ArticleFrontiers in health services2023
Socioeconomic and demographic factors predictive of missed appointments in outpatient radiation oncology: an evaluation of access.
Article in Frontiers in health services, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed, 14 citations in OpenAlex.
- Evaluation of disparities in timely stereotactic radiosurgery for brain metastases in a safety net hospital system through a centralized workflow.Journal of neuro-oncology · 2026Article
- Predictors of loss to follow-up after radiotherapy in cancer patients.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2026Article
- Determinants of Nonattendance in a Urology Outpatient Clinic: A 5-Year Retrospective Study in a Tertiary Metropolitan Hospital.ANZ journal of surgery · 2025Article
- Socioeconomic factors predictive of access delays in oncology.BMC public health · 2025Article
- The Association of Social Determinants of Health on Monitoring for Disease Progression Among Patients With Primary Open-Angle Glaucoma.Translational vision science & technology · 2025Article
- Predicting pediatric diagnostic imaging patient no-show and extended wait-times using LLMs, regression, and tree based models.Frontiers in artificial intelligence · 2025Article
- No-Show Rates at a Plastic Surgery Clinic: Insights From Appalachian Healthcare Systems.Cureus · 2025Article
- Demographic and socioeconomic determinants of missing labs and imaging for otolaryngologic clinical visits.Laryngoscope investigative otolaryngology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: While missed patient appointments reduce clinic efficiency and limit effective resource allocation, factors predictive of "no shows" are poorly understood in radiation oncology. Methods and materials: A prospective data registry of consecutive patients referred for initial consultation from October 2,018 to April 2022 was reviewed. Demographic characteristics recorded included age, gender, race, language preference, living situation, and insurance status. Zip code data linked to a patient's residential address was used to determine socioeconomic status (SES) based on publicly available data on median household income. No show encounters were defined as all encounters where the patient failed to cancel their visit and did not sign-in to their scheduled appointment. Descriptive statistics were presented to identify factors predictive of missed appointments. Results: A total of 9,241 consecutive patients were referred and logged into the database during the 4-year period, of which 5,755 were successfully scheduled and registered. A total of 523 patients (9%) failed to show for their appointments. Missed appointments were associated with low-income status, homeless living situation, and Black or Latino race ( Conclusions: Our results highlight the influence of demographic, financial, and racial disparities on proper health care utilization among patients with cancer. Future interventions aimed at reducing appointment no shows could channel resources to the at risk-populations identified in this analysis, improving access to care, and optimize clinic efficiency.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.