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      A model of access combining triage with initial management reduced waiting time for community outpatient services: a stepped wedge cluster randomised controlled trial

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          Abstract

          Background

          Long waiting times are associated with public community outpatient health services. This trial aimed to determine if a new model of care based on evidence-based strategies that improved patient flow in two small pilot trials could be used to reduce waiting time across a variety of services. The key principle of the Specific Timely Appointments for Triage (STAT) model is that patients are booked directly into protected assessment appointments and triage is combined with initial management as an alternative to a waiting list and triage system.

          Methods

          A stepped wedge cluster randomised controlled trial was conducted between October 2015 and March 2017, involving 3116 patients at eight sites across a major Australian metropolitan health network.

          Results

          The intervention reduced waiting time to first appointment by 33.8% (IRR = 0.663, 95% CI 0.516 to 0.852, P = 0.001). Median waiting time decreased from a median of 42 days (IQR 19 to 86) in the control period to a median of 24 days (IQR 13 to 48) in the intervention period. A substantial reduction in variability was also noted. The model did not impact on most secondary outcomes, including time to second appointment, likelihood of discharge by 12 weeks and number of appointments provided, but was associated with a small increase in the rate of missed appointments.

          Conclusions

          Broad-scale implementation of a model of access and triage that combined triage with initial management and actively managed the relationship between supply and demand achieved substantial reductions in waiting time without adversely impacting on other aspects of care. The reductions in waiting time are likely to have been driven, primarily, by substantial reductions for those patients previously considered low priority.

          Trial registration

          Australian New Zealand Clinical Trials Registry ACTRN12615001016527 registration date: 29/09/2015.

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          Most cited references39

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          Stepped wedge designs could reduce the required sample size in cluster randomized trials.

          The stepped wedge design is increasingly being used in cluster randomized trials (CRTs). However, there is not much information available about the design and analysis strategies for these kinds of trials. Approaches to sample size and power calculations have been provided, but a simple sample size formula is lacking. Therefore, our aim is to provide a sample size formula for cluster randomized stepped wedge designs. We derived a design effect (sample size correction factor) that can be used to estimate the required sample size for stepped wedge designs. Furthermore, we compared the required sample size for the stepped wedge design with a parallel group and analysis of covariance (ANCOVA) design. Our formula corrects for clustering as well as for the design. Apart from the cluster size and intracluster correlation, the design effect depends on choices of the number of steps, the number of baseline measurements, and the number of measurements between steps. The stepped wedge design requires a substantial smaller sample size than a parallel group and ANCOVA design. For CRTs, the stepped wedge design is far more efficient than the parallel group and ANCOVA design in terms of sample size. Copyright © 2013 Elsevier Inc. All rights reserved.
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            Advanced access: reducing waiting and delays in primary care.

            Delay of care is a persistent and undesirable feature of current health care systems. Although delay seems to be inevitable and linked to resource limitations, it often is neither. Rather, it is usually the result of unplanned, irrational scheduling and resource allocation. Application of queuing theory and principles of industrial engineering, adapted appropriately to clinical settings, can reduce delay substantially, even in small practices, without requiring additional resources. One model, sometimes referred to as advanced access, has increasingly been shown to reduce waiting times in primary care. The core principle of advanced access is that patients calling to schedule a physician visit are offered an appointment the same day. Advanced access is not sustainable if patient demand for appointments is permanently greater than physician capacity to offer appointments. Six elements of advanced access are important in its application balancing supply and demand, reducing backlog, reducing the variety of appointment types, developing contingency plans for unusual circumstances, working to adjust demand profiles, and increasing the availability of bottleneck resources. Although these principles are powerful, they are counter to deeply held beliefs and established practices in health care organizations. Adopting these principles requires strong leadership investment and support.
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              Analysis and reporting of stepped wedge randomised controlled trials: synthesis and critical appraisal of published studies, 2010 to 2014

              Background Stepped wedge cluster randomised trials introduce interventions to groups of clusters in a random order and have been used to evaluate interventions for health and wellbeing. Standardised guidance for reporting stepped wedge trials is currently absent, and a range of potential analytic approaches have been described. Methods We systematically identified and reviewed recently published (2010 to 2014) analyses of stepped wedge trials. We extracted data and described the range of reporting and analysis approaches taken across all studies. We critically appraised the strategy described by three trials chosen to reflect a range of design characteristics. Results Ten reports of completed analyses were identified. Reporting varied: seven of the studies included a CONSORT diagram, and only five also included a diagram of the intervention rollout. Seven assessed the balance achieved by randomisation, and there was considerable heterogeneity among the approaches used. Only six reported the trend in the outcome over time. All used both ‘horizontal’ and ‘vertical’ information to estimate the intervention effect: eight adjusted for time with a fixed effect, one used time as a condition using a Cox proportional hazards model, and one did not account for time trends. The majority used simple random effects to account for clustering and repeat measures, assuming a common intervention effect across clusters. Outcome data from before and after the rollout period were often included in the primary analysis. Potential lags in the outcome response to the intervention were rarely investigated. We use three case studies to illustrate different approaches to analysis and reporting. Conclusions There is considerable heterogeneity in the reporting of stepped wedge cluster randomised trials. Correct specification of the time-trend underlies the validity of the analytical approaches. The possibility that intervention effects vary by cluster or over time should be considered. Further work should be done to standardise the reporting of the design, attrition, balance, and time-trends in stepped wedge trials.
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                Author and article information

                Contributors
                61 3 9091 8880 , katherine.harding@easternhealth.org.au
                s.leggat@easternhealth.org.au
                j.watts@deakin.edu.au
                bridie.kent@plymouth.ac.uk
                luke.prendergast@latrobe.edu.au
                michelle.kotis@dhhs.vic.gov.au
                mary.oreilly@austin.org.au
                l.karimi@latrobe.edu.au
                annie.lewis@easternhealth.org.au
                david.snowdon@easternhealth.org.au
                n.taylor@latrobe.edu.au
                Journal
                BMC Med
                BMC Med
                BMC Medicine
                BioMed Central (London )
                1741-7015
                19 October 2018
                19 October 2018
                2018
                : 16
                : 182
                Affiliations
                [1 ]ISNI 0000 0004 0379 3501, GRID grid.414366.2, Eastern Health, ; Level 2/5 Arnold Street, Box Hill, VIC 3128 Australia
                [2 ]ISNI 0000 0001 2342 0938, GRID grid.1018.8, La Trobe University, ; Kingsbury Drive, Bundoora, VIC 3086 Australia
                [3 ]ISNI 0000 0001 0526 7079, GRID grid.1021.2, Deakin University, ; 221 Burwood Highway, Burwood, VIC 3125 Australia
                [4 ]ISNI 0000 0001 2219 0747, GRID grid.11201.33, University of Plymouth, ; Drake Circus, Plymouth, Devon PL4 8AA UK
                [5 ]GRID grid.453680.c, Victorian Department of Health and Human Services, ; 50 Lonsdale Street, Melbourne, VIC 3000 Australia
                Author information
                http://orcid.org/0000-0003-0207-7071
                Article
                1170
                10.1186/s12916-018-1170-z
                6194740
                30336784
                578b33f2-f69e-48dd-927e-a09e0020f9b9
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 2 May 2018
                : 10 September 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1076777
                Award Recipient :
                Funded by: Department of Health and Human Services, State Government of Victoria (AU)
                Award ID: NA
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Medicine
                waiting lists,access,appointments and schedules,outpatients,community health
                Medicine
                waiting lists, access, appointments and schedules, outpatients, community health

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