EXCESS COSTS ADDITIONAL ANALYSIS

1. EXCESS COSTS ADDITIONAL ANALYSIS Presentation to NRAC 26 February 2007 Matt Sutton HERU David Bailey ISD Keith MacKenzie ASD

2. Introduction • First draft of Technical addendum • Two parts – Community and Hospital • Consider papers in conjunction with the original HERU report • No HB level adjustment yet • Looking for NRAC’s views on options and methodology/analysis • Decide what elements should be taken forward to the final formula

3. Research Objectives The contract with HERU specifies three elements to this work 1. Written responses to the peer review (done) and points raised in the consultation (pending/to be covered by technical addendum) 2. Development of the Hospital adjustment 3. Development of the Community adjustment Today’s papers represent the first drafts on parts 2 and 3 of this work The deadline for completion of this work is 28 March 2007

4. Format of presentation • David Bailey will explain the Community work and his proposals for how the model should be changed • Matt Sutton will explain the technical work on the Hospital adjustment • Keith MacKenzie will set out the options for the Hospital adjustment with the pros and cons • Discussion and questions • Agreement on the Community and Hospital adjustments

5. COMMUNITY ADJUSTMENT Explanation of the additional work by David Bailey ISD

6. Questionnaire Response • 35 – 40 Responses (30 included here) • Five questions: 1. Contact duration 2. Within settlement travel time 3. Island contacts 4. Base locations 5. Proportion of home-visits

7. Community Nursing Physiotherapy Community Mental Health Teams Occupational Therapy Speech & Language Therapy Midwifery Arts Therapy Dietetics Community Learning Disabilities Teams Intensive Community Support Services Podiatry Services Providing Feedback

8. General Comments “It’s nice to see this finally being addressed!” “…can you make allowance for the changing models of care delivery with older people and centralisation of specialist services which will require more care to be delivered locally. In the majority of workforce plans we see this as an area of growth in demand.”

9. A Central Theme “…. grave concerns … the model … does not differentiate enough between rural and urban. It also does not differentiate between specific services. … This is a fundamental flaw and the assumptions are therefore grossly over or underestimated.” “…more account needs to be taken of the higher proportion of home-visits in rural areas.” “An island locality has different needs to urban/rural areas.” “Physiotherapists shouldn't be lumped in with District Nurses.” “Community Occupational Therapy is not clinic based … sessions are 1-4 hours duration The assumptions here don't reflect this.”

10. 1. Average Contact Duration • 16 thought our assumption reasonable • 14 thought our assumption too short • Community Mental Health Teams • Art Therapy • Intensive Community Support Services • Occupational Therapy • Physiotherapy Many Physios work with people with mental health difficulties. Contact duration depends on patient need and capability.

11. Average Contact Durations Feedback from the ‘therapeutic’ services The model can be revised to allow inter-service variation

12. 2. Within Settlement Travel Time • 7 thought 5 minutes was reasonable • 5 misinterpreted the question • 18 thought 5 minutes too short • Alternatives were 10 – 20 minutes

13. Within Settlement Travel Time “…rarely managed less than 10 minutes” “10 min would be fairer.” “Even within the semi-urban area it can be 15-20 mins. 5 mins does not consider parking in busy areas.” “No, Seems a significant underestimate.” “Not at all. When I was working in a city I initially tried to use this figure when scheduling appointments and ended up with no lunch hour and usually finishing work well after 18.00! … When I actually recorded the time spent it averaged at around twenty minutes!”

14. Traffic problems Roadworks Parking Congestion Time of Day Single-track roads Tourist traffic Adverse weather Poor public transport Patient-care decisions Speed calming Personal safety Farm vehicles One way systems Lift Maintenance Paperwork Within Settlement Travel Time

15. Revisions to the Model • Within settlement travel time increased to 20 minutes for ‘Primary Cities’ and ‘Urban Settlements’ • Increased to 15 minutes in other areas

16. 3. Island Contact Time • 12 responses • 7 thought 120 minutes was reasonable • 5 thought it unreasonable • The Main Influences: • Dependence on ferries / Check-in time • Adverse weather / Tides “For 8 consecutive weeks one respondent from Argyll & Clyde had 2-3 hours added to their journey by adverse weather and tides.”

17. Island Contact Time • The feedback is island specific and shows a diversity of experience • The responses appear to neglect the possibility of multiple visits in a single trip • A recipient who suggested that 120 minutes was an underestimate also suggested 30-40 minutes for each patient contact The original model assumption is retained unchanged.

18. 4. Base Location • 16 respondents disagreed • Some confused the settlement population the assumption is based on with their own practice populations • The group who disagree are similar to the ‘therapeutic’ group suggesting a longer contact duration

19. Those Who Disagreed • ICSS • Physiotherapy • Dietetics • Midwifery • Community Learning Disabilities Team • Some CMHT staff • Some Speech & Language Therapists • Some Occupational Therapists

20. The model A base location Typically the base is a settlement of 10,000 Staff work full-time The Feedback No base location A much greater population is served Multiple clinics are staffed for short periods The Therapeutic Services The feedback could indicate failure in communicating the model’s assumptions. In which case they can be retained.

21. 5. Home-visit Proportion • Responses varied with speciality • Those who disagreed suggested new figures

22. Are Home-visit Levels Constant? • 9 Yes • 21 No, rural areas have more home-visits • Two main reasons: • Lack of adequate public transport • Scarcity of suitable clinic facilities

23. Revisions to the Model • Lack of adequate public transport • Could be seen as a trend to increasing home-visits with rurality • Scarcity of suitable clinic facilities • Could be a seen as a step-increase in home-visits with rurality

24. Proposals for the Revised Model

25. Comparison For Health Visitors

26. Next Steps • Incorporate additional responses • Reconcile service types to Cost Book • Use adopted age-sex weights to estimate expected demand for each Output Area • Aggregate to Board level

27. Hospital analysisMatt Sutton HERU

28. Extension to hospital analysis • Avoid potential double-counting by considering rurality and MFF/location factor simultaneously • Extend model to examine population characteristics (age, deprivation and ethnicity) • Consider continuous specification of remoteness and rurality to avoid ‘cliff-edges’

29. Method development • Same local to national average cost ratios • Population variables: • % population aged 65+, 75+ and 85+ • SIMD 2006 income domain score • % black and ethnic minority groups • MFF and location factors attached to hospital locations by LA • Significance testing allows for clustering by hospital

30. Continuous version of SEURC • Settlement size (population) • Highly skewed so search for best-fitting power function • Drive time to nearest urban settlement (>10,000 population) • Island location = travel over water to nearest urban settlement

31. Effects of input price indices • Table 4.2 on page 10 of draft addendum • MFF not significant (highly negative for LD) • Location factors positive and significant for acute and outpatients (LD highly negative)

32. Original models • Table 4.1 on page 9 of draft addendum • Not significant for acute and LD • Only significant at p=0.07 for outpatients • Significant and consistent for maternity and inpatient mental health • Significant for GLS but remoteness inconsistent

33. Full multivariate models • Each model contains several insignificant factors • Population characteristics insignificant and inconsistent • MFFs not significant

34. Alternative model - acute • Only significant predictor of acute care costs

35. Alternative model - outpatients • Influence of location factor is large • Inclusion of ‘mainland very remote’ avoids under-prediction

36. Alternative models - maternity • Little to choose between all models in explanatory power • Individual variables not significant in these models

37. Alternative models – mental health • Continuous specification offers best explanatory power

38. Alternative models – GLS • Categorical specification offers best explanatory power • Not as good as original model but more consistent

39. Alternative model – LD • Only significant predictor of LD costs

40. Options for the Hospital adjustment • HERU examined a number of models • Some were rejected as the variables did not significantly affect unit costs (e.g. staff MFF) • The Options set out in the paper are those which HERU felt offered a combination of • Goodness of fit • Face validity • Statistical significance

41. The Options There are three options for the Hospital adjustment:- • Use the SEURC categories – effectively this is the approach set out in the original report • Use the best model for the each type of service (care programme?) – this would mean using the model which gives us the best statistical fit • Use the continuous measure of remoteness Arguably there is a ‘fourth’ option which would be to use a combination of all the approaches based on a judgement about what is appropriate for each care programme

42. Option 1 – SEURC categories • The approach used in the original HERU report. • Questions raised about it in consultation which led to this research being commissioned:- • Categories are too wide to reflect the differing needs of small groups of population • Unexpected Primary Cities result • Doesn’t take account of variation in input prices • Doesn’t take account of other population characteristics (e.g. deprivation

43. Pros of Option 1 Pros • Practicality – in terms of running the formula this is the most straightforward, and would be the easiest for ISD to update each year • Transparency – the SEURC categories are published and (relatively) easy to explain

44. Cons of Option 1 • Relevance/Face validity - The further analysis highlights that the costs in Acute and Outpatients are not significantly related to urban-rural category • Face validity – By reverting to the original proposals, we would need to explain why we had apparently ignored the concerns raised about SEURC in consultation. Though we can now say that we have given other options a thorough examination

45. Option 2 – Best ‘fitting’ model • This approach would involve selecting the approach that gave us the best statistical fit for each care programme. • This would mean choosing the approach with the greatest explanatory power (see figures in ‘red’ in the following table)

47. Pros of Option 2 • Objectivity – The resulting adjustment would offer the best statistical fit available with the data used • Face validity – The model has been changed to reflect concerns raised in consultation, so now where the SEURC categories do not appear appropriate, alternative approaches have been used that better reflect the position for each care programme

48. Cons of Option 2 • Practicality – This would be more complex for ISD to update – it effectively uses a mixture of the original approach and the alternatives approaches • Transparency – By moving away from one categorisation, the adjustment will be harder to explain to Health Boards, the Minister, etc

49. Option 3 – Continuous measure of remoteness This approach aims to resolve the issue of the SEURC categories not being an ideal ‘fit’ for health services. It uses the variables that underlie the index to give a continuous classification

50. Pros of Option 3 • Practicality – By using the variables that underlie the SEURC, the data required should be relatively easy for ISD to obtain each year • Objectivity – It provides a better fit for three of the care programmes (maternity, inpatient mental health, learning disabilities) than the original SEURC categories would do • Equity – By using a continuous classification, this model contains fewer ‘cliff edges’