Research article Special Issues

Defining Remoteness from Health Care: Integrated Research on Accessing Emergency Maternal Care in Indonesia

  • Received: 06 April 2015 Accepted: 25 June 2015 Published: 01 July 2015
  • The causes of maternal death are well known, and are largely preventable if skilled health care is received promptly. Complex interactions between geographic and socio-cultural factors affect access to, and remoteness from, health care but research on this topic rarely integrates spatial and social sciences. In this study, modeling of travel time was integrated with social science research to refine our understanding of remoteness from health care. Travel time to health facilities offering emergency obstetric care (EmOC) and population distribution were modelled for a district in eastern Indonesia. As an index of remoteness, the proportion of the population more than two hours estimated travel time from EmOC was calculated. For the best case scenario (transport by ambulance in the dry season), modelling estimated more than 10,000 fertile aged women were more than two hours from EmOC. Maternal mortality ratios were positively correlated with the remoteness index, however there was considerable variation around this relationship. In a companion study, ethnographic research in a subdistrict with relatively good access to health care and high maternal mortality identified factors influencing access to EmOC, including some that had not been incorporated into the travel time model. Ethnographic research provided information about actual travel involved in requesting and reaching EmOC. Modeled travel time could be improved by incorporating time to deliver request for care. Further integration of social and spatial methods and the development of more dynamic travel time models are needed to develop programs and policies to address these multiple factors to improve maternal health outcomes.

    Citation: Bronwyn A Myers, Rohan P Fisher, Nelson Nelson, Suzanne Belton. Defining Remoteness from Health Care: Integrated Research on Accessing Emergency Maternal Care in Indonesia[J]. AIMS Public Health, 2015, 2(3): 257-273. doi: 10.3934/publichealth.2015.3.256

    Related Papers:

  • The causes of maternal death are well known, and are largely preventable if skilled health care is received promptly. Complex interactions between geographic and socio-cultural factors affect access to, and remoteness from, health care but research on this topic rarely integrates spatial and social sciences. In this study, modeling of travel time was integrated with social science research to refine our understanding of remoteness from health care. Travel time to health facilities offering emergency obstetric care (EmOC) and population distribution were modelled for a district in eastern Indonesia. As an index of remoteness, the proportion of the population more than two hours estimated travel time from EmOC was calculated. For the best case scenario (transport by ambulance in the dry season), modelling estimated more than 10,000 fertile aged women were more than two hours from EmOC. Maternal mortality ratios were positively correlated with the remoteness index, however there was considerable variation around this relationship. In a companion study, ethnographic research in a subdistrict with relatively good access to health care and high maternal mortality identified factors influencing access to EmOC, including some that had not been incorporated into the travel time model. Ethnographic research provided information about actual travel involved in requesting and reaching EmOC. Modeled travel time could be improved by incorporating time to deliver request for care. Further integration of social and spatial methods and the development of more dynamic travel time models are needed to develop programs and policies to address these multiple factors to improve maternal health outcomes.


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    [1] WHO (2012) Maternal Mortailty Fact Sheet No 348. 2012; Available from: http://www.who.int/mediacentre/factsheets/fs348/en/.
    [2] Thaddeus S, Maine D (1994) Too far to walk: maternal mortality in context. Social Science and Medicine 38: 1091-1110. doi: 10.1016/0277-9536(94)90226-7
    [3] Penchansky R, Thomas JW (1981) The concept of access: definition and relationship to consumer satisfaction. Medical care 19: 127-140. doi: 10.1097/00005650-198102000-00001
    [4] Obrist B, Iteba N, Lengeler C, et al. (2007) Access to health care in contexts of livelihood insecurity: A framework for analysis and action. PLOS Med 4: 1584-1588.
    [5] Noor A, Gikandi P, Hay S, et al. (2004) Creating spatially defined databases for equitable health service planning in low-income countries: the example of Kenya. Acta Tropica 91: 239-251. doi: 10.1016/j.actatropica.2004.05.003
    [6] Perry B, Gesler W (2000) Physical access to primary health care in Andean Bolivia. Social Science and Medicine 50: 1177-1188. doi: 10.1016/S0277-9536(99)00364-0
    [7] Phillips R, Kinman E, Schnitzer P, et al. (2000) Using geographic information systems to understand health care access. Arch Fam Medicine 9: 971. doi: 10.1001/archfami.9.10.971
    [8] Ray N, Ebener S (2008) AccessMod 3.0: computing geographic coverage and accessibility to health care services using anistropic movement of patients. Int J Health Geogr 7: 63.
    [9] Tanser F, Gijsbertsen B, Herbst K (2006) Modelling and understanding primary health care accessibility and utilisation in rural South Africa: An exploration using a geographical information system. Soc Sci Med 63: 691-705. doi: 10.1016/j.socscimed.2006.01.015
    [10] Delmelle EM, Cassell C, Dony C, et al. (2013) Modelling travel impedance to medical care for children with birth defects using Geographic Information Systems. Birth Defects Res A Clin Mol Teratol 97, 673-684.
    [11] Wakerman J (2004) Defining remote health. Aust J Rural Health 12: 210-214. doi: 10.1111/j.1440-1854.2004.00607.x
    [12] UNFPA (2004) Tool Number 6: Programme Indicators PartII: Indicators for reducing maternal mortality, in Programme Manager's Planning Monitoring & Evaluation Toolkit. UNFPA: New York. pp. 18.
    [13] Say L, Raine R. (2007) A systematic review of inequalities in the use of maternal health care in developing countries: examining the scale of the problem and the importance of context. Bull World Health Organ 85:812-9. doi: 10.2471/BLT.06.035659
    [14] Agus Y, Horiuchi S. (2012) Factors influencing the use of antenatal care in rural West Sumatra, Indonesia. BMC Pregnancy Childbirth 12:9. doi: 10.1186/1471-2393-12-9
    [15] Fielding N, Cisneros-Puebla C (2006) CAQDAS-GIS Convergence. J Mixed Methods Research 3: 349-370.
    [16] Belton S, Myers B, Rambu Ngana F (2014) Maternal deaths in eastern Indonesia: 20 years and still walking: an ethnographic study. BMC Pregnancy Childbirth 14: 39. doi: 10.1186/1471-2393-14-39
    [17] Goddard M, Smith P (2001) Equity of access to health care services: Theory and evidence from the UK. Soc Sci Med 53: 1149-1162. doi: 10.1016/S0277-9536(00)00415-9
    [18] Meyer SB, Luong TCN, Mamerow L, et al. (2013) Inequities in access to healthcare: analysis of national survey data across six Asia-Pacific countries. BMC Health Serv Res 13: 238
    [19] Badan Pusat Statistik (2010) Dalam Angka NTT 2010 (NTT in Figures 2010).
    [20] Badan Pusat Statistik (2010) Dalam Angka Kabupaten TTS.
    [21] Rambu Ngana F, Myers B, Belton S (2012) Health reporting system in two subdistricts in eastern Indonesia: Highlighting the role of village midwives. Midwifery 28: 809-15. doi: 10.1016/j.midw.2011.09.005
    [22] Gething, P.W., Johnson, F.A., Frempong-Ainguah, F, et al. (2012) Geographic access to care at birth in Ghana: a barrier to safe motherhood. BMC Public Health 12: 991. doi: 10.1186/1471-2458-12-991
    [23] Upchurch C., Kuby M., Zoldak M., et al. (2004). Using GIS to generate mutually exclusive service areas linking travel on and off a network. J Transp Geogr 12: 23-33. doi: 10.1016/j.jtrangeo.2003.10.001
    [24] Delamater P L, Messina J P, Shortridge AM, et al. (2012). Measuring geographic access to health care: raster and network-based methods. Int J Health Geogr 11: 15.
    [25] Tanser, F., Gijsbertsen, B., & Herbst, K. (2006). Modelling and understanding primary health care accessibility and utilization in rural South Africa: an exploration using a geographical information system. Soc Sci Med 63: 691-705. doi: 10.1016/j.socscimed.2006.01.015
    [26] Gelman A, Hill J (2007) Data analysis using regression and multilevel/hierarchical models. Cambridge: Cambridge University Press.
    [27] Flyvbjerg B (2006) Five misunderstandings about case-study research. Qual Inq 12: 219. doi: 10.1177/1077800405284363
    [28] Badland, H. (2013) Using simple agent-based modeling to inform and enhance neighborhood walkability. Int J Health Geogr 12: 58. doi: 10.1186/1476-072X-12-58
    [29] Green N (2013) A policymaker's puzzle, or how to cross the boudary from agent-based model to land-use policymaking? Trans Inst Br Geogr. 38: 2-6. doi: 10.1111/j.1475-5661.2012.00532.x
    [30] Ligmann-Zielinska A, Jankowski P (2007) Agent-based models as laboratories for spatially explicit planning policies. Environ Plan B Plan Des. 34: 316. doi: 10.1068/b32088
    [31] Ligtenberg A., Wachowicz M, Bregt A, et al. (2004) A design and application of a multi-agent system for simulation of multi-actor spatial planning. J Environ Manage72: 43-55. doi: 10.1016/j.jenvman.2004.02.007
    [32] Torrens P (2003) Cellular automata and multi-agent systems as planning support tools, in Planning Support Systems in Practice, S. Geertman and J. Stillwell, Editors. Springer: Berlin Heidelberg. p. 205-222.
    [33] Noorali R, Luby S, Rahbar M (1999) Does use of a government service depend on distance from the health facility? Health Policy Planning 14: 191-197. doi: 10.1093/heapol/14.2.191
    [34] Okwaraji Y, Cousens S, Berhane Y, et al. (2012) Effect of geographical access to health facilities on child mortality in rural Ethiopia: a community based cross sectional study. PLoS One 7: e33564. doi: 10.1371/journal.pone.0033564
    [35] Pearson C, Stevens M, Sanogo K, et al. (2012) Access and barriers to healthcare vary among three neighbouring communities in northern Honduras. Int J Fam Medicine. 2012:298472
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