|Year : 2020 | Volume
| Issue : 1 | Page : 60-65
Out of pocket expenditure and its associated factors in neonates admitted to neonatal intensive care unit of tertiary care government hospital of Agra District, Uttar Pradesh
Renu Agrawal1, Rudresh Negi2, Sunil Kumar Kaushal1, Sunil Kumar Misra3
1 Associate Professor, Department of Community Medicine, S.N. Medical College, Agra, Uttar Pradesh, India
2 Resident, Department of Community Medicine, S.N. Medical College, Agra, Uttar Pradesh, India
3 Professor and Head, Department of Community Medicine, S.N. Medical College, Agra, Uttar Pradesh, India
|Date of Submission||25-Jan-2019|
|Date of Decision||11-May-2019|
|Date of Acceptance||27-Jan-2020|
|Date of Web Publication||16-Mar-2020|
A-965/5, Indira Nagar, Lucknow, Uttar Pradesh
Source of Support: None, Conflict of Interest: None
| Abstract|| |
Background: Neonatal health remains a thrust area of public health, and an increased out-of-pocket expenditure (OOPE) may hamper efforts toward universal health coverage. Public spending on health remains low and insurance schemes few, thereby forcing impoverishment upon individuals already close to poverty line. Objective: To determine catastrophic health expenditure (CHE) in neonates admitted to the government neonatal intensive care unit (NICU) and factors associated with of out-of-pocket expenditure. Methods: This cross-sectional study was conducted in a governmental NICU at Agra from May 2017 to April 2018. A sample of 450 neonatal admissions was studied. Respondents were interviewed for required data. OOPE included costs at NICU, intervening health facilities, and transport as well. SPSS version (23.0 Trial) and Epi Info were used for analysis. Results: Of the 450 neonates analyzed, the median total OOPE was Rs. 3000. CHE was found among 55.8% of cases with 22% spending more than their household monthly income. On binary logistic regression, a higher total OOPE of Rs. 3000 or more was found to be significantly associated with higher odds of residing outside Agra (adjusted odds ratio [AOR] = 1.829), delay in first cry (AOR = 1.623), referral points ≥3 (AOR = 3.449), private sector as first referral (AOR = 2.476), and when treatment was accorded during transport (AOR = 1.972). Conclusions: OOPE on neonates amounts to a substantial figure and is more than the country average. This needs to be addressed sufficiently and comprehensively through government schemes, private enterprises, and public–private partnerships.
Keywords: Catastrophic health expenditure, neonate, out-of-pocket expenditure
|How to cite this article:|
Agrawal R, Negi R, Kaushal SK, Misra SK. Out of pocket expenditure and its associated factors in neonates admitted to neonatal intensive care unit of tertiary care government hospital of Agra District, Uttar Pradesh. Indian J Public Health 2020;64:60-5
|How to cite this URL:|
Agrawal R, Negi R, Kaushal SK, Misra SK. Out of pocket expenditure and its associated factors in neonates admitted to neonatal intensive care unit of tertiary care government hospital of Agra District, Uttar Pradesh. Indian J Public Health [serial online] 2020 [cited 2020 Apr 3];64:60-5. Available from: http://www.ijph.in/text.asp?2020/64/1/60/280764
| Introduction|| |
Neonatal period is a vulnerable time for child survival, and neonatal mortality contributes to 75.4% of infant and 61.5% of under-five mortality in India. Admission and deteriorating health of a neonate may lead to sudden and sometimes catastrophic expenses. Growing expenditure on health can give rise to further impoverishment of the already economically weaker sections of the society. Goal 3 (to ensure healthy lives and promote well-being for all at all ages) of Sustainable Development Goals (SDG), with Target 3.8 on universal health coverage, emphasizes the importance of all people and communities having access to quality health services without risking financial hardship.
According to the National Health Accounts, the out-of-pocket expenditure (OOPE) constitutes 62.6% of total health expenditure in India and 78.3% of total health expenditure in Uttar Pradesh. Increasing out-of-pocket spending results in catastrophic health expenditure (CHE). The global incidence of catastrophic spending at 10% threshold is increasing at an estimation of 9.7% in 2000, 11.4% in 2005, and 11.7% in 2010, with South Asia showing a higher increase at 11.98% in 2000, 12.01% in 2005, and 13.53% in 2010.
Central and state financing on health remains low in India; however, to mitigate the impact of OOPE, the Government of India has envisioned to increase health spending from the existing 1.15% to 2.5% of GDP by 2025 and has rolled out interventions such as Janani Suraksha Yojana, Janani Shishu Suraksha Karyakram (JSSK), Facility Based New Born Care, Home Based New Born Care, and Pradhan Mantri Jan Arogya Yojana, and Amrit Pharmacies and price capping as steps toward ensuring zero OOPE and improving access to healthcare.
Most of the research has been on the costs of maternal healthcare. Less has been done on child healthcare costs and almost nothing on the costs of neonatal care. Thus, to generate primary data on this novel and somewhat neglected niche, this research was planned with the objective of calculating the CHE incurred and enunciating the determinants of OOPE in neonates admitted to a tertiary care government neonatal intensive care unit (NICU) in Agra, Uttar Pradesh.
| Materials and Methods|| |
This cross-sectional observational study was conducted in the NICU of medical college of Agra from May 2017 to April 2018. It remains as the only fully functional government NICU at the tertiary care level at the time of the study in this area, with extensive catchment area of Agra and neighboring districts of Uttar Pradesh along with adjoining states of Rajasthan and Madhya Pradesh, and was hence chosen for the study. All neonates admitted to the NICU during the study period were included. However, those whose parents or guardians refused to give informed written consent, left against medical advice, or brought dead neonates were excluded.
From previous years' registers, it was estimated that the facility provided for the admission of approximately around 1080–1200 admissions per year. Neonatal admissions fulfilling the eligibility criteria were included in the study during a period of 1 year. Purposive sampling was employed and approximately three visits were made to the NICU in a week, and in each visit, approximately 50% of the enrolled neonates were randomly selected from the NICU register on the planned day of discharge to facilitate its completeness and accuracy. Since the entire process of data collection was completed solely by the corresponding author himself, there was a paucity of time as each interview took approximately 30–45 min.
Of the total 485 study subjects interviewed, 35 forms were excluded due to incompletion or inconsistent responses. Thus, 450 neonates were included for analysis.
A pretested, semi-structured questionnaire was used, and data were obtained through face-to-face interviews. Before the start of the interview, the respondents (parents/relatives) were clearly explained the purpose of study and the nature of questions in the questionnaire in their local language. It was emphasized that the interview would not affect the newborns' treatment at the NICU. Care was taken to have the mother or the primary caregiver as the respondent, and an easily understandable, informed written consent was taken in Hindi and confidentiality strictly maintained.
In this study, OOPE and CHE have been defined as follows:
OOPE – direct payments made by individuals to healthcare providers at the time of service use. This excludes any prepayment for health services, for example, in the form of taxes or specific insurance premiums or contributions and, where possible, net of any reimbursements to the individual who made the payments.
CHE represented as “large household expenditure on health:” greater than 10% (SDG 3.8.2_10) and greater than 25% of total household expenditure or income (SDG 3.8.2_25).
For the purpose of the study, the total OOPE was categorized as total expenses incurred on treatment (including investigation, medicines, and other consumables) and total expenses incurred on transport. The total expenditure on treatment was further classified into (i) treatment expenses at NICU and (ii) treatment expenses at other health facilities en route to NICU (including government and private facilities).
Data were analyzed using SPSS version (23.0 Trial) and Epi Info. Since the data were nonnormal (as ascertained from Shapiro–Wilk test), Mann–Whitney U-test and Kruskal–Wallis test were applied. The variables found statistically significant through these nonparametric tests were fitted into binary logistic regression model. For the purpose of binary logistic regression, the total OOPE was divided as <Rs. 3000 and ≥Rs. 3000, 3000 being the median value. P <0.05 was considered statistically significant. Median, interquartile range (IQR), and percentages were computed where required.
Ethical clearance was obtained from the Institute Ethics Committee (Ref No. IEC/2017/35). Permission was also sought from the officer in-charge of the NICU.
| Results|| |
Of total 450 neonates, three-fourth (75.5%) newborns were in the early neonatal period, with the mean age of admission being 5.3 ± 8.5 days. There were 62.7% of low birth weight newborns and 53.2% were preterm. Average length of stay at NICU was 6.04 ± 4.2 days. The male-to-female ratio was 1.8:1 with 85% Hindus and a preponderance of the other backward caste (53.5%). An almost equal rural to urban distribution (48.7% and 51.3%, respectively) was present with 29.1% of neonates seeking admission from other districts and states. Mean monthly family income was Rs. 12772.9.
The median total amount spent on transportation was Rs. 100 (IQR = 600) and 24.4% expended in the highest quartile of more than Rs. 600, with minimum individuals (8.2%) in the second quartile. The median amount spent on final transport was Rs. 50 (IQR = Rs 500), with the maximum amount being Rs. 5000. The median expenditure on treatment at the other referral facilities en route was Rs. 350 (IQR = Rs. 5000) with nearly half (44.0%) of individuals spending in the lowest quartile, the distribution being highly positively skewed. The maximum amount spent was Rs. 186,000. The treatment expenditure in the NICU varied between zero and Rs. 15,000, with the median being Rs. 1500 (IQR = Rs. 1700), and 24.2% spent in the highest quartile [Table 1].
|Table 1: Distribution of expenditure on sick neonates admitted to neonatal intensive care unit (n=450)|
Click here to view
The proportion of subjects with CHE at >10% of income and >25% of income was extremely high at 80.9% and 55.8%, respectively. The median total OOPE was Rs. 3000 (IQR = Rs 6725). More than one-fifth (22%) of the famalies spent more than their monthly family income as total out-of-pocket expenses. Further, 13% of families spent between 51% and 100% of their total family income as OOPE, and it represents a substantial financial burden on them.
Significantly, higher median total out-of-pocket spending was done in case of neonates who were not residing in Agra (Rs. 5000), completed term (Rs. 4000), out-born (Rs. 3337.50), delayed cry (Rs. 4300), partially immunized (Rs. 3500), initial referral from private sector (Rs. 5200), referral points >3 (Rs. 12,125), treatment given during transport (Rs. 6000), distance traveled between 6 and 30 km (Rs. 4050), and admission to NICU in the late neonatal period (Rs. 3625) [Table 2].
|Table 2: Total out-of-pocket expenditure of neonates according to sociodemographic and health care-related factors|
Click here to view
On binary logistic regression, the model was good fit (Hosmer and Lemeshow test not significant at P = 0.260) explaining 26.2% of the variance (Nagelkerke R square statistic = 0.262). Higher total OOPE of more than equal to Rs. 3000 was found to be significantly associated with higher odds of not residing in Agra (adjusted odds ratio [AOR] =1.829), completing full term (AOR = 1.638), delay in first cry (AOR = 1.623), referral points ≥3 (AOR = 3.449), private sector as first referral place (AOR = 2.476), and when treatment was accorded during transport (AOR = 1.972) [Table 3].
|Table 3: Factors associated with total out-of-pocket expenditure (≥Rs. 3000) by binary logistic regression analysis|
Click here to view
| Discussion|| |
Adequate financial protection through universal health coverage is one of the targets envisioned by the WHO in course of attainment of SDG by 2030 and an increased OOPE remains a stumbling block. Making the users of health services pay out of pocket for the services they receive has a potential dual effect at the population level impoverishing some households that choose to seek services and excluding others from seeking health care.
Others studies have reported sociodemographic profile of admitted neonates similar to the current study.,,, In the current study, 43.8% of neonates had no direct total expenditure on transportation and 48% did not spend directly on final transport either due to usage of government ambulances or personnel vehicle or walking (inborn neonates). The median total amount spent on transportation was Rs. 100 which is much lower than the transportation cost of Rs. 901 in research by Sharma et al. (2017) and may reflect the growing use of free ambulance transport services under JSSK. In our study, the median amount of money spent in other health facilities was Rs. 350 which was less than that expended in the NICU at Rs. 1500, indicating a lacuna for better affordability of governmental NICU for ailing newborns. In other health institutions, 24% of the neonates contributed in spending more than Rs. 5000 signifying augmented financial burden on the family.
The median amount expended in our governmental NICU was Rs. 1500. Srivastava et al. observed the mean amount spent in hospitalized neonates as Rs. 4993. Garg et al., Venkatnarayan et al., and Khowaja et al. observed the expenditure on hospitalized neonate in public NICU to be Rs. 400–500 per day per neonate, Rs 536.8 per day, and United States Dollar (USD) 22.3 per overnight stay, respectively. Bahurupi et al. reported an average expenditure of Rs. 1150.00 ± 919.23 on hospitalizations in government facility but included infant population. Research by Karambelkar et al. conducted in a private sector NICU reported the mean cost of care at USD 90.7/patient/day. Differences in expenditures may be due to variations in the study population, location, temporality quality of care, and smaller sample sizes.
The current study indicates that the median total OOPE for neonates is more at Rs. 3000 as compared to the national per capita OOPE at Rs. 2394 and that of Uttar Pradesh at Rs. 2396, suggesting that a stronger impetus in healthcare financing is required especially toward neonatal health. Sharma et al. (2017) found the median OOPE on hospitalization in Haryana was Rs. 8000 but included individuals of all age groups. Research by Bahurupi et al. observed median direct expenditure for hospitalization at Rs. 600 (300–2500). Saini et al. (2017) and Sahu and Bharati reported mean OOPE in hospitalized neonates at USD 12.49 ± 21.15 and median at Rs. 1840 (1000–2500). Differences in the study period, population, and methodology may account for discordance in these studies.
CHE on neonates at >10% of income and >25% of income was at 80.9% and 55.8% in the current study, which is much higher than CHE for the general population at 17.3% and 3.9% according to Global Monitoring Report on tracking universal health coverage. Similar to our study, Singh et al. observed CHE at 56.6% but consisted largely of adult population. Pandey et al. (2018) similarly reported higher (AOR = 1.76 [1.65–1.88]) risk of CHE in household with children but no older people, as compared to households with no children or older people. Sharma et al. (2015) found the median OOPE on hospitalization in Haryana was Rs. 8000 but included individuals of all age groups. Thus, more households are becoming impoverished as a consequence of health expenditure on neonates as compared to the population in general, thereby a pro-active, robust financial safety net is the need of the hour for these vulnerable newborns. Further, risk pooling can protect households from facing catastrophic financial consequences of illness. Total OOPE was more than earnings in 22% of the household, contrary to the findings by Srivastava et al., where it was more than three-quarter, but their sample size was very small.
In the initial analysis of the current study, significantly higher median total out-of-pocket spending was in case of neonates who were not residing in Agra, completed term, out-born, delayed cry, partially immunized, initial referral from private, referral points >3, treatment given during transport, distance traveled between 6 and 30 km, and admission in NICU in the late neonatal period. However, on logistic regression, factors such as site of delivery, total distance traveled, and age at NICU admission which were initially statistically significant lost their significance and may be due to negation of confounders and adjustment during regression analysis. On binary logistic regression, higher total OOPE was found to be significantly associated with higher odds of not residing in Agra, term neonate, delay in first cry, referral points ≥3, private sector as first referral place, and when treatment was accorded during transport. In congruence with this study, Sahu and Bharati in their research observed no association between OOPE and gender. In contrast, Mahumud et al. and Brinda et al. concluded on regression analysis age and gender to be the predictors of OOPE. Deviation from these studies may be on account of a different study setting and inclusion of all age groups or geriatric population.
A relative large sample of neonates, data collection on planned day of discharge which is likely to reduce recall bias, data collection done by a single investigator and generation of neonate specific data on OOPE are some of the strengths of this study. Some limitations of the study are that it does not take into account the indirect costs (such as loss of wages, travel time, waiting time), intangible costs (pain of disease, patient stress and anxiety, and family stress and anxiety), sources of financing, detailed distribution pattern of OOPE, restricts itself to government NICU, and inability to include all admitted neonates during study period due to constraints of resources. CHE may be reduced by extending population coverage, protecting the poor and disadvantaged, designing benefits package, and deciding on the level of cost-sharing by patients.
| Conclusions|| |
The study highlights high costs on treatment of neonates leading to catastrophic expenditure, indicates the outlay in transportation, and enunciates some factors influencing OOPE. Thus, bridging this spending through strengthened service delivery, decreasing unnecessary referrals, and cashless care may be some of the means to mitigate overburdening of financial risks.
We acknowledge all possible assistance provided by the Department of Paediatrics and are humbly thankful to all the participants for their cooperation.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Carlo WA. Overview of mortality and morbidity. In: Kleigman RM, Stanton BF, Geme JW 3rd
, Schor NF, Behrman RE, editors. Nelson Textbook of Pediatrics. 19th
ed. Philadelphia: WB Saunders, Elsevier; 2011. p. 87, 532.
Tracking Universal Health Coverage: 2017 Global Monitoring Report. Licence: CC BY-NC-SA 3.0 IGO. World Health Organization and International Bank for Reconstruction and Development the World Bank; 2017.
National Health Systems Resource Centre. National Health Accounts Estimates for India (2014-15). New Delhi: Ministry of Health and Family Welfare, Government of India; 2017.
Wagstaff A, Flores G, Smitz MF, Hsu J, Chepynoga K, Eozenou P. Progress on impoverishing health spending in 122 countries: A retrospective observational study. Lancet Glob Health 2018;6:e180-e192.
Brearley L, Mohamed S, Eriyagama V, Elwalagedara R, Rannan-Eliya RP. Impact of Maternal and Child Health Private Expenditure on Poverty and Inequity: Review of the Literature on the Extent and Mechanisms by which Maternal, Newborn and child Healthcare Expenditures Exacerbate Poverty with Focus on Evidence from Asia and the Pacific Mandaluyong City. Philippines: Asian Development Bank; 2012.
Xu K, Evans DB, Kawabata K, Zeramdini R, Klavus J, Murray CJ. Household catastrophic health expenditure: A multicountry analysis. Lancet 2003;362:111-7.
Mehta N, Sharma MK. Correlation of acute physiological parameters with immediate outcomes among neonates transported to special care newborn unit: A prospective study. Indian J Child Health 2018;5:280-3.
Rakholia R, Rawat V, Bano M, Singh G. Neonatal morbidity and mortality of sick newborns admitted in a teaching hospital of Uttarakhand. CHRISMED J Health Res 2014;1:228-34. [Full text]
Kotwal YS, Jan FA, Yatoo GH, Kotwal S. Neonatal profile and outcome of the neonates admitted in NICU: A hospital based prospective study. Int J Sci Res 2018;7:98-101.
Mishra AK, Panda SC. Status of neonatal death in sick newborn care unit of a tertiary care hospital. Int J ContempPediatr 2017;4:1638-43.
Sharma D, Prinja S, Aggarwal AK, Bahuguna P, Sharma A, Rana SK. Out-of-pocket expenditure for hospitalization in Haryana State of India: Extent, determinants and financial risk protection. Indian J Med Res 2017;146:759-67.
] [Full text]
Srivastava NM, Awasthi S, Agarwal GG. Care-seeking behavior and out-of-pocket expenditure for sick newborns among urban poor in Lucknow, Northern India: A prospective follow-up study. BMC Health Serv Res 2009;9:61.
Garg P, Krishak R, Shukla DK. NICU in a community level hospital. Indian J Pediatr 2005;72:27-30.
Venkatnarayan K, Sankar MJ, Deorari A, Krishnan A, Paul VK. A micro-costing model of neonatal intensive care from a tertiary Indian unit: Feasibility and implications for insurance. Indian Pediatr 2014;51:215-7.
Khowaja AR, Mitton C, Qureshi R, Bryan S, Magee LA, von Dadelszen P, et al
. A comparison of maternal and newborn health services costs in Sindh Pakistan. PLoS One 2018;13:e0208299.
Bahurupi YA, Bojja SS, Boratne AV, Datta SS. Household expenditures on illnesses during infancy in a rural community: A cross sectional study from Pondicherry. Natl J Community Med 2017;8:506-11.
Karambelkar G, Malwade S, Karambelkar R. Cost analysis of healthcare in a private sector neonatal intensive care unit in India. Indian Pediatr 2016;53:793-5.
Saini AG, Bharti B, Gautam S. Healthcare behavior and expenditure in an urban slum in relation to birth experience and newborn care. J Trop Pediatr 2012;58:214-9.
Sahu KS, Bharati B. Out-of-Pocket health expenditure and sources of financing for delivery, postpartum, and neonatal health in urban slums of Bhubaneswar, Odisha, India. Indian J Public Health 2017;61:67-73.
] [Full text]
Singh T, Roy P, Jamir L, Gupta S, Kaur N, Jain DK, et al
. Assessment of universal healthcare coverage in a district of North India: A rapid cross-sectional survey using tablet computers. PLoS One 2016;11:e0157831.
Pandey A, Ploubidis GB, Clarke L, Dandona L. Trends in catastrophic health expenditure in India: 1993 to 2014. Bull World Health Organ 2018;96:18-28.
McIntyre D, Thiede M, Dahlgren G, Whitehead M. What are the economic consequences for households of illness and of paying for health care in low- and middle-income country contexts? Soc Sci Med 2006;62:858-65.
Mahumud RA, Sarker AR, Sultana M, Islam Z, Khan J, Morton A. Distribution and determinants of out-of-pocket healthcare expenditures in Bangladesh. J Prev Med Public Health 2017;50:91-9.
Brinda EM, Rajkumar AP, Enemark U, Prince M, Jacob KS. Nature and determinants of out-of-pocket health expenditure among older people in a rural Indian community. Int Psychogeriatr 2012;24:1664-73.
Yousefi M, Assari Arani A, Sahabi B, Kazemnejad A, Fazaeli S. Household health costs: Direct, indirect and intangible. Iran J Public Health 2014;43:202-9.
Xu K, Evans DB, Carrin, G, Aguilar-Riverra AM. Technical Briefs for Policy-Makers Designing Health Financing Systems to Reduce Catastrophic Health Expenditure; 2005. Available from: https://www.who.int/health_financing/pb_2.pdf
. [Last accessed on 2019 Oct 28].
[Table 1], [Table 2], [Table 3]