Identifying barriers to outpatient appointment attendance in patient groups at risk of inequity: a mixed methods study in a London NHS trust.

BACKGROUND: There is significant health inequity in the United Kingdom (U.K.), with different populations facing challenges accessing health services, which can impact health outcomes. At one London National Health Service (NHS) Trust, data showed that patients from deprived areas and minority ethnic groups had a higher likelihood of missing their first outpatient appointment. This study's objectives were to understand barriers to specific patient populations attending first outpatient appointments, explore systemic factors and assess appointment awareness. METHODS: Five high-volume specialties identified as having inequitable access based on ethnicity and deprivation were selected as the study setting. Mixed methods were employed to understand barriers to outpatient attendance, including qualitative semi-structured interviews with patients and staff, observations of staff workflows and interrogation of quantitative data on appointment communication. To identify barriers, semi-structured interviews were conducted with patients who missed their appointment and were from a minority ethnic group or deprived area. Staff interviews and observations were carried out to further understand attendance barriers. Patient interview data were analysed using inductive thematic analysis to create a thematic framework and triangulated with staff data. Subthemes were mapped onto a behavioural science framework highlighting behaviours that could be targeted. Quantitative data from patient interviews were analysed to assess appointment awareness and communication. RESULTS: Twenty-six patients and 11 staff were interviewed, with four staff observed. Seven themes were identified as barriers - communication factors, communication methods, healthcare system, system errors, transport, appointment, and personal factors. Knowledge about appointments was an important identified behaviour, supported by eight out of 26 patients answering that they were unaware of their missed appointment. Environmental context and resources were other strongly represented behavioural factors, highlighting systemic barriers that prevent attendance. CONCLUSION: This study showed the barriers preventing patients from minority ethnic groups or living in deprived areas from attending their outpatient appointment. These barriers included communication factors, communication methods, healthcare the system, system errors, transport, appointment, and personal factors. Healthcare services should acknowledge this and work with public members from these communities to co-design solutions supporting attendance. Our work provides a basis for future intervention design, informed by behavioural science and community involvement.

Raising the barcode: improving medication safety behaviours through a behavioural science-informed feedback intervention. A quality improvement project and difference-in-difference analysis.

Barcode medication administration (BCMA) technology can improve patient safety by using scanning technology to ensure the right drug and dose are given to the right patient. Implementation can be challenging, requiring adoption of different workflows by nursing staff. In one London National Health Service trust scanning rates were lower than desired at around 0-20% of doses per ward. Our objective was to encourage patient safety behaviours in the form of medication scanning through implementation of a feedback intervention. This was informed by behavioural science, codesigned with nurses and informed by known barriers to use. Five wards were selected to trial the intervention over an 18-week period beginning August 2021. The remaining 14 hospital wards acted as controls. Intervention wards had varying uptake of BCMA at baseline and represented a range of specialties. A bespoke feedback intervention comprising three behavioural science constructs (gamification, the messenger effect and framing) was delivered to each intervention ward each week. A linear difference-in-difference analysis was used to evaluate the impact of our intervention on scan rates, both for the overall 18-week period and at two weekly intervals within this timeframe. We identified a 23.1 percentage point increase in medication scan rates (from an average baseline of 15.0% to 38.1%) on the intervention wards compared with control (p<0.001) following implementation of the intervention. Feedback had most impact in the first 6 weeks, with an initial percentage point increase of 26.3 (p<0.001), which subsequently plateaued. Neither clinical specialty nor number of beds on each ward were significant factors in our models. Our study demonstrated that a feedback intervention, codesigned with end users and incorporating behavioural science constructs, can lead to a significant increase in the adoption of BCMA scanning.