Predicting Demand for Adult Social Care: Southampton Population Analysis

1. Predicting demand for services and adult social care I Intelligence & Strategic Analysis Team Southampton City Council I

2. Contents • Introduction to Southampton’s population, life expectancy and ill health (morbidity) • Modelling and forecasts • Population forecasts • Chronic condition forecasts • Chronic condition forecast index • Need for home care/physical support • Home care/physical support need requiring service provision • Further information

3. Southampton’s population, life expectancy and ill health (morbidity) Back to contents

4. Back to contents Southampton’s Population in 2017 In 2017 it was estimated that….. 253,989 people live in Southampton, and this is expected to grow by4.8%by2024to266,285 49,513 children and young people (aged 0-17) live in the city, and this is expected to grow by5.5%by2024to52,246 34,781 people aged 65+ live in the city, and this is expected to grow by14.5%by2024to39,810

5. Back to contents Life expectancy and ill health Increases in life expectancy over the last few decades mean that people are living longer However, lower levels of healthy life expectancy suggest, it is often with long term conditions and an extended period of poor health / disability Increases in life expectancy appear to have now plateaued, although the number of years spent in poor health continues to be significant

6. Back to contents Morbidity & Long Term Conditions This has clear implications for the demand for health and social care services According to the DoH, people suffering from LTCs represent……… • 69% of health care spend • 77% of inpatient bed days • 55% of GP appointments • 68% of outpatient & ED appointments Additional demand for adult social care services An ageing population will compound the problem

7. Back to contents Long Term Conditions – Multi-morbidity By age 85-89 approx. 30% have at least 6 LTCs By age 65-69 over a third (38%) have at least 3 LTCs 87% have no LTCs at age 0-4 By age 45-49 over half have at least 1 LTC

8. Back to contents Long Term Conditions – Multi-morbidity Multi-morbidity increases with age, BUT it also appears to be occurring earlier in life…..particularly for those in the most deprived areas Comparing 20% most deprived and 20% least deprived areas for prevalence of 3+ chronic conditions: • differences appear at an early age and gradually narrow (relatively) as the population ages • differences begin to appear in the early 20’s and peak between the mid-30’s and mid-40’s, where prevalence is more than double (2.2x)

9. Back to contents Need for local modelling / forecasts • In light of an ageing population, increases in morbidityand a reduction in resources, future projections of chronic conditions and how this translates into demand for services are needed • 2 areas of modelling; CCG and SCC perspectives have been considered • CCG – chronic conditions and long term support • SCC – adult social care by primary support reason • Two types of forecast • Level of underlying need in the population • Volume of need which may require service provision • All forecasts are based on Southampton resident population due to the nature of the readily available population forecasts

10. Southampton population forecasts Back to contents

11. Back to contents Available population forecast data • Population forecasts are the basis for all future modelling; there are two sets of population forecasts are available….. • Office for National Statistics (ONS) • 2016-based subnational population projections for local authorities and higher administrative areas in England (Table 2) (link) • Uses fertility and mortality rates to age on the population with adjustments for national and international migration • LA population available by age from mid-2016 to mid-2041 • Hampshire County Council (HCC) Small Area Population Forecasts (SAPF) • Extended 2017-based forecasts for Hampshire (link) • Rolls forward population from 2011 to 2017 by incorporating known births and deaths and known dwelling completions • Forecasts use local intelligence on future dwellings supply • LA population available by LSOA and age from mid-2017 to mid-2027 • HCC forecasts used up to 2027, then ONS projections from 2028 to 2038

12. Back to contents Southampton population forecast 2018-38 • Population change is most marked in the 65+ age group and this is where the biggest proportionate changes in demand will come from • Between 2018 and 2038, population estimated to grow by 9.5%; rising to 32% for 65+

13. Chronic condition forecasts Back to contents

14. Back to contents Chronic condition forecast methodology • Data sources used • GP data May 2017 (ACG tool - Southampton CCG) • 246,290 patients with a Southampton address • More than 20 conditions included in the dataset • diabetes, COPD, asthma, osteoporosis and many more… • Used to calculate prevalence of conditions by five-year age band 2017 • Combined with population forecasts by five-year age band to project forward; assuming prevalence remains the same • HCC, 2018 to 2027 • ONS, 2028 to 2038 • Gives forecast for the number of Southampton residents with chronic conditions for each year between 2018 and 2038

15. Back to contents Assumptions and limitations • Method assumes that age-related prevalence estimates remain the same in future, however… • We know prevalence of some LTCs are increasing • Where data was available and an increasing prevalence evident, alternative estimates were produced which attempt to account for the growth in morbidity based on historic trend data from QOF and HSE • Relies on accuracy of population projections which take into account births, deaths and known dwelling developments. However, they are subject to periodic revision • Two sets of population forecasts have been combined and these give slightly different answers • Resident rather than registered population • HCC population forecasts used for CCG and age group estimates and so these are limited to 2027

16. Back to contents Chronic conditions forecast index * Baseline data taken from Hospital Episode Statistics (HES) dataset

17. Back to contents Asthma forecasts Back to LTC index

18. Back to contents Heart failure forecasts Back to LTC index

19. Back to contents Learning disability forecasts Back to LTC index

20. Back to contents Learning disability forecasts – adjusted for increasing morbidity Back to LTC index • Local GP QOF data identified increasing prevalence of LD between 07/08-16/17 • Equivalent to 0.01% point increase per year…or an extra 0.28% points by 2038 • Applied to our model has a cumulative impact on the number of cases from 2018 baseline…. • 8.7% increase by 2020; was 2.1% • 21.0% increase by 2023; was 4.2% • 78.3% increase by 2038; was 7.5% • Caution is needed with these results • Increasing trend may be as a result of improved recording by GPs; rather than a true increase in prevalence • Uncertain how realistic it is to expect current trend to continue, but may provide ‘worse case’ scenario

21. Back to contents Frailty forecasts Back to LTC index

22. Back to contents Dementia (QOF) forecasts Back to LTC index

23. Back to contents Dementia forecasts – adjusted for increasing morbidity Back to LTC index • Local GP QOF data identified increasing prevalence of dementia between 07/08-16/17 • Equivalent to 0.02% point increase per year…or an extra 0.39% points by 2038 • Applied to our model has a cumulative impact on the number of cases from 2018 baseline…. • 11.5% increase by 2020; was 5.5% • 27.9% increase by 2023; was 12.6% • 104.8% increase by 2038; was 40.0% • Caution is needed with these results • Increasing trend may be as a result of improved recording by GPs; rather than a true increase in prevalence • Uncertain how realistic it is to expect current trend to continue, but may provide ‘worse case’ scenario

24. Back to contents Dementia related condition forecasts Back to LTC index

25. Back to contents Lower back pain forecasts Back to LTC index

26. Back to contents COPD forecasts Back to LTC index

27. Back to contents COPD forecasts – adjusted for increasing morbidity Back to LTC index • Local GP QOF data identified increasing prevalence of COPD between 07/08-16/17 • Equivalent to 0.04% point increase per year…or an extra 0.87% points by 2038 • Applied to our model has a cumulative impact on the number of cases from 2018 baseline…. • 8.3% increase by 2020; was 4.9% • 19.3% increase by 2023; was 10.4% • 60.3% increase by 2038; was 22.7% • Caution is needed with these results • Increasing trend may be as a result of improved recording by GPs; rather than a true increase in prevalence • Uncertain how realistic it is to expect current trend to continue, but may provide ‘worse case’ scenario

28. Back to contents Ischaemic heart condition forecasts Back to LTC index

29. Back to contents Bipolar disorder forecasts Back to LTC index

30. Back to contents Schizophrenia forecasts Back to LTC index

31. Back to contents Rheumatoid arthritis forecasts Back to LTC index

32. Back to contents Chronic renal failure forecasts Back to LTC index

33. Back to contents Hypertension forecasts Back to LTC index

34. Back to contents Hypertension forecasts – adjusted for increasing morbidity Back to LTC index • Local GP QOF data identified increasing prevalence of hypertension between 07/08-16/17 • Equivalent to 0.03% point increase per year…or an extra 0.64% points by 2038 • Applied to our model has a cumulative impact on the number of cases from 2018 baseline…. • 5.2% increase by 2020; was 4.6% • 11.3% increase by 2023; was 9.9% • 28.3% increase by 2038; was 22.2% • Caution is needed with these results • Increasing trend may be as a result of improved recording by GPs; rather than a true increase in prevalence • Uncertain how realistic it is to expect current trend to continue, but may provide ‘worse case’ scenario

35. Back to contents Age-related macular degeneration forecasts Back to LTC index

36. Back to contents Glaucoma forecasts Back to LTC index

37. Back to contents Hyperthyroidism forecasts Back to LTC index

38. Back to contents Immunosuppression forecasts Back to LTC index

39. Back to contents Parkinsons disease forecasts Back to LTC index

40. Back to contents Seizure disorders forecasts Back to LTC index

41. Back to contents Diabetes forecasts Back to LTC index

42. Back to contents Diabetes forecasts – adjusted for increasing morbidity Back to LTC index • Health Survey for England identified increasing prevalence of diabetes between 2009-2016 • Equivalent to 0.13% point increase per year…or an extra 2.65% points by 2038 • Applied to our model has a cumulative impact on the number of cases from 2018 baseline…. • 9.1% increase by 2020; was 4.0% • 21.5% increase by 2023; was 8.6% • 72.2% increase by 2038; was 17.6% • Caution is needed with these results • Uncertain how realistic it is to expect current trend to continue, but may provide ‘worse case’ scenario

43. Back to contents Osteoporosis forecasts Back to LTC index

44. Back to contents Osteoporosis forecasts – adjusted for increasing morbidity Back to LTC index • Local GP QOF data identified increasing prevalence of osteoporosis between 12/13-16/17 • Equivalent to 0.02% point increase per year…or an extra 0.30% points by 2038 • Applied to our model has a cumulative impact on the number of cases from 2018 baseline…. • 5.9% increase by 2020; was 4.4% • 13.3% increase by 2023; was 9.6% • 39.7% increase by 2038; was 24.1% • Caution is needed with these results • Increasing trend may be as a result of improved recording by GPs; rather than a true increase in prevalence • Uncertain how realistic it is to expect current trend to continue, but may provide ‘worse case’ scenario

45. Back to contents Current smoker forecasts Back to LTC index

46. Back to contents 3 or more chronic conditions forecasts Back to LTC index

47. Back to contents 5 or more chronic conditions forecasts Back to LTC index

48. Back to contents Falls leading to hospital admission (over 65s) forecasts Back to LTC index

49. Need for home care / physical support Back to contents

50. Back to contents Forecasting need for adult social care support • Need defined as being unable to carry out the activity on own i.e. • “I can only do this with help from someone“ • or • "I cannot do this“ 1 Bolton, J. Predicting and managing demand in social care. Discussion paper. April 2016. Oxford Brooks University Institute of Public Care. • Need defined as unable to carry out 5 or more activities of daily living (ADL) 1 • National data is available from Health Survey for England (HSE)