Trend in use of health care services and long term care Results of AGIR - WP 2 and WP4A Dr. Erika Schulz.

Trend in use of health care servicesand long term careResults of AGIR - WP 2 and WP4A

Dr. Erika Schulz

Erika Schulz10.03.2005

Life expectancy, morbidity and use of health and long term care services

WP2 WP 4 Part A Current situation Life expectancy - Estimations

Living longer

Morbidity - PopulationBetter health Size, age-structure

Use of health care servicesUse of long term care


Presentation of the results of– WP2, which deals with the current situation in the use of

health care and long term care services, and the connection between long term care giving at home and employment of women, and

– WP4 Part A, which deals with two different projection methods to estimate the development of the use of health and long term care services:• Projection method A, which shows the influence of

demographic development without changes in health status of the population on utilisation and

• Projection method B, which shows the influence of both – demographic development and changes in health status of the population on utilisation.


WP 2 – proceeding (I)– The first step was to collect all available data about the

current use of health and long term care services by age-groups and the trends in the past from our participants covering eight EU-countries:• Belgium, Denmark, Finland, France,• Germany, Netherlands, Spain and United Kingdom

– With these data it was possible to show the connection between age and use of health care services and long term care in institutions and at home.

– The advantage of the data is that they inlcude the whole population, the disadvantage is that they do not differentiate between the different health status of the population.


WP 2 – proceeding (II)– Therefore, in a second step the European Community

Household Panel (ECHP) was used to analyse the health care utilisation by age and health status,

– and to show the connection between care giving at home and the labour force participation of women.

– The disadvantage of the ECHP is, that this household panel covers only persons aged 16+ and provides no information about long term care giving in institutions and the need for long term care at home.

– To get an idea of the amount of people in need for long term care the „severely hampered persons who have to cut down things they usually do due to disability“ were used as a soft proxy.


WP 2 – data from participants– Hospital utilisation (admissions and length

of stay) (8 countries)– Contact with doctors ( 7 countries)– Long term care giving in institutions (6)– Long term care giving at home (4)– Household/family composition as a

determinant of long term care giving at home (up to 7) and

– Labour force participation as a determinant of long term care giving at home (5).


Hospitalised persons per 1000 inhabitants - Both sexes

0

100

200

300

400

500

600

0 - 4 5 - 14 15 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 - 74 75 +Age-groups

Rat

es

Belgium 1998 Denmark 1999 France 2000 Germany 1999Netherlands 1999 Spain 1999 Great Britain 2000


Hospitalised persons per 1000 inhabitantsMen

0

100

200

300

400

500

600

700

0 - 4 5 - 14 15 - 24 25 - 34 35 - 44 45 - 54 55 - 64 65 - 74 75 +Age-groups

Rat

es

Belgium 1998 Denmark 1999 Germany 1999 Netherlands 1999 Spain 1999 Great Britain 2000


Length of hospital stay 1999

0

2

4

6

8

10

12

14

16

unter 1 1-5 5-15 15-25 25-35 35-45 45-55 55-65 65-75 75 u.ä.

Age-groups

Day

s

Germany Netherlands Belgium Spain (1997)France (2000) England (1998/9) Denmark (1999)


Trends in hospital utilisationChanges in hospital Length of hospital stayadmissions/dischargesPeriod Changes Period Changes

1991-1998 1991-2000

Denmark 1991-2001 1991-2001

Finland 1991-2001 1991-2001

France 1998-2000 -

Germany 1993-1999 1993-1999

Netherlands 1993-2000 1993-2000

Spain 1990-1999 1990-1999

United Kingdom 1990/1-2000/1 1990/1-2000/1(England)

Country

Belgium


Hospital days per capita - GermanyHospital days per capita

0

5

10

15

20

25

30

35

40

45

0-24 25-34 35-44 45-54 55-64 65-74 75+

age-groups

day

s s

pen

t in

a h

os

pit

al

survivors

decedents in their last year of life

decedents in their second year before death

decedents in their third year before death average


People receiving long-term care in institutions per 1000 inhabitants in 2001

0

100

200

300

400

500

600

0 - 59 60 - 79 80 - 89 90+Age-groups

Ra

tes

Germany Finland Belgium Netherlands 2000 France 1998 Denmark 2000


People receiving long-term care at home per 1000 inhabitants in 2001

0

50

100

150

200

250

300

350

0 - 60 60 - 79 80 - 89 90+Age-groups

Ra

tes

Germany Finland Belgium


Trends in need for long-term care in institutions and at home

Care giving in institutions Care giving at homeChanges in prevalence rates Changes in prevalence ratesPeriod Changes Period Changes

1996-2001 1998-2001

Finland 1995-2001 1995-2001

Germany 1997-2002 1997-2002

Netherlands 1996/7-1999/2000

Denmark 1991-2001 1996-1998

Country

Belgium


WP 2 – data from ECHP– Hospital utilisation (admissions and length of stay) – Determinants of hospital utilisation (beside age, sex and

health status also education, income and marital status)– Contact with doctors (GP, SP; DE)– Severely hampered persons who have to cut down things

they usually do due to longstanding illness or disability– Characteristics of people looking after old and disabled

persons in the same household or elsewhere, in particular the employment status of people looking after old persons

– Determinants of long term care giving at home (beside age, sex and employment status also health status, family status and income)


Share of hospitalized persons by age-groups and health status in the EU 2001

0

5

10

15

20

25

30

35

15 - 29 30 - 44 45 - 59 60 - 69 70 - 79 80+Age-groups

in %

Very good/ good Fair Bad/ very bad


Share of hospitalized people in selected EU-countries 2000/2001

0

5

10

15

20

25

30

35

40

45

Belgium Denmark Finland France Germany Netherlands Spain UnitedKingdom

in %



Mean value of hospital days of inpatients by age-groups and health status in the EU 2001

0

5

10

15

20

25

15 - 29 30 - 44 45 - 59 60 - 69 70 - 79 80+Age-groups

Days



Mean value of hospital days in selected EU-countries 2001

0

5

10

15

20

25

30

Belgium Denmark Finland France Germany Netherlands Spain UnitedKingdom

Days



Coefficient T Significance Coefficient T Significance

Absolute term 3,011 27,917 0,000 12,682 13,680 0,000 Age 0,015 10,445 0,000 0,064 4,660 0,000 Women -0,188 -4,074 0,000 -0,333 -0,698 0,485 Good Health -1,731 -42,126 0,000 -6,270 -17,108 0,000 Low education -0,292 -7,784 0,000 -0,936 -2,402 0,016 Married 1,643 19,352 0,000 3,443 6,785 0,000 Income 0,000 -4,912 0,000 0,000 -2,049 0,041

*) Without Luxembourg and Sweden.Source: ECHP.

2001

Regression of hospital days - EU-countries 2001

Hospital days per inhabitant Hospital days per inpatient


Share of severely hampered persons by health status in EU-countries

0

10

20

30

40

50

60

70

0 - 29 30 - 44 45 - 59 60 - 69 70 - 79 80 +

Age-groups

in %

bad/very bad health

totalfair health

good/very good health


Share of severely hampered persons in participating countries 2000

0

5

10

15

20

25

30

35

40

45

50

0 - 29 30 - 44 45 - 59 60 - 69 70 - 79 80 +

Belgium Denmark Finland France Germany Netherlands Spain UK


Normallyworking

15 - 29 1,2 2,2 1,8 3,3 4,7 0,0 1,6 1,5 2,5 1,8 1,730 - 44 2,3 5,7 4,0 3,9 5,9 6,0 3,6 3,1 5,5 8,4 4,145 - 59 5,6 12,1 8,6 10,1 9,0 9,3 12,8 7,1 9,4 13,5 9,060 - 69 6,9 10,1 8,5 4,8 9,2 6,9 11,0 5,8 - 9,0 8,670 - 79 5,3 7,7 7,4 10,6 6,0 4,8 7,7 - - 6,6 6,6

80 + 5,5 4,8 9,0 0,0 5,1 2,7 4,2 - - 5,0 5,1

Total 3,8 7,2 6,5 6,3 7,6 5,1 3,1 - - - 5,5

1) EU (15) without Luxembourg and Sweden.- Source: ECHP.

Proportion of people looking after old persons in the EUin %

Men Women

Sex Employment statusAge-

groupsNever

married

Marital statusTotalUnem-

ployedInactiveMarried

Sepa-rated

Di-vorced

Wi-dowed


Age- Share ofgroups Men Women Total Women Men Women Total

15 - 29 7,1 6,7 6,8 66,6 7,3 15,5 12,730 - 44 17,7 21,6 20,4 72,1 11,0 16,5 15,045 - 59 35,5 39,6 38,3 70,2 10,5 19,8 17,160 - 69 22,2 17,8 19,2 62,9 16,5 24,5 21,670 - 79 12,9 10,9 11,6 64,3 20,4 26,6 24,5

80 + 4,6 3,3 3,7 60,1 21,0 29,5 25,8

Total 100,0 100,0 100,0 67,9 13,2 20,6 18,3

*) Without Luxembourg, Sweden.Source: ECHP.

Age-structure Mean value of care giving hours

Characteristics of care givers in the EU


Coefficient T Significance

Absolute term 16,2980 9,4110 0,0000Age 0,1210 4,4580 0,0000Men -5,3790 -6,9430 0,0000Good Health -3,1140 -5,2110 0,0000Low education 4,2640 6,2270 0,0000Married 0,3220 0,3180 0,7510Employed -5,1310 -8,1250 0,0000Inactive 3,9360 6,2610 0,0000Income 0,0000 5,0320 0,0000

*) Without Luxembourg, Sweden and Germany.Source: ECHP.

Regression of hours looking after old persons - EU 2001


WP 4A – proceeding (I)– The task of WP 4 Part A was to estimate the

health care utilisation taking into account the results of WP 1 and WP 2.

– To meet this task two projection methods were used:• Method A: The country specific utilisation data

collected from our participants were combined with two population scenarios. This projection method shows only the impact of demographic change and increasing life expectancy on health and long term care utilisation, but includes the whole population and long term care giving in institutions.


WP 4A – proceeding (II)

Method B: The ECHP data, which are differentiated by age-groups and health status, were combined with two population scenarios and two health scenarios. This projection method shows the impact of demographic change, increasing life expectancy and changes in the health status of the population on health care utilisation, but includes only the population aged 16+ in private households and provides no information about long term care giving in institutions.

Additional the development of potential care givers was calculated.


Demographic scenarios– As one scenario the EUROSTAT baseline scenario

was used and CPB created three additonal scenarios with higher life expectancies: the living longer low scenario, the living longer middle scenario and the living longer high scenario.

– In WP 4 Part A the baseline scenario and the living longer high scenario were used. Latter reduces the mortality rates of people aged 20 to 90 by 50 % in gradual steps until 2050 (additional to the reduction of mortality in the baseline scenario). The following table shows the assumptions.


1999 2050 1999 2050 1999 2050Living

longer high

Belgium 1,5 1,8 78,2 83,0 87,7 10978 15000Denmark 1,8 1,8 77,0 81,4 86,7 10876 10000Finland 1,7 1,7 77,9 82,9 87,8 5499 5000France 1,7 1,8 79,2 83,8 88,5 50230 50000

Germany 1,4 1,5 78,3 82,9 87,8 192000 200000Netherlands 1,7 1,8 78,6 81,5 86,7 32594 35000

Spain 1,2 1,5 79,0 82,4 87,4 30257 60000United Kingdom 1,7 1,8 78,2 82,9 87,9 175000 70000

EU (15) 1,5 1,8 78,0 82,6 87,4 637254 622000

Sources: EU-EPC 2000 (Baseline scenario); Pellikaan/Westerhout 2004 (Living-longer scenarios).

scenarioEurostat-baseline scenario

CountriesEurostat-baseline

Assumptions of population forecasts

Fertility rates MigrationLife expectancy


Countries0 - 14 15 - 59 60 - 74 75 - 89 90+ Total 0 - 14 15 - 59 60 - 74 75 - 89 90+ Total

Belgium 86 85 118 196 321 99 86 85 123 244 566 104Denmark 89 93 129 189 232 104 89 94 137 243 432 110Finland 77 81 131 194 410 95 77 82 137 242 718 101France 86 89 136 216 313 105 86 90 142 259 498 110

Germany 76 77 109 209 309 92 76 78 115 265 542 98Netherlands 97 97 143 209 308 110 97 98 151 273 594 116

Spain 72 68 124 222 351 88 72 69 131 275 611 94United Kingdom 84 91 137 193 275 104 84 91 143 245 483 109

Total 82 83 125 208 307 98 82 84 131 259 528 104

EU (15) 80 81 121 208 313 96 80 81 127 259 536 102

Sources: EU-EPC 2000 (Baseline scenario); Pellikaan/Westerhout 2004 (Living-longer scenarios).

2050

Age-groups

1999 = 100Population development by age-groups

Baseline scenario Living-longer-high scenario


WP 4A – Results of projection method A

• Projection of hospital admissions and of the total number of hospital days

• Projection of the number of contacts with a doctor

• Projection of long term care recipients in institutions

• Projection of long term care recipients at home– All projection were made for two demographic

scenarios, namely the baseline scenario and the living longer high scenario


Countries 1999*) 2020 2050 2020 2050

Belgium 14 17 19 17 22Denmark 6 7 8 7 9Finland 15 19 23 21 28France 65 76 80 77 87

Germany 170 201 207 208 238Netherlands 13 17 20 18 23

Spain 39 45 51 47 60United Kingdom 59 68 84 72 103

Total 380 451 491 468 569

*) France and United Kingdom = 2000.Source: Calculations by DIW.

Baselinescenario

Living-longer-highscenario

Development of hospital daysin million days


Countries0 - 14 15 - 64 65 - 74 75+ Total 0 - 14 15 - 64 65 - 74 75+ Total

Belgium -7 -7 17 105 35 -7 -6 24 168 58Denmark -12 0 32 93 35 -12 1 43 160 59Finland -23 -15 37 109 55 -23 -15 45 175 90France -14 -4 35 119 22 -14 -3 42 174 33

Germany -23 -18 22 118 22 -23 -17 29 188 40Netherlands -2 8 48 130 49 -2 10 58 220 77

Spain -29 -21 32 138 32 -29 -20 40 214 54United Kingdom -14 -3 36 114 42 -14 -2 45 200 73

Total -18 -12 29 118 29 -18 -11 36 191 50*) France and United Kingdom = 2000.Source: Calculations by DIW.

Age-groups

Changes within the age-groups in %Development of hospital days in the age-groups 2050/1999



Age-structure of hospital days in eight EU-countries

7,1 4,6 3,9

48,0

32,7 28,5

18,9

18,9 17,2

25,9

43,9 50,4

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 999 2050 Base 2050 Living longer

0 - 14 15 - 64 65 - 74 75+


Development of long-term care recipients in institutions - Baseline scenario2001 = 100

100

150

200

250

300

350

400

2010 2020 2030 2040 2050Years

Belgium Denmark Finland France Germany Netherlands Total


Development of long-term care recipients in institutions - Living-longer-high scenario

2001 = 100

100

150

200

250

300

350

400

2010 2020 2030 2040 2050Years

Belgium Denmark Finland France Germany Netherlands Total


Countries

0 - 591) 60 - 79 80+ Total 0 - 591) 60 - 79 80+ Total

Belgium 85 129 264 195 85 140 385 262Finland 81 135 255 181 82 146 366 237 France 88 144 280 198 89 154 396 257Germany 81 121 269 178 81 132 399 240

Total 83 129 272 185 83 139 396 246

1) France = 15-59 years.Source: Calculations by DIW.

Age-groups

2001 = 100Long-term care recipients at home by age-groups 2050



Countries Contacts with

a doctor 2)

Belgium 99 135 115 240 195Denmark 104 135 - 175 -Finland 95 155 98 201 181France 105 122 1) - 230 3) 198 3)

Germany 92 122 - 212 178Netherlands 110 149 117 233 -

Spain 88 132 100 - -United Kingdom 104 142 1) 109 - -

Belgium 104 158 128 352 262 Denmark 110 159 - 244 -Finland 101 190 104 279 237 France 110 133 1) - 314 3) 257 3)

Germany 98 140 - 306 240 Netherlands 116 177 127 358 -

Spain 94 154 1) 110 - -United Kingdom 109 173 117 - -

1) 2000 = 100.- 2) 2001 = 100.- 3) Only 15+ years.Source: Calculations by DIW.

Living-longer-high scenario

1999 = 100Population, health care utilisation and long-term care recipients 2050

Baseline scenario

institutionsPopulation Hospital days

LTC 2)

at home

LTC 2)


WP 4 Part A projection method B

Demographic constant proportion of people increasing proportion of people scenarios in good/fair/bad health in good healthBaseline baseline scenario baseline scenario with scenarios with constant health improvements in health

Living-longer-high living-longer scenario living-longer in scenarios with constant health better health scenario

Health scenarios


good1) fair bad2) good1) fair bad2)

15-29 0,85 0,13 0,03 0,87 0,12 0,0130-44 0,77 0,19 0,05 0,79 0,19 0,0245-59 0,61 0,29 0,09 0,64 0,30 0,0760-69 0,43 0,39 0,18 0,48 0,41 0,1170-79 0,32 0,43 0,26 0,35 0,45 0,2080+ 0,24 0,42 0,34 0,26 0,44 0,30

1) People in good and very good health.- 2) People in bad and very bad health.Sources: ECHP; calculations by DIW.

constant health status improving health

People aged 15+ by health status 2001, 2050

20502001Age-

groupsShare of people in ... health

EU (15 without Lux, Swe)


good health fair health bad health good health fair health bad health

2001 197 78 32 64 25 102050

Baseline-constant health 175 87 41 58 29 14

Baseline-improving health 184 90 30 61 30 10

Living-longer-constant health 181 96 48 56 30 15Living-longer-better health 190 99 35 59 31 11

*) Without Luxembourg and Sweden.Source: Calculations by DIW.

EU-Population aged 15+ by health status in 2001 and 2050

Proportion in %People aged 15+ in million inScenarios


WP 4A – Results of projection method B

• Projection of hospital admissions and of the total number of hospital days

• Projection of the number of contacts with a general practitioner• Projection of severely hampered persons • Projection of persons providing long term care at home

– All projection were made for two demographic and two health scenarios, namely the baseline scenario with constant health, the baseline scenario with improving health, the living longer scenario with constant health and the living longer in better health scenario, and for the eight participating countries, for these countries altogether and for the EU.


Hospital bed days by health status 2050 in the EU 1)

2001 = 100

104

110114

121

128

134

147

154

135

101

156

120

127

113

145

131

100

110

120

130

140

150

160

Baseline scenario Baseline scenario with improvinghealth

Living-longer-high scenario Living-longer better healthscenario

good health fair health bad health total


good fair bad total good health fair health bad health

2001 67 111 172 350 19 32 492050

Baseline-constant health 70 142 232 444 16 32 52

Baseline-improving health 75 147 169 391 19 38 43

Living-longer-constant health 76 163 269 508 15 32 53Living-longer-better health 82 169 200 451 18 38 44


EU - total bed days of people aged 15+ by health status in 2001 and 2050

Proportion in %Scenarios

Bed days in million of people in...health


good fair bad total good health fair health bad health

2001 2 7 16 26 8 29 632050

Baseline-constant health 3 10 22 34 8 28 64

Baseline-improving health 3 10 16 29 10 35 56

Living-longer-constant health 3 12 26 40 7 29 64Living-longer-better health 3 12 19 34 9 34 57


EU - severely hampered persons aged 15+ by health status in 2001 and 2050

Proportion in %Scenarios

Severely hampered persons in million


Countries Hospital Contacts Hampered

days with a GP 1) persons 2)

Baseline-constant health 99 114 127 114 135

Baseline-improving health 99 108 113 109 116

Living longer-constant health 106 128 145 126 157

Living longer-better health 106 120 131 121 1371) GP= General Practitioner.- 2) Severely hampered persons who have to cut down things they usually do due to chronic illness or disability.3) Without Luxembourg and Sweden.Source: Projections by DIW.

Population 15+

Hospital admissions

2001 = 100Population (15+), health care utilisation and severely hampered persons 2050


Countries Hospital Contacts Hampered

days with a GP 1) persons 2)

Baseline-constant health 0 0 0 0 0

Baseline-improving health 0 -7 -13 -5 -19

Living longer-constant health 7 13 18 12 22

Living longer-better health 7 6 4 7 21) GP= General Practitioner.- 2) Severely hampered persons who have to cut down things they usually do due to chronic illness or disability.3) Without Luxembourg and Sweden.Source: Projections by DIW.

2001 = 100 - Difference to baseline constant health scenario

Population (15+), health care utilisation and severely hampered persons 2050

Population 15+

Hospital admissions


2001Baseline im- Living-longer- Living-longer

proving health high scenario better health

15-29 1203 954 932 954 93330-59 9810 8354 8311 8434 839060+ 5907 8341 8445 9477 9589

15+ 16920 17649 17688 18865 18912

15-29 7 5 5 5 530-59 58 47 47 45 4460+ 35 47 48 50 51

15+ 100 100 100 100 100

*) EU (15) without Luxembourg and Sweden.Source: Projections by DIW.

Age-structure of care givers in % in the EU*)

Development of care givers using constant care giving rates in the EU *)

2050

in 1000 persons

Age-groups Baseline scenario


2001Baseline im- Living-longer- Living-longer

proving health high scenario better health

15+ 0,86 1,11 0,94 1,21 1,04

*) EU (15) without Luxembourg and Sweden.

Source: Projections by DIW.

2050

Relation of hampered persons to care givers in the EU*)

Age-groups Baseline scenario


Summary (1)– Empirical analyses in WP 2 showed that the use of inpatient

and outpatient services are related to age and health status, but also to education and income.

– The increasing life expectancy are in most countries connected with higher utilisation rates in the past.

– The need for long-term care is closely related to age. The prevalence rates for long-term care increases sharply from age 70 onwards, and women have a higher probability to receive long-term care than men, because widowhood is more often among women than men.

– Whereas life expectancy increased the prevalence rates for long-term care giving in institutions show no clear trend. Institutional care is influenced by other important factors, especially political decisions, than trends in life expectancy.


Summary (2)– On average around 5 % (7 %) of all persons (of

women) are informal care givers. Care giving at home is in most cases a hard burden for care givers. On average around 18 hours were spend for care giving at home (women spend 21 hours).

– The share of care givers is higher among inactive people than employees.

– Employment and care giving seems adversely related. If need for care giving occur within the household a great part of women leave their job, a lower part reduced their working time.


Summary (3)– Based on the results and data of WP2 and WP1 (in

particular the estimations of LEGH) in WP 4 Part A the development of health care and long term care utilisation until 2050 were shown at two levels:• In projection method A the data from national sources were

combined with two demograhic scenarios. The results show the effect of demographic changes and the impact of increasing life expectancy for the total population and provides estimations for long term care giving in institutions.

• In projection method B data from the ECHP were combined with four scenarios including changes in life expectancy and health status of the population. The results show the impact of demographic changes, increasing life expectancy and improvements in health on health care utilisation, but includes only people aged 16+ and provides no information about care giving in institutions.


Summary (4)– The results of projection method A and projection method B

are not full comparable, because they uses different sources and definitions of variables, but in general they show similar developments:• The development of hospital days and long term care giving

respectively severely hampered persons show a higher dynamic than the development of hospital admissions and contacts with a doctor

• The living-longer-high scenario lead to higher population in 2050, but the development of the utilisation show a still higher dynamic

• Countries with a decreasing population until 2050 show no general lower increases in utilisation development than countries with increasing population


Summary (5)– The estimations with the projection method B show

that improvements in health status lead to a more moderate increase in utilisation compared to the scenarios without improvements in health. But in general, under the underlying assumptions the improvements in health cannot completely compensate the effect of increasing life expectancy. In the EU are the utilisation data a little bit higher in the living-longer better health scenario as in the baseline scenario in 2050.


Summary (6)The estimation of the development of the number of care-givers at home shows that a better health status does not lead to a markedly higher number of care-givers. The main driving factors are the demographic development and the additional increase in life expectancy in the living-longer scenario. The development of the relation of severely hampered persons to the number of care-givers shows that the pressure on informal care-giving will increase. If the higher development of long-term care recipients at home from the national sources are taken into account, this relation may have a much higher dynamic. The expected changes in household composition and increase in the labour force participation of women strengthen this development, too


Trend in use of health care services and long term care Results of AGIR - WP 2 and WP4A Dr. Erika Schulz.

Documents

erika schulz slide

long term care services

health care utilisation

countries long term

determinant of long

home slide

use of health care services

longterm care