Background: This manuscript aimed to map the spatial distributions of health clinics for public and private sectors in Malaysia. It would assist the stakeholders and responsible authorities in the planning for health service delivery. Methods: Data related to health clinic were gathered from stakeholders. The location of health facilities was geo-coded using a Global Positioning System (GPS) handheld. The average nearest neighbour was used to identify whether health clinics were spatially clustered or dispersed. Hot spot analysis was used to assess high density of health clinics to population ratio and average distance of health clinics distribution. A Geographically Weighted Regression (GWR) was used to analyse the requirement of health clinic in a sub-district based on population density and number of health clinics with significant level (p < 0.001). Results: The results of the average nearest neighbour analysis revealed that the distribution of public health clinics was dispersed (p < 0.001) with z-scores 3.95 while the distribution of private clinics was clustered (p < 0.001) with z-score ?29.26. Several locations especially urban area was also identified as high density in the sub-district. Conclusions: There is a significant difference in the spatial pattern of public health clinics and private clinics in Malaysia. The information can assist stakeholder and responsible authorities in planning health service delivery.
Cite this paper
Hazrin, H. , Fadhli, Y. , Tahir, A. , Safurah, J. , Kamaliah, M. and Noraini, M. (2013) Spatial patterns of health clinic in Malaysia. Health
, 2104-2109. doi: 10.4236/health.2013.512287
 Young, G.O. (1964) Ynthetic structure of industrial plastics. In: Peters, J., Ed., Plastics, 2nd Edition, McGrawHill, New York, 15-64.
 Graham, S.R., Carlton. C., Gaede, D. and Jamison B. (2011) The benefits of using geographic innformation systems as a community assessment tool. Public Health Reports, Dominica, 126-303.
 Ministry of Health (MOH) (2011) Pelan Strategik 2011-2015. Ministry of Health (MOH), Kuala Lumpur.
 Ministry of Health (MOH) (2011) Country health plan, 10th Malaysia plan 2011. Ministry of Health (MOH), Kuala Lumpur.
 Farley Jr., E.S., Boisseau, V. and Froom, J. (1977) An integrated medical record and data system for primary care. Part 5: Implications of filing family folders by area of residence. Journal of Family Practice, 5, 427-432.
 Andrew, B., Robert, L. and Thomas, M. (2010) Harnessing Geographic Information System (GIS) to enable community-oriented primary care. JABFM, 23, 22-31
 Srividya, A., Michael, E., Palaniyandi, M., Pani, S.P. and Das, P. K. (2002) A geostatistical analysis of the geographic distribution of lymphatic filariasis prevalence in southern India. American Journal of Tropical Medicine and Hygeine, 67, 480-489.
 Department of Statistic, Malaysia (2011) Population distribution and basic demographic characteristics 2010.
 Mitchell, A. (2005) The ESRI guide to GIS analysis: Volume 2: Spatial measurements and statistics. ESRI Press, Redlands.
 Fotheringham, A.S., Brunsdon, C., et al. (2002) Geographically weighted regression: The analysis of spatially varying relationships. Wiley, Hoboken.
 Palmer, N., Mills, A. and Wadee, H. (2003) A new face for private providers in developing countries: What implications for public health? Bulletin of the World Health Organisation, 81, 292-297.
 Shaikh, M. (2009) Spatial distribution of health facilities in Islamabad, Pakistan. Eastern Mediterranean Health Journal, 594 A, 3.
 Aronson, R.E., Wallis, A.B., O’Campo, P.J. and Shafer, P. (2007) Neighborhood mapping and evaluation: Methodology for participatory community health initiatives. Maternal and Child Health Journal, 11, 373-383.http://dx.doi.org/10.1007/s10995-007-0184-5