The Spatial variance analysis of the distribution of home care beneficiaries in western Riyadh

Authors

  • Ali Abdullah Al-Shehri Department of Geography, College of Arts, King Saud University
  • Nasser Murshid Al-Zeer, PHD Department of Geography, College of Arts, King Saud University

DOI:

https://doi.org/10.31973/aj.v1i139.1317

Keywords:

Population, Spatial distribution, Home health care, Riyadh, Kingdom of Saudi Arabia

Abstract

This study analyzes the spatial distribution of the beneficiaries of the home health care service provided by King Salman Hospital at the western district of Riyadh city. The reasons for choosing this study subject are due to two main reasons: The first, is the importance of this home health service, which is considered modern in the Kingdom of Saudi Arabia and is no less important and quality than the service provided at the hospitals and medical centers.  The second, is the psychological comfort and social benefits provided by the home health care to the beneficiary instead of the costs and effort required during his hospitalization care in the usual circumstances.

 

- Study objectives:

This study aims to:

            1- Analyze the Spatial variation of the total population, the population by gender (females and males) distribution, the distribution of total beneficiaries of the home health care service, the distribution of the beneficiaries by gender (females and males) and the distribution of two age categories (over 65 years old) and (14-65 years old) during the year 2020.

            2- Determining the spatial distribution pattern of the cited variables during the year 2020.

 

- Study methodology:

            To achieve the study objectives, the research methodology relied on the inductive approach in analyzing the spatial variance of the studied variables during the year 2020. The methodology used the integrated employment of:

  1. A) - The statistical methods available in the Analyze tools in the SPSS23 statistical toolbar using the Normality test of Shapiro-Wilk appropriate to the samples size less than 30 recorded data.

B)- The GIS techniques using Spatial statistics tools and the Autocorrelation Model (Moran's Index) available on the Arc Toolbox of ArcGIS 10.7 software, to determine the pattern of spatial distribution of the studied variables during the year 2020.

 

- Study data:

The study data consist of:

A)- The data of the population distribution by gender (female and male) in a total of 20 districts and the data of patient distribution by gender (female and male) and by age category (over 65 years old) and (14-65 years) in a total of 17 districts benefiting from the health home care program available at King Sulayman Hospital during the year 2020.

B)- Official population statistics of the years 2010 and 2020.

C)- The spatial data of beneficiaries from the health home care program available by the geographical database available by the Royal Commission of Riyadh city. This data is available in the form of cadastral, road network and location points of national hospitals and health centers affiliated to the Ministry of Health. The second part of data is the patient's locations available by the King Sulayman Hospital in the Excel tables.

 

Study results:

The Shapiro-Wilk test showed that the distribution of districts areas, the distribution of population data, population density, and beneficiaries of the home health care service during the year 2020 in the western districts of Riyadh city differs from the Normal distribution. The results of the Levene test indicated that all variances are homogeneous, except for the population density data, beneficiaries (female), and beneficiaries for the age category (more than 65 years).

Therefore, the results of the Binomial test showed that the variance of the districts areas distribution and the beneficiary population data are not significant. The results of the Autocorrelation (Moran's Index) are consistent with these results. So, that the standard (Z) values ​​are ranged between (-0.01 and + 1.70) and the Moran's Index (I) values ​​between (-0.06 and +0.08) and the (p) values between (0.09 and 0.99), indicate the spatial distribution pattern of total beneficiaries, beneficiaries by gender (females and males) and by age category (14-65 years) is random, while the distribution pattern of beneficiaries from the age category (older than 65 years) is a cluster.

 

- Conclusion:

This study ended with many results emerged from the methodological steps applied in determining the Normality distribution of population and the beneficiary's data during the year 2020 in the western districts of Riyadh city. Also, their statistical significance is computed. The results of this study revealed the random spatial distribution pattern of the population and the beneficiaries of the home health care service in the western Riyadh city.

Downloads

Download data is not yet available.

References

Bagheri, N.; Benwell, G. L. & Holt, A. (2005). Measuring spatial accessibility to primary health care, 17th Annual Colloquium of the Spatial Information Research Centre (SIRC 2005): A Spatio-temporal Workshop), Dunedin, New Zeland, November 24-25, 2005.

Dudko, Y., Robey, D. E., Kruger, E., & Tennant, M. (2018). Selecting a location for a primary healthcare facility: combining a mathematical approach with a Geographic Information System to rank areas of relative need, Australian Journal of Primary Health, Vol. (24), 2: 130-134.

Frochen, S.; Ailshire, J. & Rodnyansky, S. (2019). Residential Care in Los Angeles: evaluating the spatial distribution of facilities and neighbourhood access to care among older adults, Local Environment, Vol. (24), 3: 274-288. ‏

Grekousis, G. & Photis, Y. N. (2014). Analyzing high-risk emergency areas with GIS and neural networks: The case of Athens, Greece, The Professional Geographer, Vol. (66), 1: 124-137.‏

Haynes, R. M.; Bentham, C. G.; Spencer, M. B. & Spartley, J.M. (1979). Community hospitals and rural accessibility, Franborough, Saxon House, England, p. 196-197.

Mitchell, A. (2005). The ESRI Guide to GIS Analysis, Volume 2: Spatial Measurements and Statistics, New York, ESRI Press, California, USA, 252 pages.

Moran, P.A.P. (1950). Notes on continuous stochastic phenomena, Biometrika, Vol. (37),1-2: 17-33.

Pooley, C. G.; Turnbull, J. & Adams, M. (2005). The journey to school in Britain since the 1940s: continuity and change, Area (37), 1: 43-53.

Tandi, T. E., Cho, Y., Akam, A. J. C., Afoh, C. O., Ryu, S. H., Choi, M. S., ... & - Choi, J. W. (2015). Cameroon public health sector: shortage and inequalities in geographic distribution of health personnel, International Journal for Equity in Health, (2005) 14: 43, Open access, DOI 10.1186/s12939-015-0172-0.

Unal, E.; Chen, S. E. & Waldorf, B. S. (2007). Spatial accessibility of health care in Indiana, Working Paper No. 07-07, Dept. of Agricultural Economics, Purdue University, Indiana State, USA.

Downloads

Published

2021-12-15

Issue

Section

Geography

How to Cite

Al-Shehri, A. A., & Al-Zeer, N. M. (2021). The Spatial variance analysis of the distribution of home care beneficiaries in western Riyadh. Al-Adab Journal, 1(139), 339-380. https://doi.org/10.31973/aj.v1i139.1317

Publication Dates

Similar Articles

1-10 of 405

You may also start an advanced similarity search for this article.