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Lewis AK, Taylor NF, Carney PW, Bryson A, Sethi M, Ooi S, Tse GT, Harding KE. Sustainability of an intervention to reduce waiting for access to an epilepsy outpatient clinic. Heliyon 2024; 10:e23346. [PMID: 38169770 PMCID: PMC10758808 DOI: 10.1016/j.heliyon.2023.e23346] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 12/01/2023] [Indexed: 01/05/2024] Open
Abstract
Purpose Delays in outpatient specialist neurologist care for people with epilepsy are common despite recommendations for prompt access. There is evidence to suggest that there are interventions that can minimise waitlists and waiting time. However, little is known about whether such interventions can result in sustained improvements in waiting. The aim of this study was to determine the extent to which an intervention to reduce waiting in an epilepsy specialist outpatient clinic demonstrated sustained outcomes two years after the intervention was implemented. Methods This observational study analysed routinely collected epilepsy clinic data over three study periods: pre-intervention, post-intervention and at two-year follow-up. The intervention, Specific Timely Assessment and Triage (STAT), combined a short-term backlog reduction strategy and creation of protected appointments for new referrals based on analysis of demand. After the initial intervention, there was no further active intervention in the following two years. The primary outcome was waiting measured by 1.) waiting time for access to a clinic appointment, defined as the number of days between referral and first appointment for all patients referred to the epilepsy clinic during the three study periods; and 2.) a snapshot of the number of patients on the waitlist at two time points for each of the three study periods. Results Two years after implementing the STAT model in an epilepsy clinic, median waiting time from post-intervention to two-year follow-up was stable (52-51 days) and the interquartile range of days waited reduced from 37 to 77 days post-intervention to 45-57 days at two-year follow-up, with a reduction in the most lengthy wait times observed. After a dramatic reduction of the total number of patients on the waitlist immediately following the intervention, a small rise was seen at two years (n = 69) which remained well below the pre-intervention level (n = 582). Conclusion The STAT model is a promising intervention for reducing waiting in an epilepsy clinic. While there was a small increase in the waitlist after two years, the median waiting time was sustained.
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Affiliation(s)
- Annie K. Lewis
- Eastern Health, Melbourne, Australia
- La Trobe University, Melbourne, Australia
| | - Nicholas F. Taylor
- Eastern Health, Melbourne, Australia
- La Trobe University, Melbourne, Australia
| | - Patrick W. Carney
- Eastern Health, Melbourne, Australia
- Monash University, Melbourne, Australia
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Alexander Bryson
- Eastern Health, Melbourne, Australia
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
| | - Moksh Sethi
- Eastern Health, Melbourne, Australia
- Northern Health, Melbourne, Australia
| | - Suyi Ooi
- Eastern Health, Melbourne, Australia
- The Florey Institute of Neuroscience and Mental Health, Melbourne, Australia
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Harding KE, Lewis AK, Dennett A, Hughes K, Clarke M, Taylor NF. 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 Dev 2024; 50:e13154. [PMID: 37487607 DOI: 10.1111/cch.13154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Revised: 05/21/2023] [Accepted: 06/28/2023] [Indexed: 07/26/2023]
Abstract
BACKGROUND Waiting lists for community-based paediatric therapy services are common and lead to poorer health outcomes, anxiety and missed opportunities for treatment during crucial developmental stages. The Specific Timely Appointments for Triage (STAT) model has been shown to reduce waiting lists in a range of health settings. AIMS To determine whether providing training and support in the STAT model to champions within five community health centres using a remote 'hub and spoke' approach could reduce waiting time from referral to first appointment. METHODS Representatives from five community health centres providing paediatric therapy services (speech therapy, occupational therapy and other allied health services) participated in five online workshops over 6 months. They were guided sequentially through the steps of the STAT model: understanding supply and demand, reducing backlogs, preserving space for new patients based on demand and redesigning models of care to maintain flow. Waiting time was measured in three consecutive years (pre, during and post intervention) and compared using the Kruskal-Wallis test. Employee satisfaction and perception of the model were explored using surveys. RESULTS Data from 2564 children (mean age 3.2 years, 66% male) showed a 33% reduction in waiting time from the pre-intervention (median 57 days) to the post-intervention period (median 38 days, p < 0.01). The total number of children waiting was observed to reduce from 335 immediately prior to the intervention (mean per centre 67, SD 25.1) to 112 (mean 22, SD 13.6) after implementation (t[8] = 3.56, p < 0.01). There was no impact on employee satisfaction or other aspects of service delivery. CONCLUSION Waiting lists are a major challenge across the health system. STAT provides a practical, low-cost, data-driven approach to tackling waiting times. This study demonstrates its effectiveness in paediatric therapy services and provides evidence for a 'hub and spoke' approach to facilitate implementation that could be provided at scale.
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Affiliation(s)
- Katherine E Harding
- School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, Australia
- Eastern Health Allied Health Clinical Research Office, Box Hill, Australia
| | - Annie K Lewis
- School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, Australia
- Eastern Health Allied Health Clinical Research Office, Box Hill, Australia
| | - Amy Dennett
- School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, Australia
- Eastern Health Allied Health Clinical Research Office, Box Hill, Australia
| | - Kylie Hughes
- Department of Families, Fairness and Housing, Government of Victoria, Melbourne, Australia
| | - Michelle Clarke
- Department of Health, Government of Victoria, Melbourne, Australia
| | - Nicholas F Taylor
- School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, Australia
- Eastern Health Allied Health Clinical Research Office, Box Hill, Australia
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Lewis AK, Taylor NF, Carney PW, Li X, Harding KE. An innovative model of access and triage to reduce waiting in an outpatient epilepsy clinic: an intervention study. BMC Health Serv Res 2023; 23:933. [PMID: 37653409 PMCID: PMC10470140 DOI: 10.1186/s12913-023-09845-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 07/24/2023] [Indexed: 09/02/2023] Open
Abstract
BACKGROUND Delayed access to outpatient care may negatively impact on health outcomes. We aimed to evaluate implementation of the Specific Timely Appointments for Triage (STAT) model of access in an epilepsy clinic to reduce a long waitlist and waiting time. METHODS This study is an intervention study using pre-post comparison and an interrupted time series analysis to measure the effect of implementation of the STAT model to an epilepsy clinic. Data were collected over 28 months to observe the number of patients on the waitlist and the waiting time over three time periods: 12 months prior to implementation of STAT, ten months during implementation and six months post-intervention. STAT combines one-off backlog reduction with responsive scheduling that protects time for new appointments based on historical data. The primary outcomes were the number of patients on the waitlist and the waiting time across the three time periods. Secondary outcomes evaluated pre- and post-intervention changes in number of appointments offered weekly, non-arrival and discharge rates. RESULTS A total of 938 patients were offered a first appointment over the study period. The long waitlist was almost eliminated, reducing from 616 during the pre-intervention period to 11 post-intervention (p = 0.002), but the hypothesis that waiting time would decrease was not supported. The interrupted time series analysis indicated a temporary increase in waiting time during the implementation period but no significant change in slope or level in the post- compared to the pre-intervention period. Direct comparison of the cohort of patients seen in the pre- and post-intervention periods suggested an increase in median waiting time following the intervention (34 [IQR 25-86] to 46 [IQR 36-61] days (p = 0.001)), but the interquartile range reduced indicating less variability in days waited and more timely access for the longest waiters. CONCLUSIONS The STAT model was implemented in a specialist epilepsy outpatient clinic and reduced a large waitlist. Reductions in the waitlist were achieved with little or no increase in waiting time. The STAT model provides a framework for an alternative way to operate outpatient clinics that can help to ensure that all people referred are offered an appointment in a timely manner.
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Affiliation(s)
- Annie K Lewis
- Eastern Health; Allied Health Clinical Research Office, Level 2, 5 Arnold St, Box Hill, Victoria, 3128, Australia.
- La Trobe University; School of Allied Health, Health Services and Sport, La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia.
| | - Nicholas F Taylor
- Eastern Health; Allied Health Clinical Research Office, Level 2, 5 Arnold St, Box Hill, Victoria, 3128, Australia
- La Trobe University; School of Allied Health, Health Services and Sport, La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Patrick W Carney
- Eastern Health; Allied Health Clinical Research Office, Level 2, 5 Arnold St, Box Hill, Victoria, 3128, Australia
- Monash University, 21 Chancellors Walk, Clayton, VIC, 3800, Australia
- The Florey Institute for Neuroscience and Mental Health, Melbourne Brain Centre, Burgundy Street, Heidelberg, VIC, 3084, Australia
| | - Xia Li
- Department of Mathematical and Physical Sciences, La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Katherine E Harding
- Eastern Health; Allied Health Clinical Research Office, Level 2, 5 Arnold St, Box Hill, Victoria, 3128, Australia
- La Trobe University; School of Allied Health, Health Services and Sport, La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
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Amigoni F, Lega F, Maggioni E. Insights into how universal, tax-funded, single payer health systems manage their waiting lists: A review of the literature. Health Serv Manage Res 2023:9514848231186773. [PMID: 37394445 DOI: 10.1177/09514848231186773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Background: A conspicuous consequence of gatekeeping arrangements in universal, tax-funded, single-payer health care systems is the long waiting times. Besides limiting equal access to care, long waiting times can have a negative impact on health outcomes. Long waiting times can create obstacles in a patient's care pathway. Organization for Economic Co-operation and Development (OECD) countries have implemented various strategies to tackle this issue, but there is little evidence for which approach is the most effective. This literature review examined waiting times for ambulatory care. Objective: The aim was to identify the main policies or combinations of policies universal, tax-funded, and single-payer healthcare systems have implemented to improve the governance of outpatient waiting times. Methods: Starting from 1040 potentially eligible articles, a total of 41 studies were identified via a 2-step selection process. Findings: Despite the relevance of the issue, the literature is limited. A set of 15 policies for the governance of ambulatory waiting time was identified and categorized by the type of intervention: generation of supply capacity, control of demand, and mixed interventions. Even if a primary intervention was always identifiable, rarely a policy was implemented solo. The most frequent primary strategies were: guidelines implementation and/or clinical pathways, including triage, guidelines for referral and maxim waiting times (14 studies), task shifting (9 studies), and telemedicine (6 studies). Most studies were observational, with no data on costs of intervention and impact on clinical outcomes.
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Affiliation(s)
- Francesco Amigoni
- European Master in Health Economics and Management, MCI Management Center Innsbruck Internationale Hochschule GmbH, Innsbruck, Austria
| | - Federico Lega
- Department of Biomedical Sciences for Health and Acting Director of the Research Center in Health Administration (HEAD), University of Milan, Milano, Italy
| | - Elena Maggioni
- Research Center in Health Administration (HEAD), University of Milan, Milano, Italy
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Darkwa M, Engel K, Findlay Z, Voyer AM, Waddell AE. Using co-design to improve the client waiting experience at an outpatient mental health clinic. BMJ Open Qual 2023; 12:bmjoq-2021-001781. [PMID: 36599501 PMCID: PMC9814997 DOI: 10.1136/bmjoq-2021-001781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 12/23/2022] [Indexed: 01/05/2023] Open
Abstract
Prolonged wait times in healthcare are a complex issue that can negatively impact both clients and staff. Longer wait times are often caused by a number of factors such as overly complicated scheduling, inefficient use of resources, extraneous processes, and misalignment of supply and demand. Growing evidence suggests a correlation between wait times and client satisfaction. This relationship, however, is complex. Some research suggests that client satisfaction with wait times may be improved with interventions that enhance the waiting experience and not actual wait times. This project aimed to improve the average daily rating of the client waiting experience by 1 point on a 7-point Likert scale.A quality improvement study was conducted to analyse client satisfaction with wait times and enhance clients' satisfaction while waiting. Quality improvement methods, mainly co-design sessions, were used to co-create and implement an intervention to improve clients' experience with waiting in the clinic.The project resulted in the implementation of a whiteboard intervention in the clinic to inform clients where they are in the queue. The whiteboard also included static data summarising the average wait times from the previous month. Both aspects of the whiteboard were designed to allow patients to better approximate their wait times. Though the quantitative analysis did not reveal a 1-point improvement on a 7-point Likert scale, the feedback from staff and clients was positive. Since implementation, clinic staff and management have developed the intervention into a high-fidelity digital board that is still in use today. Furthermore, the use of the intervention has been extended locally, with additional ambulatory clinics at the hospital planning to use the set-up in their clinic waiting rooms.
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Affiliation(s)
- Maame Darkwa
- Faculty of Laboratory Medicine & Pathology, University of Toronto, Toronto, Ontario, Canada
| | - Katrina Engel
- Faculty of Laboratory Medicine & Pathology, University of Toronto, Toronto, Ontario, Canada
| | - Zoe Findlay
- Faculty of Laboratory Medicine & Pathology, University of Toronto, Toronto, Ontario, Canada
| | - Anne-Marie Voyer
- Faculty of Laboratory Medicine & Pathology, University of Toronto, Toronto, Ontario, Canada
| | - Andrea E Waddell
- Department of Psychiatry, Centre for Addiction and Mental Health (CAMH), Toronto, Ontario, Canada
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Presented a Framework of Computational Modeling to Identify the Patient Admission Scheduling Problem in the Healthcare System. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:1938719. [PMID: 36483659 PMCID: PMC9726263 DOI: 10.1155/2022/1938719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Revised: 03/08/2022] [Accepted: 03/23/2022] [Indexed: 11/30/2022]
Abstract
Operating room scheduling is a prominent study topic due to its complexity and significance. The increasing number of technical operating room scheduling articles produced each year calls for another evaluation of the literature to enable academics to respond to new trends more quickly. The mathematical application of a model for the patient admission scheduling issue with stochastic arrivals and departures is the subject of this study. The approach for applying our model to real-world issues is discussed here. We present a solution technique for efficient computing, a numerical model analysis, and examples to demonstrate the methodology. This study looked at the challenge of assigning procedures to operate rooms in the face of ambiguity regarding surgery length and the arrival of emergency patients based on a flexible policy (capacity reservation). We demonstrate that the proposed methods derived from deterministic models are inadequate compared to the answers produced from our stochastic model using simple numerical examples. We also use heuristics to estimate the objective function to build more complicated numerical examples for large-scale issues, demonstrating that our methodology can be applied quickly to real-world situations that often include big information sets.
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7
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Crawford T, Parsons J, Webber S, Fricke M, Thille P. Strategies to Increase Access to Outpatient Physiotherapy Services: A Scoping Review. Physiother Can 2022; 74:197-207. [PMID: 37323714 PMCID: PMC10262743 DOI: 10.3138/ptc-2020-0119] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 06/16/2021] [Accepted: 07/25/2021] [Indexed: 07/20/2023]
Abstract
Purpose: Multiple Canadian jurisdictions have curtailed public funding for outpatient physiotherapy services, impacting access and potentially creating or worsening inequities in access. We sought to identify evaluated organizational strategies that aimed to improve access to physiotherapy services for community-dwelling persons. Method: We used Arksey and O'Malley's scoping review methods, including a systematic search of CINAHL, MEDLINE, and Embase for relevant peer-reviewed texts published in English, French, or German, and we performed a qualitative content analysis of included articles. Results: Fifty-one peer-reviewed articles met inclusion criteria. Most studies of interventions or system changes to improve access took place in the United Kingdom (17), the United States (12), Australia (9), and Canada (8). Twenty-nine studies aimed to improve access for patients with musculoskeletal conditions; only five studies examined interventions to improve equitable access for underserved populations. The most common interventions and system changes studied were expanded physiotherapy roles, direct access, rapid access systems, telerehabilitation, and new community settings. Conclusions: Studies evaluating interventions and health system changes to improve access to physiotherapy services have been limited in focus, and most have neglected to address inequities in access. To improve equitable access to physiotherapy services in Canada, physiotherapy providers in local settings can implement and evaluate transferable patient-centred access strategies, particularly telerehabilitation and primary care integration.
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Affiliation(s)
- Tory Crawford
- Department of Physical Therapy, College of Rehabilitation Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Joanne Parsons
- Department of Physical Therapy, College of Rehabilitation Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Sandra Webber
- Department of Physical Therapy, College of Rehabilitation Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Moni Fricke
- Department of Physical Therapy, College of Rehabilitation Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Patricia Thille
- Department of Physical Therapy, College of Rehabilitation Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
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Dupuis F, Déry J, Lucas de Oliveira FC, Pecora AT, Gagnon R, Harding K, Camden C, Roy JS, Lettre J, Hudon A, Beauséjour M, Pinard AM, Bath B, Deslauriers S, Lamontagne MÈ, Feldman D, Routhier F, Desmeules F, Hébert LJ, Miller J, Ruiz A, Perreault K. Strategies to reduce waiting times in outpatient rehabilitation services for adults with physical disabilities: A systematic literature review. J Health Serv Res Policy 2022; 27:157-167. [DOI: 10.1177/13558196211065707] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Objective Identifying effective strategies to reduce waiting times is a crucial issue in many areas of health services. Long waiting times for rehabilitation services have been associated with numerous adverse effects in people with disabilities. The main objective of this study was to conduct a systematic literature review to assess the effectiveness of service redesign strategies to reduce waiting times in outpatient rehabilitation services for adults with physical disabilities. Methods We conducted a systematic review, searching three databases (MEDLINE, CINAHL and EMBASE) from their inception until May 2021. We identified studies with comparative data evaluating the effect of rehabilitation services redesign strategies on reducing waiting times. The Mixed Methods Appraisal Tool was used to assess the methodological quality of the studies. A narrative synthesis was conducted. Results Nineteen articles including various settings and populations met the selection criteria. They covered physiotherapy ( n = 11), occupational therapy ( n = 2), prosthetics ( n = 1), exercise physiology ( n = 1) and multidisciplinary ( n = 4) services. The methodological quality varied ( n = 10 high quality, n = 6 medium, n = 3 low); common flaws being missing information on the pre-redesign setting and characteristics of the populations. Seven articles assessed access processes or referral management strategies (e.g. self-referral), four focused on extending/modifying the roles of service providers (e.g. to triage) and eight changed the model of care delivery (e.g. mode of intervention). The different redesign strategies had positive effects on waiting times in outpatient rehabilitation services. Conclusions This review highlights the positive effects of many service redesign strategies. These findings suggest that there are several effective strategies to choose from to reduce waiting times and help better respond to the needs of persons experiencing physical disabilities.
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Affiliation(s)
- Frédérique Dupuis
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | - Julien Déry
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | - Fabio Carlos Lucas de Oliveira
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | - Ana Tereza Pecora
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | - Rose Gagnon
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | - Katherine Harding
- Allied Health Clinical Research Office, Eastern Health, Victoria, Australia
| | - Chantal Camden
- École de réadaptation, Faculté de médecine et des sciences de la santé, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Jean-Sébastien Roy
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | - Josiane Lettre
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | - Anne Hudon
- École de Réadaptation, Université de Montréal, Montreal, QC, Canada
| | - Marie Beauséjour
- Département des Sciences de la santé communautaire, Université de Sherbrooke, Longueuil, QC, Canada
| | - Anne-Marie Pinard
- Département D’anesthésiologie et de Soins Intensifs, Faculté de Médecine, Université Laval, Québec, QC, Canada
| | - Brenna Bath
- School of Rehabilitation Science, College of Medicine, University of Saskatchewan, Saskatoon, SK, Canada
| | - Simon Deslauriers
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | - Marie-Ève Lamontagne
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | - Debbie Feldman
- École de Réadaptation, Université de Montréal, Montreal, QC, Canada
| | - François Routhier
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | | | - Luc J. Hébert
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
| | - Jordan Miller
- School of Rehabilitation Therapy, Physical Therapy Program, Queen’s University, Kingston, ON, Canada
| | - Angel Ruiz
- Département d’opérations et systèmes de décision, Faculté des sciences de l’administration, Université Laval, Québec, QC, Canada
| | - Kadija Perreault
- Center for Interdisciplinary Research in Rehabilitation and Social Integration (Cirris), Centre intégré universitaire de santé et de services sociaux (CIUSSS) de la Capitale-Nationale, Québec, Canada
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9
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Li X, Tian D, Li W, Hu Y, Dong B, Wang H, Yuan J, Li B, Mei H, Tong S, Zhao L, Liu S. Using artificial intelligence to reduce queuing time and improve satisfaction in pediatric outpatient service: A randomized clinical trial. Front Pediatr 2022; 10:929834. [PMID: 36034568 PMCID: PMC9399636 DOI: 10.3389/fped.2022.929834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 07/25/2022] [Indexed: 11/13/2022] Open
Abstract
INTRODUCTION Complicated outpatient procedures are associated with excessive paperwork and long waiting times. We aimed to shorten queuing times and improve visiting satisfaction. METHODS We developed an artificial intelligence (AI)-assisted program named Smart-doctor. A randomized controlled trial was conducted at Shanghai Children's Medical Center. Participants were randomly divided into an AI-assisted and conventional group. Smart-doctor was used as a medical assistant in the AI-assisted group. At the end of the visit, an e-medical satisfaction questionnaire was asked to be done. The primary outcome was the queuing time, while secondary outcomes included the consulting time, test time, total time, and satisfaction score. Wilcoxon rank sum test, multiple linear regression and ordinal regression were also used. RESULTS We enrolled 740 eligible patients (114 withdrew, response rate: 84.59%). The median queuing time was 8.78 (interquartile range [IQR] 3.97,33.88) minutes for the AI-assisted group versus 21.81 (IQR 6.66,73.10) minutes for the conventional group (p < 0.01), and the AI-assisted group had a shorter consulting time (0.35 [IQR 0.18, 0.99] vs. 2.68 [IQR 1.82, 3.80] minutes, p < 0.01), and total time (40.20 [IQR 26.40, 73.80] vs. 110.40 [IQR 68.40, 164.40] minutes, p < 0.01). The overall satisfaction score was increased by 17.53% (p < 0.01) in the AI-assisted group. In addition, multiple linear regression and ordinal regression showed that the queuing time and satisfaction were mainly affected by group (p < 0.01), and missing the turn (p < 0.01). CONCLUSIONS Using AI to simplify the outpatient service procedure can shorten the queuing time of patients and improve visit satisfaction.
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Affiliation(s)
- Xiaoqing Li
- School of Medicine, Shanghai Children's Medical Center, Child Health Advocacy Institute, Shanghai Jiao Tong University, Shanghai, China.,School of Public Health, Shanghai Jiao Tong University, Shanghai, China
| | - Dan Tian
- Division of Hospital Management, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Pediatric AI Clinical Application and Research Center, Shanghai Children's Medical Center, Shanghai, China.,Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China
| | - Weihua Li
- Division of Hospital Management, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Pediatric AI Clinical Application and Research Center, Shanghai Children's Medical Center, Shanghai, China.,Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China
| | - Yabin Hu
- School of Medicine, Shanghai Children's Medical Center, Child Health Advocacy Institute, Shanghai Jiao Tong University, Shanghai, China
| | - Bin Dong
- Division of Hospital Management, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Pediatric AI Clinical Application and Research Center, Shanghai Children's Medical Center, Shanghai, China.,Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China
| | - Hansong Wang
- Division of Hospital Management, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Pediatric AI Clinical Application and Research Center, Shanghai Children's Medical Center, Shanghai, China.,Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China
| | - Jiajun Yuan
- Division of Hospital Management, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Pediatric AI Clinical Application and Research Center, Shanghai Children's Medical Center, Shanghai, China.,Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China
| | - Biru Li
- Department of Pediatric Internal Medicine, Shanghai Children's Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hao Mei
- School of Medicine, Shanghai Children's Medical Center, Child Health Advocacy Institute, Shanghai Jiao Tong University, Shanghai, China.,Department of Data Science, School of Population Health, University of Mississippi Medical Center, Jackson, MS, United States
| | - Shilu Tong
- School of Medicine, Shanghai Children's Medical Center, Child Health Advocacy Institute, Shanghai Jiao Tong University, Shanghai, China.,School of Public Health and Social Work, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, QLD, Australia
| | - Liebin Zhao
- Shanghai Engineering Research Center of Intelligence Pediatrics (SERCIP), Shanghai, China
| | - Shijian Liu
- School of Medicine, Shanghai Children's Medical Center, Child Health Advocacy Institute, Shanghai Jiao Tong University, Shanghai, China.,School of Public Health, Shanghai Jiao Tong University, Shanghai, China
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Spagnolo J, Breton M, Sasseville M, Sauvé C, Clément JF, Fleet R, Tremblay MC, Rodrigue C, Lebel C, Beauséjour M. Exploring the implementation and underlying mechanisms of centralized referral systems to access specialized health services in Quebec. BMC Health Serv Res 2021; 21:1345. [PMID: 34915871 PMCID: PMC8674406 DOI: 10.1186/s12913-021-07286-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Accepted: 11/09/2021] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND In 2016, Quebec, a Canadian province, implemented a program to improve access to specialized health services (Accès priorisé aux services spécialisés (APSS)), which includes single regional access points for processing requests to such services via primary care (Centre de répartition des demandes de services (CRDS)). Family physicians fill out and submit requests for initial consultations with specialists using a standardized form with predefined prioritization levels according to listed reasons for consultations, which is then sent to the centralized referral system (the CRDS) where consultations with specialists are assigned. We 1) described the APSS-CRDS program in three Quebec regions using logic models; 2) compared similarities and differences in the components and processes of the APSS-CRDS models; and 3) explored contextual factors influencing the models' similarities and differences. METHODS We relied on a qualitative study to develop logic models of the implemented APSS-CRDS program in three regions. Semi-structured interviews with health administrators (n = 9) were conducted. The interviews were analysed using a framework analysis approach according to the APSS-CRDS's components included in the initially designed program, Mitchell and Lewis (2003)'s logic model framework, and Chaudoir and colleagues (2013)'s framework on contextual factors' influence on an innovation's implementation. RESULTS Findings show the APSS-CRDS program's regional variability in the implementation of its components, including its structure (centralized/decentralized), human resources involved in implementation and operation, processes to obtain specialists' availability and assess/relay requests, as well as monitoring methods. Variability may be explained by contextual factors' influence, like ministerial and medical associations' involvement, collaborations, the context's implementation readiness, physician practice characteristics, and the program's adaptability. INTERPRETATION Findings are useful to inform decision-makers on the design of programs like the APSS-CRDS, which aim to improve access to specialists, the essential components for the design of these types of interventions, and how contextual factors may influence program implementation. Variability in program design is important to consider as it may influence anticipated effects, a next step for the research team. Results may also inform stakeholders should they wish to implement similar programs to increase access to specialized health services via primary care.
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Affiliation(s)
- Jessica Spagnolo
- Department of Community Health Sciences, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 150, Place Charles-Le Moyne, C. P. 200, Longueuil, QC, J4K 0A8, Canada.,Centre de recherche Charles-LeMoyne, Université de Sherbrooke - Campus Longueuil, 150, place Charles-Le Moyne, C. P. 200, Longueuil, QC, J4K 0A8, Canada
| | - Mylaine Breton
- Department of Community Health Sciences, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 150, Place Charles-Le Moyne, C. P. 200, Longueuil, QC, J4K 0A8, Canada.,Centre de recherche Charles-LeMoyne, Université de Sherbrooke - Campus Longueuil, 150, place Charles-Le Moyne, C. P. 200, Longueuil, QC, J4K 0A8, Canada
| | - Martin Sasseville
- Centre de recherche Charles-LeMoyne, Université de Sherbrooke - Campus Longueuil, 150, place Charles-Le Moyne, C. P. 200, Longueuil, QC, J4K 0A8, Canada
| | - Carine Sauvé
- Centre intégré de santé et de services sociaux (CISSS) de la Montérégie-Centre, 3141 Boulevard Taschereau Bureau 220, Greenfield Park, QC, J4V 2H2, Canada
| | - Jean-François Clément
- Centre de recherche Charles-LeMoyne, Université de Sherbrooke - Campus Longueuil, 150, place Charles-Le Moyne, C. P. 200, Longueuil, QC, J4K 0A8, Canada.,Department of Family Medicine and Emergency Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 2500 Boulevard de l'Université, Sherbrooke, QC, J1K 2R1, Canada
| | - Richard Fleet
- Department of Family and Emergency Medicine, Faculty of Medicine, Université Laval, Pavillon Ferdinand-Vandry, 1050, Avenue de la Médecine, Québec, QC, G1V 0A6, Canada.,Centre de recherche en santé durable, Centre intégré universitaire de santé et services sociaux (CIUSSS) de la Capitale-Nationale, Pavillon Landry-Poulin, 2525 chemin de la Canardière, Québec, QC, G1J 0A4, Canada
| | - Marie-Claude Tremblay
- Department of Family and Emergency Medicine, Faculty of Medicine, Université Laval, Pavillon Ferdinand-Vandry, 1050, Avenue de la Médecine, Québec, QC, G1V 0A6, Canada.,Centre de recherche en santé durable, Centre intégré universitaire de santé et services sociaux (CIUSSS) de la Capitale-Nationale, Pavillon Landry-Poulin, 2525 chemin de la Canardière, Québec, QC, G1J 0A4, Canada
| | - Cloé Rodrigue
- Centre de recherche Charles-LeMoyne, Université de Sherbrooke - Campus Longueuil, 150, place Charles-Le Moyne, C. P. 200, Longueuil, QC, J4K 0A8, Canada.,Centre intégré de santé et de services sociaux (CISSS) de la Montérégie-Centre, 3141 Boulevard Taschereau Bureau 220, Greenfield Park, QC, J4V 2H2, Canada
| | - Camille Lebel
- Department of Surgery, Faculty of Medicine, Université de Montréal, C.P, 6128, succursale Centre-ville, Montréal, QC, H3C 3J7, Canada
| | - Marie Beauséjour
- Department of Community Health Sciences, Faculty of Medicine and Health Sciences, Université de Sherbrooke, 150, Place Charles-Le Moyne, C. P. 200, Longueuil, QC, J4K 0A8, Canada. .,Centre de recherche Charles-LeMoyne, Université de Sherbrooke - Campus Longueuil, 150, place Charles-Le Moyne, C. P. 200, Longueuil, QC, J4K 0A8, Canada. .,Department of Surgery, Faculty of Medicine, Université de Montréal, C.P, 6128, succursale Centre-ville, Montréal, QC, H3C 3J7, Canada.
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11
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Teramoto K, Kuwata S. Design and Evaluation of a Smartphone Medical Guidance App for Outpatients of Large-Scale Medical Institutions: A Retrospective Observational Study. JMIR Form Res 2021; 6:e32990. [PMID: 34818208 PMCID: PMC9037305 DOI: 10.2196/32990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Revised: 10/31/2021] [Accepted: 11/22/2021] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND The greatest stressor for outpatients is the waiting time before an examination. If the patient is able to use their smartphone to check in with the reception, the patient can wait for their examination at any location, and the burden of waiting can be reduced. OBJECTIVE This study aimed to report the system design and post-introductory outcomes of the Tori RinRin (TR2) system that was developed to reduce outpatient burden imposed by wait times before examination. METHODS The TR2 system was introduced at Tottori University Hospital, a large medical facility that accepts a daily average of 1,500 outpatients. The system, which links the hospital's electronic medical record database with patients' mobile devices, has the following two functions: 1) GPS-based examination check-in processing and 2) sending appointment notification messages via a cloud notification service. In order to evaluate the usefulness of the TR2 system, we surveyed the utilization rate of the TR2 system among outpatient, implemented a user questionnaire and polling the average time required for patients to respond to call notifications about their turn. RESULTS The 3 months average of TR2 users 9 months after the TR 2 system introduction was 17.9% (81,066 of 14,536 patients). In an investigation of 363 subjects, the mean examination call message response time using the TR2 system was 31 seconds (median 14 seconds). Among 166 subjects who responded to a user survey, 86.7% (144 of 166 patients) said that the system help reduce the burden of waiting time. CONCLUSIONS The app allowed 17.9% of outpatients at a large medical facility to check in remotely and wait for examinations anywhere. Hence, it is effective in preventing the spread of infection, especially during pandemics such as the coronavirus disease. The app reported in this study is beneficial for large medical facilities striving to reduce outpatient burden imposed by wait times. CLINICALTRIAL
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Affiliation(s)
- Kei Teramoto
- Tottori University Hospital, Nishi-cho36-1, Yonago, JP
| | - Shigeki Kuwata
- Department of Clinical Information Management, Nara City Hospital, Nara, JP
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12
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Lewis AK, Taylor NF, Carney PW, Harding KE. Reducing the waitlist of referred patients in a medical specialist outpatient clinic: an observational study. J Health Organ Manag 2021; ahead-of-print. [PMID: 33274613 DOI: 10.1108/jhom-08-2020-0321] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
PURPOSE Long waitlists in outpatient clinics are a widely recognised problem. The purpose of this paper is to describe and report the impact of a waitlist reduction strategy for an epilepsy clinic. DESIGN/METHODOLOGY/APPROACH This observational study described the local impact of a methodical approach to tackling a long waiting list, using targeted strategies supported by a modest additional budget. The interventions were described using the template for intervention description and replication (TIDieR). FINDINGS Over an eight-month period, the waitlist for the epilepsy clinic was reduced from 599 to 24 patients without increasing the number of days until the next available appointment. Most referrals were removed from the waitlist without an appointment. Auditing revealed a high proportion of patients no longer required the service or referrals remained on the waitlist due to administration error. A short-term increase in clinic capacity of 51 extra appointments met the needs of the remaining waiting patients. The additional project funding invested in this process was AUD $10,500 and a time-limited amount of extra work was absorbed by using existing clinic resources. PRACTICAL IMPLICATIONS This waitlist reduction strategy resulted in a very small waitlist for the epilepsy clinic, which is now well placed to trial further interventions with the aim of sustaining the service with minimal waiting times. Not every referral on the waitlist, particularly the very long waiters, required an appointment. Other outpatient clinics may be able to apply this process to reduce their waitlists using a modest budget. ORIGINALITY/VALUE Although there are reports of successful waitlist reduction, few report the intervention in detail. Use of the TIDieR in reporting enables the intervention to be appraised or adapted to other settings where long waitlists are problematic. Considerations related to implementation of policy are discussed and in this case, a locally led and executed change management strategy was a key to achieving the result.
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Affiliation(s)
- Annie K Lewis
- Eastern Health, Melbourne, Australia.,La Trobe University - Bundoora Campus, Melbourne, Australia
| | - Nicholas F Taylor
- Eastern Health, Melbourne, Australia.,La Trobe University - Bundoora Campus, Melbourne, Australia
| | - Patrick W Carney
- Eastern Health, Melbourne, Australia.,Monash University, Melbourne, Australia
| | - Katherine E Harding
- Eastern Health, Melbourne, Australia.,La Trobe University - Bundoora Campus, Melbourne, Australia
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13
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Snowdon DA, Harding KE, Taylor NF, Leggat SG, Kent B, Lewis AK, Watts JJ. Return on investment of a model of access combining triage with initial management: an economic analysis. BMJ Open 2021; 11:e045096. [PMID: 34290062 PMCID: PMC8296773 DOI: 10.1136/bmjopen-2020-045096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Abstract
OBJECTIVES Timely access to outpatient services is a major issue for public health systems. To address this issue, we aimed to establish the return on investment to the health system of the implementation of an alternative model for access and triage (Specific Timely Appointments for Triage: STAT) compared with a traditional waitlist model. DESIGN Using a prospective pre-post design, an economic analysis was completed comparing the health system costs for participants who were referred for community outpatient services post-implementation of STAT with a traditional waitlist comparison group. SETTING Eight community outpatient services of a health network in Melbourne, Australia. PARTICIPANTS Adults and children referred to community outpatient services. INTERVENTIONS STAT combined targeted activities to reduce the existing waiting list and direct booking of patients into protected assessment appointments. STAT was compared with usual care, in which new patients were placed on a waiting list and offered appointments as space became available. OUTCOMES Health system costs included STAT implementation costs, outpatient health service use, emergency department presentations and hospital admissions 3 months before and after initial outpatient appointment. Waiting time was the primary outcome. Incremental cost-effectiveness ratios (ICERs) were estimated from the health system perspective. RESULTS Data from 557 participants showed a 16.9 days or 29% (p<0.001) reduction in waiting time for first appointment with STAT compared with traditional waitlist. The ICER showed a cost of $A10 (95% CI -19 to 39) per day reduction in waiting time with STAT compared with traditional waitlist. Modelling showed the cost reduced to $A4 (95% CI -25 to 32) per day of reduction in waiting, if reduction in waiting times is sustained for 12 months. CONCLUSIONS There was a significant reduction in waiting time with the introduction of STAT at minimal cost to the health system. TRIAL REGISTRATION NUMBER Australian New Zealand Clinical Trials Registry (ACTRN12615001016527).
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Affiliation(s)
- David A Snowdon
- Peninsula Clinical School, Central Clinical School, Monash University, Frankston, Victoria, Australia
- Allied Health Clinical Research Office, Eastern Health, Box Hill, Victoria, Australia
| | - Katherine E Harding
- Allied Health Clinical Research Office, Eastern Health, Box Hill, Victoria, Australia
- School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Victoria, Australia
| | - Nicholas F Taylor
- Allied Health Clinical Research Office, Eastern Health, Box Hill, Victoria, Australia
- School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Victoria, Australia
| | - Sandra G Leggat
- School of Psychology and Public Health, La Trobe University, Bundoora, Victoria, Australia
- School of Public Health, Harbin Medical University, Harbin, People's Republic of China
| | - Bridie Kent
- School of Nursing and Midwifery, Plymouth University, Plymouth, UK
| | - Annie K Lewis
- Allied Health Clinical Research Office, Eastern Health, Box Hill, Victoria, Australia
- School of Allied Health, Human Services and Sport, La Trobe University, Bundoora, Victoria, Australia
| | - Jennifer J Watts
- School of Health and Social Development, Faculty of Health, Deakin University, Burwood, Victoria, Australia
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14
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Speed D. Improving Administrative Outcomes in Physiotherapy by Adopting Open-Access Booking. Physiother Can 2021. [DOI: 10.3138/ptc-2020-0071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Purpose: Long wait times for physiotherapy are associated with poorer health trajectories for clients. Clients’ experiences with physiotherapy services in Saint John were suboptimal; thus, this study explored making administrative changes to improve those experiences. All physiotherapy services adopted an administrative model called open-access booking (OAB), which blended elements of advanced access, triage, and centralized wait lists. Method: OAB was instituted in the first week of February 2017 and has been active since. The researcher accessed more than 20,000 anonymized case records spanning 5 years (February 2014–January 2019) and compared the 3-year pre-OAB phase with the 2-year OAB phase using interrupted time series analysis models. Results: OAB appeared to not be associated with changes in client volume, but it was associated with fewer “on-paper” clients, shorter wait times to first appointment, more consistent record keeping, a greater likelihood of being discharged after one appointment, and fewer appointments before discharge. There was less variability in these outcomes after the adoption of OAB, suggesting a more stable client experience with the physiotherapy system. Conclusions: OAB appears to be associated with improved administrative outcomes, but strict causality cannot be assessed. The results are promising but not conclusive.
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Affiliation(s)
- David Speed
- Department of Psychology, University of New Brunswick, Saint John, New Brunswick, Canada
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15
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Barriers and facilitators for implementation of a patient prioritization tool in two specialized rehabilitation programs. JBI Evid Implement 2021; 19:149-161. [PMID: 33843768 DOI: 10.1097/xeb.0000000000000281] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
INTRODUCTION AND AIMS Prioritization tools aim to manage access to care by ranking patients equitably in waiting lists based on determined criteria. Patient prioritization has been studied in a wide variety of clinical health services, including rehabilitation contexts. We created a web-based patient prioritization tool (PPT) with the participation of stakeholders in two rehabilitation programs, which we aim to implement into clinical practice. Successful implementation of such innovation can be influenced by a variety of determinants. The goal of this study was to explore facilitators and barriers to the implementation of a PPT in rehabilitation programs. METHODS We used two questionnaires and conducted two focus groups among service providers from two rehabilitation programs. We used descriptive statistics to report results of the questionnaires and qualitative content analysis based on the Consolidated Framework for Implementation Research. RESULTS Key facilitators are the flexibility and relative advantage of the tool to improve clinical practices and produce beneficial outcomes for patients. Main barriers are the lack of training, financial support and human resources to sustain the implementation process. CONCLUSION This is the first study that highlights organizational, individual and innovation levels facilitators and barriers for the implementation of a prioritization tool from service providers' perspective.
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16
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Harding KE, Lewis AK, Snowdon DA, Kent B, Taylor NF. A Multi-Faceted Strategy for Evidence Translation Reduces Healthcare Waiting Time: A Mixed Methods Study Using the RE-AIM Framework. FRONTIERS IN REHABILITATION SCIENCES 2021; 2:638602. [PMID: 36188815 PMCID: PMC9397794 DOI: 10.3389/fresc.2021.638602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 03/01/2021] [Indexed: 11/13/2022]
Abstract
Background: Waiting lists are often thought to be inevitable in healthcare, but strategies that address patient flow by reducing complexity, combining triage with initial management, and/or actively managing the relationship between supply and demand can work. One such model, Specific Timely Appointments for Triage (STAT), brings these elements together and has been found in multiple trials to reduce waiting times by 30–40%. The next challenge is to translate this knowledge into practice. Method: A multi-faceted knowledge translation strategy, including workshops, resources, dissemination of research findings and a community of practice (CoP) was implemented. A mixed methods evaluation of the strategy was conducted based on the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework, drawing on an internal database and a survey of workshop and CoP participants. Results: Demonstrating reach, at July 2020 an internal database held details of 342 clinicians and managers from 64 health services who had participated in the workshop program (n = 308) and/or elected to join an online CoP (n = 227). 40 of 69 (58%) respondents to a survey of this population reported they had adopted the model, with some providing data demonstrating that the STAT model had been efficacious in reducing waiting time. Perceived barriers to implementation included an overwhelming existing waiting list, an imbalance between supply and demand and lack of resources. Conclusion: There is high quality evidence from trials that STAT reduces waiting time. Using the RE-AIM framework, this evaluation of a translation strategy demonstrates uptake of evidence to reduce waiting time in health services.
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Affiliation(s)
- Katherine E. Harding
- Allied Health Clinical Research Office, Eastern Health, Melbourne, VIC, Australia
- School of Allied Health, La Trobe University, Melbourne, VIC, Australia
- *Correspondence: Katherine E. Harding
| | - Annie K. Lewis
- Allied Health Clinical Research Office, Eastern Health, Melbourne, VIC, Australia
- School of Allied Health, La Trobe University, Melbourne, VIC, Australia
| | - David A. Snowdon
- Allied Health Clinical Research Office, Eastern Health, Melbourne, VIC, Australia
| | - Bridie Kent
- Faculty of Health, University of Plymouth, Plymouth, United Kingdom
| | - Nicholas F. Taylor
- Allied Health Clinical Research Office, Eastern Health, Melbourne, VIC, Australia
- School of Allied Health, La Trobe University, Melbourne, VIC, Australia
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17
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Harding KE, Snowdon DA, Prendergast L, Lewis AK, Kent B, Leggat SF, Taylor NF. 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 Serv Res 2020; 20:968. [PMID: 33087110 PMCID: PMC7579912 DOI: 10.1186/s12913-020-05824-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2020] [Accepted: 10/15/2020] [Indexed: 11/21/2022] Open
Abstract
Background Timely access is a challenge for providers of outpatient and community-based health services, as seen by the often lengthy waiting lists to manage demand. The Specific Timely Appointments for Triage (STAT) model, an alternative approach for managing access and triage, reduced waiting time by 34% in a stepped wedge cluster randomised controlled trial involving 8 services and more than 3000 participants. Follow up periods ranged from 3 to 10 months across the participating services in accordance with the stepped wedge design. This study aimed to determine whether outcomes were sustained for a full 12 months after implementation of the STAT model at each site. Methods Routinely collected service data were obtained for a total of 12 months following implementation of the STAT model at each of the 8 services that participated in a stepped wedge cluster randomised controlled trial. The primary outcome was time to first appointment. Secondary outcomes included non-attendance rates, time to second appointment and service use over 12 weeks. Outcomes were compared to pre-intervention data from the original trial, modelled using generalised linear mixed effects models accounting for clustering of sites. Results A 29% reduction in waiting time could be attributed to STAT over 12 months, compared to 34% in the original trial. A reduction in variability in waiting time was sustained. There were no significant changes in time to second appointment or in the number of missed appointments in the extended follow up period. Conclusions STAT is an effective strategy for reducing waiting time in community-based outpatient services. At 12 months, small reductions in the overall effect are apparent, but reductions in variability are sustained, suggesting that people who previously waited the longest benefit most from the STAT model. Trial registration This is a 12-month follow up of a stepped wedge cluster randomised controlled trial that was registered with the Australia and New Zealand Clinical Trials Registry (ACTRN12615001016527).
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Affiliation(s)
- Katherine E Harding
- Allied Health Clinical Rsearch Office, Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia. .,La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia.
| | - David A Snowdon
- Allied Health Clinical Rsearch Office, Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia
| | - Luke Prendergast
- La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Annie K Lewis
- Allied Health Clinical Rsearch Office, Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia
| | - Bridie Kent
- Drake Circus, Plymouth University, Plymouth, Devon, PL4 8AA, UK
| | - Sandy F Leggat
- La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Nicholas F Taylor
- Allied Health Clinical Rsearch Office, Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia.,La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
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Poyah PS, Quraishi TA. The Impact of a New Triage and Booking System on Renal Clinic Wait Times. Can J Kidney Health Dis 2020; 7:2054358120924140. [PMID: 32547773 PMCID: PMC7271271 DOI: 10.1177/2054358120924140] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Accepted: 03/17/2020] [Indexed: 11/23/2022] Open
Abstract
Background: Prolonged wait times are known barriers to accessing nephrology care for
patients needing more urgent specialist services. Improved process and
standardized triage systems are known to minimize wait times of urgent or
semi-urgent care in health care disciplines. In Central Zone (CZ) renal
clinic, mean wait times for urgent (P1) and semi-urgent (P2) referrals were
prolonged before 2014. We also observed prolonged wait times for elective
(P3-P5) categories. Improving wait times was identified as an access to care
quality improvement focus in CZ renal clinic of the Nova Scotia Health
Authority (NSHA). Objectives: To describe our new referral process and new triage system, and to examine
their effect on number of referrals wait-listed and mean wait times. Design: A quasi-experimental design was used. Setting: Halifax, Nova Scotia, Canada. Participants: Patients referred to Central Zone Renal Clinic between 2012 and 2018. Measurements: A time series of referral counts and wait times for each triage category were
measured before our interventions and after implementing our
interventions. Methods: We reviewed our referral processes to identify gaps leading to prolonged wait
times. On January 1, 2014, we implemented new administrative procedures:
pretriage (standardized referral information form and staff training),
triage (standardized clinic intake criteria and new triage guidelines),
posttriage (protecting clinic spots for urgent and semi-urgent referrals,
wait-list maintenance, and increasing new referral clinic capacity). Data
were collected prospectively. Descriptive analysis on mean wait times was
done using run charts. Results: A 33% reduction in total number of referrals wait-listed was observed over
4.5 years after intervention. Descriptive analysis of the urgent and
semi-urgent categories (P1 and P2) revealed a significant shift of mean wait
times on run charts after the interventions. Target wait time was achieved
in 94% of P1 category and 78% of P2 category. Limitations: This type of study design does not exclude confounding variables influencing
results. We did not explore stakeholder satisfaction or whether the new
referral process presented barriers to resending referrals that had
insufficient triage data. The long-term sustainability of adding
demand-responsive surge clinics and opportunity cost were not assessed. Our
referral process and triage system have not been externally validated and
may not be applicable in settings without wait-lists or settings that use
electronic, telephone or telemedicine consults. Conclusion: Our selective intake of referrals with adequate triage information and
referrals needing nephrology consult as defined by our clinic intake
criteria reduced number of referrals wait-listed. We saw improved wait times
for urgent and semi-urgent referrals with these categories now falling
within target wait times for the vast majority of patients. The work of this
improvement initiative continues especially for the lower-risk triage
categories. Trial registration: Not applicable as this was a Quality improvement initiative.
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19
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Lewis AK, Taylor NF, Carney PW, Harding KE. 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 Serv Res 2019; 19:831. [PMID: 31718635 PMCID: PMC6852965 DOI: 10.1186/s12913-019-4660-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 10/21/2019] [Indexed: 11/10/2022] Open
Abstract
Background Managing demand for services is a problem in many areas of healthcare, including specialist medical outpatient clinics. Some of these clinics have long waiting lists with variation in access for referred people. A model of triage and appointment allocation has been developed and tested that has reduced waiting times by about a third in community outpatient services. This study aims to determine whether the model can be applied in the setting of a specialist medical outpatient clinic to reduce wait time from referral to first appointment. Methods A pre-post study will collect data before and after implementing the Specific Timely Appointments for Triage (STAT) model of access and triage. The study will incorporate a pre-implementation period of 12 months, an implementation period of up to 6 months and a post STAT-implementation period of 6 months. The setting will be the epilepsy clinic at a metropolitan health service in Melbourne. Included will be all people referred to the clinic, or currently waiting, during the allocated periods of data collection (total sample estimated n = 975). Data routinely collected by the health service and qualitative data from staff will be analysed to determine the effects of introducing the STAT model. The primary outcome will be wait time, measured by number of patients on the wait list at monthly time points and the mean number of days waited from referral to first appointment. Secondary outcomes will include patient outcomes, such as admission to hospital while waiting, and service outcomes, including rate of discharge. Analysis of the primary outcome will include interrupted time series analysis and simple comparisons of the pre and post-implementation periods. Process evaluation will include investigation of the fidelity of the intervention, adaptations required and qualitative analysis of the experiences of clinic staff. Discussion Prompt access to service and optimum patient flow is important for patients and service providers. Testing the STAT model in a specialist medical outpatient clinic will add to the evidence informing service providers and policy makers about how the active management of supply and demand in health care can influence wait times. The results from this study may be applicable to other specialist medical outpatient clinics, potentially improving access to care for many people.
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Affiliation(s)
- Annie K Lewis
- Allied Health Clinical Research Office and Department of Neurosciences, Eastern Health, 5 Arnold St, Box Hill, Victoria, 3128, Australia. .,School of Allied Health, Health Services and Sport, La Trobe University, Kingsbury Drive, Bundoora, Victoria, 3086, Australia.
| | - Nicholas F Taylor
- Allied Health Clinical Research Office and Department of Neurosciences, Eastern Health, 5 Arnold St, Box Hill, Victoria, 3128, Australia.,School of Allied Health, Health Services and Sport, La Trobe University, Kingsbury Drive, Bundoora, Victoria, 3086, Australia
| | - Patrick W Carney
- Allied Health Clinical Research Office and Department of Neurosciences, Eastern Health, 5 Arnold St, Box Hill, Victoria, 3128, Australia.,Neurosciences, Monash University, 21 Chancellors Walk, Clayton, Victoria, 3800, Australia.,The Florey Institute for Neuroscience and Mental Health, Melbourne Brain Centre, Burgundy Street, 3084, Heidelberg, Australia
| | - Katherine E Harding
- Allied Health Clinical Research Office and Department of Neurosciences, Eastern Health, 5 Arnold St, Box Hill, Victoria, 3128, Australia.,School of Allied Health, Health Services and Sport, La Trobe University, Kingsbury Drive, Bundoora, Victoria, 3086, Australia
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Harding KE, Robertson N, Snowdon DA, Watts JJ, Karimi L, O'Reilly M, Kotis M, Taylor NF. Are wait lists inevitable in subacute ambulatory and community health services? A qualitative analysis. AUST HEALTH REV 2019; 42:93-99. [PMID: 28131111 DOI: 10.1071/ah16145] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2016] [Accepted: 12/09/2016] [Indexed: 11/23/2022]
Abstract
Objectives Wait lists are common in ambulatory and community-based services. The aim of the present study was to explore managers' perceptions of factors that contribute to wait times. Methods A qualitative study was conducted using semi-structured interviews with managers and team leaders of ambulatory and community health services within a large health network. Interviews were transcribed and coded, and the codes were then grouped into themes and subthemes. Results Representatives from 26 services participated in the project. Four major themes were identified. Three themes related to reasons and factors contributing to increased wait time for services (inefficient intake and scheduling processes; service disruptions due to human resource issues; and high service demand). A fourth theme related to staff attitudes towards wait times and acceptance and acknowledgement of wait lists. Conclusions Service providers perceive high demand to be a key driver of wait times, but a range of other factors also contributes and may represent opportunities for improving access to care. These other factors include improving process efficiencies, greater consistency of service delivery through more efficient management of human resources and shifting to more consumer-centred approaches in measuring wait times in order to drive improvements in patient flow. What is known about the topic? Wait times are common in out-patient and ambulatory services. These services experience high demand, which is likely to continue to grow as health service delivery shifts from hospital to community settings. What does this paper add? Although demand is an important driver of wait times, there are other modifiable factors that also contribute, including process inefficiencies and service disruption related to human resource issues. An underlying staff attitude of acceptance of wait times appears to be an additional barrier to improving access. What are the implications for practitioners? The findings of the present study suggest that there are opportunities for improving access to ambulatory and community health services through more efficient use of existing resources. However, a more consumer-focused approach regarding acceptability of wait times is needed to help drive change.
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Affiliation(s)
| | - Nicole Robertson
- Eastern Health, 5 Arnold Street, Box Hill, Vic. 3128, Australia.
| | - David A Snowdon
- Eastern Health, 5 Arnold Street, Box Hill, Vic. 3128, Australia.
| | - Jennifer J Watts
- Centre for Population Health Research, Deakin University, 221 Burwood Highway, Burwood, Vic. 3125, Australia. Email
| | - Leila Karimi
- La Trobe University, Kingsbury Drive, Bundoora, Vic. 3086, Australia.
| | - Mary O'Reilly
- Eastern Health, 5 Arnold Street, Box Hill, Vic. 3128, Australia.
| | - Michelle Kotis
- Victorian Department of Health and Human Services, 50 Lonsdale Street, Melbourne, Vic. 3000, Australia. Email
| | - Nicholas F Taylor
- La Trobe University, Kingsbury Drive, Bundoora, Vic. 3086, Australia.
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Harding KE, Snowdon DA, Lewis AK, Leggat SG, Kent B, Watts JJ, Taylor NF. Staff perspectives of a model of access and triage for reducing waiting time in ambulatory services: a qualitative study. BMC Health Serv Res 2019; 19:283. [PMID: 31053118 PMCID: PMC6500050 DOI: 10.1186/s12913-019-4123-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 04/24/2019] [Indexed: 11/29/2022] Open
Abstract
Background Specific Timely Appointments for Triage (STAT) is an intervention designed to reduce waiting time in community outpatient health services, shown to be effective in a large stepped wedge cluster randomised controlled trial. STAT combines initial strategies to reduce existing wait lists with creation of a specific number of protected appointments for new patients based on demand. It offers an alternative to the more traditional methods of demand management for these services using waiting lists with triage systems. This study aimed to explore perceptions of clinicians and administrative staff involved in implementing the model. Method Semi-structured interviews with 20 staff members who experienced the change to STAT were conducted by an independent interviewer. All eight sites involved in the original trial and all professional disciplines were represented in the sample. Data were coded and analysed thematically. Results Participants agreed that shorter waiting time for patients was the main advantage of the STAT model, and that ongoing management of caseloads was challenging. However, there was variation in the overall weight placed on these factors, and therefore the participants’ preference for the new or previous model of care. Perceptions of whether the advantages outweighed the disadvantages were influenced by five sub-themes: staff perception of how much waiting matters to the patient, prior exposure to the management of waiting list, caseload complexity, approach and attitude to the implementation of STAT and organisational factors. Conclusions The STAT model has clear benefits but also presents challenges for staff members. The findings of this study suggest that careful preparation and management of change and active planning for known fluctuations in supply and demand are likely to help to mitigate sources of stress and improve the likelihood of successful implementation of the STAT model for improving waiting times for patients referred to community outpatient services.
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Affiliation(s)
- Katherine E Harding
- Allied Health Clinical Research Office, Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia. .,La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia.
| | - David A Snowdon
- Allied Health Clinical Research Office, Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia.,La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Annie K Lewis
- Allied Health Clinical Research Office, Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia.,La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Sandra G Leggat
- La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Bridie Kent
- Plymouth University, Drake Circus, Plymouth, Devon, PL4 8AA, UK
| | - Jennifer J Watts
- Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia
| | - Nicholas F Taylor
- Allied Health Clinical Research Office, Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia.,La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
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Harding KE, Leggat SG, Watts JJ, Kent B, Prendergast L, Kotis M, O'Reilly M, Karimi L, Lewis AK, Snowdon DA, Taylor NF. A model of access combining triage with initial management reduced waiting time for community outpatient services: a stepped wedge cluster randomised controlled trial. BMC Med 2018; 16:182. [PMID: 30336784 PMCID: PMC6194740 DOI: 10.1186/s12916-018-1170-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 09/10/2018] [Indexed: 11/10/2022] Open
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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Affiliation(s)
- Katherine E Harding
- Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia. .,La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia.
| | - Sandra G Leggat
- La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Jennifer J Watts
- Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia
| | - Bridie Kent
- University of Plymouth, Drake Circus, Plymouth, Devon, PL4 8AA, UK
| | - Luke Prendergast
- La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Michelle Kotis
- Victorian Department of Health and Human Services, 50 Lonsdale Street, Melbourne, VIC, 3000, Australia
| | - Mary O'Reilly
- Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia
| | - Leila Karimi
- La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Annie K Lewis
- Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia.,La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - David A Snowdon
- Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia.,La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Nicholas F Taylor
- Eastern Health, Level 2/5 Arnold Street, Box Hill, VIC, 3128, Australia.,La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
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Harding KE, Watts JJ, Karimi L, O'Reilly M, Kent B, Kotis M, Leggat SG, Kearney J, Taylor NF. Improving access for community health and sub-acute outpatient services: protocol for a stepped wedge cluster randomised controlled trial. BMC Health Serv Res 2016; 16:364. [PMID: 27506923 PMCID: PMC4977711 DOI: 10.1186/s12913-016-1611-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2016] [Accepted: 07/30/2016] [Indexed: 12/02/2022] Open
Abstract
Background Waiting lists for treatment are common in outpatient and community services, Existing methods for managing access and triage to these services can lead to inequities in service delivery, inefficiencies and divert resources from frontline care. Evidence from two controlled studies indicates that an alternative to the traditional “waitlist and triage” model known as STAT (Specific Timely Appointments for Triage) may be successful in reducing waiting times without adversely affecting other aspects of patient care. This trial aims to test whether the model is cost effective in reducing waiting time across multiple services, and to measure the impact on service provision, health-related quality of life and patient satisfaction. Methods/design A stepped wedge cluster randomised controlled trial has been designed to evaluate the impact of the STAT model in 8 community health and outpatient services. The primary outcome will be waiting time from referral to first appointment. Secondary outcomes will be nature and quantity of service received (collected from all patients attending the service during the study period and health-related quality of life (AQOL-8D), patient satisfaction, health care utilisation and cost data (collected from a subgroup of patients at initial assessment and after 12 weeks). Data will be analysed with a multiple multi-level random-effects regression model that allows for cluster effects. An economic evaluation will be undertaken alongside the clinical trial. Discussion This paper outlines the study protocol for a fully powered prospective stepped wedge cluster randomised controlled trial (SWCRCT) to establish whether the STAT model of access and triage can reduce waiting times applied across multiple settings, without increasing health service costs or adversely impacting on other aspects of patient care. If successful, it will provide evidence for the effectiveness of a practical model of access that can substantially reduce waiting time for outpatient and community services with subsequent benefits for both efficiency of health systems and patient care. Trial registration Australian and New Zealand Clinical Trials Registry ACTRN12615001016527. Approved 15/9/2015.
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Affiliation(s)
- Katherine E Harding
- La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia. .,Eastern Health, 5 Arnold Street, Box Hill, VIC, 3128, Australia.
| | - Jennifer J Watts
- Deakin University, 221 Burwood Highway, Burwood, VIC, 3125, Australia
| | - Leila Karimi
- La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Mary O'Reilly
- Eastern Health, 5 Arnold Street, Box Hill, VIC, 3128, Australia
| | - Bridie Kent
- Plymouth University, Drake Circus, Plymouth, Devon, PL4 8AA, UK
| | - Michelle Kotis
- Victorian Department of Health and Community Services, 50 Lonsdale Street, Melbourne, VIC, 3000, Australia
| | - Sandra G Leggat
- La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia
| | - Jackie Kearney
- Victorian Department of Health and Community Services, 50 Lonsdale Street, Melbourne, VIC, 3000, Australia
| | - Nicholas F Taylor
- La Trobe University, Kingsbury Drive, Bundoora, VIC, 3086, Australia.,Eastern Health, 5 Arnold Street, Box Hill, VIC, 3128, Australia
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