Skip to main content
eScholarship
Open Access Publications from the University of California

UC Irvine

UC Irvine Electronic Theses and Dissertations bannerUC Irvine

Predictors of No-Show Appointment Status in the Prenatal Genetic Counseling Setting

  • Author(s): Sabrowsky, Sonia Marie
  • Advisor(s): Smith, Moyra
  • et al.
Abstract

The negative effects of missed clinic appointments are well-studied, and certain predictive factors, such as longer lead times and lack of private insurance, have been associated with no-show behavior across a breadth of clinical specialties. However, little is known about the relationship between patient attendance and clinical characteristics specific to the prenatal genetic counseling setting. The current study examined demographic and clinical data from 3,461 pregnant patients scheduled for prenatal genetic counseling to explore factors that may predict whether a patient is more or less likely to no-show to their scheduled appointment. Logistic regression analyses demonstrated that patients were more likely to no-show if they were in the third trimester of pregnancy, had two or more living children, had a lead time of two weeks or more, were referred primarily for a personal or family history of a possible genetic condition, and/or were referred by an outside provider. Patients were less likely to no-show if they were referred for an abnormal ultrasound, had multiple referral indications, had an ultrasound scheduled the same day, and/or their visit was being paid for by a private insurance plan. This study provides additional support to current literature on no-show behavior and introduces variables specific to the unique patient population served by prenatal genetic counselors. Understanding predictors of patient attendance allows for the identification of patients at the highest risk to no-show to their scheduled appointments and provides insight for the potential development of targeted interventions to effectively mitigate this risk.

Main Content
For improved accessibility of PDF content, download the file to your device.
Current View