Shortness of breath in children at the emergency department: Variability in management in Europe.

OBJECTIVE: Our aim was to describe variability in resource use and hospitalization in children presenting with shortness of breath to different European Emergency Departments (EDs) and to explore possible explanations for variability.
DESIGN: The TrIAGE project, a prospective observational study based on electronic health record data. PATIENTS AND
SETTING: Consecutive paediatric emergency department visits for shortness of breath in five European hospitals in four countries (Austria, Netherlands, Portugal, United Kingdom) during a study period of 9-36 months (2012-2014). MAIN OUTCOME MEASURES: We assessed diversity between EDs regarding resource use (diagnostic tests, therapy) and hospital admission using multivariable logistic regression analyses adjusting for potential confounding variables.
RESULTS: In total, 13,552 children were included. Of those, 7,379 were categorized as immediate/very urgent, ranging from 13-80% in the participating hospitals. Laboratory tests and X-rays were performed in 8-33% of the cases and 21-61% was treated with inhalation medication. Admission rates varied between 8-47% and PICU admission rates varied between 0.1-9%. Patient characteristics and markers of disease severity (age, sex, comorbidity, urgency, vital signs) could explain part of the observed variability in resource use and hospitalization. However, after adjusting for these characteristics, we still observed substantial variability between settings.
CONCLUSION: European EDs differ substantially regarding the resource use and hospitalization in children with shortness of breath, even when adjusting for patient characteristics. Possible explanations for this variability might be unmeasured patient characteristics such as underlying disease, differences in guideline use and adherence or different local practice patterns.

Introduction

Children with shortness of breath form a large part of children visiting the Emergency Department (ED) [1] and in many of these children some form of resource use such as diagnostic tests, treatment with inhalation medicine or hospital admission is initiated [1-5]. Although sometimes beneficial, these forms of resource use can also have negative effects on children, their families and the health care system, as they can be painful, cause anxiety, increase ED length of stay and ED crowding and increase health care costs [6]. Furthermore, higher resource use is not automatically associated with a higher quality of healthcare or improved outcomes [7].

Observing high variation may suggest that interventions are needed to improve the standardization of management of children with respiratory complaints visiting the ED.

Although several studies have been performed regarding resource use in children with shortness of breath, most studies were performed in the United States -which has a different health care system than most European countries—focused on a specific diagnosis which is often not available at arrival at the ED or on specific forms of resource use only, such as x-rays or antibiotic prescription rates [1-5].

The aim of our study was to describe patient characteristics in children presenting with shortness of breath in five different European EDs and to assess differences in resource use between EDs after adjusting for patient characteristics and markers of disease severity, in order to identify areas with a large variation in resource use.

Methods

Study design

This study was part of the TrIAGE project: Triage Improvement Across General Emergency departments, a prospective observational study consisting of a large cohort of children visiting the ED in 5 different hospitals in 4 European countries (UK, Austria, Portugal, the Netherlands) [8]. Participating study sites were diverse regarding type of hospital, catchment area, number of ED visits, mixed adult-paediatric or paediatric ED and complexity of the patient population (S1 Table). Data collection consisted of routinely recorded, anonymized patient data, automatically extracted from electronic medical records. In order to increase completeness and accuracy of the data, we pre-specified a limited set of required variables. Data harmonization and quality checks were performed.

The study was approved by the medical ethical committees of the participating institutions: Medical Ethics Committee Erasmus MC (MEC-2013-567), Board of Directors Maasstad Ziekenhuis (L2013-103), Imperial College London Joint Research Compliance Office (14/WA/1051), Comissão de Ética para a Saúde do Hospital Prof. Dr. Fernando Fonseca EPE (Estudo Clínico TrIAGE—Parecer Favorável), Ethik Kommission Medizinische der Medizinischen Unversität Wien (EK Nr: 1405/2014). All waived the requirement for informed consent.

Study population and setting

Participating hospitals were the Erasmus MC, Rotterdam, the Netherlands (January 2012 to December 2014); Maasstad Hospital, Rotterdam, the Netherlands (May 2014 to October 2015); St Mary’s Hospital, London, United Kingdom (July 2014 to February 2015); Hospital Fernando da Fonseca, Lisbon, Portugal (March 2014 to February 2015); and General university Hospital, Vienna, Austria (January 2014 to December 2014).

Details regarding the participating hospitals are described in S1 Table.

We included all children until the age of 16 that consecutively attended the ED that presented with shortness of breath as a main complaint, defined as a Manchester triage system (MTS) flowchart of shortness of breath. The only exclusion criterion was missing data regarding presenting problem.

The MTS contains 52 flowcharts based on different presenting problems, including shortness of breath. Flowcharts contain discriminators that categorize patients into five categories of urgency, determining within how many minutes a patient should be seen by a physician [9].

Analysis included patient characteristics (age, sex, season of presentation) and markers of disease severity, such as comorbidity, increased work of breathing and vital signs: heart rate, respiratory rate, temperature, oxygen saturation and MTS urgency which was shown to be a reliable and valid reflection of urgency in children visiting the ED [10]. Vital signs were considered abnormal if they were outside the APLS reference ranges [11]. Fever was defined as a temperature of ≥ 38.0°C. Patients with MTS triage category 1 and 2 (immediate and very urgent) were classified together as very urgent. Patients with triage category 3 (urgent) were classified as urgent and patients with triage category 4 and 5 (standard and non-urgent) were classified as non-urgent. To ensure consistency among hospitals, the urgency levels according to MTS version 3 including modifications for children with fever were modelled in all hospitals [12,13].

Comorbidity was documented in free text fields and was classified into complex comorbidity, noncomplex comorbidity, and no comorbidity based on the Paediatric Medical Complexity Algorithm. This algorithm uses ICD-9 codes to distinguish three groups of comorbidity. Patients were defined as having complex comorbidity if 2 or more body systems are affected, if they suffer from a progressive condition or malignancy [14].

Referral was categorized as self-referral, referral by a primary care physician, referral by ambulance or other (e.g. referral by specialist). To facilitate comparison by severity and distinguish patients with a more severe clinical presentations or ED course from those with a less severe presentation or ED course, we developed three clinical categories of severity. Children were classified as severe if they had triage category 1 (immediate) or 2 (very urgent), or had 2 or more abnormal vital signs or had severe work of breathing or received oxygen therapy or received a life-saving intervention or were admitted to the PICU. Children were classified as non-severe if they had triage category 3, 4 or 5 and had no abnormal vital signs or increased work of breathing. All other children were classified as intermediate severity.

The main outcome measure were resource use and disposition. Resource use was categorized into diagnostics (laboratory tests and imaging) and therapy (inhalation or intravenous medication administered at the ED) at the ED.

Laboratory tests were defined as any blood test that was performed at the ED. Imaging was defined as any X-ray that was performed at the ED.

Inhalation medication was defined as any inhalation medication that was given at the ED. Intravenous medication was defined as either intravenous medication or intravenous fluid given at the ED, except in the Dutch teaching hospital, where only information on intravenous medication was available. Oral medication was not included in the analysis as this was not reliably available.

Immediate life-saving interventions were adapted from Lee et al. [15] and were categorized into the following categories: airway and breathing support, electrical therapy (e.g. cardioversion), emergent procedures, hemodynamic support and emergency medications (S2 Table).

Disposition was defined as discharge, admission and PICU admission after the ED visit.

Data analysis

For vital signs, the first measurement at triage was used for analysis. Missing vital signs, capillary refill and level of consciousness were imputed using multiple imputation, a widely used technique for handling missing data, which has shown good performance in several studies [16,17].

The imputation model included age, sex, type of referral, MTS flowchart and urgency, time of arrival, vital sign values, work of breathing, capillary refill, level of consciousness, diagnostic tests, medication, oxygen therapy, life-saving interventions and disposition of all hospitals combined. This imputation process resulted in twenty-five databases on which statistical analysis were performed and pooled for a final result [18].

Imputation was performed by using the MICE imputation package in R, version 2.15.2.

We conducted descriptive analyses to explore differences between settings regarding patient characteristics, resource use and hospitalization. We used multivariable logistic regression models to assess the association between study site, resource use and hospitalization. Dependent variables were: hospital lab tests, x-ray’s, inhalation medication, intravenous medication, hospital admission, and PICU admission.

The analyses were adjusted for age, sex, season, urgency level, abnormal vital signs and increased work of breathing, as these were considered potential confounding variables. All variables, including hospital, were included as categorical variables. Odds ratios were considered significant when the 95% confidence interval did not include 1. Analyses were performed using SPSS software (version 25.0).

Results

Patient characteristics and markers of disease severity

The total population consisted of 119,209 ED visits, of which 1,762 children (1.5%) were excluded due to a missing MTS flowchart. 13,552 (11.4%) children with shortness of breath were included for the analysis.

In all centers around half of all patients was below the age of 2 years. Patients presented most frequently in autumn or winter and least frequently in summer.

Children in the ED in Portugal were most often classified as immediate/very urgent (79.6%) while this was a minority in Austria (12.8%).

Most patients in the UK and Portugal were self-referred (81.9% and 95.9% respectively), while in the Dutch teaching hospital the majority was referred by a primary-care physician (72.0%).

Before imputation, vital signs were available with the following frequency: heart rate 93.7% (range between hospitals 91.0%-95.8%), respiratory rate 70.0% (range 15.2%-93.0%), temperature 94.9% (range 84.0%-99.7%) and oxygen saturation 97.0% (range 91.6%-99.8%).

The rate of tachypnoea varied between 3.9% in Austria and 49.2% in the UK. Fifty-nine percent of children were classified as severe (range between hospitals: 19.1–80.3%), 15% intermediate (range between hospitals 4.6–25.8%) and 26% non-severe (range between hospitals 13.7–55.1%). Detailed patient characteristics are shown in detail in Table 1.

Table 1

Patient characteristics and markers of disease severity in percentage across EDs in Europe.

Number 13,552 overall	NL tertiary N = 1,558 N (%)	NL teaching N = 1,268 N (%)	UK N = 1,639 N (%)	PT N = 5,729 N (%)	AT N = 3,358 N (%)	P-value
Sex
Male	961 (61.7)	814 (64.2)	1,028 (62.7)	3,282 (57.3)	1,904 (56.7)	<0.001
Comorbidity	848 (54.4)	(<10*)	295 (18.0)	(<10*)	367 (10.9)	<0.001
Age						<0.001
0–2 years	798 (51.2)	713 (56.2)	736 (44.9)	2,846 (49.7)	1,572 (46.8)
2–5 years	343 (22.0)	346 (27.3)	537 (32.8)	1,517 (26.5)	1,035 (30.8)
≥ 5 years	417 (26.8)	209 (16.5)	366 (22.3)	1,366 (23.8)	751 (22.4)
Referral						<0.001
Self	419 (26.9)	212 (16.7)	1,336 (81.9)	5,476 (95.9)	(>90*)
Primary care	405 (26.0)	913 (72.0)	36 (2.2)	0 (0.0)	no data
Emergency service	139 (8.9)	57 (4.5)	89 (5.5)	232 (4.1)	no data
MTS urgency						<0.001
Immediate/very urgent	753 (48.3)	767 (60.5)	867 (52.9)	4,563 (79.6)	429 (12.8)
Urgent	149 (9.6)	348 (27.4)	152 (9.3)	117 (2.0)	415 (12.4)
Standard/non-urgent	656 (42.1)	153 (12.1)	620 (37.8)	1,049 (18.3)	2,513 (74.8)
Abnormal vital signs
Fever	587 (37.7)	455 (35.9)	443 (27.0)	645 (11.3)	571 (17.0)	<0.001
Oxygen saturation ≤ 94	220 (14.1)	157 (12.4)	132 (8.1)	578 (10.1)	162 (4.8)	<0.001
Tachypnoea	739 (47.7)	593 (46.8)	806 (49.2)	1,822 (31.8)	130 (3.9)	<0.001
Tachycardia	438 (28.1)	446 (35.2)	385 (23.5)	1,345 (23.5)	481 (14.3)	<0.001
Increased work of breathing	995 (63.9)	677 (53.4)	913 (55.7)	4,393 (76.7)	557 (16.6)	<0.001
Severity classification						<0.001
Severe	959 (61.6)	870 (68.6)	968 (59.1)	4599 (80.3)	641 (19.1)
Intermediate	385 (24.7)	218 (17.2)	281 (17.1)	266 (4.6)	866 (25.8)
Non-severe	214 (13.7)	180 (14.2)	390 (23.8)	864 (15.1)	1851 (55.1)

NL teaching = Maasstad Hospital, Rotterdam, the Netherlands; NL tertiary = Erasmus MC, Rotterdam, the Netherlands; UK = St Mary’s Hospital, London, United Kingdom; PT = Hospital Fernando da Fonseca, Lisbon, Portugal; AT = General Hospital, Vienna, Austria.

* * overall data for this setting, not available for each individual patient.

Practice variation between hospitals

Laboratory tests or X-rays were performed in 8–33% of all children. Inhalation medication was prescribed to 46% of all children and 38% of children younger than 1 year. After adjusting for patient characteristics and markers of severity the rate of laboratory tests was highest in the Austrian Hospital (adjusted OR 5.3, 95% CI 4.3–6.6) while X-rays were performed most often in the Portuguese hospital (adjusted odds ratio 8.8, 95% CI 7.0–11.1, Tables 2 and 3 and S3 Table).

Table 2

Heatmap for different ages with odds ratios of resource use, corrected for patient characteristics.

	NL tertiary	NL teaching	UK	PT	AT
	aOR	aOR	aOR	aOR	aOR
Blood tests all children	3.9*	1.2**	+	1.4*	5.3*
< 1 year	3.4*	1.2**	+	1.8*	5.8*
> 1 year	4.1*	1.3**	+	1.2**	5.1*
X-rays all children	5.0*	+	2.3*	8.8*	4.1*
< 1 year	11.6*	+	5.6*	17.7*	11.2*
> 1 year	4.0*	+	1.9*	7.5*	3.3*
Inhalation medication all children	1.1**	1.6*	1.7*	2.2*	+
< 1 year	1.2**	1.8*	+	3.0*	1.8*
> 1 year	1.3*	1.8*	2.4*	2.4*	+
Intravenous medication all children	2.0*	4.1*	+	1.3**	1.1**
< 1 year	2.5*	3.7*	+	1.3**	1.6**
> 1 year	1.7*	4.4*	1.0**	1.2**	+
General admission all children	9.8*	7.6*	4.0*	+	2.2*
< 1 year	6.6*	4.6*	1.4*	+	1.4*
> 1 year	12.6*	11.1*	6.8*	+	2.9*
ICU admission all children	75.8*	1.7**	2.6**	8.5*	+
< 1 year	78.0*	+	1.2**	15.9*	1.8**
> 1 year	117.7*	3.4**	4.9**	7.1**	+

#Associations are determined by multivariable logistic regression models. Model adjusted for sex, age, season, triage urgency, fever, tachycardia, tachypnoea, low oxygen saturation and increased work of breathing.

+ reference.

* P-value <0.01.

** not significant.

NL teaching = Maasstad Hospital, Rotterdam, the Netherlands; NL tertiary = Erasmus MC, Rotterdam, the Netherlands; UK = St Mary’s Hospital, London, United Kingdom; PT = Hospital Fernando da Fonseca, Lisbon, Portugal; AT = General Hospital, Vienna, Austria.

Table 3

Heatmap for patients with different severity with odds ratios of resource use, corrected for patient characteristics.

	NL tertiary	NL teaching	UK	PT	AT
	aOR	aOR	aOR	aOR	aOR
Blood tests all children	3.9	1.2**	+	1.4	5.3
severe	3.6	+	1.0**	1.3**	5.6
non severe	14.3	4.7	+	4.3	11.7
X-rays all children	5.0	+	2.3	8.8	4.1
severe	4.7	+	2.3	8.0	4.3
non severe	9.1	+	2.3**	21.0	7.3
Inhalation medication all children	1.1**	1.6	1.7	2.2	+
severe	+	1.5	1.7	2.0	1.0**
non severe	+	2.9	2.0	4.6	1.8
Intravenous medication all children	2.0	4.1	+	1.3**	1.1**
severe	1.8	3.0	1.0**	+	1.6
non severe	9.9	65.8	+	15.1	4.3**
General admission all children	9.8	7.6	4.0	+	2.2
severe	10.0	6.9	4.1	+	2.4
non severe	10.7	12.6	1.9**	+	1.6**
ICU admission all children	75.8	1.7**	2.6**	8.5	+
severe	52.2	1.4**	2.0**	6.2	+
non severe	n.a.	n.a.	n.a.	n.a.	n.a.

#Associations are determined by multivariable logistic regression models. Model adjusted for sex, age, season, triage urgency, fever, tachycardia, tachypnoea, low oxygen saturation and increased work of breathing.

+ reference.

* P-value <0.01.

** not significant.

NL teaching = Maasstad Hospital, Rotterdam, the Netherlands; NL tertiary = Erasmus MC, Rotterdam, the Netherlands; UK = St Mary’s Hospital, London, United Kingdom; PT = Hospital Fernando da Fonseca, Lisbon, Portugal; AT = General Hospital, Vienna, Austria.

n.a. = not applicable.

After adjustment, inhalation medication was prescribed least often in the Austrian hospital (reference) and most often in the Portuguese hospital (adjusted OR 2.2, 95% CI 1.9–2.5). Intravenous medication was prescribed least often in the UK hospital (reference) and most often in the Dutch teaching hospital (adjusted OR 4.1 (95% CI 3.1–5.5) (S4 Table).

In total 2,362 children (17.4%) were admitted to a general ward. After adjustment, admission occurred most often in the Dutch tertiary hospital (adjusted OR 9.8, 95% 8.3–11.5) and least often in the Portuguese hospital (reference). Paediatric Intensive Care Unit (PICU) admission occurred most often in the Dutch tertiary hospital (adjusted OR 75.8, 95% CI 18.5–310.7, Tables 2 and 3 and S5 Table). This did not include interhospital transfers, as these children are admitted to the ICU directly.

Settings with a high rate of lab tests did not consistently have a high rate of imaging, therapy or hospital admission. Comorbidity could explain some but not all of the variance found between hospitals. Sub-analysis of the settings with ≥ 10% comorbidity (Vienna, London and the tertiary hospital in Rotterdam), showed higher resource use in children with comorbidity, especially in children with complex comorbidity (S6 Table). In the sub-analysis of children without comorbidity, the overall variability in resource use and hospitalization remained similar in the 5 EDs (S7 Table).

Furthermore, a sub-analysis of children with a past medical history of asthma, (three settings, N = 529) still shows considerable variation in resource use, including the use of inhalation medication or and lab tests (S8 Table).

To reduce the impact of the large number of missing values for respiratory rate in one setting, two additional analyses were performed. First, a sub-analysis excluding the setting with a large number of missing values for respiratory rate was performed, which showed similar variation between the remaining four EDs compared to the original analysis (S9 Table). Second, a complete case analysis for respiratory rate was performed, which showed similar variation compared to the original analysis (S10 Table).

Practice variation by age groups

Table 2 describes variation in resource use for different age groups. In general, EDs that had high rates of resources in all patients, showed comparable high rates in the age group below or above 1 year. There was no clear pattern between age group and resource use, e.g. in some EDs resource use was higher in younger children while in other settings resource use was higher in older children; no increased uniformity in resource use between EDs was observed when looking separately at young children or children above 1 year old (Tables 2 and 3 and S3–S5 Tables).

Practice variation by severity

In children with a severe presentation the rate of laboratory tests, x-rays and iv medication was higher at three EDs, while in the other two settings there was no significant difference between severity groups. There was no relationship between severity and the prescription of inhalation medication at any setting. In 4 out of 5 EDs, children with a severe presentation were admitted more often.

In general, EDs that had high or low rates of resources, had similar trends in the severe as well as the non-severe group (Table 3 and S3–S5 Tables). When performing a separate analysis after removing patients with triage urgency immediate (the highest acuity group), similar trends with high variability in all types of resource use were seen (S11 Table).

Discussion

Statement of principal findings and findings in relation to the literature

Our results show marked variability in the resource use and hospitalization in children presenting to the ED with shortness of breath. Marked variability between EDs remained after adjusting for patient characteristics and markers of disease severity.

Subgroup analyses by age groups still showed considerable variation between hospitals.

In general, EDs that had high or low rates of specific types of resource use, showed similar patterns in different age or severity groups.

Overall, variation was lower in the severe group than in the non-severe group and showed considerable variation between settings; variation in the non-severe group was highest in diagnostic tests and therapy.

Regarding specific forms of resources, variation was most pronounced in the performance of x-rays, especially in children below 1 year of age.

Furthermore, considerable variation in hospital admission was seen in patients of all ages and both in the severe and non-severe group.

Comparable to our results, previous studies have described high variability in children presenting to the ED with respiratory problems such as bronchiolitis, asthma, croup and pneumonia, even in the presence of guidelines [1-5]. Moreover, in our study this variability remained after correcting for several patient characteristics and markers of disease severity.

Factors which might explain this variation include seasonal trends, availability of immunization, availability of primary care, type of ED or physician background [1,2,5,19], parental demand [20], availability of point-of-care tests [21,22], and variability, availability and adherence to guideline content [23-25].

A recent study on guideline availability found that the use of inhalation medication in the management of bronchiolitis had increased despite national guidance to withhold inhalation medication [25].

Specific seasonal [26], and geographical [27] trends are known to influence the incidence of respiratory tract infections and thus consequently can influence resource use. Furthermore, immunization and immunization rates differ per country [28,29]. For example, while immunization against Haemophilus Influenzae Type B and pneumococcal disease is offered routinely in all participating countries, influenza immunization is offered routinely to children in the UK only [28]. Although we did not collect detailed data regarding (viral) diagnosis, as our data collection consisted of at least 12 months and including all seasons in all settings but one and we included season in our analysis, this did not explain the marked differences we found between EDs.

Primary care availability and mode of referral can have an impact on the ED patient case mix and consequently on resource use and hospitalization [30,31].

Our study showed marked variability in self-referral rates between different settings as in some settings a primary care physician was not available, or was bypassed, especially during out-of-office hours. Although we did not adjust for mode of referral in the whole analysis as detailed referral information was available in four out of five settings, sub-analysis in these four settings still showed large variation after adjusting for mode of referral (S12 Table). Furthermore, we did adjust for patient case mix by adjusting for markers of disease severity and thus indirectly adjusted for mode of referral, as this influences patient case mix.

Previous research showed that type of ED (dedicated paediatric or mixed) and physician background [1,2,5,19] can influence resource use and hospitalization. As in our dataset most settings were a dedicated paediatric ED and in all but one setting children were seen exclusively by a paediatrician, it is not likely that this factor alone explains the variation we found in our study.

We used standardized routine data for our study. Using large datasets of routinely obtained observational data (“big data”) is gaining in popularity [32], as it poses many benefits, such as presenting large amounts of patient data [32] with opportunities for generating new insights and analyzing complex correlations between patient factors and outcomes.

However, one must realize that data from different settings are not always comparable and other factors than patient-factors alone, such as local factors can influence resource use and hospitalization. Therefore, combining these datasets and interpreting results should be done with caution and with an eye on local factors. Even outcome measures that are considered to be objective and comparable at first glance, such as hospital and PICU admission, can be influenced by local protocols and thus can reflect other factors than disease severity alone.

Implications for clinical practice and research

Variability in management reflects high and potentially avoidable resource use, which increases health care costs, ED crowding, adverse events and reduces quality of care [3,33].

Reduction of this variability is a good starting point to decrease healthcare costs and improve quality of care [33].

The use of clinical practice guidelines can potentially reduce variability and improve quality of care [3], however, the mere availability of guidelines does not automatically entail guideline adherence [1,34-36]. Several studies have shown that interventions to improve guideline adherence reduce resource use without negatively affecting other outcomes such as hospital admission rates [23,37-40]. Furthermore, other interventions, such as bedside viral tests or a bedside CRP test, can positively impact resources use, such, x-rays, antibiotic use and hospital admission [22].

Our data identifies a large group of children that can benefit from adherence to guidelines and bedside tests.

Strengths and limitations

To our knowledge, this is the first study that describes variability in the management of children with shortness of breath at European EDs. The main strength of our study includes the large number of patients and that data were collected from 5 settings in 4 European countries, which increases the generalizability of the results. Furthermore, university as well as non-university hospitals participated in this study.

The enrolment period varied between the different hospitals. However, each hospital was followed for at least 8 months and in all hospitals a winter season was included to increase the comparability between settings. In one setting, only information on intravenous medication was available and not intravenous fluid, but even with this information lacking, this setting still showed the highest use of intravenous therapy. For all other variables, uniform definitions were used.

Our data does not contain information regarding diversity in antibiotic use. Antibiotic use, however, has been extensively studied previously [41] and only a minority of acute respiratory problems in children are of bacterial origin [42]. In this study we focused on initial diagnostic tests, inhaled medication, iv medication and hospitalization.

Although we adjusted for patient characteristics and markers of disease severity, we cannot exclude that unmeasured aspects of patient or setting characteristics, such as past medical history, tests or interventions performed prior to arrival at the ED, immunization status, availability of primary care or physician experience and background, could still be of influence.

We used presenting symptom as the main inclusion criterion and not final diagnosis, which is usually not available in the early phase of the diagnostic process. This resulted in a heterogeneous study population of children with different final diagnoses, such as upper respiratory tract infections, viral and bacterial lower respiratory tract infections, viral induced wheezing and asthma. Although our study included children with these different final diagnoses, and in part management depends on the final diagnosis, there is also considerable overlap in the management of these diagnoses.

At the ED final diagnoses are missing in many cases and diagnostics and interventions are based on a working diagnosis. Discrimination between different cause of respiratory illness can be difficult. Participating countries’ national guidelines regarding the main final diagnoses of children visiting the ED with shortness of breath, such as asthma, bronchiolitis and pneumonia, clearly state that diagnostic tests such as blood tests or x-rays have no place in the assessment of children with any of these diagnoses, except in atypical or severe cases (e.g. children that require PICU admission) [43-46], except the National Portuguese guidelines [47] which advice to perform lab tests in all children with suspected bacterial disease and X-rays in children with bronchiolitis with suspected bacterial infection. Although this might explain the high rate of X-rays that were seen in the Portuguese setting, our data still showed large variation in resource use and hospitalization in the severe as well as the non-severe group of children with respiratory symptoms that cannot be explained by guideline content. Furthermore, inhalation medication is not recommended in children with respiratory complaints and wheezing below the age of 1 year, as these complaints are usually caused by bronchiolitis, and there is no evidence of a positive effect of inhalation medication in this age group. However, we still found high use and high variation of inhalation medication in this specific age group [48]. Lastly, hospital admission in general is guided by disease severity and not by final diagnosis [43-47].

Finally, our results should be interpreted in light of the limitations of using standardized routinely collected data and missing data. In our study, there was a number of missing vital signs, especially respiratory rate. However, this reflects actual routine care at many EDs [49] and is one of the limitations of using routine data. For example, the multicenter study of van de Maat et al. showed that complete vital sign measurement (temperature, heart rate, respiratory rate and capillary refill) occurred in only half of pediatric ED visits and respiratory rate was the vital sign missing most frequently [49]. In our study, the median number of vital sign measurement and other clinical variables were large enough to perform multiple imputation of the missing values. When using routine data for research purposes, multiple imputation is considered a useful strategy for handling missing data and superior to other methods; this statement is supported by several simulation studies, including simulation studies showing unbiased results even with large proportions of missing data, provided sufficient auxiliary information was available [16-18,50,51]. Furthermore, we performed two sub-analyses, excluding the setting with the largest number of missing values for respiratory rate, and a complete case analysis for respiratory rate and found similar variation between ED’s in comparison to the results of the original imputed dataset.

Conclusion

Our data show that large variability in resource use and hospitalization exist in children with respiratory complaints visiting European EDs and that variability remains high even after adjusting for patient characteristics and disease severity. Possible explanations could be differences in guideline content or adherence or differences in local practice patterns. Our data show that given the high variability we found, there is a large opportunity for improvement of management and reduction of health care costs in this common clinical problem.

"What is already known on this topic"

Resource use and hospitalization rates at the ED are widely variable.

Resource use is influenced by patient level factors and hospital level factors

"What this study adds"

Large variability exist in European EDs regarding the use of diagnostic tests, initiated therapy and hospitalization in children with shortness of breath.

Variability in management between settings cannot be explained by severity of symptoms only.

Children with shortness of breath form a large patient group with room for improvement regarding uniform management and reduction of resource use.

Description of the different study sites.

(PDF)

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Immediate life-saving interventions.

(PDF)

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Differences in diagnostic tests between EDs.

(PDF)

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Differences in medication between EDs.

(PDF)

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Differences in hospital admission between EDs.

(PDF)

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Differences in resource use in children with and without comorbidity.

(PDF)

Click here for additional data file.

Heatmap with odds ratios of resource use, excluding patients with comorbidity.

(PDF)

Click here for additional data file.

Heatmap with odds ratios of resource use for children with a past medical history of asthma.

(PDF)

Click here for additional data file.

Heatmap with odds ratios of resource use, excluding patients from the ED in Austria.

(PDF)

Click here for additional data file.

Heatmap with odds ratios of resource use, complete case analysis for respiratory rate.

(PDF)

Click here for additional data file.

Heatmap with odds ratios of resource use, excluding patients with triage urgency “immediate”.

(PDF)

Click here for additional data file.

Heatmap with odds ratios of resource use, including correction for referral.

(PDF)

Click here for additional data file.

2 Oct 2020

PONE-D-20-19274

Shortness of breath in children at the emergency department: variability in management in Europe.

PLOS ONE

Dear Dr. Borensztajn,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Nov 16 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

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If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Brenda M. Morrow, PhD

Academic Editor

PLOS ONE

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #2: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: I Don't Know

Reviewer #2: I Don't Know

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #2: Yes

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

Reviewer #2: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: This article examines the variation in management of children presenting to the emergency departments across multiple institutions. This variation could represent opportunities for standardization of management to improve patient care.

Major:

-Imputation used for missing values. RR range of completion reported 15-93% which concerns me for this to be used as one of the main variables used for an illness severity marker.

-Discussion organization can be improved, current form seems to be more of a list of findings, would be helpful to add how this compares to other studies and applying the findings to clinical practice. I would focus more on why variation matters (cost, outcomes, etc) and that guidelines have been shown to improve this.

Minor

-How were comorbidities obtained? Problem list versus billing data?

- Knowing the specific respiratory past medical history would be helpful in interpreting data, especially the use of inhalation medications (i.e. asthma, BPD)

-How was increased work of breathing measured? Subjective by provider versus scoring system, if the latter is it a validated tool?

-Were vital signs recorded just initial or ongoing?

-What is electrical therapy? (line 181)

-Results: Good sample size overall, but almost half of encounters were from same hospital

-Statement majority had abnormal respiratory rate, but <50% at each site reported to be tachypnic in table 1

-abstract “categorized as very urgent ranging from 13-80%" (but in results you give 12.1 and 77% as the range)

- Alternate between commas and periods used as decimal points in text and tables

- Line 264-265 add p-value for sub-analysis

-Limitations that should be highlighted: missing factors noted to impact resource use in other studies not included in this study, unable to account for relevant pmh specific to management approach, unknown what testing/management prior to arrival for referred patients

-appendix 1 include p-values comparing sites. What does the estimation annotation mean?

Reviewer #2: This is an interesting study focused on a different way of approaching the evaluation of variability in healthcare settings. This focuses on the chief complaint of shortness of breath as opposed to diagnosis-based assessment of variability. However, they did perform statistical analysis to try to adjust for the diversity of patient population both in acuity and other possible confounding factors. The triage process was standardized throughout hospitals.

Consider removing Triage level 1 acuity (highest acuity) as this population likely should not be a population that decreases variation, in fact most patients in this category likely get a large amount of resource utilization which is likely appropriate.

With the analysis did you cluster by hospital center?

I have some concerns that the respiratory rate was missing most frequently (70% of the time, but down to 15% at its worst) in a manuscript that is addressing variability in patient presenting with shortness of breath. Can you explain this?

I think my largest concern is related to whether or not your dataset has data related to patient diagnosis to be able to adjust for differences related to a patient resource utilizations with pneumonia versus asthma. As those two presentations although may have the same chief complaint, they likely require two different workups and are based on an provider assessment.

You should consider that the tertiary center may have increased use of the ICU due to transfers from outside hospitals and have higher acuity patients. Did you account for interhospital transfers?

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Aleisha M Nabower

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

30 Nov 2020

Dear Ms. Morrow, dear reviewers

Thank you for your time, effort and expertise in reviewing our manuscript and taking it under consideration for publication.

We have adapted the manuscript according to the comments and we think that the manuscript improved after these important comments.

Please find our response uploaded as an attachment.

kind regards

Dorine Borensztajn

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

2 Feb 2021

PONE-D-20-19274R1

Shortness of breath in children at the emergency department: variability in management in Europe.

PLOS ONE

Dear Dr. Borensztajn,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Mar 19 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Brenda M. Morrow, PhD

Academic Editor

PLOS ONE

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: (No Response)

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Partly

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: I appreciate the authors addressing many of the questions that I raised. My one major concern still surrounds the following:

1) Use of the multiple imputation methodology in a manuscript describing variability in approach to shortness of breath with the vital sign that is missing most being the respiratory rate. Multiple imputation seems to be a helpful tool but I worry when it is replacing missing data within a primary variable (respiratory rate) related to the manuscripts main outcome. While I recognize that this data may not exist I worry about making conclusions based on this methodology. You could consider removing the hospital that has only 15% of the respiratory rate vital sign present with the hopes that you increase the median enough to make this more valid and hopefully supporting an accurate conclusion.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

3 Apr 2021

Dear editor, dear reviewers

Thank you for your time, effort and expertise in reviewing our manuscript and taking it under consideration for publication.

We have adapted the manuscript according to the comments and we think that the manuscript improved after these important comments.

Please find our response attached as a separate file.

Submitted filename: rebuttal.plosone.docx

Click here for additional data file.

20 Apr 2021

Shortness of breath in children at the emergency department: variability in management in Europe.

PONE-D-20-19274R2

Dear Dr. Borensztajn,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Brenda M. Morrow, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #2: All comments have been addressed

**********

2. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #2: Yes

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #2: I Don't Know

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #2: Yes

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #2: Yes

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #2: I feel that the authors have adequately addressed my concerns that were raised in the previous reviews. Thank you.

**********

7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #2: No

23 Apr 2021

PONE-D-20-19274R2

Shortness of breath in children at the emergency department: variability in management in Europe.

Dear Dr. Borensztajn:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Professor Brenda M. Morrow

Academic Editor

PLOS ONE