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☐ ☆ ✇ BMJ Open

Patient-related and organisational characteristics associated with late cancellations and non-attendance in diabetes outpatient care: a cross-sectional study

Por: Singstad · T. · Holmen · H. · Smastuen · M. C. · Nermoen · I. · Ribu · L. · Torbjornsen · A. — Octubre 30th 2025 at 04:18
Objective

We aimed to explore the patient-related and organisational characteristics associated with late cancellations and non-attendance in diabetes outpatient care and present our findings organised as a risk matrix based on these characteristics.

Design

A cross-sectional study.

Setting

Our study was conducted at an endocrinology outpatient clinic based on data extracted between January and December 2019 from electronic medical records.

Participants

Adult patients with type 1 diabetes with late cancellations or non-attendance. We compared our sample with national data for comparison and to assess representativeness.

Primary and secondary outcome measures

Main outcome was late cancellations or non-attendance, while secondary outcomes included type of cancellations and reason for cancellation.

Results

In total, 541 patients had late cancellations or non-attendance across 5040 diabetes consultations. These patients had a mean age of 43 years, 57.9% were men and half (n=301, 55%) were employed. The mean diabetes duration was 18 years, and the mean HbA1c level was elevated at 72 mmol/L. The outpatient clinic had a higher number of consultations, but the patient characteristics were comparable to the national average. Half of the patients (n=258, 52.3%) had late cancellations ahead of their consultations. Most cancellations occurred during the winter, mainly due to illness being the most frequent reason. Unemployed men with poorly regulated diabetes were more likely not to attend compared with employed females.

Conclusions

Characteristics such as being male, unemployed and having elevated HbA1c levels were significantly associated with non-attendance. Our findings contribute to understanding the reasons for at-risk patients missing consultations.

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