quantifying accessibility to health care using two step floating catchment area method 2sfca a case study in rajasthan

Peer-review under responsibility of the Department of Civil Engineering, Indian Institute of Technology Bombay doi: 10.1016/j.trpro.2016.11.080 ScienceDirect 11th Transportation Plannin

Transportation Research Procedia 17 ( 2016 ) 391 – 399

2352-1465 © 2016 Published by Elsevier B.V This is an open access article under the CC BY-NC-ND license

( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).

Peer-review under responsibility of the Department of Civil Engineering, Indian Institute of Technology Bombay

doi: 10.1016/j.trpro.2016.11.080

ScienceDirect

11th Transportation Planning and Implementation Methodologies for Developing Countries,

TPMDC 2014, 10-12 December 2014, Mumbai, India Quantifying Accessibility to Health Care Using Two-step Floating Catchment Area Method (2SFCA): A Case Study in Rajasthan

Shalini Kanugantia, A K Sarkarb* and Ajit Pratap Singhc

a Research Scholar, Department of Civil Engineering, Birla Institute of Technology and Science Pilani, 333031,India

b Senior Professor, Department of Civil Engineering, Birla Institute of Technology and Science Pilani, 333031,India

c Professor, Department of Civil Engineering, Birla Institute of Technology and Science Pilani, 333031,India

Abstract

Spatial isolation of the villages from health facilities is a concern in rural areas Quantifying accessibility to health care helps in interpreting the performance of health care system in a region Thus in this paper a technique named two-step floating catchment area (2SFCA) method was used to measure level of accessibility GIS platform was used to execute 2SFCA method A case study was carried out in Alwar district of Rajasthan to quantify the accessibility of different habitations to health care The outcome of the study helps the policy makers to identify the habitations not having access to health care and also to know the level of accessibility of the villages having access to health care This will help to take appropriate measures in terms of improving road network and construction of new health care centers to improve the overall health care facilities in the district

© 2015 The Authors Published by Elsevier B V

Selection and peer-review under responsibility of the Department of Civil Engineering, Indian Institute of Technology Bombay

Keywords: Accessibility; 2SFCA;

1 Introduction

The National Rural Health Mission (NRHM) of India as per the 12th Plan document of the Planning Commission aims to provide impelling health care to the rural population, especially to the remote and most disadvantaged groups This goal is proposed to be reached by various methods such as improving access, enabling community ownership and demand for services, strengthening public health systems for efficient service delivery, enhancing

* Corresponding author Tel.: +91-1596-515621

E-mail address: aksarkar@pilani.bits-pilani.ac.in

© 2016 Published by Elsevier B.V This is an open access article under the CC BY-NC-ND license

( http://creativecommons.org/licenses/by-nc-nd/4.0/ ).

Peer-review under responsibility of the Department of Civil Engineering, Indian Institute of Technology Bombay

equity and accountability and promoting decentralization While providing good medical facilities in the rural areas

is important, to make them accessible in terms of distance and travel time is a greater challenge

Accessibility is defined as the easiness and comfort with which a personal reaches a facility or an activity from a particular location Access to healthcare is considered as a crucial developer of health of total population (Guagliardo, 2004) Quick reach for the primary care can prevent or lessen unneeded costly specialty care (Lee 1995, Luo 2004)

In order to assure access to health care, planning commissions and policy decision makers require definite and reliable measures of accessibility values thus that appropriate health care shortage areas can be analyzed and a policy decision can be taken accordingly to pacify the problem

Accessibility often refers to spatial or physical accessibility and is concerned with the complex relationship between the spatial separation of the population and the supply of health care facilities Accessibility is influenced by both spatial factors (geographical location and travel distance) and non-spatial parameters (socio-economic status, populations health status, financial status, perception about health and health care system and traditional customs (Aday and Andersen,1974; khan 1992) However, the two most significant factors influencing access to health care are health centers supply and population demand (Luo, 2004)

The traditional gravity model is used to find the regional accessibility The gravity model is formulated to factor interaction between supply and demand located in different regions with distance decay (Guagliardo, 2004) The downside of gravity model is it requires more data inputs: location of supply and demand (Joseph and Phillips,1984), traffic network, and travel time analysis between supply and demand Moreover it requires travel friction factor or distance decay function which is to be determined by physician and patient interaction data and also it varies from region to region Acquiring this data costs a lot of time and money, which impedes to develop two-step floating catchment area method (2SFCA) 2SFCA was first proposed by Radke and Mu (2000) but later altered by Luo and Wang (2003a, b) It is a special case of gravity model and is found to be an appropriate tool as it measures accessibility

in two steps by considering both demand and supply It not only has most of the benefits of a gravity model, but is also easy to use, interpret and understand The 2SFCA method has been used in a number of recent studies measuring health care accessibility (e.g., Guagliardo, 2004; Albert and Butar, 2005; Yang et al., 2006; Wang, 2007; Wang et al., 2008)

The objective of this study is to provide a methodology to find accessibility to health care in rural areas using a simplified gravity model i.e., 2SFCA method Although many researchers have used this method to find access to health care it has been noted that the studies were limited only to urban areas There was a need to study the feasibility

of the methodology in Indian rural areas Accordingly a case study has taken up in Alwar district of Rajasthan

2 Methodology

Two-step floating catchment area method (2SFCA) enhanced the earlier floating catchment area method, which catches area twice based on population demand and health care supply It is form of physician to population ratio It

is better explained in the following steps (Luo and Yi, 2009)

Step 1 : Health centre (HC) to population (P) ratio

For each health centre location j, search for all the population or habitation locations (k) that are within the threshold travel distance (d0 ) from a given location j and the computation of heath care to population ratio, Rj, within the catchment area:

0

{ kj }

j j

k

HC

R

P

Step 2: Accessibility Index of population

0

{ij }

F

In the first step the influence or service area of a health facility is to be determined in terms of distance using the existing road network This also helps to determine the total population proportion served by each individual health centre However, there is a possibility that a village comes under the service area of more than one health centre Thus the consequence of overlapping of service areas is accounted for in the second step The accessibility level of each village is then determined in the second step by summing up the initial ratios falling within the acceptable or perceived

and is at a more advantageous position than other population Furthermore this helps in identifying the individual and cluster of villages having no or poor access to health care facilities

3 Case Study

3.1 Study area and data collection

Keeping the facts in view, a case study has been carried out in Alwar district of Rajasthan to quantify the accessibility

of different habitations to health care The preliminary data including the map of Alwar district have been obtained from National Rural Roads Development Agency (NRRDA) Total number of habitations in district are 2217 and accessibility of these habitations are measured to 81 health care centers which are scattered all over the district as shown in Figure 1 The figure shows the existing roads network with all categories of roads and highways, namely State Highway (SH), Major District Roads (MDR), Other District Roads (ODR) and location of villages with block boundaries in different colors

In the first step of analysis ArcGIS 10.0 has been used for geo-referencing and to digitize the location of villages, potential health care locations and given road network

3.2 Measuring accessibility

The crucial point in measuring accessibility is defining distance measurement There are different types of distances such as Euclidean distance, Manhattan distance, time-distance and network distance of all the most realistic and precise measure is time-distance i.e., travel time However it has been observed that acquiring travel time data for Indian rural condition is difficult as people might be using different modes of travel Therefore it has been decided that network distance will be good approximation of time-distance

Pk the population at location k whose centroid falls within the catchment (dkj ≤ d0)

dkj the travel distance between k and j

the accessibility of population at a given location i to health care based on the two step floating catchment

area method The superscript F represents it’s the calculation formula based on 2SFCA method

Rj health care to population ratio at location j whose centroid falls within the catchment (dij ≤ d0)

dij the travel distance between i and j

Fig.1 Map of Alwar District With Health Centres and Habitations

3.3 Defining Catchment area

3.3.1 Service area (or) Influence distance

As mentioned in the methodology in the first step of 2SFCA method the proportion of population served by each health centre within the service area should be calculated The service area or influence area is determined based on the threshold distance that a health centre can serve The quality of service provided by a health centre depends on the infrastructure available and the quality of physicians and their availability The Government of India has developed Public Health Standards (IPHS) in this regard However, collecting all the above mentioned data is time consuming and not feasible in some regions and thus the quality of service has not been considered in this study It was decided

to collect the data of trip length of different villages visiting to the health centers and volume of interactions The data has been collected in 10 health centres in the study area and the volume of interactions between them has been plotted

as shown in figure 2 From the scatter plot it might be observed that with distance the number visiting a health centre decreases gradually and hardly any villager travel beyond 8km Accordingly, it was decided to consider 8km as the threshold distance in this study

Fig 2 Volume Interactions between Health center and habitations

3.3.2 Acceptable distance

It has been noted from the literature that the size of the catchment does not have to be the same for step 1 and step 2 (Mao et al., 2011) Health center may serve a large area, requiring large catchment for step 1 but the population may not be willing to travel larger distances but might be forced because of their captivity Hence it was decided to find perceived distance of villagers to go to health care The acceptable distance is defined as the distance within which the villagers feel easy and comfortable enough to travel It varies with factors such as population density, geographical terrain, socio-economic factors of the individuals and public transport availability in the locality etc., In consultation with few selected villagers and local government officials it was considered that perceived acceptable road distance

to health care was 8Km and accordingly the catchment area for both the steps was considered as 8Km

GIS network analysis tool (closest facility) was used to execute the 2SFCA method For a location of a facility,

population falling within the influence distance This is obtained by adding the population of all the villages that are within 8km road distance from a health centre Next the catchment areas of all the health centers in the study area were obtained using service area tool in network analysis Different shapes of catchment areas for different health centers were observed as the influence distance follows actual network distances The extreme points of the influence distances on different roads on the network were then joined by lines to describe service areas The villages not included in the service areas were considered as inaccessible to health care facility The service areas in the study area are shown in figure 3 and the areas not served could be clearly identified from the map It could also be observed that there were other health centres located within the service area of a health centre In other words there are few health

thus a higher value would be obtained indicating better accessibility for those villages An example has been shown

in Figure 4 where within the influence area of health centre X, there is one more health centre Y and thus in this case

been calculated for all the 81 health centres in the district A few selected values have been shown in Table 1

Table 1 Health care to population ratio (Rj)

Health Center_No R j

1 2.86189E-05

2 4.82521E-05

3 5.83328E-05

4 0.000106508

5 0.00026824

6 5.77101E-05

-1 1 3 5 7 9 11 13

Distance in Km Volume interactions between PHC and villages

Fig 3 Service areas of Health centers

In the second step of 2SFCA method the accessibility of a village or habitation has been calculated The accessibility

of a village is found by following similar steps as in step 1 by using closet facility tool in GIS platform Here a particular village searches for the health centres falling within their respective catchment area i.e., acceptable distance

i

A is

the sum of Rj falling within the catchment area For the same example illustrated in step 1, the accessibility of a

i

A is calculated by summing up both the ratios of the health centers, whose centroid is falling within the

habitations catchment area as shown in figure 5 Likewise accessibility of all habitations are computed The results

i

Fig 5 Measurement of Accessibility of a habitation

Table 2 Accessibility Index of habitations

Habitation_No Accessibility Index )

From the results as obtained for all the 2217 villages, it has been observed that the maximum accessibility Index was 6.91 and minimum was 0 The mean was 0.616 and standard deviation was 0.92 The villages having accessibility were then classified into five groups depending on the Accessibility Indices as shown in Fig-6 Larger the size of the circle, higher the accessibility of the village to health care centres at all A frequency distribution plot was also prepared (Figure 7) which clearly shows that a large number of habitations (891) do not have accessibility to health care It has also been observed that all these villages either do not have road connectivity or located far away from health centers The analysis would help the policy makers to take appropriate decisions to improve overall accessibility

of the population in district

Fig.6 Accessibility Index of habitations

4 Conclusion

The study makes use of 2SFCA method, a special case of gravity model on GIS platform to quantify accessibility of habitations in rural areas It shows the area of influence of each health centre and also calculates the level of accessibility of each village From the GIS map it would be quite easy for the policy makers to identify the areas not served by any health centre and the level of accessibility of the villages having access This would help to take appropriate measures for infrastructure development in terms of improving road network and also to identify optimal locations of new health centers in the areas not served by health facilities

References

Aday, L., Andersen, R., 1974 A framework for the study of access to medical care Health Services Research 9 (3), 208–220

Albert, D.P., & Butar, F.B., 2005 Estimating the de-designation of single-county HPSAs in the United States by counting naturopathic physicians as medical doctors Applied Geography 25, 271–285

Guagliardo, M.F., 2004 Spatial accessibility of primary care: concept, methods and challenges International

Journal of Health Geographics 3 (3)

Joseph, AE., Phillips, D.R., 1984 Accessibility and Utilization—Geographical Perspectives on Health Care

Khan, A.A., 1992 An integrated approach to measuring potential spatial access to health care services

Socioeconomic Planning Science 26 (4), 275–287

Lee, P.R., 1995 Health system reform and generalist physician Academic Medicine 70, S10–S13

Luo, W., & Wang, F., 2003a Spatial accessibility to primary care and physician shortage area designation: a case study in Illinois with GIS approaches In: Skinner, R., Khan, O (Eds.), Geographic Information Systems and Health Applications Idea Group Publishing, Hershey, PA, pp 260–278

Luo, W., & Wang, F., 2003b Measures of spatial accessibility to health care in a GIS environment: synthesis and a case study in the Chicago region Environment and Planning B: Planning and Design 30, 865–884

Luo, W., 2004 Using a GIS-based floating catchment method to assess areas with shortage of physicians Health and Place 10, 1–11

Luo W ,& Yi Qi., 2009 An enhanced two-step floating catchment area (E2SFCA) method for measuring spatial accessibility to primary care physicians Health and Place 15, 1100–1107

Mao K., et al., 2011 Evaluation of Spatial Accessibility to Town and Rural in a GIS Environment: a Case Study of Dachang County, proceedings of 19th International Conference on Geoinformatics, Shanghai, China

Radke, J.,& Mu, L., 2000 Spatial decomposition, modeling and mapping service regions to predict access to social programs Geographic Information Sciences 6, 105–112

Wang, L., 2007 Immigration, ethnicity, and accessibility to culturally diverse family physicians Health and Place

13, 656–671

Wang, F., McLafferty, S., Escamilla, V., Luo, L., 2008 Late-stage breast cancer diagnosis and health care access in Illinois Professional Geographer 60 (1), 54–69

Yang, D., Goerge, R., Mullner, R., 2006 Comparing GIS-based methods of measuring spatial accessibility to health services Journal of Medical Systems 30 (1), 23–32