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Australian Health Review Australian Health Review Society
Journal of the Australian Healthcare & Hospitals Association
RESEARCH ARTICLE (Open Access)

Time to wait: a systematic review of strategies that affect out-patient waiting times

Ugenthiri Naiker A E , Gerry FitzGerald A , Joel M. Dulhunty A B C and Michael Rosemann D
+ Author Affiliations
- Author Affiliations

A School of Public Health, Queensland University of Technology, Victoria Park Road, Kelvin Grove, Qld 4059, Australia. Email: gj.fitzgerald@qut.edu.au

B Medical Administration, Redcliffe Hospital, Anzac Avenue, Redcliffe, Qld 4020, Australia. Email: Joel.Dulhunty@health.qld.gov.au

C Faculty of Medicine, The University of Queensland, St Lucia, Brisbane, Qld 4072, Australia.

D School of Information Systems, Science and Engineering Faculty, Queensland University of Technology, 2 George Street, Brisbane, Qld, 4000. Email: m.rosemann@qut.edu.au

E Corresponding author. Email: Ugenthiri.naiker@student.qut.edu.au

Australian Health Review 42(3) 286-293 https://doi.org/10.1071/AH16275
Submitted: 3 March 2016  Accepted: 1 February 2017   Published: 30 March 2017

Journal compilation © AHHA 2018 Open Access CC BY-NC-ND

Abstract

Objective Out-patient waiting times pose a significant challenge for public patients in need of specialist evaluation and intervention. The aim of the present study was to identify and categorise effective strategies to reduce waiting times for specialist out-patient services with a focus on the Australian healthcare system.

Methods A systematic review of major health databases was conducted using the key terms ‘outpatient*’ AND ‘waiting time’, ‘process*’ AND ‘improvement in outpatient clinics’. Identified articles were assessed for their relevance by sequential review of the title, abstract and full text. References of the selected manuscripts were scanned for additional relevant articles. Selected articles were evaluated for consistent and emerging themes.

Results In all, 152 articles were screened, of which 38 were included in the present review. Numerous strategies identified in the articles were consolidated into 26 consistent approaches. Three overarching themes were identified as significantly affecting waiting times: resource realignment, operational efficiency and process improvement.

Conclusions Strategies to align resources, increase operational efficiency and improve processes provide a comprehensive approach that may reduce out-patient waiting times.

What is known about the topic? Out-patient waiting times are a challenge in most countries that seek to provide universal access to health care for all citizens. Although there has been extensive research in this area, many patients still experience extensive delays accessing specialist care, particularly in the public health sector. The multiple factors that contribute to bottlenecks and inefficiencies in the referral process and affect patient waiting times are often poorly understood.

What does this paper add? This paper reviews the published healthcare literature to identify strategies that affect specialist out-patient waiting times for patients. The findings suggest that there are numerous operational strategies that affect waiting times. These strategies may be categorised into three overarching themes (resource alignment, operational efficiencies and out-patient processes) that, when actioned in a coordinated approach, have the potential to significantly reduce out-patient waiting times.

What are the implications for practitioners? This paper identifies evidence-based strategies for aligning resources, improving operational efficiency and streamlining processes, which may provide improvements to specialist out-patient waiting times for patients. Addressing the identified organisational, person-related, cultural and attitudinal factors will assist health system managers and health practitioners target the most appropriate improvement activities to reduce waiting times.

Introduction

Out-patient waiting times are a challenge in most countries that seek to provide universal access to health care for all citizens. Although there has been considerable research in this area, many patients still experience extensive delays accessing specialist care, particularly in the public health sector. There are multiple factors that affect patient waiting times and contribute to bottlenecks and inefficiencies in the referral process.

In the presence of constraints on the capacity of public health systems, demand for treatment is likely to exceed supply, so that not all patients can be treated immediately. Therefore, patients are added to a wait list for public treatment unless they are willing and able to pay for private care.1 Long waiting times for non-emergency services are a feature of several publicly funded health systems. A key policy concern is that long waiting times may worsen health outcomes or reduce expected health gains compared with timely treatment.2

In Australia, patients are not permitted direct access to specialist care, apart from access via the emergency department for acute care needs. The role of out-patient clinics is to provide access to public specialist care for diagnosis and treatment, and for review following in-patient care. In addition, in the public sector in Australia, private bulk-billing clinics are provided in some public hospitals. This increases the ability for these hospitals to earn additional revenue from the national healthcare provider, Medicare.

Out-patient services in the public sector are provided by staff specialists and visiting medical officers. In addition, the out-patient clinic is a valuable teaching and training environment in which medical students and junior medical staff contribute to services while receiving supervision and instruction by specialists.

To access out-patient specialist clinics, patients must obtain a referral from a general practitioner (GP), which is sent to the hospital, where the referral is triaged before arranging an appointment. Triage categories based on the severity of illness and other factors determine the priority of access to specialist care and therefore the length of wait time for the patient. In Queensland, patients are assigned to one of three triage categories (1, urgent; 2, non-urgent; and 3, routine) with system performance expectations assigned to these categories (Category 1 = 30 days; Category 2 = 90 days; and Category 3 = 365 days). However, these recommended waiting times are not based on sound evidence related to deteriorating health outcomes or increased clinical risk. They are also not consistent across Australia.3

The rise in health care funding and the increase in provision of health care services may not be sufficient to accommodate the growing population and an increase in life expectancy and chronic disease.4,5 Although the evidence that waiting times directly affect patient long-term outcomes is mixed,2,68 there is acceptance that waiting times affect physical and emotional well-being.6,7 Therefore, it is prudent that efficiencies are found within the current structure of the publicly funded healthcare system in order to improve access for patients. The objective of the present system review was to identify and categorise strategies associated with performance improvement from published literature.


Methods

Literature search protocol

The aim of the literature search was to identify the key strategies that affect out-patient waiting times. The databases searched were PubMed, Scopus, Embase, Web of Science, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Medline via EBSCO host, Cochrane and Google Scholar alerts. Searches were conducted with search terms in the title, abstract and keywords. No date limitations were imposed. Searches of the title, abstract and keywords were conducted with the search terms ‘outpatient*’ AND ‘waiting time’, ‘process*’ AND ‘improvement in outpatient clinics’. These searches were initially conducted in 2013 and updated continuously with the final search conducted in February 2015. Because the present review focused on improvements in the out-patient setting, all publications included in the study were limited to primary research (interventional and observational studies) on waiting times in the out-patient setting.

The key search terms outlined in Table 1 were used as a basis for determining the relevance of identified papers to the research question. After review of the title, abstracts and keywords, the full texts of articles relevant to the scope of the present study were retrieved. Articles were assessed by the principal investigator (UN) on the basis of the significant effect on out-patient waiting times. In this context, statistically significant effect was determined by a demonstrated reduction in waiting time measures (quantitative studies) and/or researchers’ observations of a significant reduction in these areas (qualitative studies). Scanning the reference lists of key studies identified additional articles of relevance. The articles that were selected were confined to the English language. Only studies in peer-reviewed journals were sourced to ensure a high level of quality and support for the validity of the findings and conclusions.9 Publications that were not available in full text were excluded from the review. Reporting guidelines for systematic reviews were followed.10 The hierarchy of evidence was assessed using the Centre for Reviews and Dissemination guidelines on assessment of study design.11


Table 1.  Summary of search results by database before scanning for relevance
CINAHL, Cumulative Index to Nursing and Allied Health Literature
T1

Analysis protocol

Qualitative methods were used for analysing the results obtained from the publications. The qualitative analysis began with the exploration of the publications and collection of a list of descriptive codes from the aims and objectives, which were related to the outcomes of the review. Coding was conducted by a process of grouping evidence and labelling ideas in order to reflect increasingly broader perspectives. Codes were grouped into broader themes that provided answers to the research question.12,13


Results

The results of the search protocol are summarised in Table 1. In all, 151 manuscripts were identified for review, with 12 additional articles sourced following reference checks and 10 articles from Google scholar alerts; 21 duplicate articles were removed (Fig. 1). Following an abstract review of the remaining 152 papers, 95 studies were excluded because these were related to other forms of waiting time experienced by patients. Fifty-seven articles were assessed for eligibility, of which 14 were excluded: 11 explored the association with in-patient stay and three focused on patient experience alone. The remaining 43 publications were further assessed to identify primary research studies; five articles that synthesised work in the form of reviews or editorials were excluded. This resulted in 38 studies that were included in the qualitative analysis. More than 60% of the studies conducted were from the US (n = 12)14,15,24,25,29,32,33,36,38,45,47,48 and the UK (n = 11).18,19,23,2628,30,31,43,49,51 There were four studies from Australia,16,17,21,50 five from various countries in Europe,20,39,41,42,44 one from Canada37 and five from other countries.22,34,35,40,46


Fig. 1.  Flow diagram of studies identified, screened and included in the present systematic review.
F1

The final articles included in the review and their recommendations are detailed in Table 2. The publications identified comprised two randomised trials, two case control studies, six case reports, 17 case studies, six cohort studies, four action research studies and one case series. From the assessment of the study designs used in these publications as per Centre for Reviews and Dissemination guidelines, 71% of publications were graded at Level 4, 21% were at Level 3 and 8% were at Level 1 on the hierarchy of evidence, where 1 is the highest level of evidence. Although the quality of the evidence is important, for the purposes of the present qualitative study all articles were included and relative weight was given to them on the basis of the quality of the evidence. For example, randomised controlled experiments (Level 1) will be more informative than case studies (Level 3).


Table 2.  Summary of recommendations to improve out-patient waiting times by theme
GP, general practitioner; HCP, health care professional; RCT, randomised control trial
Click to zoom

The strategies identified in the final articles were compiled into consistent approaches. In all, 26 separate approaches were identified from analysis of the content of the 38 articles. These 26 approaches were grouped into three consistent themes: resource realignment, operational efficiencies and process improvement (Table 2).

Most of the publications included in the present review included two or more of the themes mentioned and were coded as such. Twenty-one per cent of the publications were primarily concerned with resource alignment,1421 18% were concerned with operational efficiency2228 and 61% were concerned with process improvement.2951

Resource alignment

The major strategies involving resource alignment included: (1) limiting the number of referrals to specialists either absolutely or through the use of incentives to limit referrals; (2) wait list audits; (3) discharging patients into GP care; and (4) triaging patients by another health care professional rather than simply administrative processing. Managing demand through limiting the number of referrals, incentives and triaging patients by other health care professionals may benefit patients indirectly by ensuring that only the most appropriate patients are referred, which, in turn, should result in a shorter wait time for these patients and better patient outcomes.

Operational efficiency

Operational efficiency with time management strategies maximises capacity within the clinics and may have a significant effect on the overall waiting times for patients. The strategies highlighted within operational efficiency included: (1) clinics starting promptly; (2) improved allocation of appointment slots; (3) avoiding large blocks of patients (congestion); (4) advanced access (offering patients same-day appointments); (5) advanced access at provider, clinic and network levels; (6) a single queue for all patients and a one-stop diagnostic clinic; (7) appropriate time allocation for new and follow-up patients; and (8) strategies aligning supply with demand for services.

Process improvement

At a tactical and strategic level, process improvement strategies included: (1) aligning processes with organisational priorities, assessment and benchmarking; (2) capacity planning, new resources and efficient use of existing resources; (3) control and reduction of variation in demand and capacity; (4) no-show modelling; (5) computer simulations (to predict doctor idle time, day-dependent no-show predictions, patient arrival time to match demand and capacity); (6) appointment scheduling of patients (to predict routine vs urgent patients; scheduled and unscheduled patients); (7) clinical staff improving processes, decreased production variation and patient care optimisation by GP guidelines; (8) elimination of waste related to delays, repeated encounters and errors; (9) preparation times and referral management; (10) booking procedures, consumer engagement, overbooking and flexible capacity; (11) automation of scheduling times; (12) eReferrals; (13) telemedicine; and (14) patient text messaging.


Discussion

A significant number of strategies to improve the management of out-patient waiting times was identified in the present review. When categorised according to operational areas of focus, this paper identified 26 consistent approaches grouped into three themes. These themes included resource realignment, operational efficiencies and process improvement. However, the research found that the area of most interest with positive results was process improvement, with more than 50% of the studies conducted in this area. The value of this finding for system improvement, and therefore reduction of waiting time, lies in a comprehensive approach incorporating a range of strategies.

Resource alignment

Resource alignment focuses on the internal alignment of resources to better manage out-patient waiting times. The strategies that had the most effect on waiting times were rationalising referrals, triaging of patients and wait list audits. One of the key areas of concern is the capacity of the primary care sector to manage patients in the community. There needs to be a concerted effort by both primary and secondary care stakeholders to manage care for patients by integrated care pathways, better communication between care providers and encouraging patient participation in the management of their health.14,15

In order to facilitate a better transition from the out-patient clinic to primary care, discharge consultations in the out-patient clinic should be a high priority and allocated sufficient time. Patients should be prepared for discharge one visit in advance, and reasons for discharge should be made clear. Structured discharge criteria for the out-patient clinic may help improve discharge consultations. The transition to community care can be facilitated by a management plan for the GP, including arrangements for gaining further access to specialist care in the future and empowering patients to take responsibility for their care by sharing information.14,15

At an operational level, wait list audits provide important information on patients’ ongoing needs and the accuracy of waiting times and demand for services. This may provide the most benefit for hospitals that are currently managing long wait lists and wait times for patients. Waiting time prioritisation policies are intended to improve the management of patients on the waiting list. They do not directly affect demand for or supply of services, just the timeliness of those services.52

Triaging of out-patient referrals is intended to prioritise urgent patients. However, this has the unintended effect of placing most patients at a disadvantage, because they are not deemed urgent. Team-based approaches to care in the out-patient setting have significantly improved waiting times.1921,53 Extending the scope of practice of non-medical health professionals with the proper training has contributed to patient satisfaction and the efficient use of resources without any notable adverse effect on patient outcomes. This offers an alternative for the management of out-patients. This needs to be managed in consultation and collaboration with clinicians and patients to ensure that quality of clinical care for patients is maintained.

The expectations of patients also need to be managed to ensure that there is no perception of compromise to quality of care delivered. Given the resources required for triaging patients, the results from a study by Harding et al.54 question the value of the triage system in the out-patient setting.4 An alternative to triaging may be a single queue with advanced access provided to patients as outlined below under operational efficiency.

Operational efficiency

This area is focused predominantly on improving productivity and internal efficiency at an operational level. The recommendations that had the most effect were scheduling initiatives, advanced access and aligning supply to demand. Appropriate scheduling initiatives (clinics starting promptly, allocation of appointments and time management) have a demonstrated effect on decreasing waiting times for patients. This has the further benefit of improving internal capacity, balancing supply and demand and seeing more patients to further affect the overall decline in waiting times. This enhanced access provides a same-day appointment for patients requesting access to services.

In order to have a significant effect on waiting time and balancing demand and supply, where demand outstrips supply, advanced access needs to be operationalised at the provider, clinic and network levels.25 By providing appropriate time for an appointment, operational efficiency can be maintained and waiting times continuously improved. Scheduling initiatives, as recommended by Stainkey et al.,16 need to be conducted continuously in order to be efficient and effective. Performance measures to encourage operational improvements have proved to be mostly successful.55,56

However, there are challenges faced by implementing performance measures in healthcare, which include conflicting stakeholder priorities in relation to the use of capacity. Further, out-patient initiatives may have the unintended effect of increasing pressure on elective surgery waiting times.17

Process improvements

This theme is focused on tactical and strategic improvement in processes to gain efficiency and effectiveness in the out-patient referral process. The recommendations that had the most effect on waiting times were automation of processes like scheduling with eReferrals, telemedicine and patient text messaging. Simulations in healthcare have been explored and some implemented with varying levels of success.3338,57 These simulations provide health service managers with insight into capacity planning, aligning demand and supply and control of variation, which, in turn, may lead to inefficiency. However, computer-simulated recommendations may prove to be a challenge to implement operationally and sustain. Change management is key in the implementation of modelling approaches. Changes must be practical and implementable within the human activity system. Conflicting objectives of the various stakeholders need to be considered when recommending changes.58 There also needs to be significant investment in building the capability of stakeholders for these changes to be successfully implemented and maintained long term.

Significant improvements in process performance may be achieved by systematically identifying the sources of variability at different stages in the process and taking steps that mitigate the undesirable effect of variability.59 Waste is related to delays, preparation times and referral management and booking procedures. These can be waiting time delays, lead times, times for booking and referral management. By setting targets to these measures, process control and policy deployment can be implemented.44 There needs to be continuous governance and management of these processes to ensure that they are implemented to minimise variation and maximise efficiency and effective performance.

Research in this area continues to be challenging because there are numerous factors that affect waiting times. Previous studies have focused on resource, operational and process areas. Implementing the changes recommended by computer simulation studies3338,57 and the challenges associated with ensuring the sustainability of these changes continue to evolve.

These strategies serve as a starting point for health service managers tasked with improving out-patient waiting times for their organisations. Qualitative strategies that address organisational culture and people-related factors such as capability, performance and attitudes remain areas for further exploration.

It is recommended that further research into organisational culture and person-centred and attitudinal factors affecting waiting times is conducted. Building the capability of caregivers and health service providers is essential to ensuring sustainable change. Further, the cultural change with implementing these strategies needs to be recognised and addressing concerns of different structural interest groups is imperative for these strategies to be successful. There needs to be comprehensive and coordinated collaboration by all stakeholders in order for implemented improvements to significantly affect waiting times for patients. The evidence generated through such research will be vital for improving patient access to care and achieving better health outcomes.


Limitations

The present systematic review has several limitations. A key limitation is that none of the studies reviewed demonstrated causation of waiting times and, at best, allude to associations between strategies and out-patient waiting times. The outcome measures in each study differed and it was therefore difficult to make direct comparisons on outcome efficacy. The assessment of the study design demonstrated that more than 80% of the publications included in this review were hierarchy Levels 3 and 4. This may be due to a combination of factors, including publication bias. Assessment of risk in individual studies was not conducted because the present review did not synthesise quantitative data at the study or outcome level. Strategies that had minimal or a negative effect on waiting times were not reported on and therefore there was no comment made on whether the positive strategies identified may be context specific. The process applied to developing these themes may contain the risk of bias across studies at the outcome level. The search was limited to English peer-reviewed publications. Therefore, the findings may not be comprehensive of all interventions that have been demonstrated to be effective. The time lag from when this research was conducted to when it is published may mean that newly reported interventions are not included, although no new evidence related to this review was available at the time of submission of the article. Although significant efforts have been made to identify all relevant literature on the presented topics, it is possible that some material may have been overlooked or remain undiscovered.

No analysis has been made of the downstream effect of interventions aimed at reducing out-patient waiting times (e.g. elective surgery waiting times), which may be of relevance to clinicians, managers and patients.


Conclusions

Healthcare systems are complex structures and attempts to reform them pose significant challenges. In this context, the variations in referral pathways and the effects of external factors, including perverse financial incentives, may create variability that is difficult to change. However, research can help inform strategies that may address some of the issues. A comprehensive strategic approach involving resource realignment, operational efficiency and process improvement holds most promise for improving the efficiency and effectiveness of out-patient services and, in doing so, reducing waiting time and thus improving health outcomes. These three broad areas identified are complementary and provide a comprehensive approach to policy improvement in these domains. By identifying the evidence-based strategies that have had the most beneficial effect on waiting times, the present review provides an informed starting point for clinicians, policy makers and health services managers seeking to improve patient access to specialist out-patients in their organisations.


Competing interests

None declared.



Acknowledgements

The authors acknowledge the support of Queensland University of Technology and the constructive advice of colleagues.


References

[1]  Gutacker N, Siciliani L, Cookson R. Waiting time priorisation: evidence from England. Soc Sci Med 2016; 159 140–51.
Waiting time priorisation: evidence from England.Crossref | GoogleScholarGoogle Scholar |

[2]  Moscelli G, Siciliani L, Tonei V. Do waiting times affect health outcomes? Evidence from coronary bypass. Soc Sci Med 2016; 161 151–9.
Do waiting times affect health outcomes? Evidence from coronary bypass.Crossref | GoogleScholarGoogle Scholar |

[3]  Queensland Health. Specialist outpatient services standard. Brisbane: Queensland Government; 2016.

[4]  Australian Bureau of Statistics (ABS). Australian demographic statistics. Catalogue No. 3101.0. Canberra: ABS; 2012.

[5]  Australian Institute of Health and Welfare (AIHW). Australia’s health 2014. Catalogue no. AUS 178. Canberra: AIHW; 2014.

[6]  Dunnill M, Pounder R. Medical outpatients: changes that can benefit patients. Clin Med (Northfield Ill) 2004; 4 45–9.
Medical outpatients: changes that can benefit patients.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD2c7gsl2gtA%3D%3D&md5=71390e9ef91e71ca28963e8105536ca0CAS |

[7]  Henderson A, Caplan G, Daniel A. Patient satisfaction: the Australian patient perspective. Aust Health Rev 2004; 27 73–83.
Patient satisfaction: the Australian patient perspective.Crossref | GoogleScholarGoogle Scholar |

[8]  Hoogeboom T, Van den Endey C, Van der Sluisz G, Elingsx J, Dronkersk J, Aiken A, et al The impact of waiting for total joint replacement on pain and functional status: a systematic review. Osteoarthr Cartil 2009; 17 1420–7.
The impact of waiting for total joint replacement on pain and functional status: a systematic review.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD1Mnps1aktg%3D%3D&md5=90eaa0abba3d93282c8d7fd2e234e5f9CAS |

[9]  Hayes L, O’Brien-Pallas L, Duffield C, Shamian J, Buchan J, Hughes F, et al Nurse turnover: a literature review. Int J Nurs Stud 2006; 43 237–63.
Nurse turnover: a literature review.Crossref | GoogleScholarGoogle Scholar |

[10]  Liberati A, Altman D, Tetzlaff J. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 2009; 339 b2700
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.Crossref | GoogleScholarGoogle Scholar |

[11]  Centre for Reviews and Dissemination (CRD). Systematic reviews: CRD’s guidance for undertaking reviews in health care. York: CRD, University of York; 2008.

[12]  Saldana J. The coding manual for qualitative researchers. Thousand Oaks, CA: Sage; 2009.

[13]  Creswell J, Plano Clark V. Designing and conducting mixed methods research. London: SAGE Publications; 2007.

[14]  Baker N, Whittington J, Resar R, Griffin F, Nolan K. Reducing costs through the appropriate use of specialty services. Cambridge, MA: Institute for Healthcare Improvement; 2010.

[15]  Schillinger D, Bibbins-Domingo K, Vranizan K, Bacchetti P, Luce J, Bindman A. Effects of primary care coordination on public hospital patients. J Gen Intern Med 2000; 15 329–36.
Effects of primary care coordination on public hospital patients.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BD3czgtFWqsw%3D%3D&md5=82bd4355152a0a92b658379758404e29CAS |

[16]  Stainkey L, Seidl I, Johnson A, Tulloch G, Pain T. The challenge of long waiting lists: how we implemented a GP referral system for non-urgent specialist appointments at an Australian public hospital. BMC Health Serv Res 2010; 10 303
The challenge of long waiting lists: how we implemented a GP referral system for non-urgent specialist appointments at an Australian public hospital.Crossref | GoogleScholarGoogle Scholar |

[17]  Schoch A, Adair L. Successfully reforming orthopaedic outpatients. Aust Health Rev 2012; 36 233–7.
Successfully reforming orthopaedic outpatients.Crossref | GoogleScholarGoogle Scholar |

[18]  Burkey Y, Black M, Reeve H, Roland M. Long-term follow-up in outpatient clinics. 2: The view from the specialist clinic. Fam Pract 1997; 14 29–33.
Long-term follow-up in outpatient clinics. 2: The view from the specialist clinic.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK2s3hsV2ktA%3D%3D&md5=704f2413fb4c2f2d5bc7a6c0a35896ffCAS |

[19]  Georgiou E, Domoney C, Marsh S, Stafford M. Streamlining outpatient urogynaecology: a novel approach. J Obstet Gynaecol 2011; 31 156–63.
Streamlining outpatient urogynaecology: a novel approach.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DC%2BC3M7lslCjug%3D%3D&md5=b5a089696fd8b877aa44c31bec7cb893CAS |

[20]  Mariotti G, Siciliani L, Rebba V, Fellini R, Gentilini M, Benea G, et al Waiting time prioritisation for specialist services in Italy: the homogeneous waiting time groups approach. Health Policy 2014; 117 54–63.
Waiting time prioritisation for specialist services in Italy: the homogeneous waiting time groups approach.Crossref | GoogleScholarGoogle Scholar |

[21]  Walsh T, Pilkington D, Wong E, Brown C, Mercer G. Orthopaedic triaging by podiatrists: a prospective study of patient satisfaction and service delivery. Aust Health Rev 2014; 38 406–11.
Orthopaedic triaging by podiatrists: a prospective study of patient satisfaction and service delivery.Crossref | GoogleScholarGoogle Scholar |

[22]  Zhu Z, Heng B, Teow K. Analysis of factors causing long patient waiting time and clinic overtime in outpatient clinics. J Med Syst 2012; 36 707–13.
Analysis of factors causing long patient waiting time and clinic overtime in outpatient clinics.Crossref | GoogleScholarGoogle Scholar |

[23]  Harper P, Gamlin H. Reduced outpatient waiting times with improved appointment scheduling: a simulation modelling approach. OR Spectr 2003; 25 207–22.
Reduced outpatient waiting times with improved appointment scheduling: a simulation modelling approach.Crossref | GoogleScholarGoogle Scholar |

[24]  Murray M, Berwick D. Advanced access: reducing waiting and delays in primary care. JAMA 2003; 289 1035–40.
Advanced access: reducing waiting and delays in primary care.Crossref | GoogleScholarGoogle Scholar |

[25]  Gupta D, Potthoff S, Blowers D, Corlett J, Terry S. Performance metrics for advanced access. J Healthc Manag 2006; 51 246–59.

[26]  Willis S, Pardos-Martinez M, Coker B, Thomas K, Anderson P, Rottenber G, et al The successful, sustainable elimination of a waiting list for urology outpatients. Br J Urol 2011; 107 526–30.
The successful, sustainable elimination of a waiting list for urology outpatients.Crossref | GoogleScholarGoogle Scholar |

[27]  Laing A, Shiroyama C. Managing capacity and demand in a resource constrained environment: lessons for the NHS? J Manag Med 1995; 9 51–67.
Managing capacity and demand in a resource constrained environment: lessons for the NHS?Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaK28%2FpslKlsQ%3D%3D&md5=0c4a996beb1947a83401c28bc5328b2bCAS |

[28]  Barrass B, Wood S. The new standard of care in urology outpatients? A one-stop clinic improves efficiency and quality. J Clin Urol 2013; 6 408–13.
The new standard of care in urology outpatients? A one-stop clinic improves efficiency and quality.Crossref | GoogleScholarGoogle Scholar |

[29]  Chyna J. Wait reduction: improving operational and financial performance in outpatient services. Healthc Exec 2002; 17 14–9.

[30]  Bowers J. Simulating waiting list management. Health Care Manage Sci 2011; 14 292–8.
Simulating waiting list management.Crossref | GoogleScholarGoogle Scholar |

[31]  Silvester K, Lendon R, Bevan H, Steyn R, Walley P. Reducing waiting times in the NHS: is lack of capacity the problem? Clin Manage 2004; 12 105–11.

[32]  Daggy J, Lawley M, Willis D, Thayer D, Suelzer C, DeLaurentis P, et al Using no-show modeling to improve clinic performance. Health Informatics J 2010; 16 246–59.
Using no-show modeling to improve clinic performance.Crossref | GoogleScholarGoogle Scholar |

[33]  Huang Y, Hancock W, Herrin G. An alternative outpatient scheduling system: improving the outpatient experience. IIE Trans Healthc Syst Eng 2012; 2 97–111.
An alternative outpatient scheduling system: improving the outpatient experience.Crossref | GoogleScholarGoogle Scholar |

[34]  Shakoor M. Using discrete event simulation approach to reduce waiting times in computed tomography radiology department. Int Scholarly Sci Res Innovat 2015; 9 177–81.

[35]  Aeenparast A, Tabibi S, Shahanaghi K, Aryanejhad M. Reducing outpatient waiting time: a simulation modeling approach. Iran Red Crescent Med J 2013; 15 865–9.
Reducing outpatient waiting time: a simulation modeling approach.Crossref | GoogleScholarGoogle Scholar |

[36]  Rohleder T, Lewkonia P, Bischak D, Duffy P, Hendijani R. Using simulation modeling to improve patient flow at an outpatient orthopedic clinic. Health Care Manage Sci 2011; 14 135–45.
Using simulation modeling to improve patient flow at an outpatient orthopedic clinic.Crossref | GoogleScholarGoogle Scholar |

[37]  Samorani M, LaGanga L. Outpatient appointment scheduling given individual day-dependent no-show predictions. Eur J Oper Res 2015; 240 245–57.
Outpatient appointment scheduling given individual day-dependent no-show predictions.Crossref | GoogleScholarGoogle Scholar |

[38]  Liang B, Turkcan A, Ceyhan M, Stuart K. Improvement of chemotherapy patient flow and scheduling in an outpatient oncology clinic. Int J Prod Res 2015; 53 7177–90.

[39]  De Vuyst S, Bruneel H, Fiems D. Computationally efficient evaluation of appointment schedules in health care. Eur J Oper Res 2014; 237 1142–54.
Computationally efficient evaluation of appointment schedules in health care.Crossref | GoogleScholarGoogle Scholar |

[40]  Tang J, Yan C, Cao P. Appointment scheduling algorithm considering routine and urgent patients. Expert Syst Appl 2014; 41 4529–41.
Appointment scheduling algorithm considering routine and urgent patients.Crossref | GoogleScholarGoogle Scholar |

[41]  Kortbeek N, Zonderland M, Braaksma A, Vligen I, Boucherie R, Litvak N, et al Designing cyclic appointment schedules for outpatient clinics with scheduled and unscheduled patient arrivals. Perform Eval 2014; 80 5–26.
Designing cyclic appointment schedules for outpatient clinics with scheduled and unscheduled patient arrivals.Crossref | GoogleScholarGoogle Scholar |

[42]  Eriksson H, Bergbrant IM, Berrumand I, Morck B. Reducing queues: demand and capacity variations. Int J Health Care Qual Assur 2011; 24 592–600.
Reducing queues: demand and capacity variations.Crossref | GoogleScholarGoogle Scholar |

[43]  Young T, Brailsford S, Connell C, Davies R, Harper P, Klein P. Using industrial processes to improve patient care. BMJ 2004; 328 162–4.
Using industrial processes to improve patient care.Crossref | GoogleScholarGoogle Scholar |

[44]  Kollberg B, Dahlgaard J. Measuring lean initiatives in health care services: issues and findings. Int J Prod Perform Manag 2006; 56 7–24.
Measuring lean initiatives in health care services: issues and findings.Crossref | GoogleScholarGoogle Scholar |

[45]  LaGanga L. Lean services operations: reflections and new directions for capacity expansion in outpatient clinics. J Oper Manage 2011; 29 422–33.
Lean services operations: reflections and new directions for capacity expansion in outpatient clinics.Crossref | GoogleScholarGoogle Scholar |

[46]  Gijo E, Anthony J. Reducing patient waiting time in outpatient department using lean six sigma methodology. Qual Reliab Eng Int 2014; 30 1481–91.
Reducing patient waiting time in outpatient department using lean six sigma methodology.Crossref | GoogleScholarGoogle Scholar |

[47]  Lin S, Gavney D, Ishman S, Cady-Reh J. Use of lean sigma principles in a tertiary care otolaryngology clinic to improve efficiency. Laryngoscope 2013; 123 2643–8.
Use of lean sigma principles in a tertiary care otolaryngology clinic to improve efficiency.Crossref | GoogleScholarGoogle Scholar |

[48]  Weiner M, El Hoyek G, Wang L, Dexter P, Zerr A, Perkins A, et al A web-based generalist–specialist system to improve scheduling of outpatient specialty consultations in an academic center. J Gen Intern Med 2009; 24 710–5.
A web-based generalist–specialist system to improve scheduling of outpatient specialty consultations in an academic center.Crossref | GoogleScholarGoogle Scholar |

[49]  Khan A, Mustafa M, Sanders R. Improving patient access to prevent sight loss: ophthalmic electronic referrals and communication (Scotland). Public Health 2014; 129 117–23.

[50]  Sabesan S, Roberts L, Aiken P, Joshi A, Larkins S. Timely access to specialist medical oncology services closer to home for rural patients: experience from the Townsville Teleoncology Model. Aust J Rural Health 2014; 22 156–9.
Timely access to specialist medical oncology services closer to home for rural patients: experience from the Townsville Teleoncology Model.Crossref | GoogleScholarGoogle Scholar |

[51]  Corrigan M, McHugh S, Murphy R, Dhillon P, Shah A, Hennessy I, et al Improving surgical outpatient efficiency through mobile phone text messaging. Surg Innov 2011; 18 354–7.
Improving surgical outpatient efficiency through mobile phone text messaging.Crossref | GoogleScholarGoogle Scholar |

[52]  OECD. Waiting Time Policies in the Health Sector. What works? Siciliani L, Borowitz M, Moran V, editors. Paris: OECD Publishing; 2013.

[53]  Kreindler S. Watching your wait: evidence-informed strategies for reducing health care waiting times. Qual Manag Health Care 2008; 17 128–35.
Watching your wait: evidence-informed strategies for reducing health care waiting times.Crossref | GoogleScholarGoogle Scholar |

[54]  Harding K, Taylor N, Leggart S, Stafford M. Effect of triage on waiting time for community rehabilitation: a prospective cohort study. Arch Phys Med Rehabil 2012; 93 441–5.
Effect of triage on waiting time for community rehabilitation: a prospective cohort study.Crossref | GoogleScholarGoogle Scholar |

[55]  Dimakou S, Parkin D, Devlin N, Appleby J. Identify the impact of government targets on waiting times in the NHS. Health Care Manage Sci 2009; 12 1–10.
Identify the impact of government targets on waiting times in the NHS.Crossref | GoogleScholarGoogle Scholar |

[56]  Ham C. Incentives, priorities, and clinical integration in the NHS. Lancet 2008; 371 98–100.
Incentives, priorities, and clinical integration in the NHS.Crossref | GoogleScholarGoogle Scholar |

[57]  Fetter R, Thompson J. Patients’ waiting time and doctors’ idle time in the outpatient setting. Health Serv Res 1966; 1 66–90.
| 1:STN:280:DyaF2s%2FgvFansA%3D%3D&md5=ff0c97595f3a2a9c60678db9bef685caCAS |

[58]  O’Keefe R. Investigating outpatient departments: implementable policies and qualitative approaches. J Oper Res Soc 1985; 36 705–12.
Investigating outpatient departments: implementable policies and qualitative approaches.Crossref | GoogleScholarGoogle Scholar | 1:STN:280:DyaL2M3pt1agtA%3D%3D&md5=532fc902463b3c651c3f63e056fa6630CAS |

[59]  Chand S, Moskowitz H, Norris JB, Shade S, Willis DR. Improving patient flow at an outpatient clinic: study sources of variability and improvement factors. Health Care Manage Sci 2009; 12 325–40.
Improving patient flow at an outpatient clinic: study sources of variability and improvement factors.Crossref | GoogleScholarGoogle Scholar |