# Global Predictors of Appointment Non-Adherence in Primary Care Settings: A Systematic Review

## TL;DR

This paper reviews global factors that predict missed primary care appointments, highlighting patient and system-level issues and suggesting ways to reduce non-adherence.

## Contribution

The study systematically identifies and categorizes global predictors of appointment non-adherence in primary care across diverse populations.

## Key findings

- Non-attendance rates varied widely (~5–31%) across studies.
- Key predictors included younger age, socioeconomic disadvantage, mental health burden, and access barriers.
- Telemedicine and continuity with the same clinician were linked to lower non-attendance in recent studies.

## Abstract

Background: Missed primary care appointments disrupt continuity, reduce care quality, and increase healthcare costs. Despite numerous studies, global patterns and predictors of appointment non-adherence remain inconsistently reported. Objective: To identify, categorize, and evaluate the consistency of predictors of appointment non-adherence in primary care across diverse populations and healthcare systems. Methods: A systematic review was conducted following PRISMA guidelines (PROSPERO ID: CRD420251121963). PubMed/MEDLINE, Scopus, Web of Science, and Cochrane were searched in August 2025 for observational studies examining predictors of missed, canceled, or rescheduled primary care appointments. Study quality was appraised using the MINORS tool. Results: Twenty-seven observational studies (1982–2025) across eight countries were included, representing a total of more than 13 million appointments analyzed. Reported non-attendance varied widely (~5–31%). Predictors clustered into: patient-level (younger age, socioeconomic disadvantage, minority status in North American studies, mental health burden, and lower literacy/greater social needs), appointment-level (prior non-attendance and longer time between booking and visit), and clinic/system-level (access barriers such as transportation and scheduling friction). Telemedicine and continuity with the same clinician were associated with lower non-attendance in more recent studies. Due to heterogeneity in definitions and analyses, the results were synthesized narratively; overall study quality was modest–moderate by MINORS. Conclusions: Missed appointments reflect interacting patient- and system-level determinants, with the highest risk among younger and socioeconomically disadvantaged patients and those with mental health conditions. Interventions that reduce access friction (e.g., reminders, flexible scheduling/shorter lead times, transportation support) and equity-focused hybrid telemedicine may reduce non-adherence.