No-shows in appointment scheduling – a systematic literature review
Introduction
No-show appointments (also commonly referred to as broken or missed appointments) are a burden to essentially all healthcare systems, significantly impacting revenue, cost and use of resources [[1], [2]]. It is a well-known fact that no-show decreases the provider’s productivity and efficiency, increases healthcare costs, and limits the health clinic’s effective capacity [[3], [4]]. Negative effects are also felt by patients who keep their appointments, such as dissatisfaction with high waiting time and perception of overall decrease in service quality [[2], [5], [6]]. In addition to creating financial costs for providers, non-attendance generates social costs related with unused staff time, ineffective use of equipment and possible misuse of patients’ time [6].
There is a general consensus in literature regarding the fact that no-show does not occur arbitrarily and several studies have identified the need to statistically analyze the factors that influence its behavior in order to improve healthcare processes and dampen the effects of missed appointments. A number of the most recent of such studies attest to the existence of a relationship between no-show rates and patient behavior [[4], [7], [8], [9], [10]]. By evaluating this relationship through univariate and/or multivariate statistical methods, several works have proposed interventions to mitigate the negative effects of missed appointments [[2], [4]], such as: overbooking [[11], [12], [13], [14]], open access [15], appointment reminders [5], best management practices, among others.
There is a markedly growing interest from the healthcare community in uncovering and understanding the issues involved in no-show behavior. However, given the variability in context and specificities of health care delivery and systems, it is unlikely that a general agreement may be reached regarding the variables that statistically influence no-show behavior. Nevertheless, by aggregating studies that report on a range of different medical specialties and continents, and make use of distinct methodologies for data analysis, it is possible to identify the determinants that have been most frequently considered significant and their effect on no-show. Moreover, although a comprehensive synthesis of the state-of-the-art in this field would be of great value to researchers, practitioners, and hospital administrators alike, to the best of our knowledge, no updated systematic literature review (SLR) exists.
This paper addresses the aforementioned shortcomings by providing a SLR of no-show in appointment scheduling. The goals are threefold: for one, we provide an overview of the characteristics of existing studies in terms of their methodology, continent where the study was undertaken, medical specialties involved, dependent variables considered, and values of no-show rates. In addition to that, we report on the most common tendencies across surveyed studies and detect patterns that emerge. Finally, we discuss our findings in light of previous literature reviews [[16], [17], [18]].
Of note, we adopt the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines [19] and organize the remainder of this paper as follows. In Section 2 we detail how data collection and study selection were performed, and report on the methods used for handling such data. Section 3 contains a complete account of the studies screened, assessed for eligibility, and included in this review, with reasons for exclusions at each stage, along with the results of our analysis. Finally, we summarize our main findings and present a general interpretation of the results with implications for future research in Section 4.
Section snippets
Methods
This work entails a SLR of existing studies on no-show in appointment scheduling. As such, we rely on qualitative, non-statistical tools for integrating, evaluating and interpreting results currently available in literature [20]. In what follows we describe our search strategy, recount eligibility criteria for study selection, and elaborate on our methodology for analyzing the surveyed studies.
Results and discussion
Our search using the Scopus database yielded a total of 727 papers, three of which were duplicates, so that 724 papers were screened for eligibility based on their title and/or abstract. The remaining 230 papers were screened based on their complete text using eligibility criteria as well as the additional constraints defined in Section 2.2. A total of 105 papers and three literature reviews on the subject of interest were retained. Although these review papers were not SLR, they offer a basis
Conclusion
This work integrates and summarizes the findings of 105 papers dealing with determinants of no-show in appointment scheduling. The average no-show rate across all studies was found to be 23.0%, and further analysis revealed that this rate was highest in the African continent (43.0%) and lowest in Oceania (13.2%). We also verified that psychiatry and primary care were the most investigated specialties, and that various statistical methods were used in the reviewed papers to identify significant
Conflicts of interest
The authors declare no competing conflicts of interest.
Acknowledgements
This work was supported by the National Council for Scientific and Technological Development (CNPq) [grant numbers 443595/2014-3 and 304843/2016-4 to FLCO, grant numbers 306802/2015-5 and 403863/2016-3 to SH]; Carlos Chagas Filho Foundation (FAPERJ) [grant number E-26/202.806/2015 to FLCO]; Coordination for the Improvement of Higher Education Personnel (CAPES); and the Pontifical Catholic University of Rio de Janeiro.
References (122)
- et al.
The effectiveness of outpatient appointment reminder systems in reducing no-show rates
American Journal of Medicine
(2010) The economics of non-attendance and the expected effect of charging a fine on non-attendees
Health Policy
(2005)- et al.
Determinants of outpatient clinic attendance amongst adults with congenital heart disease and outcome
International Journal of Cardiology
(2016) - et al.
Outpatient appointment scheduling given individual day-dependent no-show predictions
European Journal of Operational Research
(2015) - et al.
Predictors of repeated no-showing to clinic appointments
American Journal of Otolaryngology
(2015) - et al.
Factors related to missed first appointments after discharge among patients with schizophrenia in Taiwan
Journal of the Formosan Medical Association
(2014) - et al.
Missed appointments at a Swiss university outpatient clinic
Public Health
(2007) Non-attendance in endocrinology and metabolism patients
Journal of the Formosan Medical Association
(2010)- et al.
Who defaults from colposcopy? A multi-centre, population-based, prospective cohort study of predictors of non-attendance for follow-up among women with low-grade abnormal cervical cytology
European Journal of Obstetrics & Gynecology and Reproductive Biology
(2012) - et al.
Factors associated with missed and cancelled colonoscopy appointments at Veterans Health Administration facilities
Clinical Gastroenterology and Hepatology
(2016)
Improving an outpatient clinic utilization using decision analysis-based patient scheduling
Socio-Economic Planning Sciences
A profile of the noncompliant patient: a thirty-month review of outpatient psychiatry referrals
General Hospital Psychiatry
A probabilistic model for predicting the probability of no-show in hospital appointments
Health Care Management Science
Patient appointments in ambulatory care
Clinic overbooking to improve patient access and increase provider productivity
Decision Sciences
Large-scale assessment of missed opportunity risks in a complex hospital setting
Informatics for Health and Social Care
Factors associated with non-attendance at a hand surgery appointment
Hand
Risk factor model to predict a missed clinic appointment in an urban, academic, and underserved setting
Population Health Management
Prevalence, predictors and economic consequences of no-show
BMC Health Services Research
A stochastic overbooking model for outpatient clinical scheduling with no-shows
IIE Transactions
Using no-show modeling to improve clinic performance
Health Informatics Journal
Clinic scheduling models with overbooking for patients with heterogeneous no-show probabilities
Annals of Operations Research
Effects of clinical characteristics on successful open access scheduling
Health Care Management Science
Dropouts and broken appointments: a literature review and agenda for future research
Medical Care
Appointment breaking: causes and solutions
Marketing Health Services
Tackling no-show behavior: a market-driven approach
Health Marketing Quarterly
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement
PLoS Medicine
Undertaking a literature review: a step-by-step approach
British Journal of Nursing
Scopus [database online]
Analise de conteudo
Patient appointment failures in pediatric resident continuity clinics
Archives of Pediatrics & Adolescent Medicine
Failed appointments in residency practices: who misses them and what providers are most affected?
Journal of the American Board of Family Medicine
Why do patients with chronic illnesses fail to keep their appointments? A telephone interview
Asia-Pacific Journal of Public Health
Determinants of appointment absenteeism at an outpatient pediatric autism clinic
Journal of Developmental and Behavioral Pediatrics
Can we predict a national profile of non-attendance pediatric urology patients: a multi-institutional electronic health record study
Journal of Innovation in Health Informatics
What factors influence follow-up in orthopedic trauma surgery?
Archives of Orthopaedic and Trauma Surgery
Introducing consultant outpatient clinics to community settings to improve access to pediatrics: an observational impact study
BMJ Quality & Safety
Lead time for appointment and the no-show rate in an ophthalmology clinic
Clinical Ophthalmology
Who did not appear? First dental visit absences in secondary care on a major Brazilian city: a cross-sectional study
Ciencia & Saude Coletiva
Patient no-show predictive model development using multiple data sources for an effective overbooking approach
Applied Clinical Informatics
Why don’t neurosurgery patients return for neuropsychological follow-up? Predictors for voluntary appointment keeping and reasons for cancellation
Clinical Neuropsychologist
Injury type and emergency department management of orthopedic patients influences follow-up rates
Journal of Bone and Joint Surgery
The usefulness of patients’ individual characteristics in predicting no-shows in outpatient clinics
Medical Care
A multivariate approach to the prediction of no-show behavior in a primary care center
Archives of Internal Medicine
Defaulted appointments in general practice
British Journal of General Practice
Can outpatient non-attendance be predicted from the referral letter? An audit of default at neurology clinics
Journal of the Royal Society of Medicine
Patients who fail to attend their first psychiatric outpatient appointment: non-attendance or inappropriate referral?
JMH
Why do patients default from follow-up at a genitourinary clinic? A multivariate analysis
GUM
Missed appointments and Medicaid managed care
Archives of Family Medicine
Factors associated with clinic non-attendance in adults with type 1 diabetes mellitus
Diabetic Medicine
Cited by (230)
Patient adherence in healthcare operations: A narrative review
2024, Socio-Economic Planning SciencesTelemedicine Reduces Missed Appointments but Disparities Persist
2024, American Journal of Preventive MedicineA Novel Nephropsychology Clinic: Partnering With Patients in the Era of Value-Based Care in Nephrology
2024, Advances in Kidney Disease and HealthMultiserver time window allowance schedules for virtual visits with uncertain time-dependent no-shows and service times
2024, Advanced Engineering InformaticsInnovation tactics for implementing an ML application in healthcare: A long and winding road
2024, International Journal of Human Computer Studies