Introduction:

Human life is productive for a nation if the person bears good health. For the smooth survival and general wellbeing of all people, good health is essential. A healthy body and brain can be very productive for a nation. Many factors are responsible for representing a better statistic of a nation with a healthy population. The linkages between health and development have been well acknowledged, and health may not be regarded as an end product of development but a significant contributor to a nation's development process [1]. And to have a healthy population, easy access and utilization of healthcare services are significant. In this regard, the government can play a vital role by stating clearly its motive to have a healthy population by spending the necessary amount on health infrastructure in the nation. Efficient and better provision of healthcare services is the key to improving health conditions and economic growth and development in countries like India [2]. A sufficient infrastructure will always ensure the motive to a great extent. A nation cannot develop without proper development in social infrastructure. Efficient and sound health infrastructure is an important determinant of improved health status people [3]. Public healthcare services significantly influence people's health status, and public healthcare infrastructure is one of the key factors affecting health outcomes in a nation. Providing proper healthcare services is one of the main objectives of national planning. And to do this, a strong healthcare infrastructure and an adequate number of physicians, nurses, and other healthcare workers are required. Also, healthcare infrastructure is essential for analyzing a country's health policies and welfare mechanism [4]. If a country's health system fails to give its people the appropriate care, the population suffers significantly despite these.

The Indian health care sector was and still is suffering from various hurdles in achieving its goal of having a healthy population. It also bears much importance from the employment perspective of the nation, where it can generate a huge number of employment opportunities right from a cleaner to the higher official staff to manage everything. But the nation’s health care system is often characterized by low spending on health care, high out-of-pocket health expenditure, lack of adequate health infrastructure, insufficient health manpower and lack of quality health care services owing to a lower infrastructure which is not at all good for a health sector. Even though India has made significant economic progress, public expenditure on healthcare in the country has not improved since the early 1990s [5]. One primary reason for India’s low performance in various health indicators is the lack of systematic investment by the government [6]. India is one of the countries with low healthcare spending since India has spent an average of 1% of GDP on healthcare over the years. Following the Covid-19 outbreak, India's health expenditure increased significantly, reaching 2.1 % of GDP for the first time. Following the Covid-19, India’s spending towards healthcare has witnessed a rise of nearly 73 % from almost 2.7 lakh crore in pre-Covid situation to 4.72 lakh crore in 2021-22 (Economic Survey, 2021-22). The United States of America spends much more on healthcare (16.77%). Norway, which ranked second among 191 countries on the 2021 UNDP Human Development Index, spends more than 10 % of its GDP on healthcare.

Any type of health emergency may be managed by a strong public healthcare system. The world has already seen several different health crises, with Covid-19 being the most recent. The pandemic has put the world as a whole into previously unseen crises. Yet, many countries have been able to effectively tackle the pandemic due to their well-equipped and adequate health infrastructure. Even after handling more than 10 million COVID-19 cases across the country, India is still facing the shortage of physical infrastructure but also shortage of doctors, health care professionals, and medical equipments. Assam, the North-eastern state of the country, with almost 200000 confirmed COVID-19 cases has become a hotspot among the north –eastern region. The state has 24,718 beds, 1209 ICU beds, 604 ventilators, and 1226 hospitals as per National Health Profile (NHP, 2019) which is not sufficient even in a non-pandemic situation. The government of Assam reserved 70 % of resources from private health sectors for COVID-19, creating panic in the state for other patients. This scenario is not only for Assam but is the same in all the states of the country. Along with inadequate infrastructure in the state, unequal distribution of health care facilities is also observed among the districts.

Though the government is trying, it is still not easily achievable since 70 % of our population lives in rural areas. The rural population is always observed to have difficulty accessing health care services. The utilization of health care services in rural areas has been an issue over the years owing to lower infrastructure. Rural populations mostly rely on public health care services. In some cases of illness, they find it very difficult to access health services from the public health system and have to go for private health institutions. Private health care services are mostly expensive and sometimes cost them immensely, which puts financial pressure on the household. Dominance of private sector contributes to inequities in accessibility and utilization of healthcare services [7]. High cost of medical services leads to high out-of-pocket expenditure. High out-of-pocket (OOP) expenditure poses barriers to healthcare access [8]. In the rural areas, health institutions are set up at different level, yet this isn’t up to the mark. In terms of accessibility, there is a huge gap between the rural and urban populations. There is easy access by the urban population towards the health care services as private health institutions are also available along with the public health sector. The majority of the Indian population still depends on private health service providers; in rural areas 52 % people sought treatment from private sectors, whereas in urban areas 35 % people went to government hospitals, (NHP, 2019).

Materials and Methods:

The study's main objectives is to analyze the inter-district disparities in health infrastructure in Assam. The study also tries to categorize the districts of the state based on their development in terms of health infrastructure. The present study is focused on public health infrastructure at district level in the state Assam for the year 2020-21 and solely based on secondary data. The required secondary data have been collected from various government publications, including Census of India (2011), Economic Survey of Assam (various issues) and Statistical Handbook of Assam 2021. Attempt has been made to study the inter district variation in public health infrastructure in the state Assam. A composite index is constructed to examine the extent of variations using appropriate indicators. The composite Health Infrastructure Index (HII) gives relative information regarding each district of Assam public health infrastructure. The public health infrastructure of Assam has been discussed in this study with following variables-

1. Number of hospital beds per lakh population (H₁)
2. Number of Primary Health Centre (PHC) per lakh population (H₂)
3. Number of Sub Centre (SC) per lakh population (H₃)
4. Number of Community Health Centre (CHC) per lakh population (H₄)
5. Number of doctors per lakh population (H₅)
6. Number of district hospitals per lakh population (H₆)
7. Number of Pharmacist per lakh population (H₇)
8. Number of Nurses per lakh population (H₈)
9. Number of Sub-divisional hospital per lakh population

Principal Component Analysis (PCA) is adopted to construct a composite index to measure in different health infrastructure variables. PCA involves a mathematical procedure that transforms number correlated variables to uncorrelated variables to reduce the dimension of the data. In mathematical term from an initial set of n variables, PCA creates uncorrelated indices or components, where each element is a linear weighted combination of the primary variables [9]. The value of selected nine indicators for the year 2020-21 of all 33 districts of Assam were collected and tabulated. The tabulated values of those indicators were modified in term of per lakh population by using following formula-

(Total No of a particular health infrastructure of the district)/(Total population of the district) x 100000

The modified tabulated value of the indicators are normalized using Min-Max normalization technique [10] [11], and the normalized values are came up within the range of 0-1.

Normalized value =(Actual value of Indicator H₁-Minimum value of indicator H₁)/(Maximum value of indicator H₁-Minimum value of indicator H₁)

Health Infrastructure Index (HII) is constructed by the statistical methods of weighted mean approach [3].

HII_j =(∑HijWi)/(∑Wi)

Where HII_j= Health Infrastructure index of j^th district

H_ij= Normalized value of i^th variable on j^th district

W_i= Weight of the i^th variable

∑ W_i= Sum of weights

On the basis of HII, relative positions of each district have been given by assigning rank to the given district.

Relative weight of the variables have been assigned as, [3][12]

W_i =F_ikV_k

Where W_i is the weight of the i^th variable

F_ik is the factor loading of i^th variable on k^th variable

V_k is the variation explained by k^th factor

From the obtained index the districts were classified in four categories based on mean (μ) and standard deviation (σ) of the index.

High Level Development if HII≥μ+σ

High Middle Level Development if µ< HII< µ+σ

Low Middle Level Development if µ-σ < HII< µ

Low Level Development if HII≤ µ-σ

Results and Discussion

Health status in Assam and India

The primary goal of a nation’s health system are improving and maintaining good health of its population. various health indicators, such as the crude birth rate, crude death rate, life expectancy at birth, infant mortality rate (IMR), maternal mortality rate (MMR), and others, can depicts a picture of the health of the people of a country. The health status of the Indian people has significantly improved over time when measured in terms of these widely recognized health indicators. Though India has made progress on the health front of its population, there exist wide variation between and within states [13].

Assam's population's health has significantly improved over time like India's. Assam has lower CBR, CDR, and neonatal mortality compared to the national level. The IMR is also lower in Assam than in India. The IMR has finally reduced to a level below the national level for the first time after having one of the highest IMR in the nation for several years. The IMR for Assam dropped from 47.6 in 2015–16 to 31.9 in 2019–21. Neonatal mortality also has improved in the state, falling from 32.8 to 22.5, which is lower than the national level. Under 5 mortality is also lower in Assam but MMR is very high in the state than in the national level. Maternal mortality in India decreased from 122 in 2015–17 to 103 in 2017–19. Even though Assam's MMR decreased from 215 in 2016–18 to 205 in 2017–19, it still ranks among the states with the highest MMR in the country. India's life expectancy at birth increased to 69.7 in 2015–19, although it is still below the global average of 72.6, which is considered to be a key indicator of human development. Assam’s LEB is 67.5 years, and there is an almost eight-year difference in the LEBs in rural and urban areas in the state. The LEB at birth is the highest in Delhi (75.9 years) and whereas it is lowest in Chhattisgarh (63.7 years).

Health infrastructure in Assam

The number of various public health institutions in Assam in 2019 and 2021 is shown in table 3.4. The number of PHCs, SCs, and CHCs was 704, 4034, and 179 in 2019, considered the pre-Covid condition. Except for district hospitals and sub-divisional hospitals, the number of healthcare facilities significantly increased in 2021. The table shows that from 6 in 2019 to 8 medical colleges in 2021, the number of medical colleges—the highest level of the public healthcare delivery system has also increased. An increase in health institution in the state in the crucial time of health emergency due to Covid-19 have helped the state government to deal with the pandemic.

Here an attempt has been made to study Assam's inter-district variations in public health infrastructure by constructing a composite index. Since health infrastructure combines various health indicators, a composite Health infrastructure index has been constructed using PCA for 2020-21. Principal component analysis is a multivariate approach that converts several correlated variables into several linearly uncorrelated variables [14]. To identify underlying dimensions or factors, factor analysis has been used. Factors have been extracted using principal component analysis approach of factor analysis.

To evaluate the number of factors or principal components, it is necessary to see whether the present data is suitable for PCA or not. To examine sample adequacy, Kaiser-Meyer-Olkin (KMO) test is used. The data is considered suitable for factor analyses as KMO value is 0.755. Bartlett’s test is an another indicator of judging that whether original variables are sufficiently correlated or not. The chi-square test statistics is 182.355 and the corresponding p-value is under the acceptance level and thus the data is suitable for PCA (Table 3)

Decision for number of components

To identify the principal components or number of factors, the present study adopts eigenvalue-one criterion [10]. According to this criterion, factors having Eigen values greater than one are selected as principal components.

To identify the principal components or number of factors, the present study adopts eigenvalue-one criterion [10]. According to this criterion, factors having Eigen values greater than one are selected as principal components

Initial eigenvalues reveals that only the first two components have eigenvalues greater than one; hence, two factors are extracted from nine selected health infrastructure indicators for 33 districts of Assam, which explains 66.84 % variations. Here and hence initial nine indicators are reduced to these two factors.

Two factors are extracted from nine selected health infrastructure indicators for 33 districts of Assam. These two factors explain 66.84 % inter-district variation. The first factor explains 50.529 % variation and most important indicators for the first factor that come out are number of Primary Health Centres (PHC) per lakh population, number of Sub Centres (SC) per lakh population, number of Community Health Centres (CHC) per lakh population, number of doctors per lakh population, number of Pharmacists per lakh population, number of Nurses per lakh population and number of Sub-divisional hospitals per lakh population. The second factor accounts for 16.311% of total inter-district variations and have indicators such as number of hospital beds per lakh population and number of district hospitals per lakh population.

Health infrastructure index at district level for the districts of Assam has been constructed by applying Principal Component Analysis. HII for the districts are presented in Table 6. It is seen that the value of index varies within the range of 0.063 to 0.755. Dima Hasao district is at the top with the highest value of 0.755. Majuli, Sivasagar, Nalbari and Chirang districts are next to Dima Hasao with the HII value 0.647, 0.464, 0.421 and 0.4 respectively. Hojai district has the lowest HII value (0.063). The bottom five districts are Tinsukia (0.1520, Cachar (0.162), South Salmora (0.177) and Biswanath (0.196).

From the obtained index the districts are classified in three categories based on mean (µ) and standard deviation (σ) of the index. Classification of districts on the basis of mean and standard deviation of the composite indices provides a more meaningful characterization of various stages of development [15]. Districts are classified into four levels of development- high, high middle, low middle and low [16]. Categorization of the districts according to their HII is presented in Table 7.

The high level of development category has three districts, high-middle development category has nine districts, 19 districts are in the category of low-middle development and two districts are in the low-level development group. Three districts, namely Dima Hasao, Majuli and Sivasagar are in the high level development group, and these three districts cover about 9.64% area and 3.44% population of the state. Nine districts namely Chirang, Golaghat, Jorhat, Kamrup Metro, Karbi Anglong, Kokrajhar, Lakhimpur, Nalbari, West Karbi Anglong are in the group high middle development and cover 32.2% area and 23.67% population. More than half of the population (65.65%) live in the districts categorized as low middle developed covering 51.6% area of the state and this group has districts namely Baksa, Barpeta, Biswanah, Bongaigaon, Cachar, Charaideo, Darrang, Dhemaji, Dhuburi, Dibrugarh, Goalpara, Hailakandi, Kamrup Rural, Karimganj, Marigaon, Nagaon, Sonitpur, South Salmara, Udalguri. Two districts namely Hojai and Tinsukia are considered as low developed districts occupying 6.64% area and 7.24% population of the state.

Conclusion

One of the main goals of national planning is to guarantee adequate health care services. And to do this, there must be sufficient medical infrastructure and enough physicians, nurses, and other medical professionals. The population suffers greatly if, despite all of these, the nation's health institution cannot give its citizens the appropriate care. The public health care sector is essential for the population's wellbeing in a country like India, which is still growing and has about 70% of its population residing in rural areas. An effective public health care system is capable of dealing with any kind of health crisis. The rural population is always observed to have difficulties in accessing health care services. They mostly have to rely on the public health care services which provide them the needed treatment. But if they suffer from serious issues, they find it very difficult to access the government hospitals far from them. Over the years, private health care services are expanding, mostly in urban areas. Though the rural population can visit the private centres expecting a better treatment, it cost them immensely, even sometimes making them lose everything they have. People opt for private hospitals not because they can afford them, but because sometimes they are bound as the government hospitals cannot provide the same treatment. The high cost of medical services leads to higher out-of-pocket expenditure. It is even worse in the case of people who are not covered under any health care schemes by the government or any other insurance company. It puts a much heavier burden upon them. The major issues are the shortages of hospital beds and human resources at the national and state levels. Governments are putting their efforts into strengthening public health infrastructure to fight COVID-19. The central government approved 5000 crores to improve the healthcare system in the post COVID-19 period. The study has noticed variations in health infrastructure among the various districts of Assam, reflecting the shortage of health infrastructure-physical and human in rural and remote areas of the state. The majority of the districts fall in the low middle developed category necessitating a suitable policy framework to improve health infrastructure. And to eliminate these variations and develop the state as a whole, careful planning is required.

References

1. Lyngdoh LM. Inter-State Variations in the Rural Healthcare Infrastructure in North-East India. The NEHU Journal. 2015;XIII(2):31-48.
2. Banerjee A, Deaton A, Duflo E. Wealth, health, and health services in rural Rajasthan. American Economic Review. 2004 May 1;94(2):326-30.
3. Kumar G, Singh J. Health infrastructure disparities in Punjab: An inter-district analysis. Journal of Infrastructure Development. 2020 Jun;12(1):25-38.
4. Taqi M, Bidhuri S, Sarkar S, Wani SA, Wangchok P. Rural Healthcare Infrastructural Disparities in India: a Critical Analysis of Availability and Accessibility. J. Multidiscip. Res. Healthcare. 2017;3(2):125-49. Available from: https://jmrh.chitkara.edu.in/index.php/jmrh/article/view/25
5. Yadav J, John D, Menon GR, Allarakha S. Out-of-Pocket payments for delivery care in India: do households face hardship financing?. Journal of Health Management. 2021 Jun;23(2):197-225.
6. Mukherjee AN, Karmakar K. Untreated morbidity and demand for healthcare in India: an analysis of national sample survey data. Economic and Political Weekly. 2008 Nov 15:71-7.
7. Verma CS, Singh S, Ranjan A, Sundararaman T. Social and systemic determinants of utilisation of public healthcare services in Uttar Pradesh. Econ Polit Wkly. 2018 Nov 17;53:45.
8. Prinja S, Kumar MI, Pinto AD, Jan S, Kumar R. Equity in hospital services utilisation in India. Econ Polit Wkly. 2013 Mar 23:52-8.
9. Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy and Planning. 2006 Nov 1;21(6):459-68..
10. OECD. Handbook on constructing composite indicators: Methodology and user guide. 2008. Retrieved from https://www.oecd.org/std/42495745.pdf
11. Goel MM, Garg I. Construction of health infrastructure index in Haryana: An econometric approach. Journal of Technology Management for Growing Economies. 2018;9(1):103-23.
12. Kaur P, Dhillon SS. An Inter-State Analysis of Economic Development in India. Journal of Economic and Social Development. 2015;XI(2):1
13. Meher R, Patro RP. Interstate Level Comparison of People’s Health Status and the State of Public Health Care Services in India. Journal of Health Management. 2014;16(4):489-507
14. Mahmoudi MR, Heydari MH, Qasem SN, Mosavi A, Band SS. Principal component analysis to study the relations between the spread rates of COVID-19 in high risks countries. Alexandria Engineering Journal. 2021 Feb 1;60(1):457-64.
15. Rai SC, Bhatia VK. Dimensions of regional disparities in socio-economic development of Assam. J. Ind. Soc. Agril. Statist. 2004;57:178-90.
16. Mishra PK. Socio-economic Development Disparities Across Indian States: A Principal Component Analysis. Journal of Economic Policy and Research. 2019 Apr 1;14(2):80-8.