Demands on children’s tertiary health services in Australia and other high-income countries are growing [1]. Across Australia, children aged <15 years represent 26% of all lower urgency emergency department (ED) presentations and the highest presentation rates at ED [2]. While low urgency conditions do not necessarily equate with low severity or complexity [2], up to 74% of such presentations could be appropriately managed in a timely and safe manner within primary care [3]. High costs are involved in the hospitalization of children, both for governments and consumers. Alternative ways to strengthen pediatric primary care could avert some of the costs implicated in low-acuity presentations to hospitals [4,5].

Australia’s health care system is centralized around primary care provided by general practitioners (GPs). Over time, GPs have seen a diminishing proportion of pediatric cases, reducing their confidence in managing common pediatric conditions [6,7]. Adherence to clinical practice guideline recommendations by GPs has also been found to be reduced for some common conditions [8,9]. As the burden and complexity of disease evolve in high-income settings, increasingly, children present to general practice with medical complexity, including chronic diseases, neurodevelopmental, behavioral, and mental health issues [10-12]. The most common health system concerns expressed by GPs in Australia include an unsustainable workload in the context of this increasing patient complexity and difficulty navigating a fragmented health system [12]. These pressures impact the delivery of high-quality care, highlighting the need to better support GPs in fulfilling their vital role [13]. Challenges faced at the primary care level contribute to health inequities, especially for children living in rural and remote Australia, who experience reduced access and longer waitlists for specialist health services, contributing to diagnostic and treatment delays, adversely impacting health outcomes, and increasing health care costs [14,15].

The need for service redesign and exploration of new approaches to health care delivery for children, young people, and families has been identified to effectively manage health service demands. The primary care workforce requires support to improve care pathways for children, especially those with medical complexity and living in nonmetropolitan areas. Telemedicine and innovative technologies to support the sharing of clinical information have been highlighted as a mechanism to address this need [16].

Our group has implemented and evaluated an integrated GP-pediatrician model of care through several trials: the Strengthening Care for Children (SC4C), based on the UK Children and Young People’s Health Partnership [17], and Connecting Care for Children studies. These studies aimed to support GPs to strengthen the delivery of pediatric care, reducing unnecessary tertiary health service use and improving quality of care at the primary care level. In the UK setting, the intervention was implicated in a reduction in new patient hospital appointments, specialty referrals, and ED attendances, which was reported as a result. Families reported an increasing preference to see their GP, whilst GPs reported improved pediatric knowledge and understanding of how to navigate hospital services [18]. In Australia, the SC4C study, using an in-person, GP-pediatrician engagement model with pediatricians supporting GPs in their practices, demonstrated a reduction in referrals to hospital EDs and was found acceptable and suitable for GPs, pediatricians, and families [19]. However, the in-person model included considerable travel distances for pediatricians, even within metropolitan areas, posing equity and scalability challenges [20].

The evaluation design of the trial was discussed and piloted with GPs [19]. Although there was equipoise, one of the key areas discussed was the wish for all GPs to have access to the intervention. A stepped wedge randomized controlled trial (RCT) design was preferred to a 2-arm cluster RCT. The stepped wedge RCT design offers the gold standard of a cluster RCT. The advantage of a stepped wedge trial design ensures that all participating GP practices receive the intervention [21].

Building on learnings from the SC4C study, we propose to evaluate a model of integrated GP-pediatric care that uses a virtual approach to integrating GP-pediatric care, with the aim of demonstrating scalability and sustainability through a more equitably available model of care. The SUSTAIN study also evaluates the renowned Sydney Child Health Program (SCHP), a modular, web-based pediatric training program that has been developed for GPs, supported through the Sydney Children’s Hospital Network (SCHN) in New South Wales (NSW), and which has not previously been robustly evaluated [22].

Our primary and secondary objectives are to (1) reduce GP referrals to hospital ED and outpatient (OP) clinics for children and young people younger than 18 years and (2) improve GP pediatric care aligned with best practice (BP) guidelines, GP confidence, and increase family trust in primary care, while reducing family preference for specialist pediatrician referral.

Our implementation objective is to examine factors that help or hinder the implementation of SUSTAIN and understand factors associated with acceptability and scalability, and to assess the sustainability of the model.

Our economic objective is to assess the cost-effectiveness of SUSTAIN compared to that of standard GP care by undertaking a health economic evaluation (Table 1).

This paper reports the research protocol for the SUSTAIN trial, including how we will partner with primary care, government, and pediatric hospitals to evaluate the effectiveness and cost-effectiveness of SUSTAIN in a cohort of general practices across NSW, using a stepped-wedge cluster RCT. The trial will be conducted according to the SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) checklist. We will apply the Medical Research Council framework used for developing and evaluating complex interventions [23].

SUSTAIN is a stepped wedge cluster RCT of a virtual GP-pediatrician integrated model of care compared with standard GP care. This trial design has the rigor of a cluster RCT but allows all participating general practices to be exposed to the SUSTAIN care model, providing control, intervention, and postintervention data. This trial design was selected to ensure all practices receive the intervention [21] (Figure 1).

Each general practice provides control period data (referral and medical record data) during the control period (standard GP care, no SUSTAIN model operating). Each month thereafter, 3 practices switch concurrently from control to intervention where a pediatrician supports GPs through telehealth coconsultations, virtual case-based discussions, and being available by phone and email contact in working hours. During the first month of the intervention for each practice, a 1-month transition period is allowed to embed the SUSTAIN model of care into the practice, where data do not contribute to the analysis. This embedding period assists with implementation of the model of care into the practice and allows time to address any procedural issues. After the embedding period, each practice is exposed to an 11-month intervention period. Sustainability data are collected following cessation of the intervention until the intervention is completed for the final practice.

SUSTAIN is a multisite trial conducted across GP practices in different local health districts within NSW. GP practices in both metropolitan and nonmetropolitan (regional, rural, and remote) areas of NSW, including areas with higher-than-average proportions of priority populations, will be eligible to participate.

Trial participants will include general practices with consenting GPs across NSW. Families of children <18 years attending the general practice may be asked to complete anonymous surveys regarding their experience of pediatric care in GP services.

Eligible general practices include those responding to an expression of interest and meeting the inclusion criteria (Textbox 1).

Participating practices will be randomized for intervention using a predetermined web-based randomization sequence generated by an independent trial statistician. Participating general practices will be randomly ordered in terms of when they switch from standard GP care to the SUSTAIN model of care by the independent statistician. To avoid recruitment bias in clusters, randomization will occur once all general practices have been recruited and enrolled; that is, after all inclusion and exclusion criteria are addressed, and all general practices sign the relevant trial agreements. Following randomization, practices will be unblinded to their allocation status/model of care start date. It is necessary for each general practice to know their randomization position to prepare for intervention, so allocation is not concealed. It is not anticipated that GPs knowing their randomization status will impact/change their standard practice due to their demanding workload. The research team is also unblinded to each practice’s allocation status to allow them to effectively engage with each practice to prepare their implementation schedule.

SUSTAIN is a 12-month-long virtual model of care offered to all consenting GPs in participating general practices. It consists of four components: (1) virtual GP-led, shared GP-pediatrician consulting sessions with patients younger than 18 years, (2) virtual pediatrician-led case discussion sessions, (3) phone/email pediatrician support, and (4) complimentary access to the internationally renowned SCHP learning platform (Figure 2).

During their 12-month intervention period, GPs may engage with any component of the model of care based on their needs, capacity, and learning style. The SUSTAN model of care will be delivered by a 1.0 FTE pediatrician (can be a shared position). The pediatricians will be employed through the SCHN.

All participants (GPs and caregivers) will be assigned a unique numerical identifier (an ID code) generated in REDCap (Research Electronic Data Capture; Vanderbilt University) for use throughout the trial. A single electronic, password-protected database in REDCap will record all general practices, GP details, and survey data. Any data recorded will be stored on the secure University of New South Wales (UNSW) network drive on a password-protected computer and will be made available for importing into the project secure research environment. The project database will only be accessible by the designated research team members (investigators, statistician, and project managers) and hosted on the UNSW secure server, which meets security and ethical confidentiality requirements.

GRHANITE, developed and managed by the Health and Biomedical Informatics Center at the University of Melbourne (UoM), specifically designed for research purposes [25,26], extracts and curates the delivery of deidentified and encrypted primary care data to secure research data storage facilities. Person identifiers are removed from the data, in keeping with data custodian permission, and subject to ethics committee approval and legal agreement. Data extracted by GRHANITE will be stored in a Research Databank on the UoM Research Cloud, physically located within the UoM Secure Data Center. GRHANITE data will be made available to the research team from this databank via a UoM secure virtual research environment that gives researchers access to the data in a controlled manner. Upon completion of GRHANITE data extraction, only deidentified data will be transferred to the project analysis team, with a project ID unique to each patient. GRHANITE is only compatible with BP and medical director (MD) electronic medical records (EMRs), used by ≈90% of Australian general practices [27].

Patient confidentiality will be strictly held in trust by the participating investigators, research staff, and the sponsoring institution and their agents. No information concerning the trial or the data will be released to any unauthorized third party without the participant’s consent and written approval of the sponsoring institution.

All interview data will be transcribed and deidentified for analysis and will be stored in a restricted-access folder on UNSW network drives on a password-protected computer. Any personal information or quotes attributed to individual participants in published form will be anonymized.

In the SC4C pilot study, there was a 7% reduction in GP referrals to hospital EDs and OPs, but we have powered our trial using a conservative 4% reduction [19,32]. The sample size of 18 practices with at least 60 pediatric consultations per practice per month will have 90% power to detect a 3.7% reduction (from the baseline rate of 10%) in the percentage of children who are referred to OP clinics or EDs following their GP appointment, assuming an intracluster correlation of 0.06 (derived from the pilot data [19]) and 2-sided type I error of 0.05. With the same sample size, we will have 80% power to detect a 5.5%‐6.55% reduction in the proportion of referrals to OP or ED for our planned stratification analysis by practice rurality, GP baseline referring level, years of practice, and gender.

Several methods will be used to maintain general practice and GP engagement in the trial and minimize “withdrawals” or “lost to follow-up.” These will include email reminders on accessing the SUSTAIN model of care components, “touch point” meetings by the researchers with practices, and quarterly newsletters providing updates and relevant trial information.

We will undertake descriptive analysis to describe the GP referral rate alongside the numbers of all children seen and the numbers of children referred to OP or ED by month during the study period for each practice.

All available data from each recruited GP and family will be analyzed according to an intention-to-treat principle. For the outcomes of GP referrals identified using the GP EMR data (eg, GP referral to OP clinic or ED), we will conduct mixed effects logistic regression, fitted to data collected during the control and intervention periods. The model will include a fixed effect of group (intervention vs control) and adjust for calendar time (as a continuous variable), and random effects to allow for variation in the outcomes for 3 hierarchical levels, including GP practice, GP within each practice, and patients seen by each GP.

Secondary outcomes collected at the child consultation level will be analyzed similarly, with separate models for the 5 common childhood conditions to measure quality of care. GP survey outcomes will be analyzed using mixed effects logistic regression, again including a fixed effect for group by intervention status and calendar time, and a random effect for GP practice, GPs, and patients.

We will control for baseline levels of GP referral for each practice in the analyses, GP-level factors (eg, rurality of the practice’s location, billing type, GP gender, years of practice, and number of children patients seen per week), and patient-level sociodemographic factors (eg, age at the encounter and socioeconomic status of residence). We will also consider whether the intervention effect varies by rurality of practice and GP-level factors (eg, referring level during baseline, years of practice, and GP gender) by the inclusion of interaction terms between group (intervention vs control) and these variables in the regression models.

We will assess whether the correlation structure has been mis-specified. The primary analysis will assume an exchangeable within-cluster correlation structure, meaning that the correlation between any 2 individuals within the same cluster is considered constant. To evaluate the impact of potential misspecification, we will conduct a sensitivity analysis using a block-exchangeable correlation structure within periods. This structure assumes stronger correlations among individuals within the same period, with weaker correlations across different periods. To implement this, we will extend the random-effects model to include an interaction between time and the GP practice random effect.

Prior to analysis, we will understand the mechanisms of the occurrence of missing data in the primary and secondary outcomes. If there is a small number of missing data (<5%), complete case analysis will be presented as the primary analysis. Missing data can occur due to 2 main reasons, considering the current study design: the pop-up failure to launch due to technical issues (nonmonotone missingness), and GP or GP practices withdrawal from the trial (generally monotone missingness, though could also be instances of nonmonotone, for example, personal leave such as maternity leave and retirement). It is reasonable to assume that data missing due to technical failure or personal leave occur missing completely at random. Based on our knowledge, the main reason for GP and GP practice withdrawal is the GP leaving the participating practice. Therefore, it is reasonable to assume these missing data occur as missing at random, and we will undertake multiple imputation to account for the impact of the missing data on the outcomes. It is unlikely that data is “missing not at random (MNAR)” in the nature of this current study, that is, GPs withdraw from the study because of their referral patterns, and this cannot be accounted for by all observed data. If we identify any MNAR, we will not impute the data and will report and discuss the results with limitations and the reasons potentially responsible for the missingness.

We will conduct an intention-to-treat analysis as the primary approach to understand the effect of offering the intervention on referral patterns, under real-world conditions. This means the data will be analyzed based on the information generated from a consenting GP in a randomized GP practice, according to the intervention that is supposed to be delivered in a particular period, irrespective of whether the intervention has been implemented as planned (practices analyzed by randomized step, irrespective of actual start date). Prespecified sensitivity analyses included as-treated and per-protocol analyses, modeling approaches that incorporate the exact calendar date of intervention initiation (to address early or delayed starts), and methods to explore the influence of contamination or noncompliance (for example, complier average causal effect estimates or instrumental variable techniques where appropriate).

From a health sector perspective, a within-trial economic evaluation will be conducted following methodological and reporting guidelines [33-35]. The investment costs of conducting SUSTAIN (including GP training, practice administrative support, pediatrician time, consults, and case-study discussions) will be assessed relative to GP usual care using standard price lists and any patient out-of-pocket payments (including Medicare Benefits Schedule, Pharmaceutical Benefits Schedule, and Independent Hospital Pricing Authority). The costs (and cost offsets) associated with changes in study outcomes (including ED presentations and OP attendances) will then be estimated using similar methods and aligned with the statistical analysis (described above). Three forms of complementary economic analysis and metrics will then be conducted using the information generated. First, the incremental net cost per referral avoided (primary study outcome) will be generated relative to usual care to estimate cost-effectiveness. Second, a return on investment will assess (expected) net cost offsets from avoiding ED/OP relative to the investment in SUSTAIN, and changes in Medicare Benefits Schedule/Pharmaceutical Benefits Scheme use. Probabilistic sensitivity analysis will assess statistical uncertainty in both analyses and the cost-effectiveness acceptability curves generated. Third, a budget impact analysis [36] will estimate the costs of implementing the model at the national level and disaggregated by multiple potential payers (State and Commonwealth). This will inform affordability considerations and combine with wider trial findings to guide translation and sustainable implementation.

This trial is approved by the Human Research Ethics Committees of SCHN (2022/ETH02068), NSW, Australia. The trial has been registered on the Australian New Zealand Clinical Trials Registry (ANZCTR number ACTRN12623000543684).

Written informed consent is obtained from each GP prior to participating in the SUSTAIN trial (Section S1 in Multimedia Appendix 1). All participants in focus groups or interviews (GPs, practice managers, administration staff, and pediatricians) are asked to complete a web-based consent form via REDCap (Section S6 in Multimedia Appendix 5).

A waiver of consent to collect deidentified data on GP care provided during a GP-pediatrician coconsultation was approved (2022/ETH02068).

Informed consent is obtained from families participating in the family experience surveys by agreeing to this through the web-based survey via REDCap. All families are provided with a plain-language statement about the study, explaining the purpose of the study and offering an opportunity to voluntarily participate in the anonymous survey (Section S2 in Multimedia Appendix 6). If the caregiver agrees to take part in the survey, the caregiver’s consent will be indicated via a checkbox at the start of the web-based survey.

Follow-up family surveys will include an item seeking their permission to be contacted about an opportunity to participate in a telephonic or web-based (eg, via Zoom and Teams) interview. Prior to conducting interviews with families, the researcher provides a participant information sheet and consent form for families to consent via web if they agree to participate (Section S7 in Multimedia Appendix 7). The REDCap e-Consent Framework provides a standardized tool to obtain consent and store consent, which automatically generates a “hard-copy” PDF of the signed forms.

Participant confidentiality will strictly be held in trust by the investigators, research staff, and the sponsoring institutions and their agents, and will be extended to cover clinical information relating to participants. The trial protocol, documentation, data, and all other information generated will be held in strict confidence and in password-protected electronic files. No information concerning the trial or the data will be released to any unauthorized third party without prior written approval of the sponsoring institutions. Investigators will have access to the final dataset via permissions maintained by the data managers.

GP practices will receive a one-off AU $1000 (US $655) payment to support implementation of the trial into their practice. GPs and families are not otherwise compensated.

The chief investigators (CIs) will maintain overall accountability, and a project manager and research assistant will provide support and assistance with trial implementation and address any process issues through the duration of the trial. Project team (weekly), research team (monthly), and advisory committee (quarterly) meetings will be held to foster information sharing, problem-solving, and decision-making regarding the trial, as well as ongoing consideration of knowledge translation. The project team includes CIs, trial pediatricians, project manager, research assistant, and implementation evaluation team; research team, in addition to project team, includes economic evaluator, trial statistician, GRHANITE representative; advisory committee, in addition to project and research teams, includes GPs, consumers, and policymakers.

CIs will hold the primary responsibility for publication of the results of the trial in accordance with the trial publication and dissemination plan. The findings from this trial will be reported according to the CONSORT (Consolidated Standards of Reporting Trials) statement guidelines [47].

One method to prevent rising pediatric attendance at emergency departments and OP services could be strengthening the quality of pediatric health care provided by GPs closer to where people live and by increasing family confidence in the care provided by GPs for their children. This is particularly important in rural areas of countries like Australia due to the vast geographical regions. The further primary care providers are located outside of metropolitan centers in Australia, the fewer specialist services are available [48].

A primary care workforce operating at the top of the scope of practice is key to maintaining appropriate levels of services within the health care system, regardless of location. The recently released “Unleashing the Power of our Health Workforce—a Scope of Practice Review” reports that almost all health professionals in the primary care sector in Australia face some restrictions or barriers to working at the full scope of practice [49]. The SUSTAIN model, using a virtual care platform to bring GPs and pediatricians together, has the potential to empower GPs, wherever they are located, to play a greater role across the spectrum of pediatric health care from prevention, early diagnosis, management of common problems, through to chronic disease management. For children, this could reduce the need for families to seek specialist referrals for routine issues, potentially saving health care costs and wait times and leading to better long-term health outcomes. GPs may also provide recommendations for interventions for children while they are awaiting pediatrician appointments, potentially averting negative consequences of prolonged nonintervention, such as in neurodevelopmental or behavioral conditions.

Using the same rigorous mixed methods approach as for SC4C, including a stepped wedge trial design, we will be able to conduct an impact, implementation, and economic evaluation of this integrated virtual GP-pediatrician model of care for children.

There are minimal anticipated risks to patient care, as opposed to the potential benefits, with this integrated GP-pediatrician model of care proposed. However, since the model relies on relationship development between the pediatricians and GPs, it is feasible that personality issues may surface with potential negative consequences to the strengthening of confidence and skills that this model aims to enhance in primary care providers. The use of telehealth and virtual modalities for the development of these relationships may also be a challenge, as opposed to in-person models. These difficulties will be explored particularly through the implementation evaluation, where GPs, practice staff, and pediatricians are involved in focus group discussions or interviews to uncover these underlying issues. Using digital tools for health and education delivery has become more technologically stable and acceptable since the COVID-19 pandemic, and in-person modalities are less affordable and scalable. Although the estimated time available for the pediatrician to provide support for the GPs is based on prior projects, it is conceivable that this is under or overestimated. If underestimated, GPs may find it difficult to obtain the support required to assist with behavior change in practice. If overestimated, this could have financial implications for underused specialist time. These issues will be evaluated carefully, both quantitatively and qualitatively, as well as through the economic evaluation, to determine the most cost-effective way of delivering the intervention. The voice of consumers (patients/families) is obtained through anonymized surveys at baseline and postintervention, with an invitation to patients/families to voluntarily participate in an interview to gather their views on pediatric care provided at GP practices that have participated in the SUSTAIN trial.

The stepped wedge design is susceptible to trends over calendar time, and delay in the implementation of the model could potentially decrease motivation to participate and subsequently increase withdrawal, although researchers will maintain regular contact with prospective practices through regular “touch points,” newsletters, and emails to support motivation and engagement. Results may not be generalizable due to the general practices self-selecting to participate. In a real-world setting, cooperation of GP practices in such a study is crucial to engagement, and we actively target recruitment of a diverse range of practices through PHNs and GP networks, aiming to reach GP practices that care for underrepresented or harder-to-reach population groups, for example, remote, regional, rural general practices. General practices that only use BP or MD EMR software are included for compatibility with GHRANITE, although these EMRs are used by ≈90% of general practices in Australia [27]. Extracted data that are collected from GP EMR may not represent the true scope of care provided by the GPs who also make notes in free text, which could provide a more comprehensive assessment of care quality provided. Nevertheless, the GHRANITE data extraction tool provides a robust mechanism and is the only one of which we are aware that can extract useful data from GP practices in Australia. The voice of consumers relies on voluntary agreement to respond to pre- and postintervention surveys as well as to participate in a postintervention interview. The voice of consumers is important, and we recognize the inherent risk posed by poor participation. Nevertheless, participants are aware that this is voluntary, and their data are provided anonymously. Budget constraints also have meant that family surveys are restricted to English-speaking populations, limiting the generalizability of our findings outside these groups. To highlight the consumer voice, in further implementation and scale-up of this integrated model of care, consumer engagement will need to be a focus, including prioritizing non–English-speaking and other priority population consumers. Financial constraints also limit the collection of sustainability data beyond the period post intervention, which may underestimate the ongoing need for support between GPs and pediatricians in an ongoing manner.

This study provides the potential to deliver quality pediatric care for patients across diverse settings and closer to where they live, in an equitable and scalable fashion. If this innovative integrated care approach is found to be effective and cost-effective, this could be adapted in different settings across Australia and beyond.