Abstract
Patient no-shows for scheduled primary care appointments are common. Unused appointment slots reduce patient quality of care, access to services and provider productivity while increasing loss to follow-up and medical costs. This paper describes patterns of no-show variation by patient age, gender, appointment age, and type of appointment request for six individual service lines in the United States Veterans Health Administration (VHA). This retrospective observational descriptive project examined 25,050,479 VHA appointments contained in individual-level records for eight years (FY07-FY14) for 555,183 patients. Multifactor analysis of variance (ANOVA) was performed, with no-show rate as the dependent variable, and gender, age group, appointment age, new patient status, and service line as factors. The analyses revealed that males had higher no-show rates than females to age 65, at which point males and females exhibited similar rates. The average no-show rates decreased with age until 75–79, whereupon rates increased. As appointment age increased, males and new patients had increasing no-show rates. Younger patients are especially prone to no-show as appointment age increases. These findings provide novel information to healthcare practitioners and management scientists to more accurately characterize no-show and attendance rates and the impact of certain patient factors. Future general population data could determine whether findings from VHA data generalize to others.
Highlights
No-show patient appointments have been defined as “patients who neither kept nor cancelled scheduled appointments” [1]
The Veterans Health Administration (VHA) outpatient appointments were grouped into stop codes and aggregated into six service lines: Primary Care; Mental Health; Specialty Medicine; Rehabilitation; Surgery; and Other
This paper describes the variation of no-show rates with patient age, gender, appointment age, and type of request within six individual service line of the United States VHA
Summary
No-show patient appointments have been defined as “patients who neither kept nor cancelled scheduled appointments” [1]. The documented rates of missed appointments may vary somewhat between countries, health care systems, and clinical settings [2], appointment-breaking behaviors constitute a widespread, global issue [2,3,4]. Missed appointments represent a major burden on health care systems and have a negative impact on patient care [8]. Patient no-shows can cause scheduling and operational difficulties for clinics [9,10] and reduced productivity [11,12]. The level of economic impact differs according to the health care system, the overall financial cost of no-shows is substantial [17]. In one of the few national studies, it was estimated that the financial cost to the United
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