Risk Factor Model to Predict a Missed Clinic Appointment in an Urban, Academic, and Underserved Setting

Abstract

In the chronic care model, a missed appointment decreases continuity, adversely affects practice efficiency, and can harm quality of care. The aim of this study was to identify predictors of a missed appointment and develop a model to predict an individual's likelihood of missing an appointment. The research team performed a retrospective study in an urban, academic, underserved outpatient internal medicine clinic from January 2008 to June 2011. A missed appointment was defined as either a "no-show" or cancellation within 24 hours of the appointment time. Both patient and visit variables were considered. The patient population was randomly divided into derivation and validation sets (70/30). A logistic model from the derivation set was applied in the validation set. During the period of study, 11,546 patients generated 163,554 encounters; 45% of appointments in the derivation sample were missed. In the logistic model, percent previously missed appointments, wait time from booking to appointment, season, day of the week, provider type, and patient age, sex, and language proficiency were all associated with a missed appointment. The strongest predictors were percentage of previously missed appointments and wait time. Older age and non-English proficiency both decreased the likelihood of missing an appointment. In the validation set, the model had a c-statistic of 0.71, and showed no gross lack of fit (P=0.63), indicating acceptable calibration. A simple risk factor model can assist in predicting the likelihood that an individual patient will miss an appointment.

Association between missed appointment and related factors of patients with cancer in a tertiary hospital

“…First, rates differ significantly by gender: in our dataset, males and females failed to appear for 4.39% and 3.37% of appointments, respectively. This finding was consistent with the results of prior studies . However, there were no gender‐specific patterns in the relationship between cancer type and no‐show rate: both males and females had high no‐show rates for liver, pancreas, and colon and rectum cancer.…”

If You Book It, Will They Come? Attendance at Postdischarge Follow‐Up Visits Scheduled by Inpatient Providers

“…In contrast to several previous studies of outpatient nonattendance,we did not find that visits scheduled for time points further in the future were more likely to be missed. 14,24,25,36,37 Unlike other appointments, it may be that PDFV lead time does not affect attendance because of the unique manner in which PDFV times are scheduled and conveyed to patients. Unlike other appointments, patients do not schedule PDFVs themselves but instead learn about their PDFV dates as part of a large set of discharge instructions.…”

“…B) Appointments scheduled for patients (n = 47) who would otherwise be ineligible for UPHS outpatient care for insurance reasons; see Supplementary Table A NS/SDC rates for the variables listed above. 17,[22][23][24][25] We additionally calculated NS/SDC and attendance-as-scheduled rates stratified by the number of PDFVs per patient to assess for a "high-utilizer" effect with regard to PDFV attendance.…”

A review of 145 234 ophthalmic patient episodes lost to follow-up

“…11 In another study, to identify why patients might miss an appointment, the main risk factors were found to be older age and non-English proficiency. 12 A study of the views of health-care professionals as to why children did not attend a general paediatric appointment also suggested the reasons were multifactorial 13 and included socioeconomic factors, issues relating to other children as well as factors relating to hospital administration. King et al, 14 found a 12.9% DNA rate in a study in a specialist eye hospital in 1991 but did not find any specific reasons for patients failing to attend.…”