ArticleRisk management and healthcare policy2020
Who Misses Appointments Made Online? Retrospective Analysis of the Outpatient Department of a General Hospital in Jinan, Shandong Province, China.
Article in Risk management and healthcare policy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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.
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Who cites it
3 citing papers in PubMed, 8 citations in OpenAlex.
- Examining the Reasons for Patient No-Show in an Outpatient Adult Rehabilitation Department in King Abdulaziz Medical City, Riyadh: A Cross-Sectional Study.Health science reports · 2025Article
- Efficient patient care in the digital age: impact of online appointment scheduling in a medical practice and a university hospital on the "no-show"-rate.Frontiers in digital health · 2025Article
- Efficient patient care in the digital age: Online appointment scheduling in an ophthalmology practice.Digital healthArticle
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeMissed appointments in outpatient registration pose challenges for hospital administrators, especially in the context of China's shortage of medical resources. Previous studies have identified factors that affect healthcare access via traditional appointment systems. Few studies, however, have specifically investigated Internet appointment systems. Therefore, this study explored the key factors related to missed appointments made on the Internet appointment system of a general hospital in Jinan, Shandong Province.
methodsOnline appointment data were collected from the outpatient department of a general hospital in Jinan from September 2017 to February 2018. Logistic regression was used to analyze the relative importance of eight variables: gender, age, interval between scheduling and appointment, day of the week, physician's academic rank, appointment fee, previous missed appointments, and clinical department.
resultsA total of 48,777 online appointment records were collected, which included a 15% no-show rate. The key factors associated with no-shows included age, interval between scheduling and appointment, previous missed appointments, and clinical department. No significant relationships were found between no-shows and gender, day of the week, and appointment fee.
conclusionNo-show rates were influenced by many factors. Based on this study's findings, targeted measures can be taken to decrease no-show frequency and improve medical efficiency.
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