitals in Norway are financially compensated at a fixed rate tied to the various discharge diagnoses, it is possible that the first diagnosis is not the main diagnosis but the one triggering the largest economic compensation. However, this cannot be confirmed without reviewing the patients’ hospital records. Finally, the number of discharge diagnoses was used to indicate comorbidity within the two groups, which may be a poor variable for comorbidities at the individual level. However, it may indicate comorbidities at the group level.

In summary, 7.3% of the patients who contacted the EMS due to a medical emergency in 2022 were categorised according to the NSP prehospital criteria. This group comprised older patients, more men, and more patients with comorbidities. They typically had a higher level of urgency than the control group categorised by any criteria other than NSP. A majority of these patients received a non-specific main diagnosis after hospital admission with significantly higher 1- and 30-day mortality rates than patients with complaints categorised as specific. Our findings indicate that the current decision support tool may need to be modified to better classify the callers’ conditions, and to better suit the EMCC operators’ way of using it.

EMS

emergency medical system

EMCC

emergency medical communication centre

Index

Norwegian Index for Medical Emergency

NSP

non-specific problem

EPJ

electronic patient record

health trust

PCI

percutaneous coronary intervention

WHO

World Health Organization

ICD-10

International Classification of Diseases 10th Revision

REK

Regional Committees for Medical and Health Research Ethics

IQR

interquartile range

95% CI

95% confidence interval

Ethics approval and consent to participate

The Regional Committee for Medical and Health Research Ethics West (REK vest, ref. No. 606320) waived the requirement for formal review because according to law, quality improvement projects do not need this, and had no objections to publication of the data. The Data Protection Officer (PVO) at Haukeland University Hospital approved the project.

Consent for publication

Not applicable.

Availability of data and materials

Data are available from corresponding author on reasonable request.

Competing interests

The authors declare that they have no competing interests.

Funding

Departmental funding, and open access funding provided by University of Bergen.

Authors' contributions

GB conceived the study, and VFS, HMF and LM decided the design. VFS and HM drafted and revised the manuscript. GB contributed with drafting and revision of the manuscript. LM contributed with acquisition of data and statistical analysis. VFS and HMF contributed with data analysis, drafting and revision of the manuscript. All authors read and approved the final manuscript.

Acknowledgements

Not applicable.

Omsorgsdepartementet H-ogNOU. 2015: 17. 2015 [cited 2024 Jun 25]; https://www.regjeringen.no/no/dokumenter/nou-2015-17/id2465765/
McNamara RL, Herrin J, Wang Y, Curtis JP, Bradley EH, Magid DJ, et al. Impact of delay in door-to-needle time on mortality in patients with ST-segment elevation myocardial infarction. Am J Cardiol [Internet]. 2007;100:1227–32. 10.1016/j.amjcard.2007.05.043.
Association of outcome with early stroke treatment: pooled analysis of ATLANTIS, ECASS, and NINDS rt-PA stroke trials. Lancet [Internet]. 2004;363:768–74. 10.1016/s0140-6736(04)15692-4
Roivainen P, Hoikka MJ, Raatiniemi L, Silfvast T, Ala-Kokko T, Kääriäinen M. Telephone triage performed by nurses reduces non-urgent ambulance missions: A prospective observational pilot study in Finland. Acta Anaesthesiol Scand [Internet]. 2020;64:556–63. 10.1111/aas.13542.
Kjærvoll HK, Andersson L-J, Bakkelund KEN, Harring AKV, Tjelmeland IBM. Description of the prehospital emergency healthcare system in Norway. Resusc Plus [Internet]. 2024;17:100509. 10.1016/j.resplu.2023.100509.
Ellensen EN, Hunskaar S, Wisborg T, Zakariassen E. Variations in contact patterns and dispatch guideline adherence between Norwegian emergency medical communication centres - a cross-sectional study. Scand J Trauma Resusc Emerg Med [Internet]. 2014;22. 10.1186/1757-7241-22-2.
Lexow K. The Norwegian medical dispatch system and the Norwegian index for emergency medical dispatch. Notf Rett Med [Internet]. 2012;15:342–6. 10.1007/s10049-011-1536-7.
Nakos.no. [cited 2024 Jun 25]. https://www.nakos.no/pluginfile.php/1269/block_html/content/2019%20engelske%20hjelpetekster%20NIMN%204%20nav.pdf
Otten S, Rehbock C, Krafft T, Haugaard MV, Pilot E, Blomberg SN, et al. The unclear problem category: an analysis of its patient and dispatch characteristics and its trend over time. BMC Emerg Med [Internet]. 2022;22. 10.1186/s12873-022-00597-6.
Ibsen S, Dam-Huus KB, Nickel CH, Christensen EF, Søvsø MB. Diagnoses and mortality among prehospital emergency patients calling 112 with unclear problems: a population-based cohort study from Denmark. Scand J Trauma Resusc Emerg Med [Internet]. 2022;30. 10.1186/s13049-022-01052-y.
Møller TP, Kjærulff TM, Viereck S, Østergaard D, Folke F, Ersbøll AK, et al. The difficult medical emergency call: A register-based study of predictors and outcomes. Scand J Trauma Resusc Emerg Med [Internet]. 2017;25. 10.1186/s13049-017-0366-0.
Nielsen FV, Nielsen MR, Amstrup J, Lorenzen IL, Kløjgaard TA, Færk E, et al. Non-specific diagnoses are frequent in patients hospitalized after calling 112 and their mortality is high – a register-based Danish cohort study. Scand J Trauma Resusc Emerg Med [Internet]. 2020;28. 10.1186/s13049-020-00768-z.
Dami F, Golay C, Pasquier M, Fuchs V, Carron P-N, Hugli O. Prehospital triage accuracy in a criteria based dispatch centre. BMC Emerg Med [Internet]. 2015;15. 10.1186/s12873-015-0058-x.
Helse-. vest.no. [cited 2024 Jun 25]. https://www.helse-vest.no/om-oss/kommunar-og-innbyggjartal-per-helseforetak
11342. Areal og befolkning i kommuner, fylker og hele landet (K) 2007–2024. Statistikkbanken [Internet]. SSB. 2021 [cited 2024 Jun 25]. https://www.ssb.no/statbank/table/11342
Traumeplan NKT. [Internet]. Traumeplan.no. [cited 2024 Jun 25]. https://traumeplan.no/index.php?action=showtopic&topic=PAt8pVGd
Av S. PCI – [Internet]. Store medisinske leksikon. [cited 2024 Jun 25]. https://sml.snl.no/PCI
Flo E, Pallesen S, Åkerstedt T, Magerøy N, Moen BE, Grønli J, et al. Shift-related sleep problems vary according to work schedule. Occup Environ Med [Internet]. 2013;70:238–45. 10.1136/oemed-2012-101091.
ICD-10 version. 2019 [Internet]. Who.int. [cited 2024 Jun 25]. https://icd.who.int/browse10/2019/en
ICD-10 [Internet]. ehelse. [cited 2024 Jun 25]. https://www.ehelse.no/kodeverk-og-terminologi/ICD-10-og-ICD-11
Wachelder JJH, Stassen PM, Hubens LPAM, Brouns SHA, Lambooij SLE, Dieleman JP, et al. Elderly emergency patients presenting with non-specific complaints: Characteristics and outcomes. PLoS One [Internet]. 2017;12:e0188954. 10.1371/journal.pone.0188954.
Schmidt M, Schmidt SAJ, Sandegaard JL, Ehrenstein V, Pedersen L, Sørensen HT. The Danish National Patient Registry: a review of content, data quality, and research potential. Clin Epidemiol [Internet]. 2015;449. 10.2147/clep.s91125.

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

Characteristics and mortality of patients categorised with non-specific symptoms when dialling the emergency medical number: A register-based cohort study

Status:

Version 1

Abstract

Background

Methods

Results

Conclusions

Figures

Background

Methods

Study design and data sources

Setting

Participants

Variables and outcomes

Statistical analysis

Ethics

Results

Discussion

Characteristics of patients categorised with a non-specific problem

Mortality

Diagnoses at discharge

Strengths and limitations

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1