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A targeted approach to reduce health inequalities through the use of Child & Adolescent Mental Health Services (CAMHS) Neighbourhood Profiles Dr Rachel A Harris, Research and Development Manager Scott Wilson, Senior Information Analyst Dr Annabelle Nicol, Assistant Psychologist

A targeted approach to reduce health inequalities through ......Profiles highlight population based trends and support comparisons at ... (2014). Improving attendance at child and

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Page 1: A targeted approach to reduce health inequalities through ......Profiles highlight population based trends and support comparisons at ... (2014). Improving attendance at child and

A targeted approach to reduce health inequalities through the use of

Child & Adolescent Mental Health Services (CAMHS) Neighbourhood Profiles

Dr Rachel A Harris, Research and Development Manager

Scott Wilson, Senior Information Analyst

Dr Annabelle Nicol, Assistant Psychologist

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Overview

Part of a wider study that aims to address inequalities by reducing DNAs in CAMHS in NHS GGC

Aim I – To identify potential risk factors for non-attendance at initial CAMHS appointments.

Methodology Phase 1 - Understand the current system and identify potential

interventions to pilot • Literature review - risk factors & non-attendance, impact of

non-attendance, understanding DNAs • Data from EMIS Web

NHSGGC CAMHS DNA Neighbourhood Profile Conclusions and next steps

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Inequalities & the use of CAMHS

A critical part of reducing health inequalities includes addressing the levels of access to and use of services. Yet: the risk of non-attendance is higher in the most deprived deciles

in Scotland (Campbell et al, 2015);

non-attendance or Did Not Attends (DNA) for initial CAMHS appointments is known to be high (Michelson & Day, 2014).

Non-attendance in NHS GGC CAMHS is higher in the most deprived quintile.

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The Impact of Non-Attendance

In an average month, 356 children and young people will be offered an initial CAMHS appointment in NHS GGC

53 will not attend and a further 15 will cancel

Children and young people risk conditions remaining untreated or worsening. The earlier children and young people receive mental health interventions, better

their emotional, behavioural, social and academic prospects. (Becker et al , 2011)

Impacts in short and long-term: half of all adult mental health disorders begin by the age of 15, rising to 75% by the age of 18 (Kessler et al, 2012; Kim-Cohen, et al, 2003).

ScotPHO estimate “Each outpatient appointment DNA costs NHS Scotland an estimated mean of £120” (Campbell et al, 2015).

Impact on clinician time, affects service waiting times, appointment slots cannot be reallocated. (Clemente et al 2006; Clouse et al 2017; Kazdin, 1996; Minty & Anderson, 2004).

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Understanding DNAs

Reasons why initial appointments are not attended: Structural Factors Service Factors Patient Factors Genuinely forgetting

Predictive factors : Male, younger (15-29), live in urban residences and in areas of

deprivation, mental health rather than physical health specialities - higher risk of missing first appointments (Campbell et al, 2015)

Amongst child populations: Previous non-attendance, the referrer, parental illness, maternal history

of depression, substance misuse or feeling too overwhelmed to prioritise appointment. (Calam et al, 2002; Harrison, 2004; Kapoor, 2012)

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NHSGGC Context – CAMHS DNAs

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NHSGGC CAMHS DNA Neighbourhood Profile

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Methodology

Data from EMIS Web (NHSGGC’s electronic children’s record system) used to understand service-side factors that affect DNAs within CAMHS

Operational data, including DNAs, was extracted resulting in

over 76,000 data points.

Postcodes used to map to ‘Intermediate

Zones’, roughly equivalent to

neighbourhood level

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Conclusions and Next Steps

CAMHS Neighbourhood Profiles show activity and performance data in far more detail than previously possible.

Profiles highlight population based trends and support comparisons at local level.

There is a link to deprivation, though not consistently across NHS GGC. We need to look across the range of administrative data to

understand DNAs Next steps Develop a theory of change around reducing DNAs Consult with children and families Pilot an intervention(s) to improve attendance.

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References I

Becker, K. D., Chorpita, B. F., & Daleiden, E. L. (2011). Improvement in symptoms versus functioning: how do

our best treatments measure up? Administration and Policy in Mental Health and Mental Health Services

Research, 38, 440-458.

Calam, R., Bolton, C., & Roberts, J. (2002). Maternal expressed emotion, attributions and depression and entry

into therapy for children with behaviour problems. British Journal of Clinical Psychology, 41, 213-216.

Campbell, K., Millard, A., McCartney, G., & McCullough, S. (2015). Who is least likely to attend? An analysis of

outpatient appointment ‘did not attend’ (DNA) data in Scotland. NHS Health Scotland.

Clemente, C., McGrath, R., Stevenson, C., & Barnes, J. (2006). Evaluation of a waiting list initiative in a child

and adolescent mental health service. Child and Adolescent Mental Health, 11, 98-103.

Clouse, K. M., Williams, K. A., & Harmon, J. M. (2017). Improving the No‐Show Rate of New Patients in

Outpatient Psychiatric Practice: An Advance Practice Nurse‐Initiated Telephone Engagement Protocol Quality

Improvement Project. Perspectives in Psychiatric Care, 53, 127-134.

Harrison, M. E., McKay, M. M., & Bannon, W. M. (2004). Inner-city child mental health service use: The real

question is why youth and families do not use services. Community Mental Health Journal, 40, 119-131.

Kapoor, V. (2012) ‘Did not attend’ (DNA) Audit on Appointments in Community Paediatrics: The Story Since

2006 (Abstract only). Annual Scientific Meeting of the British Association for Community Child Health, 9 & 10

October, Aston Business School, Birmingham.

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References II Kazdin, A. E. (1996). Dropping out of child therapy: Issues for research and implications for practice. Clinical

Child Psychology and Psychiatry, 1, 133-156.

Kazdin, A. E., Holland, L., & Crowley, M. (1997). Family experience of barriers to treatment and premature

termination from child therapy. Journal of Consulting and Clinical Psychology, 65, 453-463.

Kessler, R. C., Petukhova, M., Sampson, N. A., Zaslavsky, A. M., & Wittchen, H. U. (2012). Twelve‐month and

lifetime prevalence and lifetime morbid risk of anxiety and mood disorders in the United States. International

Journal of Methods in Psychiatric Research, 21, 169-184.

Kim-Cohen, J., Caspi, A., Moffitt, T. E., Harrington, H., Milne, B. J., & Poulton, R. (2003). Prior Juvenile

Diagnoses in Adults With Mental Disorder: Developmental Follow-Back of a Prospective-Longitudinal Cohort.

Archives of General Psychiatry, 60(7), 709–717. https://doi.org/10.1001/archpsyc.60.7.709

Kourany, R. F., Garber, J., & Tornusciolo, G. (1990). Improving first appointment attendance rates in child

psychiatry outpatient clinics. Journal of the American Academy of Child & Adolescent Psychiatry, 29, 657-660.

Minty, B., & Anderson, C. (2004). Non-attendance at initial out-patient appointments at a hospital-based child

psychiatric clinic. Clinical Child Psychology and Psychiatry, 9, 403-418.

Michelson, D., & Day, C. (2014). Improving attendance at child and adolescent mental health services for

families from socially disadvantaged communities: Evaluation of a pre-intake engagement intervention in the

UK. Administration and Policy in Mental Health and Mental Health Services Research, 41, 252-261.