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Table 1 Description of the selected studies evaluating the impact of the Seguro Popular

From: A systematic review of the literature on the impact of the Seguro Popular

Author Outcome Data Population Evaluation design Group of comparison
Knox 2018 [15] – General physical exams
– Cervical cancer screening
– Diabetes screening
– Urban Evaluation Survey (ENCERLUB, 2009 and 2014)b – 23,599 individuals living in urban areas Two-stage least squares (2SLS) with instrumental variables – Uninsured
Rivera-Hernández 2019 [16] – Pap smears
– Mammography/clinical examination
– Diabetes screening
– Hypertension screening
– National Health and Nutrition Surveys (ENSANUT, 2000, 2006, 2012)a – 17,640 adults aged 50 to 75 years Two-stage least squares (2SLS) with instrumental variables, with fixed effects
(pseudo panel from ENSANUT)
– Uninsured
Parker 2018 [17] – Utilization and diagnostic tests
– Receiving treatment: for hypertension, diet for diabetes, taking insulin for diabetes
– Longitudinal Mexican Health and Aging Study (2001–2012)b – 15,186 adults, 50 years old or older Difference-in-difference propensity score matching estimators – Uninsured
Servan-Mori 2017 [18] – Antenatal care cascade – National Demographic Dynamics Survey (ENADID, 2009)a – 14,414 women aged 15 to 50 years Propensity score matching – Uninsured
Servan-Mori 2015 [19] – Access to prescribed medicines – National Health and Nutrition Survey (ENSANUT 2012)a – 6123 users of outpatient services Two-stage least squares (2SLS) with instrumental variables – Uninsured
Servan-Mori 2015 [20] – Timely first antenatal visit (up to third month of gestation) and attendance at four antenatal visits – National Health and Nutrition Survey, (ENSANUT, 2012)a – 6175 women aged 14–49 Propensity score matching – Uninsured
Sosa-Rubí 2009 [21] – Access to laboratory tests, visits for diabetes control, treatment with any drug, number of control tests/month – National Health and Nutrition Survey (ENSANUT, 2006)a – 1491 adults with diabetes Propensity score matching – Uninsured
Sosa-Rubí 2009 [22] – Access to obstetrical services – National Health and Nutrition Survey (ENSANUT, 2006)a – 3890 women who delivered babies during 2001–2006 Multinomial choice model with a discrete endogenous variable – Non-SP-accredited clinic
– Private
Bleich 2007 [23] – Coverage of antihypertensive
treatment
– Coverage of antihypertensive treatment with control of blood pressure
– National Health and Nutrition Survey, (ENSANUT 2005)a
– Mexican National Registry of Health infrastructure
– 4032 adults with hypertension Propensity score matching – Uninsured
Arenas 2015 [24] – Consultations and hospitalization – Mexican Family Life Survey 2002 and 2015
(ENNViH, 2002 and 2015)b
– 6063 households Propensity score matching – Uninsured
Nikoloski 2018 [25] – Out-of-pocket and catastrophic health spending – National Health and Nutrition Survey (ENSANUT, 2006 and 2012)a – 45,837 households in 2006
– 50,023 households in 2012
Two-stage least squares (2SLS) with instrumental variables – Social security
García-Díaz 2018 [26] – Out-of-pocket health spending – National Income and Expenditure Survey (ENIGH, 2010)a – 11,117 households Propensity score matching – Uninsured
Serván-Mori 2018 [27] – Monetary and nonmonetary health service consumption – National Income and Expenditure Survey (ENIGH, 2012)a – 7040 households Two-stage least squares (2SLS) with instrumental variables – Social security
– Uninsured
Knaul 2018 [28] – Out-of-pocket and catastrophic expenditures – National Income and Expenditure Surveys 2004–2012a – 109,513 households Propensity score matching – Social security
Doubova 2015 [29] – Access to healthcare
– Catastrophic health-related expenditures
– National Health and Nutrition Survey (ENSANUT, 2012)a – 18,847 older adults, 13,180 households that have an elderly member Propensity score matching – Social security
– Uninsured
Ávila-Burgos 2013 [30] – Out-of-pocket and catastrophic health spending – National Health and Nutrition Survey (ENSANUT, 2012)a – 12,250 households Propensity score matching – Uninsured
Wirtz 2012 [31] – Out-of-pocket health spending – National Income and Expenditure Survey (ENIGH, 2008)a – 28,260 households Propensity score matching and instrumental variables – Uninsured
– Social security
– Mixed affiliations
Sosa-Rubí 2011 [32] – Out-of-pocket and catastrophic health spending – Seguro Popular evaluation Survey (2005–2008)a – Rural cohort: 29,000 households
– Urban cohort: 6000 households
Fixed effects with instrumental variables – Uninsured
García-Díaz 2011 [33] – Out-of-pocket health spending – National Income and Expenditure Survey (ENIGH, 2006)a – 3665 SP affiliates
– 7638 “Oportunidades” affiliates,
– 1506 SP and “Oportunidades” affiliates
– 43,539 without any affiliation
Propensity score matching and instrumental variables – Oportunidades
– Uninsured
Galárraga 2010 [34] – Out-of-pocket and catastrophic health spending – National Health and Nutrition Survey (ENSANUT, 2006)a
– SP Impact Evaluation Survey (2005–2006)a
– SP Impact Evaluation Survey: 4033 SP-insured households and 16,759 uninsured households
– ENSANUT: 4440 SP-insured households and 16,376 uninsured households
Two-stage least squares (2SLS) with instrumental variables – Uninsured
King 2009 [35] – Out-of-pocket and catastrophic health spending Survey designed by the authorsb – 16,256 households
– 1205 households enrolled
– 15,051 households unenrolled
A matched-pair cluster-randomized experiment – Uninsured
Hernández-Torres 2008 [36] – Catastrophic health spending – Seguro Popular evaluation Survey, 2002a – 2158 households
– 482 were affiliated with the SP and 1676 had no affiliation
Two-stage least squares (2SLS) with instrumental variables – Uninsured
Rivera-Hernandez 2016 [37] – Diabetes treatment and care process indicators
– Hypertension treatment and care process indicators
– National Health and Nutrition Survey (ENSANUT, 2000, 2006 and 2012)a – 3015 older adults aged over 50 diagnosed with diabetes
– 5307 older adults aged over 50 diagnosed with hypertension
Two-stage least squares (2SLS) with instrumental variables, with fixed effects – Uninsured
Celhay 2019 [38] – Out-of-pocket expenses
– Health outcomes in children
– Data sets from the National Institute of Statistic and Geographyc – 11.39 million children born and living in Mexico Difference-in-difference using interrupted time series and fixed effects – Social security
– Uninsured
Grogger 2012 [39] – Out-of-pocket expenses – National Income and Expenditure Survey (ENIGH, 2008)a – 31,040 households in rural areas
– 56,696 households in urban areas
Propensity score matching and instrumental variables – Uninsured
Gutierrez 2018 [40] – Out-of-pocket expenses – National Health and Nutrition Survey (ENSANUT, 2012)a – 44,000 households with at least one member with diabetes, hypertension, or both Propensity score matching – Uninsured
– Social security
  1. Data source design: across-sectional, blongitudinal, ctime series