Exploring reasons for clients’ non-attendance of appointments within a community-based alcohol service: clients' perspectives. Faisal Mahmood Faisal Mahmood

Faisal Mahmood BACP Accredited & Registered Counsellor Counselling Theoretical Approach: Gestalt Therapy Theory & Integrative Senior Lecturer in Counselling – Newman University, Birmingham Undertaking a PhD at MMU 20 Years of Experience in Addiction Research Supervisors: Dr Sarah Galvani, Dr Lucy Webb & Dr Andy Guppy Faisal Mahmood

Literature review 12 million GP appointments are missed each year in the UK, costing in excess of £162 million per year. A further 6.9 million outpatient hospital appointments are missed each year in the UK, costing an average of £108 per appointment in 2012/13 (NHS, 2015). Coulson et al (2009) found four separate categories for DNA in substance misuse treatment programmes. These consisted of extraneous factors (e.g. work commitments, illness, social and logistical issues), perceived service shortcomings, no further need for service, and motivational ambivalence. Faisal Mahmood

Literature review Ethnic minority communities are significantly less likely to seek treatment and advice for drinking problems, keeping them hidden from there strict culture (Hurcombe, Bayley and Goodman, 2010). Orford et al (2009) looked more closely at the attributes of behaviour change that facilitate whether the client continues treatment or not. Involving significant others in a client’s treatment signified a change in behaviour and retention in the treatment programme. Faisal Mahmood

Aim, Methodology & Data Aim: To gain a deeper understanding of the reasons for non-attendance of appointments within alcohol misuse community services. Methodology: Mixed Methods Data (Quantitative Study) Secondary dataset analysis West Midlands based substance misuse agency – data from 10 sites in different regions. Appointments’ attendance history of four years (Jan 2010 – Dec 2013). Faisal Mahmood

Demographics Unique service users: 22,405 Total sessions’ data: 194,679 Ethnicity: White British: 68%; Blank: 14% Faisal Mahmood

Demographics Faisal Mahmood

Attended 62% Cxd by Client 13% Cxd by Service 2% DNA 23% Faisal Mahmood

Quantitative Study Secondary analysis of existing datasets Key research questions: To what extent do socio-demographic factors of clients such as age, gender, employment status, accommodation needs, parental status, and number of children living with client determine non-attendance? To what extent do clinical factors of clients such as risk levels, smoking status, pregnancy, dual diagnosis, and overall discharge reasons determine non-attendance? To what extent do the receipts of text messages (appointment reminders) determine non-attendance? To what extent do the session times determine non-attendance? Faisal Mahmood

CHI-SQUARED TEST Faisal Mahmood

Age DNA Percentage 18-24y 37.80% 25-34y 32.50% 35-44y 27.50% 45-54y 24.10% 55-64y 19.00% 65-74y 14.00% 75+ 14.30% DNA Percentage X2(6) = 2323.921, p<.001 Faisal Mahmood

Gender Male 28.60% Female 24.10% X2(1) = 389.078, p<.001 Faisal Mahmood

Ethnic Origin Bangladeshi 37.60% Pakistani 36.70% African 34.60% Other Black 34.20% Caribbean 31.50% Other Mixed 31.30% White and Black Caribbean 30.80% Other Asian 30.40% White and Black African 28.50% White Irish 28.20% Indian 27.10% White and Asian 26.80% Other White 26.10% White British 24.40% Chinese 6.50% X2(14) = 465.441, p<.001 Faisal Mahmood

Smoking Current smoker 23.70% Ex smoker 17.80% Never smoked 16.40% X2(2) = 130.438, p<.001 Faisal Mahmood

Types of session DNA Percentage Arrest Referral 60.90% Assessment 40.90% Individual Session 24.00% Care Plan Review 15.30% Healthcare Review Meeting Family Session 5.40% DNA Percentage X2 (5) = 7618.016, p<0.001 Faisal Mahmood

Employment Not in education or training or employment 62.50% Unemployed 28.00% Job Seekers Allowance 27.00% Work Programme or Training 19.80% Regular Employment 18.30% Unpaid voluntary work 15.70% Retired from work 15.40% Homemaker 14.80% Retired from paid work 10.80% X2(18) = 1547.811, p<0.001 Faisal Mahmood

Locations Site 1 32.70% Site 2 29.60% Site 3 27.80% Site 4 26.70% 26.00% Site 6 21.80% Site 7 21.00% Site 8 16.00% Site 9 13.20% Site 10 9.30% X2(9) = 3213.266, p<0.001 Faisal Mahmood

LOGISTIC REGRESSION Faisal Mahmood

Predictors of Non-Attendance Significant Predictors Not Significant Predictors Age Current Employment Status Accommodation Needs Parental Status Number of Children Living with Client Overall Discharge Reason Clinical Risk Levels Event Time Gender Smoking Status Pregnancy Status Dual Diagnosis Text Messages* (Only 12% sent sms) (p<.001) Faisal Mahmood

LOGISTIC REGRESSION Accommodation: Young Persons in settled accommodation were over five times more likely to not attend. Parental status: Clients who live with ‘some of their children’, clients where ‘none of the children with them’ and the clients who are not parent are more likely to not attend as compared to clients who have all the children living with them. Faisal Mahmood

LOGISTIC REGRESSION Age: 18-24 and 75+ years old are more likely to not attend as compared to other age groups. Employment: Clients on employment support allowance, economically inactive due to mental health and clients who are long term sick or disabled are more likely to not attend. Faisal Mahmood

LOGISTIC REGRESSION Overall discharge reason: Clients are more likely to complete their treatment in a successful manner if they attend their treatment appointments. Faisal Mahmood

LOGISTIC REGRESSION Health and wellbeing risk levels: Clients are more likely to not attend if they have high risk levels. Appointment times: Two appointment time slots 15.30-15.59 and 11.00-11.29 increase the likelihood of non-attendance. Faisal Mahmood

Appointment Times – High Attendance 11.30-11.59am event time reduced DNA by 74.5% 10.00-10.29am event time reduced DNA by 38.5% Out of hours (after 5pm) event times reduced DNA by 28.1%. Faisal Mahmood

Qualitative Study Method: Semi Structured Interviews Analysis: Framework Analysis Key research questions: What is the client’s subjective experience of not attending their appointment? What time was the decision taken by the client that the session could not be attended? For example, last minute, a day before, when the session was booked? What are the main reasons for clients’ non-attendance? Faisal Mahmood

Feedback: f.mahmood@newman.ac.uk Thank You Faisal Mahmood