No-shows in appointment scheduling – a systematic literature review

Dantas, Leila Figueiredo; Fleck, Julia L.; Oliveira, Fernando Luiz Cyrino; Hamacher, Śılvio

doi:10.1016/j.healthpol.2018.02.002

Cited by 308 publications

(285 citation statements)

References 99 publications

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“…However, while our results have identified a vulnerable population, this consideration ultimately applies to patients of all backgrounds. Consistent with the majority of no‐show studies, our findings show that the most reliable predictor of nonattendance is a history of no‐show in the past …”

Section: Discussionsupporting

confidence: 91%

“…While there is a growing body of literature on nonattendance in primary care and other specialty clinics, there is a paucity of data on nonattendance in the ACHD population. As both the rate and predictors of nonattendance vary considerably across specialties, a closer look into the ACHD population is merited. Kempny and colleagues have published the only study to date examining nonattendance in an ACHD outpatient clinic in the United Kingdom in which the prevalence of nonattendance was 23.4% .…”

Section: Discussionmentioning

confidence: 99%

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Clinic nonattendance is associated with increased emergency department visits in adults with congenital heart disease

Awh

Venuti

Gleason

et al. 2019

Congenital Heart Disease

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Objective To determine the prevalence and predictors of nonattendance in an ACHD outpatient clinic, and to examine the relationship between nonattendance and emergency department (ED) visits, hospitalizations, and death. Methods Patients ≥ 18 years who had scheduled appointments at an ACHD outpatient clinic between August 1, 2014 and December 31, 2014 were included. The primary outcome of interest was nonattendance of the first scheduled appointment of the study period, defined as “no‐show” or “same‐day cancellation.” Secondary outcomes of interest were ED visits, hospitalizations, and death until December 2017. Results Of 527 scheduled visits, 55 (10.4%) were nonattended. Demographic and socioeconomic characteristics such as race, income, and insurance type were associated with non‐attendance (all P values < .05), whereas age, gender, and disease complexity were not. On multivariable analysis, predictors of nonattendance were black race (adjusted odds ratio [AOR] 4.95; P < .001), other race (AOR 3.54; P = .003), and history of no‐show in the past (AOR 4.95; P < .001). Compared to patients who attended clinic, patients with a nonattended visit had a threefold increased odds of multiple ED visits and a significantly lower rate of ED‐free survival over time. There were no significant differences in hospitalizations or death by attendance. Conclusions ACHD clinic nonattendance is associated with race and prior history of no‐show, and may serve as a marker of higher ED utilization for patients with ACHD.

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Section: Discussionsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Clinic nonattendance is associated with increased emergency department visits in adults with congenital heart disease

Awh

Venuti

Gleason

et al. 2019

Congenital Heart Disease

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“…It is considered a global problem in health care both in the public and private sectors as per papers published in Brazil 2, 3 and worldwide 4-6 . A systematic review on the subject revealed a 23% worldwide nonattendance average rate, being the highest rate found in Africa (43.0%), followed by South America (27.8%), Asia (25.1%), North America (23.5%), Europe (19.3%) and Oceania (13.2%) 7 . When the Unified Health System (SUS) is concerned, non-attendance to specialized healthcare appointments is accounted as a chronic problem since rates are close to or beyond 25% 8 , reaching high percentages in various types of care and medical specialties 9 .…”

Section: Introductionmentioning

confidence: 99%

Absenteísmo de usuários como fator de desperdício: desafio para sustentabilidade em sistema universal de saúde

et al. 2019

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Non-attendance to specialized healthcare appointments, diagnostic, and therapeutic procedures is a global problem in healthcare, leading to the wastage of resources both in the public and private sectors. This study aims to estimate financial wastage of resources linked to non-attendance to scheduled health specialist appointments and procedures in the metropolitan region of the Espírito Santo State (ES), Brazil, between 2014 and 2016. We studied 1.002.719 specialized healthcare procedures, being 666.182 appointments with specialized physicians and other healthcare professionals, and 336.537 specialized diagnostic and other therapeutic procedures. Non-attendance date were retrieved from the administrative procedure scheduling database (SisReg-ES) available in the ES Regulatory Agency and provided by the ES Health Office. Financial values used to estimate wastage were retrieved from the SUS and other standard tariff lists for medical procedures, and used according to the administrative regime of the three types of service providers. Non-attendance average rate for medical and health specialists' appointments achieved 38.6%, or 257.025 missed appointments, equivalent to an estimated waste of resources of R$3.558.837,88. Non-attendance as for other specialized procedures reached 32.1%, or 108.103 missed procedures, equivalent to R$15.007.624,15. Total wasted resources reached significant values, evincing the ongoing challenge to managers seeking to attain SUStainable universal health care systems.KEYWORDS Absenteeism. Secondary care. Health management. Integrality in health. RESUMO O absenteísmo de usuários em consultas e exames é considerado um problema mundial na assistência à saúde, gerando desperdício de recursos tanto no setor público como no setor privado. O objetivo deste estudo foi o de estimar o desperdício de recursos monetários vinculado ao absenteísmo em procedimentos especializados no Sistema Único de Saúde (SUS) naRegião de Saúde Metropolitana do Espírito Santo (RSM-ES) entre os anos de 2014 e 2016. Analisaram-se 1.002.719 procedimentos, sendo 666.182 consultas e 336.537 exames especializados. Os dados de absenteísmo foram retirados dos registros administrativos do Sistema de Regulação do ES (SisReg-ES), fornecidos pela Secretaria Estadual de Saúde. Os valores monetários foram obtidos por meio da Tabela SUS, da tabela complementar de convênios e da tabela de custos estimados, segundo o tipo de prestador envolvido no atendimento. A taxa média de absenteísmo para consultas foi de 38,6% (257.025 consultas), gerando um total estimado de R$3.558.837,88; e para exames especializados, foi de 32,1% (108.103 exames), em um total estimado de R$15.007.624,15. Os valores totais desperdiçados são significativos e evidenciam o desafio constante na agenda dos gestores na busca pela SUStentabilidade em sistemas universais de saúde. PALAVRAS-CHAVE Absenteísmo. Atenção secundária à saúde. Gestão em saúde. Integralidade em saúde.

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“…Missed appointments that have not been canceled by the patient are commonly referred to as no-show appointments (Bush et al, 2014;Dantas et al, 2018;Kalb et al, 2012;Miller et al, 2015;Weingarten et al, 1997;Zailinawati et al, 2006). However, researchers often consider late cancellations as missed appointments since such late cancellations do not allow the scheduling system to set an appointment for a new patient (Topuz et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…It is well-known that patient no-shows and/or late cancellations adversely affect healthcare systems in terms of efficiency and productivity (Miller et al, 2015). No-shows not only limit other patients' access to required healthcare, but also negatively impact patients through high waiting time (Dantas et al, 2018). The rate of patient no-shows may vary from 3% to 80%, depending on the type of clinic and patient demographic information (Alaeddini et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

A metaheuristic-based stacking model for predicting the risk of patient no-show and late cancellation for neurology appointments

Ahmadi

Garcia-Arce

Masel

et al. 2019

IISE Transactions on Healthcare Systems Engineering

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Patient no-shows and late cancellations for an appointment are common problems in healthcare, which adversely affect the financial performance and quality of service of healthcare organizations. A high rate of patient no-show and late cancellation in a clinic can significantly limit access to healthcare. In general, hospitals create predictive models to assess risk of no-show, and then assign overbooking appointments utilizing those risks. In this paper, by incorporating machine learning and optimization techniques, we proposed a predictive model to assist with the overbooking decision. The model consists of two phases. First, we utilized a metaheuristic optimization technique to explore the best subset of featuresknown as feature selection problemthat can significantly contribute to the prediction outcomes. Second, using the output of the first stage, we proposed a stacking model to improve the prediction performances further. Our extensive computations and comparisons across different classifiers show that formulating the feature selection problem as a multi-objective problem instead of a single-objective problem using random forest classifier yields better results. The proposed model will improve the overbooking at clinics, by increasing the patient access to care. We introduced important new features to the literature that can describe the no-show and late cancellation behavior.

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No-shows in appointment scheduling – a systematic literature review

Cited by 308 publications

References 99 publications

Clinic nonattendance is associated with increased emergency department visits in adults with congenital heart disease

Clinic nonattendance is associated with increased emergency department visits in adults with congenital heart disease

Absenteísmo de usuários como fator de desperdício: desafio para sustentabilidade em sistema universal de saúde

A metaheuristic-based stacking model for predicting the risk of patient no-show and late cancellation for neurology appointments

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