specialist referral rates and patient nationality in spain
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SPECIALIST REFERRAL RATES
AND PATIENT NATIONALITY IN
SPAIN
Agency for Health Technology AssessmentAgency for Health Technology Assessment
INSTITUTO DE SALUD CARLOS IIIINSTITUTO DE SALUD CARLOS III
Antonio Sarría SantameraMª del Rocío Carmona AlférezMª Auxiliadora Martín Martínez Pilar Gallego BercianoEnrique Regidor Poyatos
Sandín Vázquez MConde Espejo Pde Bustos Guadaño MAsunsolo del Barco ARiesgo Fuertes RGarrido Elustondo SCabello Ballesteros MLEscortell Mayor MESanz Cuesta T
Calvo Parra IVillaitodo Villén PBartolomé Casado MSJiménez Carramiñana JCasado López MParralejo Buendía MBasanta López MBonache Blay MMartínez-Toledano Olaya
P Rico Blázquez M
Primary Health Care Utilization Research Group
INTRODUCTION
The phenomenon of immigration is relatively new in Spain: the number of immigrants is low but increasing in the last few years.
12% of the population of Spain is of foreign nationality (INE, 2009). 44.8% of all registered immigrants in Spain reside in in three provinces (Madrid, Barcelona and Alicante).
The phenomenon of immigration is relatively new in Spain: the number of immigrants is low but increasing in the last few years.
12% of the population of Spain is of foreign nationality (INE, 2009). 44.8% of all registered immigrants in Spain reside in in three provinces (Madrid, Barcelona and Alicante).
INTRODUCTION
Previous research indicates that the immigrant population is young and healthy, and there are no differences (age-adjusted).
Although their health status could be similar to that of local populations, they could have different behaviors in accessing the health care system.
Also, health care professionals could have different behavior when treating immigrants.
Previous research indicates that the immigrant population is young and healthy, and there are no differences (age-adjusted).
Although their health status could be similar to that of local populations, they could have different behaviors in accessing the health care system.
Also, health care professionals could have different behavior when treating immigrants.
OBJECTIVE
To compare referrals to specialists from PC
in the Region of Madrid between immigrant
and native populations.
To compare referrals to specialists from PC
in the Region of Madrid between immigrant
and native populations.
METHODOLOGY
Design, location and sources of Design, location and sources of informationinformation
Design: transversal, observational and ecological.
Location: 6 health areas in the Community of Madrid.
Sources of information:
- Electronic medical records of Primary Care (OMI-AP).
- Institute of Statistics of the Community of Madrid.
Design, location and sources of Design, location and sources of informationinformation
Design: transversal, observational and ecological.
Location: 6 health areas in the Community of Madrid.
Sources of information:
- Electronic medical records of Primary Care (OMI-AP).
- Institute of Statistics of the Community of Madrid.
Health areas: 1, 3, 7, 8, 9 y 10
METHODOLOGY
Flowchart of patient selectionFlowchart of patient selectionFlowchart of patient selectionFlowchart of patient selection
PATIENTS OVER 24 YEARS WITH AT LEAST ONE VISIT TO THE CENTRE OF HEALTH IN 2006
IN 6 HEALTH AREAS (1,325,327)
PATIENTS INCLUDED IN STUDY (1,053,266)
DUPLICATE PATIENTS (7,307)
PATIENTS WITHOUT NATIONALITY (264,754)
METHODOLOGYPATIENT VARIABLES
Socio-demographic
1. Age2. Sex 3. Nationality4. User Type5. Social Problems
Morbidity
1. Diseases (CIAP-1)2. Temporary Disability3. Patient Overview4. Protocols5. Drugs prescribed
Use of Health Services
1. Total medical PC consultations (2006 and 2007).2. Total nursing PC consultations (2006 and 2007).3. Analytics4. Radiology tests5. Referrals to specialists
PRIMARY CARE TEAM VARIABLES
Organizational Characteristics and Health System Capacity
1. Location of the PCT2. Type of primary health care team3. Time schedule2. Average PC doctor workload3. Average PC nursing workload4. Percentage of patients aged ≥ 65 years of primary care team
Socioeconomic
1. Educational level of the Basic Health Zone (Population and Housing Census 2001 of the CM)2. Per capita Gross Disposable Income of the Basic Health Zone (Statistical Institute of the CM)
METHODOLOGY
Nationality variable was used to reflect whether a patient was an immigrant or not.
8 categories of nationality:
a) Nativeb) Western Countriesc) Eastern Europed) North Africae) Sub-Saharan Africaf) Central America and Caribbeang) South Americah) Middle East, South Asia and East
Nationality variable was used to reflect whether a patient was an immigrant or not.
8 categories of nationality:
a) Nativeb) Western Countriesc) Eastern Europed) North Africae) Sub-Saharan Africaf) Central America and Caribbeang) South Americah) Middle East, South Asia and East
METHODOLOGY
“SOCIO-ECONOMIC DATA”
Patient
Per capita Gross Disposable Income in 2000 of the Basic Health Zone
“SOCIO-ECONOMIC DATA”
Patient
Per capita Gross Disposable Income in 2000 of the Basic Health Zone
METHODOLOGY
MODEL 1MODEL 1: BINOMIAL REGRESSION: BINOMIAL REGRESSION
DEPENDENT VARIABLE: DEPENDENT VARIABLE: Referral (yes/no)Referral (yes/no)
INDEPENDENTS VARIABLES: INDEPENDENTS VARIABLES:
Immigrant (yes/no) Immigrant (yes/no) AgeAge Sex Sex Total diseaseTotal disease Per capita incomePer capita income
MODEL 1MODEL 1: BINOMIAL REGRESSION: BINOMIAL REGRESSION
DEPENDENT VARIABLE: DEPENDENT VARIABLE: Referral (yes/no)Referral (yes/no)
INDEPENDENTS VARIABLES: INDEPENDENTS VARIABLES:
Immigrant (yes/no) Immigrant (yes/no) AgeAge Sex Sex Total diseaseTotal disease Per capita incomePer capita income
Socio-demographic
MorbiditySocio-economic
METHODOLOGY
MODEL 2MODEL 2: BINOMIAL REGRESSION: BINOMIAL REGRESSION
DEPENDENT VARIABLE: DEPENDENT VARIABLE: Referral (yes/no)Referral (yes/no)
INDEPENDENTS VARIABLES: INDEPENDENTS VARIABLES:
Nationality (8 categories)Nationality (8 categories) AgeAge SexSex Total diseaseTotal disease Per capita incomePer capita income
MODEL 2MODEL 2: BINOMIAL REGRESSION: BINOMIAL REGRESSION
DEPENDENT VARIABLE: DEPENDENT VARIABLE: Referral (yes/no)Referral (yes/no)
INDEPENDENTS VARIABLES: INDEPENDENTS VARIABLES:
Nationality (8 categories)Nationality (8 categories) AgeAge SexSex Total diseaseTotal disease Per capita incomePer capita income
Socio-demographic
MorbiditySocio-economic
RESULTS
PATIENT CHARACTERISTICS (N=1,053,266)
Both sexes(%)
Male(%)
Female(%)
IMMIGRANT 14.2 14.1 14.3
NATIONALITY OF IMMIGRANTS (n=149,564)
Western Countries 10.2 10.4 10.1
Eastern Europe 18.3 17.6 18.9
North Africa 10.8 13.8 8.4
Sub-Saharan Africa 6.2 7.8 4.9
Central America and Caribbean 6.9 5.6 8.0
South America 42.9 39.5 45.7
Middle East, South Asia and East 4.7 5.3 4.1
RESULTS
PATIENT CHARACTERISTICS NATIVE IMMIGRANT
(N=1,053,266) Mean S.D. Mean S.D.
AGE 50.34 16.79 39.90 12.05
WOMEN (%) 55.5 55.8
TOTAL NUMBER DISEASES 5.69 4.01 3.84 3.10
PER CAPITA INCOME 9977 2236 10226 2609
REFERRALS 0.43 0.77 0.42 0.77
CHARACTERISTICS OF PATIENTS REFERRED TO SPECIALIST NATIVE IMMIGRANT
N=315,038 Mean S.D Mean S.D.
AGE 51.97 16.24 40.68 12.07
WOMEN (%) 60.90 66.57
TOTAL NUMBER DISEASES 6.84 3.91 4.86 3.20
PER CAPITA INCOME 9687 1841 10007 2435
REFERRALS 1.42 0.75 1.43 0.77
RESULTS
REFERRALS TO SPECIALIST (N=1,053,266)Both sexes
(%) Male (%)Female
(%)
NATIVE 30.0 26.4 33.0
IMMIGRANT 29.2 22.1 34.9
Western Countries 27.4 23.4 30.6
Eastern Europe 26.5 18.6 32.2
North Africa 26.6 20.4 34.8
Sub-Saharan Africa 26.6 20.1 34.9
Central America and Caribbean 31.4 23.9 35.6
South America 32.3 24.7 37.5
Middle East, South Asia and East 22.2 16.9 27.7
TOTAL 29.9 25.8 33.2
RESULTS
BOTH SEXES MALE FEMALE MODEL 1: BINOMIAL REGRESSION PR SE 95% CI PR SE 95% CI PR SE 95% CI
IMMIGRANT (Ref. native) 1.19 0.005 (1.18, 1.20) 1.10 0.009 (1.08, 1.12) 1.23 0.006 (1.18, 1.20)
AGE (Ref. 25-34 years)
35-44 years 1.06 0.005 (1.05, 1.07) 1.15 0.009 (1.13, 1.16) 1.01 0.006 (1.00, 1.02)
45-54 years 1.14 0.005 (1.13, 1.16) 1.26 0.010 (1.24, 1.28) 1.09 0.006 (1.08, 1.10)
55-64 years 1.18 0.005 (1.17, 1.19) 1.38 0.011 (1.36, 1.41) 1.08 0.006 (1.07, 1.10)
65-74 years 1.18 0.006 (1.17, 1.20) 1.41 0.012 (1.39, 1.44) 1.07 0.007 (1.06, 1.09) ≥ 74 years 1.01 0.006 (1.00, 1.03) 1.32 0.014 (1.29, 1.34) 0.89 0.007 (0.88, 0.91)
FEMALE (Ref. male) 1.16 0.004 (1.16, 1.17) PER CAPITA INCOME (Ref. low income)
Intermediate 1.07 0.004 (1.06, 1.08) 1.09 0.006 (1.08, 1.10) 1.06 0.005 (1.05, 1.07)
High 0.96 0.004 (0.95, 0.96) 1.00 0.006 (0.98, 1.01) 0.94 0.004 (0.93, 0.94)
Very High 0.73 0.005 (0.72, 0.74) 0.76 0.009 (0.75, 0.78) 0.71 0.006 (0.70, 0.72) TOTAL DISEASES (Ref. no disease)
1-3 diseases 2.19 0.036 (2.12, 2.26) 2.33 0.058 (2.22, 2.45) 2.07 0.045 (1.98, 2.15)
4-6 diseases 3.51 0.057 (3.40, 3.62) 3.79 0.094 (3.61, 3.98) 3.22 0.069 (3.09, 3.36)
≥ 7 diseases 4.57 0.074 (4.42, 4.71) 4.69 0.117 (4.47, 4.93) 4.31 0.092 (4.13, 4.49)
PR: percentage ratio, SE: standard error , CI: confidence interval.
RESULTS BOTH SEXES MALE FEMALE MODEL 2: BINOMIAL REGRESSION PR SE 95% CI PR SE 95% CI PR SE 95% CI
NATIONALITY (Ref. native)
Western Countries 1.09 0.014 (1.07, 1.12) 1.11 0.024 (1.06, 1.15) 1.09 0.017 (1.05, 1.12)
Eastern Europe 1.19 0.012 (1.16, 1.21) 1.02 0.020 (0.98, 1.06) 1.25 0.014 (1.23, 1.28)
North Africa 1.03 0.013 (1.01, 1.06) 0.95 0.019 (0.91, 0.99) 1.11 0.018 (1.07, 1.14)
Sub-Saharan Africa 1.09 0.018 (1.05, 1.12) 1.01 0.027 (0.96, 1.07) 1.15 0.024 (1.10, 1.20)
Central America and Caribbean 1.21 0.017 (1.18, 1.25) 1.13 0.032 (1.07, 1.19) 1.24 0.020 (1.20, 1.28)
South America 1.29 0.007 (1.27, 1.30) 1.23 0.013 (1.20, 1.25) 1.31 0.009 (1.29, 1.32)
Middle East, South Asia and East 1.01 0.022 (0.96, 1.05) 0.88 0.032 (0.82, 0.95) 1.10 0.029 (1.05, 1.16) AGE (Ref. 25-34 years)
35-44 years 1.06 0.005 (1.05, 1.07) 1.15 0.009 (1.13, 1.16) 1.02 0.006 (1.00, 1.03)
45-54 years 1.15 0.005 (1.14, 1.16) 1.26 0.010 (1.24, 1.28) 1.09 0.006 (1.08, 1.10)
55-64 years 1.18 0.005 (1.17, 1.19) 1.39 0.011 (1.36, 1.41) 1.09 0.006 (1.07, 1.10)
65-74 years 1.19 0.006 (1.17, 1.20) 1.41 0.012 (1.39, 1.44) 1.08 0.007 (1.06, 1.09)
≥ 74 years 1.02 0.006 (1.01, 1.03) 1.32 0.014 (1.29, 1.35) 0.90 0.007 (0.88, 0.91) FEMALE (Ref. male) 1.16 0.004 (1.15, 1.17) PER CAPITA INCOME (Ref. low income)
Intermediate 1.07 0.004 (1.06, 1.08) 1.09 0.006 (1.08, 1.10) 1.06 0.005 (1.05, 1.07)
High 0.96 0.004 (0.95, 0.96) 0.99 0.006 (0.98, 1.01) 0.94 0.004 (0.93, 0.94)
Very High 0.73 0.005 (0.72, 0.74) 0.76 0.009 (0.74, 0.77) 0.71 0.006 (0.70, 0.72) TOTAL DISEASES (Ref. no disease)
1-3 diseases 2.18 0.036 (2.12, 2.26) 2.32 0.058 (2.21, 2.44) 2.07 0.045 (1.98, 2.16)
4-6 diseases 3.50 0.057 (3.39, 3.61) 3.77 0.094 (3.59, 3.96) 3.22 0.069 (3.09, 3.36)
≥ 7 diseases 4.56 0.074 (4.42, 4.71) 4.67 0.117 (4.45, 4.90) 4.31 0.092 (4.14, 4.50) PR: percentage ratio, SE: standard error , CI: confidence interval.
CONCLUSIONS
Immigrants are younger and healthier than the
native population.
Immigrants are younger and healthier than the
native population.
Overall, women have a higher probability of being
referred to specialists.
Overall, women have a higher probability of being
referred to specialists.
After controlling for socio-demographic and
economic characteristics, and morbidity, immigrants
show a higher likelihood of referrals to specialist.
After controlling for socio-demographic and
economic characteristics, and morbidity, immigrants
show a higher likelihood of referrals to specialist.
CONCLUSIONS
Compared to Spanish natives, specialist referrals
are higher in women from those from Eastern Europe,
Central and South America, and in men for those from
South America.
Compared to Spanish natives, specialist referrals
are higher in women from those from Eastern Europe,
Central and South America, and in men for those from
South America.
Further studies will allow to gain a better
understanding of the relationship between national
origin and referrals.
Further studies will allow to gain a better
understanding of the relationship between national
origin and referrals.
THANK YOUTHANK YOU
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