Carrigan et al. BMC Pediatrics(2024) 24:502
https://doi.org/10.1186/s12887-024-04945-2

BMC Pediatrics

RESEARCH

Open Access

Benefits, implementation and sustainabilityof innovative paediatric models of carefor children with type 1 diabetes: a systematic
review
Ann Carrigan1, Isabelle Meulenbroeks2, Mitchell Sarkies1,3, Genevieve Dammery1, Nicole Halim1, Nehal Singh1,
Rebecca Lake1, Elizabeth Davis4,5, Timothy W. Jones4,5, Jeffrey Braithwaite1 and Yvonne Zurynski1,6*
Abstract
Background and aim The evidence about the acceptability and effectiveness of innovative paediatric models ofcare for Type 1 diabetes is limited. To address this gap, we synthesised literature on implemented models of care,model components, outcomes, and determinants of implementation and sustainability.
Methods A systematic review was conducted and reported in accordance with Preferred Reporting Items for
Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Database searches of Medline, CINAHL, EMBASE andScopus were conducted. Empirical studies focused on Type 1 diabetes paediatric models of care, published from 2010
to 2022 in English were included.
Results Nineteen extant studies reported on models and their associations with health and psychosocial outcomes,
patient engagement with healthcare, and healthcare costs. Thirteen studies described multidisciplinary teamwork,
education and capacity building that supported self-care. Four studies involved shared decision making between
providers and patients, and two discussed outreach support where technology was an enabler. Fourteen studies
reported improvements in health outcomes (e.g. glycaemic control), mostly for models that included multidisciplinary
teams, education, and capacity building (11 studies), outreach support or shared care (3 studies). Four studies
reported improvements in quality of life, three reported increased satisfaction for patients and carers and, and one
reported improved communication. Four of five studies describing shared care and decision-making reported
improvements in quality of life, support and motivation. Outreach models reported no negative outcomes, however,accessing some models was limited by technological and cost barriers. Eight studies reported on model sustainability,
but only half reported implementation determinants; none reported applying a theoretical framework to guide theirresearch.

*Correspondence:
Yvonne Zurynski
Yvonne.Zurynski@mq.edu.au
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0
International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you
give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified thelicensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it.The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to thematerial. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation
or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.To view a copy of this licence, visit http://
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Conclusion Some health and psychosocial benefits were associated with newer models. To address knowledge
gaps about implementation determinants and model sustainability, longitudinal studies are needed to inform future
adoption of innovative models of care for children with Type 1 diabetes.
Keywords Type 1 diabetes, Children, Families, Model of care, Innovation, Person-centred care, Multidisciplinary
teamwork, Health outcomesBackground
Type 1 diabetes (T1D) is typically diagnosed in childhood. In 2021 there were approximately 8.4 million
individuals worldwide with T1D and of these, 1.5 million (18%) were younger than 20 years [1]. In Australia,
T1D affects around 140,000 young people [2]. Despiteadvances in care, children and adolescents who develop
T1D have a reduced life expectancy by around 12–16
years compared with those without T1D [3, 4]. Increased
morbidity and mortality is attributed to an ongoing gap
between the recommended glycaemic control levels andthe levels achieved in practice, and this poor glycaemic management can lead to cardiovascular disease [5],nephropathy and mental health disorders [6]. Increased
attention on the models used to deliver care is needed tobetter understand how and whether these are associatedwith improved outcomes, e.g., optimising the maintenance of glycaemic levels among children with T1D.
Paediatric care for T1D is complex as there are a range
of developmental stages to consider. For younger children (< 14 years) care tends to be family orientated, as
they lack the maturity to self-manage their care delivery
and planning [5], whereas, adolescents are encouraged totake on more responsibility for self-management as they
approach adulthood [7]. Successful outcomes require a
psychosocial approach with education and support fromclinical teams for the child and their family, to empower
and motivate them to effectively manage the treatment
24-h a day, seven days a week, and through life events.
Commonly, models of care for paediatric T1D involve
routine outpatient clinic visits every 3–4 months with amultidisciplinary team (MDT) [8, 9]. Regular consultations are usually undertaken face-to-face with the childand family, with between visit communication initiatedby families/carers as needed [10]. MDT care typically
includes specialist doctors and nurses, diabetes educators, dieticians and psychologists, and has been proposed as an effective way of providing care to increasesafe levels of glycaemia [11]. A model of care involving an MDT approach is one where professionals bring
their skills and expertise from a range of disciplines for
a combined team effort that responds to the individual
child and family needs. Team members typically collaborate to discuss the patient and family and develop sharedcare plans. Although several implementation barriers
have been identified to adoption of such models, including time constraints, inaccessibility, cost and conflicting

recommendations from different providers, this approachhas the potential to strengthen clinical care and improvehealth outcomes, especially when it is consumer focusedand involves shared-decision making between the provider and patient [12]. Although the International Society
for Pediatric and Adolescent Diabetes (ISPAD) guidelines
provide evidence based recommendations for care [13],it is not known whether these are being implemented
in practice. Additionally, there have been no systematic
reviews to describe current models of care, nor a synthesis of current evidence for the effectiveness of models ofcare for T1D. It is unclear how the effectiveness of models of care has been conceptualised and, in examining
these models, what types of study designs have been used
and which outcomes have been measured.
Our group recently conducted a systematic review onmodels of care for individuals with T1D transitioning
from paediatric to adult health care [14]. We identified agap in the evidence about the implementation determinants and the sustainability of models of care, with few
studies applying longitudinal designs to measure longterm outcomes. Given this gap in the transition context,
a synthesis of evidence about the implementation determinants and sustainability of non-transitional models ofcare for T1D is needed.
This review aims, first, to map the scope of implemented models of care for children living with T1D, todescribe the model components, how and to what extent
these contribute to improved health, psychosocial andhealth services outcomes. Second, we aim to synthesise
evidence about factors associated with implementationand sustainability of effective models of care to informfuture adoption of successful models at scale and in different contexts.

Methods
Review protocol

The studies in this review were identified in the resultsof a concurrent review that reports on models of carefor transitioning young adults living with T1D [14]. As
such, the methodology sections are similar. The systematic review was guided by the Preferred Reporting Items
for Systematic Reviews and Meta-Analyses extension for
Systematic Reviews (PRISMA) guidelines [15] and follows a registered protocol (CRD42021262727) which isavailable here: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=262727.

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Search methods

Data extraction and synthesis

The review team met with a medical librarian to design
the search strategy. Four databases were searched: Scopus, Medline, CINAHL, and EMBASE on 6th June 2021
and updated on 11th November 2022. An example ofthe search strategy is provided in Supplemental File 1.
Search limits were applied to include to publications inEnglish, published from January 2010 to November 2022.
Snowballing techniques identified other relevant publications in the reference list of included studies and thesewere screened according to the inclusion and exclusion
criteria.

A custom data extraction workbook was created in
Microsoft Excel. The workbook underwent pilot testing
on five articles, and adjustments were made as necessary
to accommodate the different types of data reported in
the articles. Four reviewers (AC, MS, NH, RL) systematically extracted the data, and any discrepancies among
the reviewers were resolved through discussion. The relevant information extracted included: specific publication
details such as authors, year published, country; design,
methods and setting; patient details such as age, gender,
race/ethnicity, socio- economic status, mean duration ofdiabetes, and insurance status; description of the modelof care, their components, staffing, resources, and setting;a description of usual care, outcomes related to health,psychosocial aspects, or health service use, the utilisationof an implementation framework, and the determinants,
enablers, barriers, and adoption of the model into practice (Table 2). Common themes, features specific to themodel, and categories of outcomes were extracted by the
research team.

Inclusion and exclusion criteria

We included peer-reviewed articles and reviews describing the intervention of a person centred model of care
implemented in high income countries [16], and patients
under the age of 18 years diagnosed with T1D. Studies
that described telehealth, in addition to describing othermodel components, that was facilitated and delivered by
MDT approaches or innovative diabetes education were
included. Studies had to report on health related and/or
psychosocial outcomes, and/or experiences from the perspective of the health provider, health consumer, and/or
caregiver.
Studies that were published prior to 2010, in a language other than English, were conducted in a low- or
middle-income country, focused on transitional care of
T1D, Type 2 diabetes or maternal health interventions or
clinical interventions, e.g., clinical trials involving drugs
or specific equipment were excluded. Other reasons for
exclusion were commentaries, publications of opinion
or perspective, letters to the editor, editorials, and conference abstracts. We also excluded studies that discussed routine consultations through telehealth without
a description of a broader model of care.
Study selection

The reference details for articles returned from search
results were downloaded to a folder and duplicates were
removed and exported into Rayyan, an electronic literature screening program [17]. Ten percent were screened
independently by IM and MS, and a separate sample
of 10% were screened by YZ and IM. For the updated
searches, all title/abstract and full text screening wasundertaken independently by two reviewers (AC, GD).
Any disagreements among reviewers were resolved bydiscussion with the whole review team. The full textof selected studies was then examined. Studies were
excluded if they failed to meet the inclusion criteria on
full-text screening.

Results
The search for primary studies yielded 1951 results(CINAHL: 727, EMBASE: 572, Medline: 446, Scopus:
205; identified from other sources: 1). Among these, 361
duplications were removed. After screening 1590 title/
abstracts, 1313 papers were excluded as they did notmeet the inclusion criteria. Two hundred and seventy
studies underwent full text review and a further 258
papers were excluded. Nineteen primary studies were
included for data extraction and synthesis, as shown in
Fig. 1. Interrater reliability scores (Cohen’s kappa) [18]were all above k = 0.6, which is considered a “good” interrater reliability score.
Quality assessment

Methodological quality was appraised using the Mixed
Methods Appraisal Tool (MMAT) [19]. To ensure consistency, two investigators (AC and RL) appraised 10%of the articles independently. Twelve of the 19 studies reported a quantitative non-randomised design andincluded a representative sample and complete outcome
data [9, 11, 20–29], however, two of these studies did
not account for confounders [9, 29]. There were six randomised controlled trials that reported appropriate randomisation and complete outcome data [8, 10, 30–33],
however, outcome assessors were not blinded, potentially introducing a bias. One study reported a qualitative
design that adopted an appropriate approach, adequate
data collection and substantiated interpretation [34]. We
did not exclude any studies based on quality assessment.
See Supplemental File 2 for further detail.

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Fig. 1 PRISMA flow chart describing the study selection process

Scope of models

Model components

Most studies (13/19, 68%) were from the USA [8–10,
20–22, 24, 26, 27, 30, 31, 33, 34]. The remaining studies
were from Australia (4/19, 22%) [11, 23, 25, 28], Canada(1/19, 5%) [29], and Denmark (1/19, 5%) [32], (Table 1).
Most studies were conducted using quantitative methodologies (12/19, 63%) [9, 11, 20–29], a third used
randomised controlled trial designs (6/19, 32%) [8, 10,
30–33], and there was one qualitative study (1/19, 5%)[34]. The models of care described in the 19 included
papers were comprised of several components such as
MDT care, shared decision making, capacity building
and education for self-care, remote monitoring, andoutreach support (Table 1).

Although there was often overlap among the components(e.g., MDT, shared care and outreach), common components and approaches to care provision were identified asdemonstrated in Fig. 2. These included MDT care, shareddecision making, capacity building and education to support self-care, outreach support and mentoring and integrated care where technology such as a paging system
was used as an enabler.
Multidisciplinary team care, education and capacity building
for self care

MDT care was a central model component across 13
studies (68%). Teams provided T1D care in different contexts including in hospital settings, outpatient clinics,

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Table 1 Key characteristics of the included studies
Study

Country

Setting

Model of care components
as implemented

InterTime at which outvention comes measured
duration

Bergmann et al.
2020 [20]USA

Metropolitan tertiary carepaediatric clinic

Child education and MDT

2 years

Ellis et al. 2017 [30]USA

Community paediatricdiabetes clinic
Metropolitan and rural multidisciplinary diabetes clinics
Metropolitan tertiary carepaediatric clinic (University)
Metropolitan tertiary carechildren’s hospital
Metropolitan tertiary careacademic medical centre
Rural clinics

Capacity building for self-care(family education) and MDT
Capacity building for self-care(family education) and MDT
Capacity building for self-care(family education) and MDT
Outreach support using apager service
Integrated care where technology is an enabler
Shared decision making/integrated care
Capacity building for self-care(family education) and MDT

6months9months9months32
months6months7monthsNotstatedHusted et al. 2014
Denmark Metropolitan paediatric[32]
outpatient clinics
Gandrud et al. 2018 USA
Metropolitan paediatric[10]
outpatient clinic
Goss et al. 2010 [11] Australia Rural outreach clinics

Shared decision making/integrated care
MDT remote monitoring

8 to 12months6months3 years

Ilkowitz et al. 2016
[24]

Metropolitan tertiary care
centreCapacity building for self-care(family education) and MDT

5 years

Metropolitan tertiary care
hospital and regional outreach clinics
Home care

Outreach support

12monthsCapacity building for self-care(family education) and MDT
Capacity building for self-care(family education) and MDT
Education and MDT

Notstated2 years

Fiallo-Sharer et al.
USA
2019 [8]Floyd et al. 2017 [21] USA
Franklin et al. 2014[22]
Hannon et al. 2018[31]
Hatherly et al. 2011[23]
Herbert et al. 2024
[34]

USA
USA
Australia
USA

USA

Joshi et al. 2017 [25] Australia

Katz et al. 2012 [26]USA

Nansel et al. 2012[33]
Pascual et al. 2019[27]
Simm et al. 2014[28]
Versloot et al. 2022
[29]
Wan et al. 2022 [9]USA
USAAustralia
CanadaUSA

Metropolitan children’s
hospitals

Rural MDT

Metropolitan paediatricendocrine clinics
Metropolitan childhood
diabetes centre
Metropolitan tertiary outpa- Outreach support and MDTtient and rural clinics
Community paediatric clinics Integrated stepped careacross three sites
Metropolitan Centre for
Education and MDT
Diabetes

ParAgetici(years)**
pants
(n)
Pre-implementation: 67
Median4 years, 2 months.
(IQR) 15
Post-implementation:(1–17)
2 years, 8 months
Baseline and at 7
47
Mean 14months.
Baseline and 3
214
Range
monthly for 2 years
8–16
Baseline and at 3, 6,
32
Range
and 9 months
12–16
Retrospective analysis 979
Meanof visits to ED
11.1
Baseline, 3 and 6
128
Meanmonths14.7
Baseline
158
Mean
12.9
Baseline13
Meanchild/ 15.7
parentdyads
Baseline, every 3
43
Meanmonths14.7
6 and 9 months
117
Mean
12.7
Baseline, 12, 24, 36
221
Mean 14monthsBaseline (3 years),
1119 Mean 14
post intervention (2years)
12 months
1017 Mean
12.8
Baseline

583

Baseline, every 3–4
months, 24 months
Baseline, 12, 24
monthsEvery 3–4 months

390

34
Baseline, 12 months
months6
Baseline, 3 and six
months months

116

2 years
6 years

88
1456

86

Range
0–17
Mean
12.5
Range
8.4–14.6
Mean
10.7
Mean
14.5
Mean
11.8

USA: United States of America; ED: emergency department; MDT: multidisciplinary team** Age was reported by different studies as either a mean, median, range or interquartile range (IQR)

outreach services or via telemedicine. MDTs were comprised of medical staff such as paediatric emergency
medicine physicians, paediatric endocrinologists, primary healthcare providers as well as nurse practitioners, mental health nurses, dieticians, pharmacists,and patients. MDT model components and the work of

MDTs often included education for patients and providers [20, 27]; shared medical appointments that involved
the child living with T1D, their caregivers and multiple
healthcare providers [9]; capacity building for patient
self-care and education [8, 24, 26, 30]; education andremote monitoring in outreach and rural settings [10,

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Fig. 2 Components of T1D paediatric models of care11]; and support between clinic visits from diabetes nurse
educators for patients residing in rural settings [28]. The
structure and work of the MDT models was variable withno model being described in the same way. Examples
include MDTs implementing and embedding evidencebased treatment guidelines into their practice for patientswith diabetic ketoacidosis (DKA) [20]; a Spanish speaking MDT involved in shared medical appointments(SMA) for Latino children with T1D [27], and an MDT
model where individuals and caregivers participated in
SMAs involving education and clinical care [9]. Another
MDT was involved in weekly review of outpatient data
uploaded from an activity monitor, insulin pump and glucose sensor [10].
Capacity building for self-care included family education programs comprised of education initiatives offeredto patients and families in diabetes clinics. A key component was the exploration and identification of self-management barriers that subsequently lead to solutions suchas the design and delivery of tailored self-management
education resources [8, 30, 33], and coping skills programs [34]. These included tailored delivery of resources
to help families improve diabetes management [8], training sessions on cognitive behavioural skills and relapse
prevention to improve maintenance of safe glycaemic levels [30], and training in insulin pump usage and the basal
bolus regimen [24]. Others described accessible, co-ordinated, family-centred care [26], individualised treatment

plans for patients to improve glycaemic maintenance andquality of life, and group support to increase knowledge
about T1D, goal setting, and glucose pattern recognition[21]. Additionally, identification of child and family psychosocial issues enabled the development of a steppedcare model where the intensity of clinical intervention
was matched to each case as needed [29]. Concerns werediscussed and addressed among the individuals livingwith T1D, their caregiver and the care team [29].
Shared decision making

A shared decision making model was described byHatherly et al. (2011) [23], where paediatric endocrinologists from large metropolitan hospitals provide outreach and travel to rural and regional sites to integratecare with a primary health care provider and patients,
to empower patient/family relationships with specialist physicians, nurses and dieticians, providing carethat includes self-reflection and the development of life
skills [32]. Integrated care with technology as an enabler
included real-time mobile health technology that sharespatient blood glucose data with their parents, and clinicbased healthcare providers facilitated shared decision
making [31].
Outreach support

Outreach support often involved digital and remote monitoring and was described in three studies (16%) [22, 25,

Carrigan et al. BMC Pediatrics(2024) 24:502

28]. Outreach rural services included a visiting medical
specialist who attended routine medical appointments
at three-month intervals and follow up by allied healthteams or diabetes nurse educators between appointments[28]. In a study in regional and remote Western Australia, all patients are offered 24-h, 7 days-a-week telephone
support with an in-hospital or outreach team, and four
visits from a metropolitan-based outreach team per year[25]. Triaging in remote settings was undertaken using apaging system that families could access [22].

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Table 2 Outcomes for T1D models of care
Outcome

Outcome measures and citation

HealthGlycaemic control [8–11, 21, 23, 25, 27,
29–33]
Hypoglycaemia [25, 28]
Diabetic ketoacidosis [22, 25]Continuous glucose monitor usage [9]Insulin pump usage [9, 27]
Insulin regimen adherence [21, 30, 33]
Hospital admission rate due to diabetic
ketoacidosis [20, 22, 24]
Quality of life [8, 10, 11, 21, 29, 30]
Psychosocial function [21]Diabetes related quality of life [29]Diabetes support for children and families[23]
Perceived competence in diabetes [32]Treatment self-regulation [32]Degree of autonomy support from healthcare provider [32]Perceived burden of diabetes related
problems [32]Amotivation [32]
Emotional well-being [32]Impact of T1D on family [26]Communication [21]Parent perception [32]Patient satisfaction [27, 34]
Caregiver satisfaction [25, 30]
Emergency department charges [20]Health care use and cost [9]Ability to function at school [23]Attended diabetes educator [23]Income [23]Visits to clinic [28]Number of clinic visits [9]Model outcomes and effectivenessMany different outcomes were measured and reported
in the 19 included studies. Outcomes could be grouped
under the broad categories of health, psychosocial, satisfaction, cost, hospital admissions, regimen adherence
and other (Table 2).
Table 3 presents the evidence for effectiveness based on
the outcomes, stratified by model components.
Glycaemic control was the most frequently reported
health outcome. Five studies (26%), involving MDT, education and capacity building for self-care, reported significant improvements in glycaemic control associatedwith the model of care [8, 11, 27, 30, 33]. Three studies(16%) reported no change in HbA1c levels indicatingthat the model of care was comparable to routine care [9,10, 21]. Two studies (11%) reported a significant reduction in DKA and hospital admissions [20, 24], anothertwo studies (11%) reported comparable insulin regimen
adherence compared with usual care [30, 33], one study(5%) showed an increase in insulin pump usage for Latino
patients [27], and one study (5%) reported comparable
insulin pump usage compared to usual care [9] (Table 3).
For studies describing shared care and decision making, the evidence for health benefits was mixed. Twostudies (11%) reported no change in HbA1c levels (perceived benefit) [23, 32], one study (5%) reported shortterm benefits at three months but this effect was not replicated at six months [31]. One study (5%) reported anincrease in HbA1c across 18 months compared to baseline [29]. Compared with usual care, four studies (21%)
describing outreach support and mentoring, reported
comparable health outcomes including similar levels of
HbA1c [25, 35], and episodes of severe hypoglycaemia[25, 28], or DKA [22, 25] (Table 3).
Quality of life and psychosocial outcomes are important measures of the effectiveness of care; however,benefits were not consistently reported. For MDT, education and capacity building for self-care models threestudies (16%) reported improved quality of life [11, 21,30], one (5%) reported better communication [21], andthree (16%) reported improved satisfaction for caregivers [30] and patients [27, 34]. Three studies (16%)
reported improved quality of life [29], greater support

Psychosocial

Satisfaction
Cost
Other

Number ofstudies (%)
13 (68)2 (11)
2 (11)
1 (5)
2 (11)
3 (16)
3 (16)
6 (32)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)
2 (11)
2 (11)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)
1 (5)

from a diabetes educator [23], and improved motivation[32]. For outreach support, one study (5%) reported anincreased number of rural clinic visits [28].
Two studies (11%) compared healthcare costs for MDT,
education and capacity building for self-care models
with usual care [9, 20], with one reporting a decrease in
ED charges because of decreased presentations of DKA[20]. A further study showed a reduction in the negative impact of T1D on factors such as school attendance
and finances for families involved in medical care in theirhomes compared to usual care [26].
Implementation determinants and model sustainability

None of the 19 studies mentioned implementation frameworks or theories to guide their adoption of multidisciplinary models of care. Twelve studies (63%) discussed

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Table 3 Evidence for effectiveness of model components stratified by outcome type
Model
Outcomecompenents
MDT, education, Healthand capacity building forself-care

Variablemeasured
Glycaemic
control

Study

Evidece

Benefit?

Ellis et al.
2017 [30]

Clinically significant (0.7%) improvements in HbA1c for those who
received an individualised treatment plan and training sessions(p = 0.05).

BenefitGlycaemic
control

FialloScharer et
al. 2019 [8]No difference in mean HbA1c levels between those who received
tailored self-management resources to identify barriers and subsequent delivery of resources, compared with usual care. However,there was a significant improvement in HbA1c levels for teens(ages 13–16 years) at one site compared with usual care (9.68% vs.
10.76%, p < 0.05).
No change in HbA1c levels for those engaged in SMAs (p = 0.98).

Mixed

Glycaemic
control
Glycaemic
control

Psychosocial

Floyd et al.
2017 [21]Gandrud et Compared with conventional care, intensive remote monitoringal. 2018 [10] combined with outreach resulted in a statistically non-significant
decrease in HbA1c levels of 0.34 (3.7 mmol/mol, p = 0.071) at 6
months.
Glycaamic
Goss et al.
Compared with usual care, the intervention group who received
control
2010 [11]education and support via a rural MDT model of care had significantly lower levels of HbA1c (9.6% vs. 8.1%, p < 0.001) from 2006 to
2009.
Glycaemic
Nansel et al. There was a significant decrease in HbA1c levels for a clinic
control
2012 [33]integrated behavioural intervention compared with usual careobserved at 24 months (0.44 vs. 0.76, p = 0.03). (Ages 12 to 14 years,
p = 0.009; ages 9 to 11 years no effect).
Glycaemic
Pascual et al. Routine care with SMAs for Latino patients resulted in a significant
control
2019 [27]improvement in HbA1c levels from baseline to year 1 (p = 0.0146)
and from year 1 to 2 (0.0082), compared to routine care alone.
Glycaemic
Wan et al.
There was no significant difference in HbA1c levels for patients
control
2022 [9]undertaking SMAs compared to usual care (p = 0.49).
Continuous gly- Wan et al.
There was no significant difference in CGM usage for patients
caemic monitor 2022 [9]undertaking SMAs compared to usual care (1 vs. 4, p = 0.18).
(CGM) usage
Insulin pump
Pascual et al. Routine care with SMAs for Latino patients resulted in a signifiusage
2019 [27]cant increase in insulin pump usage from baseline to year 2 forparticipants aged < 12 years (p = 0.0455) and > 12 years (p = 0.0027)
compared to routine care alone.
Insulin pump
Wan et al.
There was no significant difference in insulin pump usage forusage
2022 [9]patients undertaking SMAs compared to scare (18 vs. 13, p = 0.16).
Insulin regimen Ellis et al.
Non-significant improvements based on self-report for those readherence
2017 [30]ceiving individualised treatment plans with cognitive-behaviouralskills training (p > 0.05).
Nansel et al. No effect for a clinic integrated behavioural intervention compared2012 [33]with usual care based on child and parent reports (p > 0.05).
Hospital admis- Bergmann
A quality improvement initiative resulted in a decreased rate ofsion due to DKA et al. 2020
hospitalisations compared to usual care (74% vs. 55%, p = 0.011).
[20]
Ilkowitz et
A three-pronged intervention (intensive insulin management,al. 2016 [24] education program, increased access to appointments and support events and groups resulted in a decrease in DKA admissions(16.7% vs. 9.3%, p = 0.006), and a decrease in unique patient 30-day
readmissions (20% vs. 5%, p = 0.001), and a reduction in length ofstay (p < 0.0001).
Clinic visits
Wan et al.
There were significantly more clinic visits for the SMA group com2022 [9]pared with usual care (2.38 vs. 1.7, p < 0.01)
Quality of life
Ellis et al.
Those receiving individualised treatment plans with cognitive-be2017 [30]havioural skills training reported improved diabetes related qualityof life compared with control group (p = 0.001).

No benefit
No benefit

Benefit

Mixed

BenefitNo change(benefit)
No change(benefit)
BenefitNo change
No change(benefit)
No change(benefit)
Benefit

Benefit

Benefit
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Table 3 (continued)
Modelcompenents

Outcome

Variablemeasured

Study

Evidece

FialloScharer et
al. 2019 [8]Floyd et al.
2017 [21]Gandrud etal. 2018 [10]Satisfaction

Cost

Other

Shared care and Healthdecision making, and integration of care

Psychosocial

Benefit?

No difference in quality of life for the child with diabetes or theirparent between those who received tailored self-management
resources, compared with usual care (p > 0.05).
Significant improvement in quality of life for those engaged in
SMAs with a MDT (p = 0.005).
Compared with conventional care, intensive remote monitoring
combined with outreach resulted in no difference in quality of life(p > 0.05).
Goss et al.
Compared with usual care, the intervention group aged greater
2010 [11]than 10 years of age who received education and support via arural MDT model of care had significant improvements in qualityof life.
Communication Floyd et al. Significant improvement in communication for those engaged in2017 [21]SMAs with a MDT (p = 0.02).
Impact of T1D
Katz et al.
Compared to usual care, a medical home resulted in a 15% reducon the family[26]tion in family impact (p = 0.01), care coordination resulted in a 18%
reduction in family impact (p = 0.002), family-centred care resulted
in a 10% reduction in family impact (p = 0.08).
Patient
Herbert etHalf reported the TeamWork Project as “pretty helpful”. Specifically,al. 2014 [34] the model reinforced current skills. Compared with the educationgroup, the coping group felt that the model helped with communication, problem solving, new perspectives and skills (qualitativedata).
Pascual et al. Routine care with SMAs for Latino patients reported a high satisfac2019 [27]tion rating of 76%.
Caregiver
Ellis et al.
All of those receiving individualised treatment plans with cogni2017 [30]tive-behavioral skills training reported high levels of satisfaction
with treatment location and the program.
Emergency
Bergmann
Total adjusted median ED charges decreased from pre to post
Department
et al. 2020
implementation period.
[20]
Health care use Wan et al.
Compared to usual care, there were no differences in 6-month total
and cost
2022 [9]costs between SMAs and usual care (p = 0.84).
School function Floyd et al. Significant improvement in school function for those engaged in2017 [21]SMAs with a MDT (p = 0.006).
Treatment
Floyd et al. Significant improvement in treatment adherence for those enadherence
2017 [21]gaged in SMAs with a MDT (p = 0.01).
Barriers to treat- Floyd et al. Significant reduction in barriers for those engaged in SMAs with ament adherence 2017 [21]MDT (p = 0.02).
Glycamic
Hatherly et Glycamic control was not compromised in a shared care model
controlal. 2011 [23] compared with specialist care (p > 0.05).

No change

Glycamic
control
Glycamic
control

No change(positive)
Mixed

Husted et al.
2014 [32]Hannon etal. 2018 [31]No change in HbA1c levels for those receiving a life skills program
compared with usual care (p = 0.85).
Patients using a combined approach of real-time mobile healthtechnology and family centred goal setting, had a significant
decrease in HbA1c levels from baseline to three months, but not at
six months.
GlycamicVersloot et For the stepped care model, HbA1c levels worsened between 6–18
controlal. 2022 [29] months compared to baseline (p = 0.001).
Quality of life
Versloot et Significant improvement in quality of life for those participatingal. 2022 [29] in a stepped care model at 6–18 months compared to baseline(p = 0.048).
Diabetes-related Versloot et Significantly less diabetes related concerns for those participating
quality of life
al. 2022 [29] in a stepped care model at 6–18 months compared to baseline(p = 0.001)

BenefitNo change(benefit)
Benefit

Benefit
Benefit

Perceived
benefit

Perceived
benefit
Perceived
benefit
BenefitNo change(positive)
Benefit
Benefit
BenefitNo change(positive)

No benefit
Benefit

BenefitCarrigan et al. BMC Pediatrics(2024) 24:502

Page 10 of 15

Table 3 (continued)
Modelcompenents

Outcome

Variablemeasured
SupportAmotivation

Other

Outreachsupport

HealthOther

Wellbeing andperceived burden of diabetesParentperception
Hospital
admissions

Study

Evidece

Benefit?

Hatherly et Those receiving shared care were more likely to visit a diabetes
al. 2011 [23] educator in the prior 12 months compared with specialist care(p = 0.02).
Husted et al. Compared with usual care, those receiving a life skills program had
2014 [32]significantly reduced amotivation (p < 0.0001).
Husted et al. Compared with usual care, those receiving a life skills program had
2014 [32]no change in wellbeing or perceived burden of diabetes (p > 0.05).

BenefitHusted et al.
2014 [32]Hatherly et
al. 2011 [23]No change

Glycaemic
controlJoshi et al.
2017 [25]Compared with usual care, those receiving a life skills program had
no change in parent perception (p > 0.05).
Those receiving shared care were more likely to be admitted tohospital in the prior 12 months compared with specialist care(p = 0.002).
No change in mean HbA1c for those who attended an outreachclinic compared to a metropolitan clinic (p = 0.39).

Severehypoglycaemia

Joshi et al.
2017 [25]No change in severe hypoglycaemic events for those who attended an outreach clinic compared to a metropolitan clinic (p = 0.74).

Simm et al.
2014 [28]No difference in mean HbA1c levels between an urban diabetes
clinic and outreach, rural clinics (8.3% for both groups, p = 0.87).

Diabetic
ketoacidosis
Diabetic
ketoacidosis

Franklin etal. 2014 [22]Joshi et al.
2017 [25]Those using a pager service to access care were 2.75 times more
likely to visit the ED for DKA, compared to nonusers (p < 0.00001).
No change in the DKA rate for those who attended an outreachclinic compared to a metropolitan clinic (p = 0.68).

ED and inpatient admissions
due to DKA
Number of clinic
visitsFranklin etThose using a pager service to access care were less likely to be
al. 2014 [22] admitted to the ED for DKA, compared to nonusers (odds ratio
0.58, p < 0.02).
Simm et al. Increased number of clinic visits for those who attended a rural,
2014 [28]outreach clinic and an urban diabetes clinic (p < 0.001)

BenefitNo change

No benefit

No change(positive
outcome)No change(positive
outcome)No change(positive
outcome)BenefitNo change(positive
outcome)Benefit

Benefit

SMA: shared medical appointment; MDT: multidisciplinary team; ED: emergency department; DKA: diabetic ketoacidosis

implementation enablers, and 11 (58%) reported barriers to implementation (Table 4). For models incorporating MDT, education, or capacity building for self-care,
the reported enablers included: group-based sessions, [8]care managed by a single facilitator [8, 11], a small team[11], adequate provider to patient ratio [24], integration
into existing clinics [33], close collaboration between
primary care doctors and the diabetes team in hospital[26], and adopting a multicultural approach [27]. Barriers
included length of program being too long for patients toengage with consistently [30], low frequency of sessions[8], lack of skilled staff to cover periods of leave [11], lowhealth literacy of patients and caregivers [26], and a lower
drive among older children (> 12 years) to undertake diabetes related education [27].
For models that included outreach support, theenablers included having a dedicated and well-trained
team [22], the adoption of a MDT approach [25] that is
consistent and cohesive, and coupled with effective communication [28]. In one study, support between routine
consultations was facilitated by 24-hour phone access tothe diabetes team [25]. Access to clinics for those living inremote regions was a reported barrier by one study [28].
For models using shared care and decision making andintegration of care, a reported enabler was having all themodel components working well together [21]. A barrier
was a lack of access to 24-hour ambulatory care and inequitable access for families of lower socio-economic status
due to higher costs [23].
In the assessment of the sustainability of the models
or care, three of 19 studies (16%) measured outcomes at
two years [20, 27, 33], and five (26%) measured outcomes
two years or longer after model implementation [11, 22,
24, 28, 29] (Table 1). Four of these studies (21%) did not
mention sustainability of the model of care after implementation, although outcomes were measured [20, 27,
29, 33]. The remaining studies presented evidence formodel sustainability by measuring outcomes once acrossa period of time [11, 22, 24, 28]. Several barriers andenablers associated with the sustainability of the models
of care were described (Table 4).

Carrigan et al. BMC Pediatrics(2024) 24:502

Page 11 of 15

Table 4 Enablers and barriers of implementation of T1D models of care
Model
Study
MDT, educa- Bergmann ettion, andal. 2020 [20]capacitybuilding forself-care
Ellis et al.
2017 [30]Model description
Enablers
Evidence based guidelines: EMR order set up- Nil stated.
dates, ED physicians and stakeholders’ regular
updates and nursing education.

Barriers
The providers were concerned
about the early discharge ofpatients increasing the risk ofreadmission for low-risk DKA.

Individualised treatment plans, mandatory
and optional skills training and relapse prevention delivered at home.

Over one third did not complete the program as it was felt
to be too long and home visits
too frequent.
Program intensity was reducedby the low frequency of thesessions: every three to fourmonths rather than weekly or
every two weeks.
Nil reported.

Nil stated.

Fiallo-Sharer
et al. 2019[8]

“Project ACE (Achieving control, Connecting
Model acceptance was boosted byresources, Empowering families.)” Tailored self- group-based sessions where a single
management resources.
facilitator managed several families
together.

Floyd et al.
2017 [21]Shared medical appointments, groups sessions and peer support.

The model was well accepted by practitioners, patients and their families as
all the components were perceived towork together in a group setting in asingle appointment.
Goss et al.
“Rural Australian Diabetes – RADICAL)” - MDT Positive attitudes promoting hope and2010 [11]team meetings with education sessions.
empowerment improved outcomes.
The model was facilitated by a counsellor who helped develop a personalised
and realistic approach to care. A small
team allowed for provider consistency
for consultations.
Ilkowitz et al. Education, and support events and groups
Improved patient to provider ratio,
2016 [24]and increased access to clinics.
decreased wait times for appointments
and increased number of sessions.
Katz et al.
“Medical Home” - family centred, coordinated, A close collaboration between primary2012 [26]comprehensive, compassionate, and culturcare doctors and the diabetes team.
ally effective.
Nansel et al. A program to facilitate problem-solving, com- Integration into existing clinics.
2012 [33]munication skills and responsibility sharing
via telephone calls and in-person contact.
Program delivered by a specialised healthadvisor.
Pascual et al. Shared medical appointments within a Latino Multicultural team involvement in2019 [27]program.
a culturally sensitive educational
program.

Wan et al.
2022 [9]Shared medical appointments among provid- Team environment increased provider
ers and peers
satisfaction

Shared care Hatherly etand decision al. 2011 [23]making, andintegrationof careShared care among paediatric endocrinologists from large metropolitan hospitals who
travel to rural and regional sites to integratecare with a primary health care giver.

Nil reported.

OutreachsupportAllied health personnel support with 24/7
paediatric diabetes self-management.
A 24 h/7 days telephone support with an inhospital or outreach team, and four visits froma metropolitan-based outreach team per year.

The team were reported to be dedicated and well-trained.
The model involves a centralised and
MDT approach.

Franklin et al.
2014 [22]Joshi et al.
2017 [22]Reduced support in lesspopulated regions for similarly
skilled members of the MDT
when team members on leave.

Nil stated.

Reduced health literacy forsome families.
Nil stated.

Study attrition was reported
for teenager group thought tobe due to a lower drive to be
educated compared to parents
and their dependent children.
In person visits only (rather
than online option) prevented
some individuals from attending clinics.
A lack of access to 24-hourambulatory care increased
hospital admissions. There wasa suggestion of inequity for
those of lower socioeconomic
status.
Nil reported.
Nil reported.

Carrigan et al. BMC Pediatrics(2024) 24:502

Page 12 of 15

Table 4 (continued)
Model

Study
Simm et al.
2014 [28]Versloot etal. 2022 [29]Model description
Outreach rural services included a visiting
medical specialist who attended routine medical appointments at three-month intervals
and follow up by allied health teams (diabetes
nurse educators).
Individualised stepped care.

Enablers
A consistent, cohesive approach,effective communication and shared
protocols allowed for the successful
initiation and maintenance of complex
treatment regimens.
Having access to external funding toembed mental health support in theclinic.

Barriers
The number of clinic visits washigher for rural patients andthe access to services for thoseliving in more remote regions
was difficult.
There was a suggestion of
ethnic diversity preventing
access.

MDT = Multidisciplinary team, EMR = electronic medical records, ED = emergency doctors

Discussion
Our evidence synthesis identified a variety of implemented innovative models of care for T1D, with an MDT
approach most frequently reported. The key componentsof the models included MDTs, shared medical appointments, shared decision making, capacity building forself-care, outreach support and mentoring and integrated
care enabled by technology such as telehealth consultations and interactive educational programs delivered
online or by teleconference.
The literature shows enormous variety of outcome
measures reported across studies, which makes it difficult to synthesise evidence of benefits across different
models. For example, some reported benefits in termsof improved maintenance of glycaemic levels [10, 21,
27, 30], and increased insulin pump usage, while others
reported no improvements in health outcomes [29, 31,
32].
Improved psychosocial outcomes, including quality oflife were consistently reported for models that included
shared care, decision making, and integrated care [23,29, 32]. These benefits are consistent with previous studies on integrated care models for other conditions suchas chronic kidney disease [36], cancer survival [37],and mental illness [38]. It remains uncertain, however,whether improvements, or lack of improvements, canbe directly attributed to the innovative model of care orits components, because of the differing models in use,
and the large variety of outcome tools and measures
being used across studies. Versloot et al. (2022) [29] forexample, applied both a general measure of quality of life
and a diabetes-specific measure of quality of life, showing that effects were stronger when the diabetes-specificmeasure was used [29]. This suggests that a greater consistency and standardisation of diabetes specific outcome
measures may be needed to improve the reliability of evidence synthesis across studies and settings in the future.
Outreach support had previously been reported tocontribute to positive health behaviors for adults livingwith diabetes [39], and for the provision of social support and capacity for skill building among people livingwith chronic conditions in rural areas [40]. Consistent
with our findings, these positive outcomes are enabled

by technology – usually a combination of telephone andonline support, in addition to face-to-face consultationsas previously described in a model of care for children
living with medical complexity [41].
Over half of the studies reported on the implementation determinants of the model of care, however none
used implementation science frameworks or theories toguide their work. Commonly reported enablers of successful model of care implementation included communication and team cohesiveness [9, 11, 21, 22, 25–28, 33].
These findings are consistent with those reported in otherstudies of paediatric integrated care models [41], andby adult consumers and providers commenting on integrated care models [42]. A review conducted by Bradford
et al. (2016) [43] reported that establishing clear, efficient
processes to support teams to manage care is important
for the successful implementation and sustainability ofmodels of care [43].
The key barriers identified for patient engagement with
T1D models of care included program intensity requiring
frequent engagement or long educational sessions [30],difficulties in accessibility due to connectivity problems
for online components [39], or additional travel and costfor families living in rural regions [28]. This suggests thatgroups developing new models of care may benefit withcloser engagement and co-design with end-users before
launching new models of care or programs for T1D. Limited availability of skilled staff when team members wereon leave also limited access [11], suggesting the need foradequate human resource planning and staff training
when implementing new models of care.
Short follow-up periods after implementation limited assessment of the evidence for models’ sustainability. Nine (47%) of studies were evaluated at 12 months
post implementations, and the follow-up period was notreported in two studies (11%). Only eight studies (42%)
measured outcomes two years or longer after implementation, the longest follow-up period being six years [28].
For example, a rural MDT model of care that offerededucation and support showed significant benefits forglycaemic management and quality of life measures every
12 months for 3 years [11]. These findings are consistent
with the known gaps in evidence for the sustainability of

Carrigan et al. BMC Pediatrics(2024) 24:502

health programs [44], including for models of care forchronic health conditions [45]. Understanding the determinants of successful model of care implementation andsustainability should be a research priority to informfuture T1D models of care development and co-design,
as well as informing strategies for implementation andscaling up. For example, the Consolidated Framework
for Implementation Science Research (CFIR) [46] andthe Integrated Sustainability Framework (ISF) [45] provide comprehensive, flexible frameworks underpinned
by robust theoretical grounding that lends itself to thestudy of implementation and sustainability of models ofcare while taking account of specific internal and external
contexts [46].
Strengths and limitations of the current review

Applying the PRISMA guidelines, a rigorous multi-stepteam-based study selection process, a comprehensive
search of four international academic databases andadhering to a registered protocol are all methodological strengths of this study. Most studies were from the
USA and were conducted in large metropolitan settings
which limits the generalisability of findings to other settings. Other limitations include selecting only articles
written in English and from high income countries, andomitting grey literature may have impacted the comprehensiveness of results. Grey literature may be particularly
important in this area as models of care may be reported
in “in-house” service reports or evaluations that are notsubmitted for peer review and publication in journals.
Additionally, our search criteria focused on implemented
T1D models of care, and did not focus on other waysof driving improved health outcomes for T1D based on
population registries or networks, for example the Swedish paediatric diabetes quality registry, SWEDIABKIDS[47] or the SWEET global network [48]. Future reviews
should consider including grey literature and the impactsof registry data to drive improvements in health outcomes for T1D. Due to the wide heterogeneity of study
methodologies, analysis methods, and outcome measures we were not able to pool data, and synthesis waschallenging, limiting the generalisability of our findings.
Other limitations included small sample sizes [21], limited scope [34], and single site models [10, 20–22, 24, 30,
31].

Conclusions
The evidence for the effectiveness, acceptability andsustainability of paediatric T1D models of care is currently limited and inconsistent, although a pattern isemerging. Across three broad categories of model components, that include an MDT approach, some studies
reported benefits for children living with T1D, including
improved glycaemic management, although other studies

Page 13 of 15

reported no benefit. Several psychosocial benefits suchas improved quality of life and motivation were reported,
especially for shared care models, but again some studies reported no benefit. Barriers to accessing these models by patients/families included program intensity, timecommitment required, cost and location. Enhanced
communication and team cohesiveness were reported
as important enablers for effective care delivery. Thereis a need for greater consistency of outcome measures
to enable more robust evidence synthesis across studies
and contexts. We also identified a need to adopt longitudinal study designs with larger sample sizes and longer
follow-up periods to better understand model of caresustainability. Future studies should be guided by robust
theoretical frameworks to study implementation determinants and sustainability of T1D models of care.

Supplementary Information

The online version contains supplementary material available at https://doi.
org/10.1186/s12887-024-04945-2.
Supplementary Material 1: Example of the search strategy for Medline
Ovid
Supplementary Material 2: Quality Appraisal of included studies using theMixed Methods Appraisal Tool (MMAT)
Acknowledgements
A review describing similar methodologies has been published in BMC HealthServices Research [14].
Author contributions
YZ, ED, TJ and JB designed the research. YZ, AC, MS, IM, GD, NH, and RL
conducted the research. AC and YZ analysed the data and drafted themanuscript. All authors read and approved the final manuscript.
Funding statement
This work was funded by the JDRF Australia [5_SRA_2021_1088_m-X].
The funding source played no role in the design, collection, analysis, orinterpretation of the data or in the decision to submit the manuscript for
publication.
Data availability
The datasets used and/or analysed during the current study are available fromthe corresponding author on reasonable request.

Declarations
Ethics approval and consent to participate
Not required as a review article.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Author details
1
Centre for Healthcare Resilience and Implementation Science, AustralianInstitute of Health Innovation, Macquarie University, 75 Talavera Road,
Sydney, Australia
2
Centre for Health Systems and Safety Research, Australian Institute of
Health Innovation, Macquarie University, Sydney, Australia

Carrigan et al. BMC Pediatrics(2024) 24:502

Page 14 of 15

3

Sydney School of Health Sciences, Faculty of Medicine and Health,
University of Sydney, Sydney, Australia
4
Telethon Kids Institute, Perth Children’s Hospital, Western, Australia
5
Perth Children’s Hospital, Perth, Western, Australia
6Partnership Centre for Health System Sustainability, Australian Instituteof Health Innovation, Macquarie University, Sydney, Australia

20.
21.

Received: 4 September 2023 / Accepted: 15 July 2024
22.

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