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