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2. MARCO TEÓRICO CONCEPTUAL

2.1 BASES TEÓRICAS

2.1.1 LA POSESIÓN Y SUS DERIVACIONES

2.1.1.5 CLASES DE POSESIÓN

The Correlations between Training and Experience and Health Provider Knowledge

Are training and experience correlated with the knowledge of health providers? It is not easy to answer the question because information on health provider knowledge and prior training is rarely found in survey data. However, the 2007 wave of the IFLS collected the information nec- essary to examine the association between training and knowledge. The following cross-sectional model can therefore be examined:

Qj=a+bPubj+Train'jg+dExperj+md+e j,

Table A5.1 Growth of the Private Sector and Change in District Average Prenatal Care Vignette Scores, 1997–2007

Dependent variable: Change in prenatal care vignette score

Indicator Model 1 Model 2 Model 3 Model 4

District average of all facilities Change in number of private practices

per 100,000 population 0.01[0.023] 0.018[0.014] Change in number of physician

practices per 100,000 population [0.044] 0.084* 0.057**[0.025]

Change in number of midwife

practices per 100,000 population [0.020]–0.023 –0.001[0.013]

Lag 1997 prenatal vignette score –1.029*** –1.025***

[0.056] [0.056]

Observations 291 291 291 291

R-squared 0.05 0.62 0.06 0.62

District average of public facilities Change in number of private practices

per 100,000 population –0.004[0.022] 0.003[0.014] Change in number of physician

practices per 100,000 population [0.044] 0.044 0.021[0.026]

Change in number of midwife

practices per 100,000 population [0.024]–0.026 –0.001[0.014]

Lag 1997 prenatal vignette score –1.031*** –1.029***

[0.054] [0.054]

Observations 285 285 285 285

R-squared 0.05 0.64 0.05 0.64

Source: IFLS 1997, 2007, http://www.rand.org/labor/FLS/IFLS, estimated by authors.

Notes:Robust standard errors are in brackets. Other correlates include utilization rate, population per square mile,

log per capita expenditure, indicator for Askeskin/Jamkesmas insurance availability in the community (yes = 1), and indicator for asphalt main road in community, all of which are at the community level and in first-differences, and two region indicators (Sumatra = 1 and Other Provinces = 1) to control for regional growth effects.

where Q is health provider knowledge, Pub is dummy variable for public health provider, Train' is a vector of training programs that a health provider may have received during the previous 12 months, Exper is health provider work experience (in years), and mdis district fixed effect.

Subscript j represents observations at the health provider level. As infor- mation on types of training received by health providers is only available in IFLS4 (2007), it is only possible to estimate simple contemporaneous correlations of training and experience with knowledge of health providers. District-level fixed effects are included in the estimation to control for unobserved heterogeneity, such as district-level health poli- cies or funding that might be correlated both with opportunities to

Health Provider Knowledge and the Private Sector 125

Table A5.2 Growth of the Private Sector and Change in District Average Child Curative Care Vignette Scores, 1997–2007

Dependent variable: Change in child curative care score

Indicator Model 1 Model 2 Model 3 Model 4

District average of all facilities Change in number of private practices

per 100,000 population [0.023]0.006 [0.018]0.001

Change in number of physician practices

per 100,000 population [0.044]*0.078 [0.031]**0.069

Change in number of midwife

practices per 100,000 population –0.026[0.033] –0.018[0.027]

Lag 1997 prenatal vignette score –0.871***

[0.060] –0.869[0.060]***

Observations 291 291 291 291

R-squared 0.04 0.50 0.05 0.50

District average of public facilities Change in number of private practices

per 100,000 population [0.027]0.004 –0.005[0.020]

Change in number of physician

practices per 100,000 population [0.050]0.003 [0.037]0.023

Change in number of midwife practices

per 100,000 population [0.032]0.004 –0.002[0.025]

Lag 1997 prenatal vignette score –0.767*** –0.775

[0.060] [0.060]***

Observations 288 288 288 288

R-squared 0.03 0.43 0.03 0.43

Source:IFLS 1997, 2007, http://www.rand.org/labor/FLS/IFLS, estimated by authors.

Notes:Robust standard errors are in brackets. Other correlates include utilization rate, population per square mile, log per capita expenditure, indicator for Askeskin/Jamkesmas insurance availability in the community (yes = 1), and an indicator for an asphalt main road in community, all of which are at the community level and in first- differences, and two region indicators (Sumatra = 1 and Other Provinces = 1) to control for regional growth effects. * significant at 10%; ** significant at 5%; *** significant at 1%.

participate in training to improve knowledge and skills and with health provider knowledge.

Interpreting the parameters of interest, g and d, however, should be done cautiously. The estimated parameters can only be interpreted as cor- relations between health provider knowledge and training and experi- ence, respectively. Potential biases, from individuals’ endogenous take-up of training opportunities or from targeting of training to lower-skilled health workers, may lead to either under- or overstatement of the associ- ation between training and quality of care.

Table A5.3 What Is the Association between Training and the Prenatal Care Vignette Score?

Independent variable

Prenatal care quality Percentage

raw score

Scored above average (yes = 1) Trained in 12 months, safe delivery

(yes = 1) 0.01 [0.013] 0.001 [0.015] 0.021 [0.041] 0.040 [0.046] Trained in 12 months, high-risk

pregnancy (yes = 1) 0.003 [0.015] 0.012 [0.017] 0.004 [0.047] 0.007 [0.053] Trained in 12 months, labor assistance

(yes = 1) 0.000 [0.014] 0.003 [0.017] –0.002 [0.045] –0.016 [0.052] Trained in 12 months, HIV transmission

in pregnancy (yes = 1) 0.006 [0.012] 0.013 [0.013] 0.002 [0.037] –0.02 [0.041] Trained in 12 months, obstetrical

emergency (yes = 1) 0.003 [0.012] 0.003 [0.014] 0.021 [0.038] 0.035 [0.042] Trained in 12 months, family planning

(yes = 1) –0.011 [0.011] –0.017 [0.012] 0.018 [0.033] 0.004 [0.038]

Trained in 12 months, other (yes = 1) –0.002 –0.006 –0.060 –0.060

[0.013] [0.015] [0.041] [0.046]

Health provider is public (yes = 1) 0.015** 0.039

[0.008] [0.024]

Work experience (years) 0.000 0.002*

[0.000] [0.001]

Constant 0.447*** 0.440*** 0.697*** 0.660***

[0.004] [0.008] [0.012] [0.026]

Observations 1,877 1,537 1,877 1,537

R-squared 0.471 0.499 0.280 0.315

Source:IFLS 2007, http://www.rand.org/labor/FLS/IFLS.

Notes:Standard errors in brackets. District fixed effect is included in each specification. *** p < 0.01, ** p < 0.05, * p < 0.10.

Health Provider Knowledge and the Private Sector 127

Table A5.4 What Is the Association between Training and the Child Curative Care Vignette Score?

Independent variable

Child curative care quality Percentage

raw score

Scored above average (yes = 1) Trained in 12 months,

child immunization (yes = 1) –0.001 [0.012] –0.007 [0.014] 0.028 [0.035] 0.026 [0.039] Trained in 12 months, acute respiratory

infection (yes = 1) 0.020 [0.013] 0.037** [0.015] –0.002 [0.038] 0.002 [0.043]

Trained in 12 months, diarrhea (yes = 1) –0.011 –0.016 –0.029 –0.034

[0.015] [0.017] [0.042] [0.047]

Trained in 12 months, malaria (yes = 1) 0.062*** 0.065*** –0.033 –0.033

[0.017] [0.019] [0.048] [0.053]

Trained in 12 months, nutrition (yes = 1) 0.022* 0.015 –0.036 –0.026

[0.013] [0.014] [0.037] [0.040]

Trained in 12 months, HIV transmission

in pregnancy (yes = 1) 0.021 [0.014] 0.019 [0.016] 0.010 [0.040] 0.008 [0.044] Trained in 12 months, prenatal care

(yes = 1) 0.022* [0.013] 0.022 [0.014] –0.094*** [0.036] –0.089** [0.041]

Health provider is public (yes = 1) 0.039*** –0.052**

[0.009] [0.024]

Work experience (years) 0.000 0.001

[0.000] [0.001]

Constant 0.612*** 0.610*** 0.589*** 0.587***

[0.004] [0.008] [0.011] [0.024]

Observations 2,309 1,929 2,309 1,929

R-squared 0.437 0.448 0.252 0.269

Source:IFLS 2007, http://www.rand.org/labor/FLS/IFLS.

Notes:Standard errors in brackets. District fixed effect is included in each specification. *** p < 0.01, ** p < 0.05, * p < 0.10.

Table A5.5 What Is the Association between Training and the Adult Curative Care Vignette Score?

Independent variable

Adult curative care quality Percentage

raw score

Scored above average (yes = 1) Trained in 12 months, diag. algorithm

(yes = 1) 0.061*** [0.015] 0.068*** [0.017] –0.029 [0.039] –0.027 [0.043] Trained in 12 months, noncommunicable

disease (yes = 1) 0.012 [0.014] 0.005 [0.016] 0.030 [0.037] 0.034 [0.042] Trained in 12 months, respiratory disease

(yes = 1) 0.033** [0.017] 0.018 [0.019] –0.067 [0.043] –0.061 [0.050] Trained in 12 months, antibiotics for

respiratory disease (yes = 1) 0.027 [0.017] 0.035* [0.020] –0.036 [0.045] –0.045 [0.052]

Health provider is public (yes = 1) 0.044*** –0.132***

[0.009] [0.022]

Work experience (years) 0.000 0.000

[0.000] [0.001]

Constant 0.525*** 0.522*** 0.328*** 0.374***

[0.004] [0.008] [0.010] [0.022]

Observations 2,199 1,824 2,199 1,824

R-squared 0.413 0.428 0.326 0.363

Source:IFLS 2007, http://www.rand.org/labor/FLS/IFLS.

Notes:Standard errors in brackets. District fixed effect is included in each specification. *** p < 0.01, ** p < 0.05, * p < 0.10.

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