Evaluations of the NHS Health Trainer Service

Transcription

Evaluations of the NHS Health Trainer Service
Health behaviour change among
users of NHS Health Trainer Services
Benjamin Gardner1,
James Cane1, Nichola Rumsey2 & Susan Michie1
1: University College London; 2: University of the West of England
3rd July 2012
This work was
undertaken as part
of a BPS DHP
consultancy to the
Department of
Health
(2003-2010)
Evaluations of the NHS Health Trainer Service
• 2007-09: data from hub leads (‘hub reports’)
• Yearly audits of workforce and clients
– Who are the HTs?
– Is the workforce growing?
– Who is using the HT service? (Wilkinson et al, 2007; D Smith et al, 2008)
• 2009: DCRS data
• Evaluation of service effectiveness
• Does behaviour change among users of the HT
service?
Questions
1) Who uses the HT service?
- Are we reaching ‘hard to reach’ clients?
2) Does (diet and activity) behaviour change
following use of HT service?
3) Do all clients benefit equally?
Data
• Drawn from DCRS
– Period: 1st April 2008 – 31st March 2009
– Data extracted from DCRS v2.4 by BPCSSA
• Final extraction for DCRS report: December 2009
• Final extraction for paper mid-2010
– Data recording on DCRS then non-compulsory
• At start of time period, estimated from hub report that 62% of
HTSs entered data into DCRS
• Paper accepted for publication in Dec 2011
Data availability
Drop-out bias?
• Setting PHPs:
– White clients (35%) and Asian clients (30%) more likely
to set PHPs than Black clients (25%)
– More PHPs set in least deprived quintile (42%) than
others (~36%)
• Pre-post HTS data availability:
– White clients (35%) more likely to have pre-post than
Asian (30%) or Black clients (27%)
– More data available in least deprived quintile (45%)
than others (~29%)
Measures
Pre- and post-HTS
- Baseline demographics
- Pre- and post-HTS:
• Behaviour measures
– BMI (height, weight)
– Self-reported behaviour (diet [snacks, fruit & veg],
activity [moderate/intensive sessions])
Results
1) Who uses the HTS?
• 3503 female (79%) (UK population, 2001 = 51% female)
• Typical age 36-45 years (22.4%) (UK 2001 = 19%)
• Deprivation:
–
–
–
–
–
Q1 (most deprived):
Q2
Q3
Q4
Q5 (least deprived)
1836 (43.2%)
1093 (25.7%)
688 (16.2%)
405 (9.5%)
230 (5.4%)
Results
1) Who uses the HTS?
• Ethnicity:
–
–
–
–
White
Asian
Black
Mixed or other
(UK 2001 = 93% White)
3647 (83.2%)
485 (11.1%)
175 (4.0%)
79 (1.8%)
Results
1) Who uses the HTS – and for what purpose?
• Weight status:
– Obese
– Overweight
– Normal weight
2717 (72.3%)
824 (22.4%)
218 (5.8%)
• PHP focus:
– Diet
– Physical activity
3346 (75.7%)
1072 (24.3%)
Results
2) Diet change following diet PHP
achievement
Outcome
Number of
clients
Pre-HTS
mean
Post-HTS
mean
% change
Daily fruit &
veg
(portions)
2376
3.08
5.23
70%
increase
No. of daily
fried snacks
1869
1.99
0.79
60%
decrease
BMI
3164
34.33
32.45
6%
decrease
Results
2) Activity change following
activity PHP achievement
Outcome
N
Pre-HTS
mean
Post-HTS
mean
% change
Weekly
moderate
sessions
921
3.06
4.77
56%
increase
Weekly
intensive
sessions
637
0.63
1.71
171%
increase
BMI
595
32.46
31.24
4%
decrease
3) Do all clients benefit equally?
• Ethnicity or deprivation differences?
– All clients
• Deprivation & BMI:
– Less BMI reduction in most deprived quintile vs all others (0.28 BMI
points)
– Diet:
• Deprivation & BMI:
– Less BMI reduction in most deprived quintile vs all others (0.24 BMI
points)
• Ethnicity & BMI:
– Less BMI reduction in Asian versus White clients (0.55 BMI points)
Conclusions
• HTS is reaching disadvantaged clients and
changing behaviour
• Effects similar across demographic groups
– But more PHPs set and more data recorded in less
deprived groups
Challenges and recommendations
• Missing data problematic
– Pre- and post-HTS behaviour data essential
• Reliance on self-report
– May overestimate behaviour change
– Ideally need objective measures, e.g. biochemical
verification, objectively measured weight
• Whether data self-report or objective should be
recorded
Challenges and recommendations
• Need to ensure continued fidelity to HTS as
originally devised
• Qualitative data needed
– Quantitative data allows for ‘birds eye view’ group-level
analyses
– Qualitative data engages with contextualised individual
experiences
– Would reveal ‘real-life’ benefits of HTS
Challenges and recommendations
• Qualitative data needed
– Brief interviews with clients/feedback from clients?
• How do clients feel they have benefitted?
– Written case studies?
• Description of individual client’s journey
– Need a DCRS repository for qualitative evidence
storage
Thank you
Acknowledgements:
Janet Andelin and Rachel Carse, Dept of Health
Jan Smith, CORE, UCL
Ertan Fidan & David Hopkinson, Birmingham
Primary Care Shared Services Agency
For a copy of the published paper, contact me at
b.gardner@ucl.ac.uk