The evidence

STAT has been tested in multiple trials. After initial indications of success in two pilot trials, the model has been tested in a large scale trial involving eight community based health services and more than 3000 patients. Further trials have been undertaken in medical outpatients and paediatric community health services, and we have evidence from a survey of more than 50 service providers across Victoria, Australia, suggesting that the model is being successfully implemented beyond trial settings.

From these evaluations we know that:

1 STAT has consistently reduced waiting time by 30-40% and dramatically reduced waiting lists.

2 STAT reduces variability of waiting time

3 STAT improves efficiency, transparency and distribution of workloads

4 Early access to services reduces anxiety, improves quality of care and may improve outcomes

5 Reduced waiting times can be maintained over at least 12 months

6 STAT represents good return on investment for health services

7 STAT works across a range of services, and can be implemented beyond trial settings

8Citation list

Reduced waiting time

STAT has consistently reduced waiting time by 30-40%: Following implementation of STAT in a community rehabilitation setting median waiting time reduced by 40% compared to a control service. A trial in outpatient physiotherapy showed 22% reductions (more for low priority patients). These results were confirmed in a fully powered, stepped wedge cluster randomised controlled trial involving 8 services and more than 3000 patients, where waiting times were reduced by 34%. An implementation study involving 5 paediatric community health services recorded a 35% reduction in waiting time and halved the number of children on waiting lists. A project to implement STAT virtually eliminated a waiting list of 600 people in a medical outpatient clinic.

Reduced variability of waiting time

STAT reduces variability of waiting time: A major benefit of the STAT model is that it reduces unwanted variation in waiting time. By booking in all patients for a timely first appointment regardless of the nature or perceived urgency of their presenting issue, no one is left languishing as a “low priority” patient with a long wait. Patients with less need can be expected to receive a less intensive intervention, but the services they are eligible for are still provided promptly. Reduced variation has been seen consistently across all trials of the STAT model, as indicated by a decrease in the interquartile range or standard deviation of waiting time data.

Improved efficiency, transparency and distribution of workloads

STAT improves efficiency, transparency and distribution of workloads: Two qualitative studies (2019 and 2013) involving interviews with staff who have implemented STAT have both noted these benefits. Allocating set numbers of new patient appointments in clinician diaries at the point of referral saves time in contacting clients, and ensures that work is distributed fairly across the team. In the words of one clinician “It is definitely a lot more efficient processing referrals; a lot less time consuming. All those processes have been more streamlined”

Improved quality of care

Early access to services reduces anxiety, improves quality of care and may improve outcomes: Shorter waiting times are good for patients. A systematic review of the literature demonstrated associations between shorter waiting times for community based health services and patient outcomes, with the strongest evidence in the fields of musculoskeletal conditions and cardiac rehabilitation. This finding was also supported by a qualitative study in which consumers waiting for outpatient healthcare were asked about their experiences. They talked about deteriorations in their health conditions, fear and anxiety. Most of all they wanted access to clear information about what was happening with their care, so that they could make a plan.

Reduced waiting times can be maintained

Reduced waiting times can be maintained over at least 12 months: Sustaining interventions in healthcare is challenging, but two trials conducted to date with the STAT model have shown that improvements have been maintained for at least one year in community outpatient services , and two years in a specialist medical clinic. Both studies identified some threats to sustainability – STAT is not a silver bullet or a “set and forget” model. However with the right conditions and monitoring in place it has the potential to reduce waiting lists and stop them growing back over long periods of time.

Good return on investment

STAT represents good return on investment for health services: A health economics evaluation using a return on investment approach conducted alongside a stepped wedge cluster randomised controlled trial provides evidence that implementing STAT represents a good return on investment for health services. A modest upfront investment to implement the model and reduce the existing backlog is likely to be offset by savings associated with improved efficiency and reduced waiting time for patients.

Works across a range of services

STAT works across a range of services, and can be implemented beyond trial settings: In contrast to other strategies designed to reduce waiting time, STAT has not been designed for a single sector of the health service. We have conducted trials in paediatric services , multi-disciplinary specialist clinics , allied health outpatient services , community outpatient settings and specialist medical outpatients . In addition, a follow up survey of service providers who attended STAT training showed that more than half of respondents had either implemented the model or were in the process of doing so, providing evidence that this approach can be applied to a variety of services outside of trial settings.

Citation list

Effectiveness and sustainability of STAT

Lewis, A, Harding KE, Carney P, Taylor NF (2023) An innovative model of access and triage to reduce waiting in an outpatient epilepsy clinic: an intervention study. BMC Health Services Research (early online)

Harding KE, Lewis AL, Dennett A, Hughes K, Clark M, Taylor NF (2023). An evidence-based demand management strategy using a hub and spoke training model reduces waiting time for children’s therapy services: An implementation trial. Child: Care health and Development (early online)

Harding KE, Lewis AK, Snowdon D, Kent B, Taylor NF (2021) A multi-faceted strategy for evidence translation reduces healthcare waiting time: A mixed methods study using the RE-AIM framework. Frontiers in Rehabilitation Science 2:638302.

Harding KE, Leggat S, Watts J, Kent B, Prendergast L, Kotis M, O’Reilly M, Karimi L, Snowdon D, Lewis A et al. A model of access combining triage with initial management reduced waiting time for community outpatient services: a stepped wedge cluster randomised controlled trial. BMC Medicine 2018; 16:182.

Lewis AK, Taylor NF, Carney PW, Harding KE. Reducing the waitlist of referred patients in a medical specialist outpatient clinic: an observational study. Journal of Health Organisation and Management 2020 35(1):115-130

Harding, KE, Snowdon DA, Prendergast L, Lewis AK, Kent B, Leggat SG, Taylor F (2020) Sustainable waiting time reductions after introducing the STAT model for access and triage: 12-month follow up of a stepped wedge cluster randomised controlled trial. BMC Health Services Research. 20(1):968

Lewis AK, Taylor NF, Carney P, Harding KE 2019) Specific Timely Appointments for Triage to reduce wait times in a medical outpatient clinic: protocol of a pre-post study with process evaluation. BMC Health Services Research. 2019; 19 (1)

Harding KE, Watts JJ, Karimi L, O’Reilly M, Kent B, Kotis M, et al (2016) Improving access for community health and sub-acute outpatient services: protocol for a stepped wedge cluster randomised controlled trial. BMC Health Services Research 16(a):364.

Harding KE, Bottrell J (2015) Specific Timely Appointments for Triage (STAT) Reduced Waiting Lists in an Outpatient Physiotherapy Service. Physiotherapy. 102(4):345-50.

Harding KE, Leggat S, Bowers B, Stafford M, Taylor NF (2013) Reducing waiting time for community rehabilitation services: A controlled before and after trial. Archives of Physical Medicine and Rehabilitation. 94(3):23-31.

Economic Evaluation of the STAT model

Snowdon DA, Harding KE, Taylor NF, Leggat SG, Kent B, Lewis AK, Watts JJ (2021) Return on investment of a model of access combining triage with initial management: an economic analysis. BMJ Open. 11:e045096

Staff and patient perspectives

Harding KE, Snowdon D, Lewis A, Leggat S, Kent B, Watts J, et al (2019) Staff perspectives of a model of access and triage for reducing waiting time in ambulatory services: A qualitative study. BMC Health Services Research. 1: 283

Harding KE, Leggat S, Bowers B, Stafford M, Taylor NF (2013) Clinician and patient perspectives of a new model of triage that reduced waiting time: a qualitative analysis Australian Health Review. 37:324-30.

Impact of delays in access to outpatient and community health services

Harding KE, Lewis AK, Taylor NF (2023) “I just need a plan”: Consumer perceptions of waiting for healthcare. Journal of Evaluation in Clinical Practice. 29(6):976-983

Lewis A, Harding KE, Carney P, Taylor N (2021) What is the effect of delays in access to specialist epilepsy care on patient outcomes? A systematic review and meta-analysis. Epilepsy & Behavior. 122:108192

Lewis AK, Harding KE, Snowdon D, Taylor NF. Reducing wait time from referral to first visit for community outpatient services may contribute to better health outcomes: A systematic review. BMC Health Serv Res 2018; 18: 169.

Interventions to reduce healthcare waiting times

Harding KE, Camden C, Lewis AK, Perreault K, Taylor N (2022) Service redesign interventions to reduce waiting time for paediatric rehabilitation and therapy services: A systematic review of the literature. Health and Social Care in the Community 30(6):2057-2070

Dupuis F, Déry J, Lucas de Oliveira FC, Pecora AT, Gagnon R, Harding K et al (2022) Strategies to reduce waiting times in outpatient rehabilitation services for adults with physical disabilities: A systematic literature review. Journal of Health Services Research and Policy. 2022 Apr;27(2):157-167

Foundational studies contributing to the development of the STAT model

Brady J, Harding KE. Clinical Judgement Just as Reliable as an Explicit Prioritisation Tool: A Comparison of Three Prioritisation Approaches for Inpatient Speech Language Pathology. International Journal of Speech and Language Pathology 2018; 20(2):57-61.

Harding KE, Robertson N, Snowdon DA, Watts JJ, Karimi L, O’Reilly M, et al (2018) Are wait lists inevitable in subacute ambulatory and community health services? A qualitative analysis. Australian Health Review. 42(1):93-9.

Harding KE, Taylor NF, Leggat SG, Stafford M (2012) Effect of triage on waiting time for community rehabilitation services: A prospective cohort study. Archives of Physical Medicine and Rehabilitation. 93(3):441-5.

Harding KH, Taylor NF, Leggat SG, Wise V (2011) A training programme did not increase agreement between allied health clinicians prioritising patients for Community Rehabilitation. Clinical Rehabilitation. 25(7):599-606.

Harding KE, Taylor NF, Leggat (2011) Do triage systems in healthcare improve patient flow? A systematic review of the literature. Australian Health Review. 35(3):371-83.

Harding KE, Taylor NF, Leggat SG, Wise V (2010). Prioritising patient for community rehabilitation services: Do clinicians agree on triage decisions? Clinical Rehabilitation. 24(10):928-34.

Harding KE, Taylor NF, Leggat S, Shaw-Stuart L (2009). Triaging patients for Allied Health services: A systematic review of the literature. British Journal of Occupational Therapy 72(4):153-62.