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Health Care and Social Health Care and Social AssistanceAssistance
ofof an Ageing an Ageing SocietySociety in Poland in Poland - -
characteristiccharacteristicss and trends and trends
Berlin SCORUS Meeting, 29 - 31 March 2010
Relations between Generations Relations between Generations
and the Challenges of an Ageing Societyand the Challenges of an Ageing Society
Anna Jasiówka, Marta Pompa, Monika WałaszekAnna Jasiówka, Marta Pompa, Monika Wałaszek
PLAN OF THE PRESENTATION
1. Ageing society in Poland:Demographic characteristicsDemographic predictions (Central Statistical Office, United Nations)Comparison with Europe and rest of the world
2. Future changes in both health care and social assistance areas related to ageing of the Polish society - results of the forecast model:
Estimation of an expected number of physiciansEstimation of an expected number of nursesEstimation of an expected number of residents of stationary social welfare facilitiesEstimation of expenditure on social assistance
Source: Central Statistical Office of Poland
PEOPLE OVER 65 ANDCHILDREN BELOW 14 IN POLAND
VITAL STATISTICS OF POLISH POPULATION
Source: Central Statistical Office of Poland
LIFE EXPETANCY AT BIRTH
Source: United Nations
RATIO OF PEOPLE OVER 65 TO THE TOTAL POPULATION
Source: United Nations
CONCLUSIONS FOR POLISH SOCIETY
Beginning from 2015 new trends will be observed:The number of live births will be lower than the number of deathsThe number of people at the age of at least 65 will be higher than the number of children
The goal was to create a regression model, based on available data, in order to estimate the expected number of physicians and nurses in the future
Because there is not enough data required to build an appropriate estimation model and there are hardly measurable qualitative data, we make the regression model by using two independent variables, which described the dependent variable (physicians, midwives) in the best possible way
To obtain estimated value of dependent variable in the future, we used the CSO data on the population projection
MODEL ASSUMPTION
PHYSICIANS = 3,53 * PEOPLE + 0,74 * NET MIGRATION
Standard error of estimation
Corrected R2 0,97
11 335
REGRESSION MODEL FOR PHYSICIANS
Standard error of estimation
Corrected R2 0,98
18 674
NURESES=0,0004*PEOPLE2+4 833*NET MIGRATION+ 105*NET MIGRATION2
REGRESSION MODEL FOR NURSES
ESTIMATION OUTCOMES
below 472472 - 523524 - 574above 574
200820102015
People over 65 per one physician
People per one physician
66 65 73
69 66 74
61 64 66
68 69 81
63 63 68
64 63 66
63 62 66
81 81 86
72 73 77
65 64 65
63 63 72
64 62 66
72 71 75
73 74 82
73 72 84
60 59 68
ESTIMATED NUMBER OF PEOPLE PER ONE PHYSICIAN
Standard error of estimation
Corrected R2 0,99
1 333
RESIDENS=0,0075*PEOPLE44+-0,0023*PEOPLE0-17
REGRESSION MODEL FOR RESIDENTS
PREDICTION MODEL FOR SOCIAL EXPENDITURE
Standard error of estimation 141
Corrected R2 0,99
EXPENDITURE=1 077,4*%GDP 2 +146 641,6*% SOCIAL EXPENDITURE
REGRESSION MODEL FOR EXPENDITURE
ESTIMATION OUTCOMES
OUTCOMES OF CORRESPONDANCE ANALYSIS IN THE AREA OF DISABILITY
Source: Central Statistical Office of Poland
DolnośląskieKujawsko-pomorskie
Lubelskie
LubuskieŁódzkie
MałopolskieMazowieckie
Opolskie
Podkarpackie
Podlaskie
Pomorskie
ŚląskieŚwiętokrzyskieWarmi ńsko-mazurskie
WielkopolskieZachodniopomorskie
30-49
50-69
70+
meanly
many
a great many
-2,5 -2,0 -1,5 -1,0 -0,5 0,0 0,5 1,0 1,5-2,5
-2,0
-1,5
-1,0
-0,5
0,0
0,5
1,0
1,5
2,0
2,5
3,0
3,5
DolnośląskieKujawsko-pomorskie
Lubelskie
LubuskieŁódzkie
MałopolskieMazowieckie
Opolskie
Podkarpackie
Podlaskie
Pomorskie
ŚląskieŚwiętokrzyskieWarmi ńsko-mazurskie
WielkopolskieZachodniopomorskie
30-49
50-69
70+
meanly
many
a great many
OUTCOMES OF CORRESPONDANCE ANALYSIS FOR LONG-TERM HEALTH PROBLEMS AND
CHRONIC DISEASES
Source: Central Statistical Office of Poland
DolnośląskieKujawsko-pomorskie
Lubelskie
Lubuskie
Łódzkie
Małopolskie
Mazowieckie
Opolskie
Podkarpackie
Podlaskie
Pomorskie
Śląskie
Świętokrzyskie
Warmińsko-mazurskie
Wielkopolskie
Zachodniopomorskie
35-49
50-69
75+
long-term health problems
chronical diseases
-2,5 -2,0 -1,5 -1,0 -0,5 0,0 0,5 1,0 1,5 2,0 2,5 3,0-2,5
-2,0
-1,5
-1,0
-0,5
0,0
0,5
1,0
1,5
2,0
2,5
DolnośląskieKujawsko-pomorskie
Lubelskie
Lubuskie
Łódzkie
Małopolskie
Mazowieckie
Opolskie
Podkarpackie
Podlaskie
Pomorskie
Śląskie
Świętokrzyskie
Warmińsko-mazurskie
Wielkopolskie
Zachodniopomorskie
35-49
50-69
75+
long-term health problems
chronical diseases
OUTCOMES OF CORRESPONDANCE ANALYSIS FOR DISEASES AND AGE
Source: Central Statistical Office of Poland
15-29
35-49
50-69
75+
allergy
asthma
coronary heart disease without heart attackcoronary heart disease after heart attack
diabetesdiscopathy
other heart disorders
other disorders of liver
other disorders of kidney
calculus of kidney
cholelithiasis
sclerosishypertension
oestheporosis
rheumatism
stroke
duodenal ulcer
arthrosis
-3,5 -3,0 -2,5 -2,0 -1,5 -1,0 -0,5 0,0 0,5 1,0 1,5-2,0
-1,5
-1,0
-0,5
0,0
0,5
1,0
1,5
2,0
15-29
35-49
50-69
75+
allergy
asthma
coronary heart disease without heart attackcoronary heart disease after heart attack
diabetesdiscopathy
other heart disorders
other disorders of liver
other disorders of kidney
calculus of kidney
cholelithiasis
sclerosishypertension
oestheporosis
rheumatism
stroke
duodenal ulcer
arthrosis
Although the projected number of physicians will increase, one physician will give more medical consultations during a year than nowadays. It will be mainly a result of changes in the age structure of Polish population.
Disparity between the voivodships will be observed when it comes to workload of physicians. It will be related to the expected number of old people different in each voivodship and greater health needs of these people.
Increasing number of nurses may be insufficient to meet the needs of an aging population.
CONCLUSIONS (1)
A group of people with long-term health problems, chronic diseases and disability which require greater medical care, will raise. It may cause, that increasing number of nurses will be insufficient.
Increasing number of patients in institutions of social assistance will require raise the employment in these organization, if the standard workload of employees will be maintained. Otherwise it may lead to decline in service quality.
The financial resources allocated to social assistance will be reduced which mainly come from the state budget. It will be a result of dwindling stocks of economically active people.
CONCLUSIONS (2)
THANK YOU THANK YOU FOR YOUR FOR YOUR ATTENTIONATTENTION
