Measuring the Protective Effect of Health Insurance Coverage on Out-of-Pocket Expenditures During the COVID-19 Pandemic in the Peruvian Population

Document Type : Original Article

Authors

1 Centro de Excelencia en Investigaciones Económicas y Sociales en Salud, Vicerrectorado de Investigación, Universidad San Ignacio de Loyola, Lima, Peru

2 Universidad de Buenos Aires, Buenos Aires, Argentina

3 Universidad Científica del Sur, Lima, Peru

4 Centro de Investigación Epidemiológica en Salud Global, Universidad Privada Norbert Wiener, Lima, Peru

Abstract

Background 
Health insurance coverage is expected to protect individuals from out-of-pocket (OOP) expenditures, potentially preventing them from falling into poverty. However, to date, the effect of health insurance on OOP spending during the coronavirus disease 2019 (COVID-19) pandemic has not been fully explored. This study aimed to estimate differences in the proportion and the amount of OOP expenditures among Peruvians during the pre- and post- mandatory lockdown response to COVID-19 in 2020 according to the health insurance coverage status.

Methods 
This study utilized repeated cross-sectional data from the National Household Survey on Living and Poverty Conditions (ENAHO) from the first quarter of 2017 until the fourth quarter of 2020. The outcomes were (i) the proportion of individuals who incurred OOP expenditures and (ii) the monetary value of OOP expenditures. An interrupted time series analysis (ITS) and a quasi-experimental difference-in-difference (DID) analysis were performed to examine the outcomes among the control (individuals without health insurance) and treatment groups (individuals with health insurance) after the COVID-19 pandemic.

Results 
ITS analysis showed that the proportion of individuals reporting OOP expenditures after implementation of mandatory lockdown due to COVID-19 in Peru decreased in both groups, but no difference in the slope trend was found (P = .916). The average quarterly amount of OOP spending increased in both groups, but no difference in the slope trend was found (P = .073). Lastly, the DID analysis showed that the mandatory lockdown was associated with a higher amount of OOP, but there was no evidence to indicate that the higher amount was different between the control and treatment groups.

Conclusion 
The mandatory lockdown in response to the COVID-19 was associated with a higher amount of OOP expenditures and a lower likelihood of incurring OOP expenditures. However, our findings suggest that health insurance coverage does not lower OOP expenditures or reduce the likelihood of incurring OOP expenditures.

Keywords

Main Subjects


  1. Johns Hopkins University. COVID-19 Dashboard by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University (JHU). https://coronavirus.jhu.edu/map.html. Accessed June 27, 2021. Published 2021.
  2. World Health Organization. Out-of-pocket payments, user fees and catastrophic expenditure. http://www.who.int/health_financing/topics/financial-protection/out-of-pocket-payments/en/. Accessed June 22, 2021. Published 2021.
  3. Agarwal SD, Sommers BD. Insurance coverage after job loss - the importance of the ACA during the COVID-associated recession. N Engl J Med. 2020;383(17):1603-1606. doi:1056/NEJMp2023312
  4. Economic Policy Institute. Health insurance and the COVID-19 shock: What we know so far about health insurance losses and what it means for policy. https://www.epi.org/publication/health-insurance-and-the-covid-19-shock/. Accessed June 22, 2021. Published 2020.
  5. Ministerio de Salud. Sala situacional COVID-19 Perú. https://covid19.minsa.gob.pe/sala_situacional.asp. Accessed June 28, 2021. Published 2021.
  6. Gobierno del Perú. Decreto Supremo que declara Estado de Emergencia Nacional por las graves circunstancias que afectan la vida de la Nación a consecuencia del brote del COVID-19. Decreto supremo No 044-2020-PCM del 15 de marzo de 2020 El Peruano (15-03-2020). https://busquedas.elperuano.pe/normaslegales/decreto-supremo-que-declara-estado-de-emergencia-nacional-po-decreto-supre-mo-n-044-2020-pcm-1864948-2/. Accessed June 21, 2021. Published 2020.
  7. Gamero J, Pérez J. Perú › Impacto de la COVID-19 en el empleo y los ingresos laborales. https://www.ilo.org/wcmsp5/groups/public/---americas/---ro-lima/documents/publication/wcms_756474.pdf. Accessed June 20, 2021. Published 2020.
  8. Hernández-Vásquez A, Rojas-Roque C, Vargas-Fernández R, Rosselli D. Measuring out-of-pocket payment, catastrophic health expenditure and the related socioeconomic inequality in Peru: a comparison between 2008 and 2017. J Prev Med Public Health. 2020;53(4):266-274. doi:3961/jpmph.20.035
  9. Instituto Nacional de Estadística e Informática. Perú - Encuesta Nacional de Hogares sobre Condiciones de Vida y Pobreza 2017. http://webinei.inei.gob.pe/anda_inei/index.php/catalog/613. Accessed January 6, 2021. Published 2018.
  10. Hernández-Vásquez A, Alarcon-Ruiz CA, Díaz-Seijas D, Magallanes-Quevedo L, Rosselli D. Purchase of medications without prescription in Peru: a cross-sectional population-based study. F1000Res. 2018;7:1392. doi:12688/f1000research.15886.2
  11. Banco Central de Reserva de Perú. Índice de Precios al Consumidor (IPC). https://estadisticas.bcrp.gob.pe/estadisticas/series/anuales/resultados/PM05197PA/html. Accessed September 20, 2021. Published 2021.
  12. The World Bank. The World Bank Country Dataset. https://data.worldbank.org/country. Accessed February 2, 2021. Published 2020.
  13. Colegio Médico del Perú. El sistema de salud en Perú. Situación y desafíos. http://repositorio.cmp.org.pe/bitstream/CMP/32/1/libroSistemaSaludPeru.pdf. Accessed September 20, 2021. Published 2016.
  14. Instituto Nacional de Estadística e Informática. Población sin seguro de salud. https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib1587/libro02.pdf. Accessed September 27, 2021. Published 2018.
  15. Instituto Nacional de Estadística e Informática. Acceso a Los Servicios Básicos en El Perú, 2013-2019. https://www.inei.gob.pe/media/MenuRecursivo/publicaciones_digitales/Est/Lib1756/. Accessed September 20, 2021. Published 2020.
  16. Bernal JL, Cummins S, Gasparrini A. Interrupted time series regression for the evaluation of public health interventions: a tutorial. Int J Epidemiol. 2017;46(1):348-355. doi:1093/ije/dyw098
  17. Kontopantelis E, Doran T, Springate DA, Buchan I, Reeves D. Regression based quasi-experimental approach when randomisation is not an option: interrupted time series analysis. BMJ. 2015;350:h2750. doi:1136/bmj.h2750
  18. Levin A, Lin C-F, James Chu C-S. Unit root tests in panel data: asymptotic and finite-sample properties. J Econom. 2002;108(1):1-24. doi:1016/s0304-4076(01)00098-7
  19. Harris RD, Tzavalis E. Inference for unit roots in dynamic panels where the time dimension is fixed. J Econom. 1999;91(2):201-226. doi:1016/s0304-4076(98)00076-1
  20. Breitung J, Das S. Panel unit root tests under cross-sectional dependence. Stat Neerl. 2005;59(4):414-433. doi:1111/j.1467-9574.2005.00299.x
  21. Im KS, Pesaran MH, Shin Y. Testing for unit roots in heterogeneous panels. J Econom. 2003;115(1):53-74. doi:1016/S0304-4076(03)00092-7
  22. Linden A. Conducting interrupted time-series analysis for single- and multiple-group comparisons. Stata J. 2015;15(2):480-500. doi:1177/1536867x1501500208
  23. Cumby RE, Huizinga J. Testing the Autocorrelation Structure of Disturbances in Ordinary Least Squares and Instrumental Variables Regressions. Cambridge, Mass: National Bureau of Economic Research; 1990.
  24. Royston JP. A Simple Method for Evaluating the Shapiro-Francia W' Test of Non-Normality. J R Stat Soc Ser D. 1983;32(3):297-300. doi:2307/2987935
  25. Pedraja-Chaparro F, Santín D, Simancas R. The impact of immigrant concentration in schools on grade retention in Spain: a difference-in-differences approach. Appl Econ. 2016;48(21):1978-1990. doi:1080/00036846.2015.1111989
  26. Tatah L, Delbiso TD, Rodriguez-Llanes JM, Gil Cuesta J, Guha-Sapir D. Impact of refugees on local health systems: a difference-in-differences analysis in Cameroon. PLoS One. 2016;11(12):e0168820. doi:1371/journal.pone.0168820
  27. Oduse S, Zewotir T, North D. The impact of antenatal care on under-five mortality in Ethiopia: a difference-in-differences analysis. BMC Pregnancy Childbirth. 2021;21(1):44. doi:1186/s12884-020-03531-5
  28. Wing C, Simon K, Bello-Gomez RA. Designing difference in difference studies: best practices for public health policy research. Annu Rev Public Health. 2018;39:453-469. doi:1146/annurev-publhealth-040617-013507
  29. Kleinbaum DG, Kupper LL, Muller KE. Applied Regression Analysis and Other Multivariate Methods. 2nd ed. Boston, Massachusetts: PWS-Kent; 1988:210.
  30. DiCiccio TJ, Efron B. Bootstrap confidence intervals. Stat Sci. 1996;11(3):189-228.
  31. Imlach F, McKinlay E, Kennedy J, et al. Seeking healthcare during lockdown: challenges, opportunities and lessons for the future. Int J Health Policy Manag. 2021. doi:34172/ijhpm.2021.26
  32. Huston P, Campbell J, Russell G, et al. COVID-19 and primary care in six countries. BJGP Open. 2020;4(4). doi:3399/bjgpopen20X101128
  33. Moynihan R, Sanders S, Michaleff ZA, et al. Impact of COVID-19 pandemic on utilisation of healthcare services: a systematic review. BMJ Open. 2021;11(3):e045343. doi:1136/bmjopen-2020-045343
  34. Vázquez-Rowe I, Gandolfi A. Peruvian efforts to contain COVID-19 fail to protect vulnerable population groups. Public Health Pract. 2020;1:100020. doi:1016/j.puhip.2020.100020
  35. Taylor L. Covid-19: why Peru suffers from one of the highest excess death rates in the world. BMJ. 2021;372:n611. doi:1136/bmj.n611
  36. Peru: riot police block highway as people attempt to flee amid lockdown. The Guardian. April 20, 2020. http://www.theguardian.com/world/2020/apr/20/peru-riot-police-highway-teargas-coronavirus-lockdown. Accessed June 25, 2021.
  37. Almeida F. Exploring the impact of COVID-19 on the sustainability of health critical care systems in South America. Int J Health Policy Manag. 2020. doi:34172/ijhpm.2020.116
  38. Burki T. COVID-19 in Latin America. Lancet Infect Dis. 2020;20(5):547-548. doi:1016/s1473-3099(20)30303-0
  39. Covid: Why has Peru been so badly hit? BBC News. June 1, 2021. https://www.bbc.com/news/world-latin-america-53150808. Accessed June 21, 2021.
  40. Ministerio del Interior. Capturan red criminal acusada de cobrar por camas UCI en hospital Almenara - Gobierno del Perú. Plataforma digital única del Estado Peruano. Available from: https://www.gob.pe/institucion/mininter/noticias/507481-capturan-red-criminal-acusada-de-cobrar-por-camas-uci-en-hospital-almenara. Accessed September 27, 2021. Published 2020.
  41. Defensoría del Pueblo. CRISIS DE OXÍGENO PARA PACIENTES DE COVID-19: Alternativas de solución. https://www.defensoria.gob.pe/wp-content/uploads/2020/06/Serie-Informes-Especiales-N%C2%BA-017-2020-DP.pdf. Published 2020.
  42. Fraser B. COVID-19 strains remote regions of Peru. Lancet. 2020;395(10238):1684. doi:1016/s0140-6736(20)31236-8
  43. La República. Buscar oxígeno, una travesía entre la vida y la muerte. https://larepublica.pe/sociedad/2020/06/02/coronavirus-en-peru-buscar-oxigeno-una-travesia-entre-la-vida-y-la-muerte-covid-19/?ref=lre. Published 2020.
  44. Wagstaff A, Flores G, Hsu J, et al. Progress on catastrophic health spending in 133 countries: a retrospective observational study. Lancet Glob Health. 2018;6(2):e169-e179. doi:1016/s2214-109x(17)30429-1
  45. Gutiérrez C, Romaní-Romaní F, Wong P, Del Carmen Sara J. Gap between population coverage and health benefits: a challenge for health reform in Peru. An Fac Med. 2018;79(1):65-70.
  46. Herrera-Añazco P, Uyen-Cateriano A, Mezones-Holguin E, et al. Some lessons that Peru did not learn before the second wave of COVID-19. Int J Health Plann Manage. 2021;36(3):995-998. doi:1002/hpm.3135
  47. Pesantes MA, Lazo-Porras M, Cárdenas MK, et al. [Healthcare challenges for people with diabetes during the national state of emergency due to COVID-19 in Lima, Peru: primary healthcare recommendations]. Rev Peru Med Exp Salud Publica. 2020;37(3):541-546. doi:17843/rpmesp.2020.373.5980
  48. Málaga G. [Causes of admission to the Cayetano Heredia Hospital during the COVID-19 pandemic]. Rev Peru Med Exp Salud Publica. 2020;37(3):587-588. doi:17843/rpmesp.2020.373.5868
  49. Ceron W, Gruszynski Sanseverino G, de-Lima-Santos MF, Quiles MG. COVID-19 fake news diffusion across Latin America. Soc Netw Anal Min. 2021;11(1):47. doi:1007/s13278-021-00753-z
  50. Mostajo-Radji MA. Pseudoscience in the times of crisis: how and why chlorine dioxide consumption became popular in Latin America during the COVID-19 pandemic. Front Polit Sci. 2021;3(25). doi:3389/fpos.2021.621370
  51. Zavala-Flores E, Salcedo-Matienzo J. Pre-hospitalary medication in COVID-19 patients from a public hospital in Lima-Peru. Acta Méd Peru. 2020;37(3):393-395. doi:35663/amp.2020.373.1277
  52. Tenorio-Mucha J, Lazo-Porras M, Hidalgo AM, Málaga G, Cárdenas MK. Prices of essential drugs for management and treatment of COVID-19 in public and private Peruvian pharmacies. Acta Méd Peru. 2020;37(3):267-277. doi:10.35663/amp.2020.373.1560

Articles in Press, Corrected Proof
Available Online from 07 November 2021
  • Receive Date: 30 June 2021
  • Revise Date: 28 September 2021
  • Accept Date: 06 November 2021