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Transforming Non-Attendance at Psychological Outpatient Appointments


Transformation constitutes a radical and significant adjustment in a specific thing’s structure, essence, or form. In healthcare, transformation involves a total overhaul of care delivery, organizational framework, and philosophy of care. Transformation seeks to create a paradigm shift for improvement in the patient experience, quality of care, and resource utilization. The process is complex, including adapting technologized innovations for healthcare provision, modifying the models of caring for patients, enhancing inter-professional relationships within the healthcare system, and prioritizing patient-centeredness. The broad objective entails designing an efficient, effective, patient-centered healthcare service delivery model. It means combining evidence-based practices, ongoing improvements in healthcare delivery, and readiness for changes in the light of new challenges. Transformation in health care provision would be critical to healthcare providers in offering a comprehensive, adaptable, and durable approach to caring for patients aligned with the evolving health environment.


DNA occurs when patients who have scheduled outpatient appointments only attend with notifying or canceling (Dashtban and Li, 2019). The issue of non-attendance has been affecting mental health and psychological therapy services for a considerable length of time, casting a shadow on diverse health services. It is striking even in the UK where about one in ten patients do not attend outpatient appointments, leading to about £600m costs per annum (Binnie and Boden, 2016). However, the economic burden is just one among many facets. Non-monetary implications of this ubiquitous problem echo throughout the healthcare domain, involving delays of long hours, wastage of resources, and questionable therapy endpoints. To be specific, there is collateral damage that goes way beyond logistics; for example, patient non-attendance puts a strain on allied health practitioners emotionally, as they ponder its implications (Wong et al., 2023).

More shockingly, UK empirical research, funded by various governmental departments, exposes an astounding reality. The average absentee rates in general health care settings with a DNA are 8.5%, and cancellations range between 10%. This percentage rises to terrifying 20% in particular mental health settings posing immense clinical challenges. (Binnie and Boden, 2016). In this context, a picture is drawn about the people who never showed up at their scheduled appointments for mental health treatment. This highlights an association between worsened illness, higher attrition rate, greater chance of re-admission to hospital and even further longer interval in waiting lists for other individuals (Wong et al., 2023).

These missed appointments have multiple causes that are very complicated to analyze because they result from a combination of several factors related to both patients and health care organizations. Often, forgetfulness becomes a common feature, manifesting cognitive breakdowns in attendance of appointments (Philpott-Morgan et al. 2021). Health issues also become problematic as patients may feel too unhealthy to do something about it and have their conditions worsened by attending the appointment. The complex topography is compounded by administrative errors that occur in the hospital infrastructures and the day-to-day challenges of work obligations and transport difficulties. Consequently, even the resolution of symptoms is a double edged sword, since patient might feel better and then stop attending mental health appointments contributing to the increase in non-attendance (Philpott-Morgan et al. 2021).


Binnie, J. and Boden, Z., 2016. Non-attendance at psychological therapy appointments. Mental Health Review Journal21(3), pp.231-248.

Dashtban, M. and Li, W., 2019. Deep learning for predicting non-attendance in hospital outpatient appointments.

Philpott-Morgan, S., Thakrar, D.B., Symons, J., Ray, D., Ashrafian, H. and Darzi, A., 2021. Characterising the nationwide burden and predictors of unkept outpatient appointments in the National Health Service in England: A cohort study using a machine learning approach. PLoS Medicine18(10), p.e1003783.

Wong, B.H.C., Chu, P., Calaminus, P., Lavelle, C., Refaat, R. and Ougrin, D., 2023. Association between continuity of care and attendance of post-discharge follow-up after psychiatric emergency presentation.


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