Using behavioural economics to understand and address radiology non-attendance in Singapore: A mixed-methods study

: (Alternative Format Thesis)

Abstract

This study explores healthcare non-attendance in radiology, highlighting its clinical and economic implications, particularly in Singapore, where rising demand for medical imaging is driven by an ageing population and increasing chronic diseases. Non-attendance strains healthcare resources and escalates costs, with concerns that Singapore’s multi-payer healthcare financing and co-payment systems may discourage service utilisation due to fear of out-of-pocket (OOP) payments. Existing studies reveal a link between non-compliance and patients' attitudes and beliefs, as conceptualized in the Health Belief Model (HBM), but there is limited research incorporating behavioural economics to address these challenges. This study aims to examine factors influencing non-attendance, the impact of patients’ perceptions and broader socio-economic factors on health-seeking behaviour, and to propose behavioural economics-based strategies to improve appointment adherence and align healthcare services with patient needs.

A sequential mixed-methods approach was adopted to explore outpatient radiology non-attendance at a public radiology center in Singapore. Purposeful sampling targeted English-speaking outpatients aged 21 and above, excluding individuals reliant on third-party care services, such as nursing homes or prisons, due to differing financial funding mechanisms. Phase 1 employed semi-structured interviews guided by the Health Belief Model (HBM) to explore the attitudes and beliefs underlying non-attendance in radiology appointments. Thematic analysis revealed six key themes: prioritising health, acceptance of medical conditions, perceived severity, perceived benefits and barriers, influential prompts, and confidence in attendance. These findings informed the development of Phase 2, a Discrete Choice Experiment (DCE) survey designed to quantify patient preferences among a broader sample.

The DCE evaluated preferences across six appointment-related attributes: (1) waiting time for the appointment, (2) choice of appointment time, (3) reminder system, (4) out-of-pocket (OOP) costs, (5) upfront deposit fees, and (6) time taken to receive results. Statistical analyses using SPSS and Cox regression estimated preferences and modeled willingness-to-pay (WTP). Results highlighted two critical factors influencing patient decisions: the reminder system and OOP costs. Flexible reminder systems, particularly those offering options for cancellations or rescheduling, were pivotal for non-attendees, whereas OOP costs had a stronger impact on attendees. These insights emphasise the importance of tailoring appointment systems to meet patient needs effectively.

The study highlights inefficiencies in the existing appointment system, emphasising the need for greater patient engagement and addressing financial concerns. Tailoring appointment scheduling to offer flexible time slots that accommodate patients of different ages and commitments can enhance attendance rates. Additionally, framing messages to highlight the importance of attending appointments such as the potential health consequences of missing one or the likelihood of a long wait for the next available slot leverages loss aversion and gain-framed messaging to encourage adherence. Besides that, implementing default appointments, where a pre-set date is assigned unless changed by the patient, can reduce decision fatigue and improve screening rates.

One effective nudge mechanism to reduce non-attendance is a personalised, two-way digital reminder system. Integrating Short Message Service (SMS) or mobile app notifications that allow patients to confirm, cancel or reschedule appointments with minimal effort can improve adherence. Behavioural prompts within these messages can enhance engagement by making reminders more relevant and actionable. For instance, social norm messages highlighting that most patients attend their appointments or emphasising the cost of non-attendance can reinforce commitment. Personalised messages from trusted healthcare providers, such as respected doctors, can further increase compliance.

Patient engagement is another critical factor in addressing non-attendance. When patients understand the value of healthcare services and recognize their necessity, adherence increases. The patient-provider relationship plays a crucial role, as positive experiences contribute to trust and commitment. Behavioural nudges, such as messages from reputable healthcare providers emphasising the benefits of attending, can help reinforce the perceived value of care. Framing health messages in terms of potential gains (improved health outcomes) or losses (worsening conditions) can further influence behaviour. Strengthening health literacy through clear communication also enhances self-efficacy, empowering patients to take proactive steps in managing their health. Moreover, positive past encounters and advice from healthcare staff serve as strong cues to action, reinforcing the importance of appointment adherence.

Another potential nudge mechanism involves addressing out-of-pocket (OOP) costs through dynamic cost transparency paired with financial incentives. Leveraging the principle of loss aversion, patients may be more likely to prioritise their appointments when they perceive potential savings or penalties for non-attendance.

Integrating these nudge mechanisms offers a promising approach to reducing non-attendance, refining behavioural interventions, and optimising appointment systems. By applying these insights, healthcare providers and policymakers can design targeted strategies to enhance patient engagement, minimise the impact of missed appointments on resource allocation, and improve overall patient satisfaction. A well-designed reminder system, coupled with strong patient engagement and appropriate cost structures, can contribute to a more inclusive, responsive and patient-centered healthcare system.

Date of Award	26 Mar 2025
Original language	English
Awarding Institution	University of Bath
Supervisor	Max Western (Supervisor)