Toddler Track: Streamlining Developmental Assessments—A Retrospective Cohort Study

ABSTRACT

Aims

To design, implement and evaluate a novel model of care, Toddler Track Model (TTM), at a specialist outpatient developmental assessment service to determine whether the model: (1) reduced wait times to access the service; (2) reduced length of time to complete developmental assessment; (3) resulted in any change to the formulation of developmental profiles.

Methods

TTM utilised a Plan–Do–Study–Act (PDSA) framework to redesign service delivery. Children aged 18 months to 3 years 11 months were triaged into one of four streams based on clinical information, with tailored pathways involving allied health and paediatrician input. Outcomes were measured through a retrospective chart audit, comparing key time points and service metrics before and after implementation of TTM.

Results

The average time from initial clinical session (ICS) to diagnostic formulation decreased from 116 to 63 days (p < 0.001), with statistically significant reductions observed at all measured service time points. The number of children assessed in 2024 increased substantially (n = 132). Importantly, diagnostic outcomes did not differ between cohorts, indicating no change in clinical formulation. Service‐wide wait times declined by 61.5%, with 68% of this reduction estimated to be associated with TTM.

Conclusion

The findings suggested that TTM is a novel model of care for children aged 18 months to 3 years 11 months. Its implementation successfully reduced wait times and assessment duration while increasing service capacity, without altering diagnostic outcomes or clinical practice standards.

Key Points

• What is already known on this topic

  • ○
    There is significant demand for timely neurodevelopmental assessment, resulting in significant stress on families and on systems.
  • ○
    There is an emerging evidence base that supports the role of advanced allied health practitioners to reduce wait times in public hospital outpatient settings.
  • ○
    There is an ongoing need for quality improvement cycles that trial and review novel models of assessment in paediatric developmental outpatient clinics.
• What this paper adds

  • ○
    An example of an allied health‐led model of care that improved timely access to appropriate developmental assessment for toddlers.
  • ○
    The model improved specialist developmental outpatient service waiting times for all age groups referred to the service.
  • ○
    The model was feasible and did not result in any change to the developmental formulation of children in the study population.

1. Introduction

Queensland's public child development services face overwhelming demand, with waitlists often exceeding 12 months [1, 2]. Many children referred to developmental services require several multidisciplinary developmental assessments across time to develop a comprehensive understanding of the child's developmental profile [3, 4]. Traditional assessment pathways are often time‐intensive, involving multiple appointments across disciplines, which can result in stress, disengagement, and inequitable access for families [4]. A 2023 rapid review by Children's Health Queensland emphasised the need for contemporary, family‐centred service models that are streamlined and responsive to clinical urgency [3, 5, 6].

There is increasing demand from families, carers, schools, and organisations for autism assessments, reflecting the rising prevalence of Autism in Australia [7]. This growth may be attributed to increased community awareness, evolving diagnostic criteria, and the influence of disability funding models that require diagnostic confirmation to access support [7, 8]. The Lancet Commission on Autism advocates for reform, promoting multidisciplinary, community‐based approaches that reduce delays and improve equity [9].

Complex neurodevelopmental assessment requires a holistic consideration of behavioural, neuropsychological, biological, and environmental factors, making it resource intensive [10, 11]. Balancing high demand with timely, best‐practice developmental care remains challenging; however, tailoring developmental assessment journeys to informed clinical hypotheses can reduce unnecessary costs and time. Importantly, parental satisfaction does not differ significantly between paediatrician‐led and allied health‐led models, nor between in‐person and hybrid (telehealth) delivery [4]. This demonstrates a clear need for more efficient, equitable, and high‐quality models of care that reflect both clinical best practice and the lived experiences of families [4, 10, 12].

The aim of this study was to design, implement, and evaluate a novel model of care, Toddler Track Model (TTM), at a specialist outpatient developmental assessment service to consider whether the model:

1. reduced wait times to access the service;

2. reduced length of time to complete developmental assessment;

3. resulted in any change to the formulation of developmental profiles.

2. Methods

2.1. Setting

The Child Development Program (CDP) is made up of several Child Development Service (CDS) service areas and delivered within the Children's Health Queensland Hospital and Health Service, in the Brisbane greater metropolitan area. It provides family‐centred services to children who have developmental concerns requiring assessment. It is a multidisciplinary team made up of several health disciplines, including Speech Pathologists, Psychologists, Occupational Therapists, Physiotherapists, Social Workers, Dietitians, Nurses, and Developmental Paediatricians [12].

All referrals to CHQ CDP must be from a General Practitioner or Medical Specialist for children with significant differences across two or more developmental domains between 0 and 16 years [13]. Referrals are triaged by a clinical intake team (Community Access and Booking Service) according to information provided in the referral and a phone consultation. The general population accessing services in this region is highly diverse, comprising a wide range of cultural and linguistic backgrounds of varying socioeconomic statuses.

The project took place within CDP's CDS South service area. Services in this area are delivered in community health centres, and this project was undertaken in two locations, Browns Plains and Logan Central.

3. Study Design

This quality assurance project used a participatory action research approach, guided by a Plan–Do–Study–Act (PDSA) cycle [14]. This model is used internationally to improve processes and patient outcomes in daily practice (Figure 1).

FIGURE 1.

P‐D‐S‐A cycle.

A 2023 review of CDS South referrals showed that children aged 2–3 years made up 27.7% of the waiting list and 28.6% of cases exceeding wait‐time KPI thresholds. This group was identified as suitable for a streamlined service model, as they typically require fewer standardised assessments than older children. In response, senior multidisciplinary clinicians developed a streamlined clinic model to improve efficiency while maintaining clinical standards (Figure 2). Paediatrician availability was a key dependency, and service leaders secured a temporary 0.6 FTE increase in Developmental Paediatrician time to support the initiative.

FIGURE 2.

Standard journey versus modified service journey for TTM.

3.1. Data Collection

Following implementation of the TTM, a retrospective audit of electronic health records was undertaken. Data were analysed for the 2023 pre‐implementation cohort and a 2024 post‐implementation cohort. The audit was designed to evaluate key service outcomes, including individual wait times, overall journey duration, and system‐wide changes in the prevalence of long waits.

This quality assurance initiative was reviewed by the Children's Health Queensland Hospital and Health Service Human Research Committee (HREC) as meeting minimum requirements of Section 5.1.22 and 5.1.23 of the National Standards and granted exemption of ethics review for the project (120325).

3.2. Typical Journey Through CDP

Through the Typical Journey (TJ) at CDS South, toddlers triaged to Category 2 or 3 usually exceeded their recommended clinical triage time, waiting approximately 9–14 months for their first in clinic appointment. Additional assessments occur after this appointment, guided by the clinical hypothesis and parent priorities. For younger children with a high likelihood of ASD and expected clinician agreement, an ADOS is usually unnecessary, and they proceed directly to Developmental Paediatrician review. Paediatrician availability often created the final bottleneck in the TJ, delaying formulation and subsequent feedback to the family.

3.3. Modified Journey Protocol

The TTM team developed an electronic medical record template enabling experienced allied health clinicians to collect comprehensive medical and developmental histories through a single phone call, replacing the initial two‐clinician appointment. The AH clinician collated supporting documents (e.g., ECEC reports, therapy reports), developed a working hypothesis, and identified the most suitable assessment pathway, with redirection possible at any stage (Figure 2). Co‐location of the team supported timely case discussions and clear documentation of clinical impressions, hypothesis testing, and formulation throughout the TTM process.

The TTM included a 90‐min joint Allied Health (AH)–Paediatrician appointment. As information was collated and dynamically formulated beforehand, this appointment served as both medical review, diagnostic formulation, and feedback to families, eliminating the need for a separate follow‐up feedback session (Figure 2).

The redesigned developmental assessment pathway, TTM, was piloted for children aged 18 months to 3 years 11 months old at CDS South over the 12‐month project period (January–December 2024). All children who fell within the identified age range were triaged to the TTM, except for children in out‐of‐home care (triaged as Category 1), who remained in the TJ pathway to allow better understanding of the overtly complex psychosocial circumstances.

Families received a comprehensive (60–90 min) phone‐based Initial Clinical Session (ICS) with an experienced, ADOS trained AH clinician to gather their history and relevant documentation (e.g., ECEC and therapy reports). The AH clinician collated and recorded all available information into a dynamic formulation and formed a clinical impression and working hypothesis of the child's developmental profile. For families from culturally and linguistically diverse backgrounds, the ICS occurred in clinic, with interpreter support (Figure 3).

FIGURE 3.

Toddler Track Model (TTM) service delivery method.

Children were then triaged into one of four service streams based on the clinician's hypothesis:

1. Highly suggestive of ASD level 3: Children with minimal spontaneous language (e.g., non‐speaking, echolalia), clear social differences, and evident restricted and repetitive behaviours (RRB's) and sensory difficulties were referred directly to a 90‐min joint Paediatrician–AH appointment. The paediatrician completed a developmental observation and medical exam (30–45 min) while the AH clinician gathered additional history and collateral information. Clinicians then conferred mid‐session before providing feedback, diagnoses, documentation and referrals within the same appointment (Figure 3).

2. Unclear developmental concerns/possible ASD traits: Children with spontaneous phrase speech (flexible, non‐echoed three‐word utterances or better), possible social differences, and some RRB's and sensory features were scheduled for an ADOS‐2 assessment (two clinicians) or an early childhood education centre (ECEC) observation. This was followed by a joint paediatrician–AH appointment (Figure 3).

3. Developmental concerns without ASD indicators: Children with developmental delays but no reported social differences or RRBs were assessed by AH clinicians using tools such as the Bayley Scales or discipline‐specific measures. Those meeting criteria for diagnoses (e.g., Global Developmental Delay, ASD) were referred for a joint appointment; others (e.g., isolated speech/language delay) continued in AH‐only care (Figure 3).

4. Medical complexity beyond neurodiversity: Children with broader medical complexity were reviewed in a multidisciplinary clinical forum (including paediatricians) to determine an alternative pathway (Figure 3).

An AH‐only follow‐up care planning session was held 2–4 weeks following assessment to answer any parent questions, support adjustment to diagnosis and address practical family needs (Figure 3). Paediatricians also arranged follow‐up of any medical investigations as required.

A total of 250 charts were audited (n = 59 for 2023, n = 191 for 2024) for all children aged 18 months to 3 years 11 months seen, with key time measurements for each journey analysed and compared. Additional demographic information including developmental profile was also included.

Key time measurements (ICS to Formulation, ICS to Feedback, ICS to Goal Setting [GS], ICS to Outcome) were summarised using mean, standard deviation (SD), medians and inter‐quartile ranges (IQR), and diagnosis was summarised using counts and percentages (Table 1). The time intervals observed between 2023 and 2024 were compared with the Mann–Whitney U test since the data were non‐normally distributed. Changes in diagnosis between 2023 and 2024 were explored with the Fisher's exact test and the Freeman–Halton extension since the variable had 3 or more categories.

TABLE 1.

Summary statistics of full cohort and by year.

Variable	Full cohort N = 250	Year		p a
		2023 N = 59	2024 N = 191
ICS to formulation				< 0.001
Mean (SD)	76.40 (73.07)	115.61 (80.54)	64.84 (66.68)
Median (Q1, Q3)	54.50 (27, 106)	106 (77, 171)	49 (24, 86)
Min, max	0, 389	0, 358	0, 389
ICS to feedback				< 0.001
Mean (SD)	86.14 (78.73)	132.32 (88.75)	72.87 (70.47)
Median (Q1, Q3)	56.50 (28.5, 132.5)	130.00 (84, 184)	53.00 (27, 95)
Min, max	0, 389	0, 387	0, 389
ICS to goal setting				0.002
Mean (SD)	115.23 (81.44)	147.71 (84.62)	103.44 (77.31)
Median (Q1, Q3)	97 (48, 173)	149 (91, 190)	84 (44, 141)
Min, max	0, 470	0, 308	0, 470
ICS to outcome				< 0.001
Mean (SD)	131.90 (101.96)	219.75 (109.53)	104.63 (82.48)
Median (Q1, Q3)	107 (53, 176)	195 (153, 280)	84 (43, 143)
Min, max	0, 524	0, 524	0, 493

^a p‐value from the Mann–Whitney U test.

All data analyses were performed in R version 4.3.3 (2024‐02‐29 ucrt) and developed in RStudio Desktop 2023.6.0.421, statistical significance was reported at 5% and all p‐values reported are two‐tailed. These findings are outlined below, at Table 1.

4. Results

All service timepoints were significantly reduced in 2024 compared with 2023 (all p < 0.01). The Mann–Whitney U test showed a significant decrease between 2023 and 2024 in time between ICS to Formulation (W = 6245, p‐value < 0.001, panel A); in time between ICS to Feedback (W = 6108.5, p‐value < 0.001, panel B); in time between ICS to Goal Setting (W = 3079.5, p‐value = 0.002, panel C); and in time between ICS to Outcome (W = 9174.5, p‐value < 0.001, panel D).

A graphical representation of the relationship between the variables can be observed below, at Figure 4.

FIGURE 4.

Box plots measuring target time points (days) between 2023 and 2024.

The Fisher's exact test (Figure 5) showed that no significant change in diagnostic outcomes between 2023 and 2024 was observed (p = 0.688, df = 9, Cohen's ω = 0.16).

FIGURE 5.

Pie graph representing diagnostic distribution across 2023 and 2024.

4.1. Service‐Wide Waitlist Changes for Long Waits

Change in long wait data (those who have waited longer than their categorised triage time) was tracked across CDS South over 2024. Between January and December 2024, there was a marked decline in long waits, decreasing from 462 in January to 178 in December. This represents a total reduction of 284 patients, equating to a 61.5% overall long wait decrease over the 12‐month period.

When accounting for other initiatives across the service, a significant portion of this reduction (191 patients [68%]) was estimated to be associated with the TTM. This means that of the total decrease in long waits of 284 patients, the other 93 children (32%) were a result of individual site‐based initiatives and were accounted for in data collection, not attributed to TTM. It is important to acknowledge that although 68% of the reduction in long waits was largely attributed to TTM, this occurred alongside a 21.2% increase in Paediatrician staffing capacity. This additional workforce resourcing enhanced throughput and managed bottlenecks across the service, as well as enabled this pilot of TTM.

5. Discussion

This study demonstrates that hypothesis‐driven, allied health‐led triage can streamline early developmental assessment pathways without altering diagnostic outcomes while substantially improving service efficiency. The TTM was feasible and effective in reducing overall wait times for all children to access developmental assessment at CDS South, in reducing the overall assessment time for young children with developmental concerns and increasing the number of children assessed at CDS South.

Assessment processes did not change for children with high diagnostic certainty for ASD, where an ADOS was not required in either model. The prevalence and type of developmental diagnoses remained consistent between the TTM and TJ. Given persistently long global wait times for developmental assessments, this model offers a practical strategy for more efficient waitlist management [4, 11].

AH clinician feedback supports clinician acceptability of TTM, highlighting flexibility for families, efficient multidisciplinary collaboration, and confidence in early hypothesis generation following structured triage. Joint Paediatrician–AH appointments, as well as use of telephone appointments, further streamlined care while maintaining comprehensive assessment. Interpreters supported equitable access for culturally and linguistically diverse families.

Developmental Paediatricians reported adequate time for review and formulation, with the multidisciplinary 90 min consult rarely feeling time pressured. Multidisciplinary appointments allowed dedicated interaction time with the child and supported informed clinical impressions. Successful implementation required strong interdisciplinary trust, shared diagnostic frameworks, and co‐location of team members.

While service‐level tracking was used when considering waitlist reductions, variations in data recording may affect precision. Increased Paediatrician time also contributed to improved journey times. Differences in group sizes may introduce bias, though the magnitude of differences and robust statistical testing support the findings. Future research with balanced samples or propensity matching is recommended.

The absence of formal family feedback is another limitation. Future evaluations should incorporate structured family feedback. Finally, the project's implementation at only two community sites limits generalisability. Broader trials across other Brisbane Child Development Service areas are underway to assess wider applicability.

This model demonstrates potential applicability across high‐demand paediatric services internationally, particularly in settings with constrained specialist workforce capacity.

6. Conclusion

The TTM is a feasible and effective approach to improving access to developmental assessment services, reducing wait times and assessment duration while increasing service capacity without compromising diagnostic outcomes.

Funding

The authors have nothing to report.

Ethics Statement

The authors declare that the research presented in this manuscript adheres to the ethical principles outlined by the Children's Health Queensland Hospital and Health Service Human Research Ethics Committee (HREC). All procedures involving human participants were conducted in accordance with the ethical standards of the Children's Health Queensland Hospital and Health Service and the Declaration of Helsinki (1964), as revised in 2013.

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Data S1: STROBE Statement – Checklist of items that should be included in reports of cohort studies.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.