Literature DB >> 28607037

International comparison of emergency hospital use for infants: data linkage cohort study in Canada and England.

Katie Harron1, Ruth Gilbert2, David Cromwell1, Sam Oddie3, Astrid Guttmann4, Jan van der Meulen5,6.   

Abstract

OBJECTIVES: To compare emergency hospital use for infants in Ontario (Canada) and England.
METHODS: We conducted a population-based data linkage study in infants born ≥34 weeks' gestation between 2010 and 2013 in Ontario (n=253 930) and England (n=1 361 128). Outcomes within 12 months of postnatal discharge were captured in hospital records. The primary outcome was all-cause unplanned admissions. Secondary outcomes included emergency department (ED) visits, any unplanned hospital contact (either ED or admission) and mortality. Multivariable regression was used to evaluate risk factors for infant admission.
RESULTS: The percentage of infants with ≥1 unplanned admission was substantially lower in Ontario (7.9% vs 19.6% in England) while the percentage attending ED but not admitted was higher (39.8% vs 29.9% in England). The percentage of infants with any unplanned hospital contact was similar between countries (42.9% in Ontario, 41.6% in England) as was mortality (0.05% in Ontario, 0.06% in England). Infants attending ED were less likely to be admitted in Ontario (7.3% vs 26.2%), but those who were admitted were more likely to stay for ≥1 night (94.0% vs 55.2%). The strongest risk factors for admission were completed weeks of gestation (adjusted OR for 34-36 weeks vs 39+ weeks: 2.44; 95% CI 2.29 to 2.61 in Ontario and 1.66; 95% CI 1.62 to 1.70 in England) and young maternal age.
CONCLUSIONS: Children attending ED in England were much more likely to be admitted than those in Ontario. The tendency towards more frequent, shorter admissions in England could be due to more pressure to admit within waiting time targets, or less availability of paediatric expertise in ED. Further evaluations should consider where best to focus resources, including in-hospital, primary care and paediatric care in the community. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Entities:  

Keywords:  emergency department; health services research; healthcare quality improvement; hospital medicine; paediatrics

Mesh:

Year:  2017        PMID: 28607037      PMCID: PMC5750429          DOI: 10.1136/bmjqs-2016-006253

Source DB:  PubMed          Journal:  BMJ Qual Saf        ISSN: 2044-5415            Impact factor:   7.035


Background

Paediatric emergency admissions in England have risen by a third over the past decade and are continuing to rise.1 2 For serious conditions, admissions are necessary and appropriate. However, the majority of unplanned admissions within the first year of life are for minor conditions, particularly minor infections, which could be treated outside hospital.1 3 Responding to infant illness in ways that avoid emergency admission could help reduce inconvenience to families (eg, emotional distress, interruption of work or school) and the risk of iatrogeny (eg, hospital-acquired infection or medical errors). However, there is a lack of evidence on the best approaches to reducing unplanned infant admissions.4 Analyses of trends over time in admission rates have provided important insights into how changes to policy influence paediatric healthcare use (eg, how UK primary care policy reforms aimed at improving working conditions for physicians and outcomes for patients are related to increasing rates of short-stay paediatric admissions).1 5 Comparisons of healthcare use in different settings provide further opportunities to identify determinants of variation in service use.6 Specifically, Ontario (Canada’s largest province) and England have similar cultural and environmental risk factors and similar levels of child poverty.7 Both countries offer universal healthcare systems, with no user fees at the point of care. General practitioners (GPs) also operate similar gatekeeper functions in both countries, referring families to hospital where appropriate. However, important organisational differences between these jurisdictions provide an opportunity to understand how different policies and service provision may contribute to paediatric acute healthcare use. For example, although most of the Ontario population has a primary care provider, access to a doctor out of hours without attending emergency department (ED) is very low in comparison to other OECD (Organisation for Economic Co-operation and Development) countries.8 Primary care reform in Ontario has attempted to improve access through incentives aimed at general/family practitioners, although children also receive primary care from paediatricians (predominantly in urban centres).9 There are also differences in postnatal support during early infancy: all families in England are supported by home visiting by qualified midwives and health visitors, whereas follow-up is less well established in Ontario, where only 9% of pregnant mothers are cared for by a midwife and less than 35% of low-risk newborns receive the recommended follow-up visit in the first week of life.10–12 While Canada has a well-established history of paediatric emergency medicine (PEM) in tertiary centres and a system of consultant paediatricians in the ED in large community hospitals,13 consultant PEM provision in the UK varies regionally, and is only recommended for emergency care settings seeing more than 16 000 children per year (around half of EDs in the UK).14 Finally, ED wait time targets also differ between countries: in England, 95% of patients attending an ED should be seen, treated, admitted or discharged in under 4 hours (98% prior to 2010), whereas in Ontario, 90% of ED visits for patients with only minor or uncomplicated conditions are expected to be completed within 4 hours. We performed an in-depth comparison of emergency hospital use during infancy, a time of high need for acute care, within which admissions may be avoidable, and a time when neonatal morbidity and social risk factors may be especially important. We evaluated both inpatient admissions and ED visits in order to gain an overall picture of hospital contact. We aimed to identify differences in patterns of hospital use and maternal and neonatal risk factors, based on standardised birth cohorts of healthy populations, derived from linked administrative hospital data.

Methods

Data sources

We extracted data for Ontario from linked population-based administrative databases at the Institute for Clinical and Evaluative Sciences in Toronto.15 Eligible mothers and infants were identified from the Registered Persons Database, which holds information on all Ontario residents (currently over 13 million) with a provincial health card number. Linked maternal and newborn health records were extracted from the MOMBABY dataset, which provides information on all births in hospitals in Ontario and is linked using a unique health card number. Inpatient admissions and ED visits were extracted for all hospitals providing acute inpatient facilities in Ontario from the Canadian Institute of Health Information Discharge Abstract Database and the National Ambulatory Care Reporting System Database. For England, data were extracted from Hospital Episode Statistics (HES).16 HES is an administrative database holding detailed information for all admissions to National Health Service (NHS) hospitals in England. Maternal and baby birth characteristics were linked using non-identifiable clinical and demographic information available on the main HES record (including admission dates, postcode district and GP practice) and delivery information contained in the ‘baby tail’ (including gestational age, birth weight and mode of delivery). Full details of the linkage have been published elsewhere.17 Inpatient admissions and ED visits were extracted from the Admitted Patient Care dataset and the Accident & Emergency dataset. For both countries, hospital records are collected for reimbursement purposes, and are encoded, allowing admissions for the same patient to be tracked over time. Admission records allow the entry of multiple fields of clinical diagnoses (24 fields in Ontario, 20 in England) coded using the International Statistical Classification of Diseases and Related Health Problems 10th Revision (ICD-10).

Study population

Our study population comprised newborns alive at postnatal discharge. Newborns <34 weeks’ gestation were excluded due to their more complex health needs (1.8% of births in Ontario and 1.7% of births in England). Since we knew that gestational age distributions differed between countries, and expected that gestational age would be strongly predictive of healthcare contact, we stratified results by late-preterm (34–36 weeks), early-term (37–38 weeks) or full-term (39+ weeks) births. We focused our analysis on data on births from April 2010 onwards, as ED data were not available in England prior to this time. Follow-up data were complete until March 2014 for all births before 1 March 2013. We therefore included births between 1 April 2010 and 1 March 2013. We also plotted trends in admissions from April 2005 onwards. For mothers with multiple deliveries during the study period, we randomly selected one delivery for inclusion in analyses, to avoid clustering of outcomes by mother. We excluded infants with missing gestation or birth weight or suspected coding errors (birth weight >4 SDs from the average according to published reference values for each country).18 19 For England, the percentage of births excluded due to missing values ranged from 10% in 2010/2011 to 7% in 2012/2013. The level of missing data in the Ontario data was negligible (<1%).

Outcomes

All outcomes were captured in hospital records up to 12 months from postnatal discharge. The primary outcome was the percentage of infants with one or more unplanned admissions. Admissions were defined as unplanned based on the method of admission coded within the hospital record, and were defined as episodes of care starting more than 2 days following the end of a previous admission. Transfers between hospitals were not counted as readmissions. We also evaluated a number of secondary outcomes. We compared ED visits to any hospital (with or without subsequent admission). For England, ED data were provided for all NHS hospitals included in the study population (n=152), but reliable ED diagnosis data were not available. To measure overall hospital contact, we compared the percentage of infants with any emergency contact (unplanned admission or ED) and the total number of inpatient days from unplanned admissions (both including and excluding the birth episode). We also compared postdischarge deaths. A further secondary outcome was overnight admissions, where infants were admitted and discharged on different days (ie, admissions starting and ending on the same day were excluded). Finally, we compared the number of unplanned admissions for different diagnosis groups, based on the 10 most frequently occurring ICD-10 code groups in the main diagnosis fields for admission records in each country.

Risk factors

Gestational age in completed weeks was obtained from the linked maternal-baby data, based on best estimates from menstrual dates or ultrasound. Small or large for gestation (<10th or >90th percentile of birth weight for gestation) was derived from national birth weight percentiles.18 19 Delivery by caesarean section, sex, multiple birth, admission to neonatal intensive care, season of discharge and maternal age were considered as additional covariates. Measures of deprivation were obtained via postal code of residence mapped to neighbourhood income quintile in Ontario, and Index of Multiple Deprivation (IMD) for England.20 Based on code lists used in previous studies, we also derived a number of pregnancy, delivery and neonatal risk factors using ICD-10 codes recorded in any diagnosis field during the birth episode or pregnancy (see table 1 and online supplementary appendix table 1 for code lists).21 22 We explored trends by including a variable for quarterly trend, that is, taking values of 1–12 for each quarter year of postnatal discharge between April 2010 and March 2013. We also plotted outcomes by quarter. Due to the size of the datasets, p values for differences in outcomes between countries were not presented, as all comparisons were statistically significant at the 95% confidence level.
Table 1

Characteristics of mothers and live births between 2010 and 2013 by country

Ontario (n=253 930)England (n=1 361 128)
N%N%
Gestational age groupFull term (39+ weeks)170 44567.11 047 53277.0
Early term (37–38 weeks)69 34927.3250 02918.4
Late preterm (34–36 weeks)14 1365.663 5674.7
Birth weight<15001400.111250.1
1500–<250010 8174.363 3194.7
2500–<4000216 77785.41 141 54483.9
4000+26 19610.3155 14011.4
Size for gestationSmall (<10th percentile)25 82510.2120 3228.8
Normal204 27180.41 103 89381.1
Large (>10th percentile)23 8349.4136 91310.1
Maternal age (years)<2094393.778 6595.8
20–2431 97412.6255 98618.9
25–2970 75927.9375 83527.7
30–3485 01633.5385 70028.4
35–3945 44817.9207 26915.3
40+11 2914.454 0214.0
Female infant123 93748.8663 79848.8
Multiple birth46181.819 9731.5
Primiparous mother133 16752.4661 40248.6
Income/deprivation quintileMost deprived: 155 94522.0266 21119.8
250 81820.0269 66420.1
350 47219.9268 79920.0
451 91420.4270 12520.1
Least deprived: 539 12115.4267 06819.9
Newborn length of stay (days)<297 72838.5727 46153.5
2–6147 29458.0577 45242.4
7+89083.556 2154.1
Caesarean section74 06729.2319 19423.5
Neonatal ICU26 46310.4148 95710.9
Delivery risk factor (Any)33 95913.437 06210.1
Hypoxia12420.578 8945.8
Amniotic fluid embolism140.0180.0
Placental transfusion syndrome610.02030.0
Umbilical cord prolapse27 78010.919 3741.4
Chorioamnionitis22700.924120.2
Fetal haemorrhage3580.157830.4
Birth trauma17480.739 3132.9
Complications of delivery16880.718 2441.3
Umbilical cord problem8880.328710.2
Pregnancy risk factor (Any)31 10312.249 68711.0
Previous intrauterine fetal death210.01390.0
Eclampsia28581.131 0842.3
Gestational hypertension11 9114.779 5765.9
Diabetes in pregnancy15 4056.153 1703.9
Placental abruption or infarction32111.314 4681.1
Uterine rupture2260.16790.1
Neonatal medical condition (Any)10 4784.159 8184.4
Congenital anomaly58842.324 7631.8
Perinatal infection18760.729 0932.1
Neonatal abstinence syndrome10240.425040.2
Respiratory distress syndrome29241.294050.7

ICU, intensive care unit.

Characteristics of mothers and live births between 2010 and 2013 by country ICU, intensive care unit.

Statistical analysis

The risk of one or more admissions or ED visits was modelled using multilevel logistic regression, allowing for clustering within healthcare provider at postnatal discharge (hospital for Ontario and NHS Trust for England were included as random effects). In models for admission or ED visits, infants who died within 12 months post discharge were treated as having the outcome. Adjusted ORs (aOR) were used to compare the risk of admission or ED visit according to common risk factors within each country. To allow us to assess the impact of common risk factors on outcomes in each country, all predefined variables were retained in models, irrespective of statistical significance. Sharing of record-level data outside of each country was not permitted, and we could not incorporate a ‘country’ variable within our models. Instead, we separately modelled data within each country. However, this allowed us to explore the impact of risk factors within each country, without making assumptions about similarity of coding. For example, deprivation was derived from income quintile in Ontario (ie, a direct measure of income) and IMD in England (ie, a measure of material deprivation). Separate models allowed us to compare the impact of being in the lowest versus highest quintile within each country. Analyses were performed in Stata V.14.23

Results

A total of 253 930 (Ontario) and 1 361 128 (England) mother–baby dyads were included in the study (table 1). Characteristics of mothers and infants were broadly similar between countries, with a few exceptions: Ontario had a greater proportion of early-term and late-preterm births, more births by caesarean section and fewer young mothers (table 1). The percentage of infants with at least one unplanned admission within 12 months of postnatal discharge was substantially lower in Ontario (7.9% vs 19.6% in England, table 2 and figure 1), while the percentage of infants attending ED but not being admitted was much higher (39.8% vs 29.9% in England). ED visits were much less likely to result in an admission in Ontario (7.3% of ED visits resulted in an admission vs 26.2% in England), and were of a slightly longer duration (median 2 hours 5 min vs 1 hour 49 min in England). The percentage of unplanned admissions admitted via ED was similar in both countries (66.1% in Ontario, 67.9% in England), while the percentage recorded as being admitted via a physician or GP was slightly lower in Ontario (23.6% vs 29.1% in England).
Table 2

Infant outcomes within 12 months post discharge, by gestational age group and country, for births between 2010 and 2013

N (%) infants with ≥1 event to 12 months postnatal dischargeMean inpatient days per infant to 12 months postnatal discharge
All-cause admissionOvernight admission*ED visit not admittedAny ED visitAny contact (admission or ED)MortalityFrom postnatal dischargeFrom day of birth
TotalOntario n=253 93020 01618 954101 060105 661108 9031390.32.7
(7.9)(7.5)(39.8)(41.6)(42.9)(0.05)
England n=1 361 128266 771160 690407 331491 991565 8968370.62.8
(19.6)(11.8)(29.9)(36.2)(41.6)(0.06)
Full term (39+ weeks)Ontario n=170 44511 17810 52466 63469 35170 910670.22.2
(6.6)(6.2)(39.1)(40.7)(41.6)(0.04)
England n=1 047 532189 921112 235307 362368 752421 0975060.52.4
(18.1)(10.7)(29.3)(35.2)(40.2)(0.05)
Early term (37–38 weeks)Ontario n=69 3496929660128 27029 80531 102540.42.8
(10.0)(9.5)(40.8)(43.0)(44.9)(0.08)
England n=250 02958 34336 30979 00596 726113 1162150.73.3
(23.3)(14.5)(31.6)(38.7)(45.3)(0.09)
Late preterm (34–36 weeks)Ontario n=14 13619091829650568916156180.67.7
(13.5)(12.9)(46.0)(48.8)(43.6)(0.19)
England n=63 56718 50712 14620 96426 51331 6831161.28.2
(29.1)(19.1)(33.0)(41.7)(49.9)(0.18)

*All-cause admission excluding those admitted and discharged on the same day.

ED, emergency department.

Figure 1

Trends in the percentage of infants with ≥1 unplanned admission, ED visit or any contact (admission or ED) within 12 months of postnatal discharge. Symbols=observed rates; lines=three-quarter moving average. ED, emergency department.

Trends in the percentage of infants with ≥1 unplanned admission, ED visit or any contact (admission or ED) within 12 months of postnatal discharge. Symbols=observed rates; lines=three-quarter moving average. ED, emergency department. Infant outcomes within 12 months post discharge, by gestational age group and country, for births between 2010 and 2013 *All-cause admission excluding those admitted and discharged on the same day. ED, emergency department. Overall hospital contact during infancy was similar between countries: the percentage of infants with either unplanned admission or ED attendance was 42.9% in Ontario and 41.6% in England. Mortality was also the same in both countries (0.05% in Ontario, 0.06% in England). Infants who were admitted were more likely to stay for ≥1 night in Ontario (94.0% vs 55.2% in England) and have longer admissions (median 3.9 days compared with 2.2 days in England). However, due to the greater number of admissions, mean inpatient days per infant post discharge in England were almost double those in Ontario (table 2). Rates of unplanned admissions and ED visits were increasing over time in both countries, but to a greater extent in England (figure 1, table 3). Other risk factors for infant admission were of similar magnitudes in both countries, with the exception of caesarean section and newborn length of stay (table 3). Gestational age at birth was the most important risk factor for infant admission: aORs for infants born late preterm (34–36 weeks) were 2.44 (95% CI 2.29 to 2.61) in Ontario and 1.66 (95% CI 1.62 to 1.70) in England, compared with full-term babies (39+ weeks) (table 3). Young maternal age (<20 years) was highly predictive of infant admission (aOR 1.36, 95% CI 1.26 to 1.46 in Ontario; 1.49, 95% CI 1.46 to 1.52 in England; table 3) and ED visits (see online supplementary appendix table 2). Deprivation was also an important risk factor in both countries, particularly for ED visits (see online supplementary appendix table 2).
Table 3

Risk factors for unplanned hospital admission in infants in England and Ontario, 2010–2013

OntarioEngland
OR (95% CI)p ValueOR (95% CI)p Value
Gestational age at birth (weeks)Full term (39+)1<0.0011<0.001
Early term (37-38)1.64 (1.59 to 1.70)1.39 (1.37 to 1.40)
Late preterm (34-36)2.44 (2.29 to 2.61)1.66 (1.62 to 1.70)
Newborn length of stay (days)<210.0241<0.001
2–61.02 (0.98 to 1.06)1.08 (1.07 to 1.10)
7–130.91 (0.83 to 1.00)1.38 (1.34 to 1.41)
Size for gestationSmall (<10th percentile)1.02 (0.98 to 1.03)<0.0011.07 (1.05 to 1.09)<0.001
Normal11
Large (>90th percentile)1.06 (1.01 to 1.12)1.00 (0.98 to 1.01)
Maternal age (years)≤191.36 (1.26 to 1.46)<0.0011.49 (1.46 to 1.52)<0.001
20–241.18 (1.12 to 1.24)1.20 (1.19 to 1.22)
25–2911
30–340.96 (0.93 to 1.00)0.90 (0.89 to 0.91)
35–390.95 (0.91 to 1.00)0.83 (0.82 to 0.84)
≥400.95 (0.88 to 1.03)0.82 (0.80 to 0.84)
Female sex0.79 (0.76 to 0.81)<0.0010.80 (0.80 to 0.81)<0.001
Primiparous mother0.92 (0.89 to 0.95)<0.0010.89 (0.88 to 0.90)<0.001
Multiple birth0.66 (0.59 to 0.74)<0.0010.81 (0.78 to 0.84)<0.001
Deprivation quintileMost deprived1.12 (1.06 to 1.17)<0.0011.03 (1.01 to 1.04)<0.001
21.05 (1.00 to 1.10)1.01 (1.00 to 1.03)
31.06 (1.00 to 1.11)1.01 (0.99 to 1.02)
41.06 (1.00 to 1.11)0.99 (0.98 to 1.00)
Most affluent11
Caesarean section0.77 (0.74 to 0.80)<0.0011.04 (1.02 to 1.05)<0.001
Admission to neonatal intensive care1.03 (0.98 to 1.09)0.2321.03 (1.01 to 1.05)<0.001
Season of dischargeJanuary to March1<0.0011<0.001
April to June0.89 (0.85 to 0.93)1.08 (1.07 to 1.10)
July to September0.91 (0.87 to 0.95)1.08 (1.07 to 1.10)
October to December1.06 (1.02 to 1.11)1.08 (1.06 to 1.09)
Quarter year of discharge1.01 (1.01 to 1.02)<0.0011.00 (1.00 to 1.00)<0.001
Perinatal infection1.09 (0.94 to 1.28)0.2491.09 (1.06 to 1.12)<0.001
Prematurity related risk factor0.87 (0.77 to 0.99)0.0331.01 (0.96 to 1.06)0.715
Neonatal medical condition1.82 (1.68 to 1.97)<0.0011.84 (1.79 to 1.89)<0.001
Pregnancy risk factor1.07 (1.02 to 1.12)0.0031.00 (.099 to 1.03)0.525
Delivery risk factor1.01 (0.97 to 1.06)0.6051.01 (1.00 to 1.03)0.112
Risk factors for unplanned hospital admission in infants in England and Ontario, 2010–2013 The most frequently occurring admission diagnoses in both countries were acute upper respiratory tract infections, bronchiolitis and viral infections (figure 2). Despite lower admission rates overall, the percentage of infants readmitted with neonatal jaundice was substantially higher in Ontario compared with England.
Figure 2

Most frequently occurring diagnoses from unplanned admissions within 12 months of postnatal discharge.

Most frequently occurring diagnoses from unplanned admissions within 12 months of postnatal discharge.

Discussion

Our study illustrates the complexities of international comparisons of hospital use. Despite similar health service provision and standardised cohorts of healthy babies in our study populations, focusing solely on the inpatient setting would have revealed substantially higher levels of emergency hospital use in England compared with Ontario. However, by considering both inpatient admissions and ED visits, we showed that overall hospital contact (either ED or admission) and total inpatient days from birth to 12 months were similar across countries. We found different patterns of hospital use that suggest variation in admission thresholds between countries: in Ontario, infants seen in EDs were much less likely to be admitted compared with those in England, while infants admitted in England were more often discharged on the same day as admission. Infant admission rates observed in our study were low for Ontario (7.9%) and relatively high for England (19.6%) compared with those reported in Australia (15%–20%) and the USA (8%–12%).24–27 There are various contributing factors that might explain the differences in hospitalisation patterns between the two countries in our study, including differences in primary or secondary care practice, or in the underlying population.28 Although we could not directly assess the role of primary care in either country, data suggested that the percentage of infants admitted via a physician or GP was slightly higher in England (29.1% vs 23.6%). Our study populations reflect official statistics published in each jurisdiction and demonstrate some important differences between populations: Ontario has fewer young mothers,29 30 more births by caesarean section31 32 and a greater proportion of early-term births.33 34 Although the greater number of infants born early in Ontario was not reflected in an overall higher admission rate during infancy, jaundice (an early outcome associated with early-term birth) appeared to be a greater problem in Ontario.24 35 Another possible explanation for differences in admission rates between countries is the availability of trained emergency paediatricians in ED. Although we could not directly measure this in our study, consultant PEM is better established in Canada than England.13 14 Only one study has evaluated the effectiveness of PEM provision, finding that increased consultant provision was associated with lower admission rates.36 Further research is needed to determine whether increasing emergency paediatrician provision in EDs in England could reduce the numbers of infants admitted for short-stay emergency admissions, or whether this could better be achieved through more efficient management of children with acute illnesses within the community.2 5 28 Differences in ED wait time targets between countries may also have contributed to differences in admission rates. Implementation of ED waiting time targets in the NHS has resulted in increased pressure to admit, and a marked increase in admissions just before the 4-hour cut-off.37 Targets may also have altered health-seeking behaviours, motivating families to seek ED review rather than wait for an appointment with a GP.38 This was reflected in increasing ED attendance rates over time in both countries. In our study, ‘zero-day’ admissions were much more common in England (45% of admissions were admitted and discharged on the same day compared with 6% in Ontario). Pressure to admit from ED explains some but not all of this difference: in England, 50% of admissions with a preceding ED visit were discharged on the same day, compared with 38% of admissions without a preceding ED visit. Greater travel distances in Ontario may also have a role in explaining the greater proportion of overnight admissions. For example, clinicians in Ontario may choose to admit an infant overnight rather than send them on a long late-night journey. Data were not available to test this within our study. Further research is needed to determine whether service provision is more effective in Ontario or England. Hospital admission increases exposure to nosocomial infection, medical error and adverse drug reactions, and can contribute to psychological distress, disruption, or economic loss for children and/or their families.39–41 Reducing unplanned admissions has the potential to improve quality of life for children and their families, as well as alleviating pressure on hospital resources, and is recognised as an important indicator of quality by the NHS Outcomes Framework.42 However, there is a complex relationship between relevant outcomes for children and their families, and primary care access, ED attendances and short-stay admissions, and it is unclear where best to focus investment.38 43 44 As with all studies based on data collected for purposes other than research, careful interpretation of observed differences is required, taking into account the implications of any variation in data quality or coding practices.45 A limitation of this study was the level of missing data on gestational age or birth weight in the English data, which led to the exclusion of some records. However, the representativeness of the study population that did have complete data, means that missing data are unlikely to have led to substantial biases. A lack of validation of risk-factor codes could have led to some misclassification, for example, on capturing congenital anomalies or admission to neonatal intensive care. Although gestational age should be recorded in the same way in both countries (estimated from either ultrasound or last menstrual period), there may be differences in derivation between countries that could have led to misclassification. Since measures of socioeconomic status were different in each country, adjustments within countries were made assuming that differences between quintiles (of either income or multiple deprivation) were similar. However, recording of admission and ED patterns, based on event data, is likely to be accurate. A further limitation of our study was a lack of information on general practice and out-of-hospital care. Health-seeking behaviour appeared similar between countries, with the proportion of families visiting EDs being slightly higher in Ontario. We were unable to assess staffing provision or supply of hospital beds. Administrative data provide a powerful tool for determining how service use varies between countries with similar cultural and environmental risk factors, identifying policy areas that could be compared, and generating hypotheses about how organisational-level factors and service provision contribute to outcomes.6 46 Our study in particular demonstrates the importance of incorporating detailed information on both maternal and baby characteristics and complete healthcare trajectories for exploring variation in emergency care.17 In Ontario, linkage was facilitated by a population spine (the Registered Person database). No such spine currently exists for England, although linkage of prospective maternity data is being developed by NHS Digital for the Maternity and Children’s Dataset.17 47 Further research on the burden of recurrent admissions in both countries would support policymakers to consider the comparative effectiveness and cost-effectiveness of focusing paediatric expertise in ED versus inpatient settings and primary care.
  33 in total

1.  Preventing hospitalisations for children.

Authors:  Glenn Flores
Journal:  Lancet       Date:  2005 Jan 15-21       Impact factor: 79.321

2.  Positive impact of increased number of emergency consultants.

Authors:  Gary C Geelhoed; Elizabeth A Geelhoed
Journal:  Arch Dis Child       Date:  2007-09-03       Impact factor: 3.791

3.  Persistence of morbidity and cost differences between late-preterm and term infants during the first year of life.

Authors:  Kimmie K McLaurin; Caroline B Hall; E Anne Jackson; Oksana V Owens; Parthiv J Mahadevia
Journal:  Pediatrics       Date:  2009-02       Impact factor: 7.124

4.  Data linkage enables evaluation of long-term survival after intensive care.

Authors:  T A Williams; G J Dobb; J C Finn; M Knuiman; K Y Lee; E Geelhoed; S A R Webb
Journal:  Anaesth Intensive Care       Date:  2006-06       Impact factor: 1.669

Review 5.  Hospital based alternatives to acute paediatric admission: a systematic review.

Authors:  D Ogilvie
Journal:  Arch Dis Child       Date:  2005-02       Impact factor: 3.791

6.  Late preterm infants: birth outcomes and health care utilization in the first year.

Authors:  T Mac Bird; Janet M Bronstein; Richard W Hall; Curtis L Lowery; Richard Nugent; Glen P Mays
Journal:  Pediatrics       Date:  2010-07-05       Impact factor: 7.124

7.  Children's psychological responses after critical illness and exposure to invasive technology.

Authors:  Janet E Rennick; C Celeste Johnston; Geoffrey Dougherty; Robert Platt; Judith A Ritchie
Journal:  J Dev Behav Pediatr       Date:  2002-06       Impact factor: 2.225

8.  Primary Care Physicians In Ten Countries Report Challenges Caring For Patients With Complex Health Needs.

Authors:  Robin Osborn; Donald Moulds; Eric C Schneider; Michelle M Doty; David Squires; Dana O Sarnak
Journal:  Health Aff (Millwood)       Date:  2015-12       Impact factor: 6.301

9.  Impact of UK Primary Care Policy Reforms on Short-Stay Unplanned Hospital Admissions for Children With Primary Care-Sensitive Conditions.

Authors:  Elizabeth Cecil; Alex Bottle; Mike Sharland; Sonia Saxena
Journal:  Ann Fam Med       Date:  2015 May-Jun       Impact factor: 5.166

10.  Linking Data for Mothers and Babies in De-Identified Electronic Health Data.

Authors:  Katie Harron; Ruth Gilbert; David Cromwell; Jan van der Meulen
Journal:  PLoS One       Date:  2016-10-20       Impact factor: 3.240

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  9 in total

1.  Reductions in hospital care among clinically vulnerable children aged 0-4 years during the COVID-19 pandemic.

Authors:  David Etoori; Katie L Harron; Louise Mc Grath-Lone; Maximiliane L Verfürden; Ruth Gilbert; Ruth Blackburn
Journal:  Arch Dis Child       Date:  2022-06-21       Impact factor: 4.920

2.  Geospatial and seasonal variation of bronchiolitis in England: a cohort study using hospital episode statistics.

Authors:  Kate Marie Lewis; Bianca De Stavola; Pia Hardelid
Journal:  Thorax       Date:  2020-01-20       Impact factor: 9.139

3.  Geographical disparities in emergency department presentations for acute respiratory infections and risk factors for presenting: a population-based cohort study of Western Australian children.

Authors:  Rosanne Barnes; Christopher C Blyth; Nicholas de Klerk; Wei Hao Lee; Meredith L Borland; Peter Richmond; Faye J Lim; Parveen Fathima; Hannah C Moore
Journal:  BMJ Open       Date:  2019-02-24       Impact factor: 2.692

4.  Our data, our society, our health: A vision for inclusive and transparent health data science in the United Kingdom and beyond.

Authors:  Elizabeth Ford; Andy Boyd; Juliana K F Bowles; Alys Havard; Robert W Aldridge; Vasa Curcin; Michelle Greiver; Katie Harron; Vittal Katikireddi; Sarah E Rodgers; Matthew Sperrin
Journal:  Learn Health Syst       Date:  2019-03-25

5.  Developing a national birth cohort for child health research using a hospital admissions database in England: The impact of changes to data collection practices.

Authors:  Ania Zylbersztejn; Ruth Gilbert; Pia Hardelid
Journal:  PLoS One       Date:  2020-12-15       Impact factor: 3.240

6.  Determinants of accident and emergency attendances and emergency admissions in infants: birth cohort study.

Authors:  Selina Nath; Ania Zylbersztejn; Russell M Viner; Mario Cortina-Borja; Kate Marie Lewis; Linda P M M Wijlaars; Pia Hardelid
Journal:  BMC Health Serv Res       Date:  2022-07-21       Impact factor: 2.908

7.  Temporal trends and socioeconomic differences in acute respiratory infection hospitalisations in children: an intercountry comparison of birth cohort studies in Western Australia, England and Scotland.

Authors:  Hannah C Moore; Nicholas de Klerk; Christopher C Blyth; Ruth Gilbert; Parveen Fathima; Ania Zylbersztejn; Maximiliane Verfürden; Pia Hardelid
Journal:  BMJ Open       Date:  2019-05-19       Impact factor: 2.692

8.  Socio-demographic patterns in hospital admissions and accident and emergency attendances among young people using linkage to NHS Hospital Episode Statistics: results from the Avon Longitudinal Study of Parents and Children.

Authors:  Leigh Johnson; Rosie Cornish; Andy Boyd; John Macleod
Journal:  BMC Health Serv Res       Date:  2019-02-26       Impact factor: 2.655

9.  Preterm birth, unplanned hospital contact, and mortality in infants born to teenage mothers in five countries: An administrative data cohort study.

Authors:  Katie Harron; Maximiliane Verfuerden; Ibinabo Ibiebele; Can Liu; Alex Kopp; Astrid Guttmann; Jane Ford; Jan van der Meulen; Anders Hjern; Ruth Gilbert
Journal:  Paediatr Perinat Epidemiol       Date:  2020-04-28       Impact factor: 3.103

  9 in total

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