Design of decision support system incorporating data mining algorithms for strengthening maternal and child health systems: Inclusion of systems-thinking approach

Design of decision support system incorporating data mining algorithms for strengthening maternal and child health systems: Inclusion of systems-thinking approach

Автор: Partha Saha

Журнал: Cardiometry @cardiometry

Рубрика: Report

Статья в выпуске: 20, 2021 года.

Бесплатный доступ

Reduction of maternal and infant mortality rates has been recognised as one of the important goals of this century. Both coverage improvement and inequity reduction have been set up as millennium targets. Despite the availability of effective interventions, maternal and child healthcare conditions are not improving in developing countries because of inefficiently functioning health systems. Knowledge generation about behaviors of health system building blocks on the implementation of several healthcare interventions will help policymakers to design situation- specific and strategic interventions. A decision support system has been devised incorporating data mining algorithms which would help to understand the condition of maternal and child healthcare indicators; educational, socio, and economic situations; healthcare status; and healthcare service blocks and their relationships with each other. In this paper, the design of the DSS has been discussed elaborately. To enhance a system- wide understanding of the healthcare system, all healthcare- related factors have been incorporated into this system. Three knowledge generation modules have been prepared by utilizing different visualization and data mining algorithms.

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Data mining, Health system, Decision support system, Maternal and child health care, Systems-thinking approach

Короткий адрес: https://sciup.org/148322438

IDR: 148322438   |   DOI: 10.18137/cardiometry.2021.20.100109

Список литературы Design of decision support system incorporating data mining algorithms for strengthening maternal and child health systems: Inclusion of systems-thinking approach

  • Andersen R, Newman JF. Societal and individual determinants of medical care utilisation in the United States. The Milbank Memorial Fund Quarterly. 1973;51(1):95–124. https://doi.org/10.1111/j.1468-0009.2005.00428.x
  • Anthony RN. Planning and Control Systems: A Framework for Analysis. Harvard University Graduate School of Business. 1965.
  • Balarajan Y, Selvaraj S, Subramanian SV. Health care and equity in India. The Lancet. 2011; 377(9764):505–15. https://doi.org/10.1016/S0140-6736(10)61894-6
  • Barros AJ, et al. Equity in maternal, newborn, and child health interventions in Countdown to 2015: A retrospective review of survey data from 54 countries. The Lancet. 2012;379(9822):1225–33. https://doi.org/10.1016/S0140-6736(12)60113-5
  • Bhatia JC, Cleland J. Determinants of maternal care in a region of South India. Health Transition Review. 1995;5(2):127–42.
  • Cassels A. Health Sector Reform: Key Issues in Less Developed Countries. Journal of International Deevelopment. 1995;7(3):329–47.
  • Chaudhuri R. Millennium development goals to sustainable development goals: Journey continues for a better world. Indian Journal of Public Health. 2015;59(4):255. https://doi.org/10.4103/0019-57X.169648
  • Countdown 2008 Equity Analysis Group. Mind the gap : equity and trends in coverage of maternal , newborn , and child health services in 54 Countdown countries. Lancet. 2008;371:1259–67.
  • De Savigny D, Adam T. Systems thinking for health systems strengthening. In Alliance for Health Policy and Systems Research, World Health Organization (Vol. 7). 2009. https://doi.org/10.1155/2010/268925
  • Delen D, Sharda R, Kumar P. Movie forecast Guru: A Web-based DSS for Hollywood managers. Decision Support Systems. 2007;43(4):1151–70. https://doi.org/10.1016/j.dss.2005.07.005
  • Frenk J. Dimensions of health system reform. Health Policy. 1994;27(1):19–34. https://doi.org/10.1016/0168-8510(94)90155-4
  • Gorry GA, Scott-Morton MS. A Framework for Management Information Systems. Sloan Management Review. 1971;13(1):55–70.
  • Halfon N, et al. Lifecourse health development: past, present and future. Maternal and Child Health Journal. 2014;18(2):344–65. https://doi.org/10.1007/s10995-013-1346-2
  • Hogan MC, et al. Maternal mortality for 181 countries, 1980-2008: a systematic analysis of progress towards Millennium Development Goal 5. Lancet. 2010;375(9726):1609–23. https://doi.org/10.1016/S0140-6736(10)60518-1
  • Joe W, Mishra US, Navaneetham K. Socio-economic inequalities in child health: recent evidence from India. Global Public Health. 2010;5(5):493–508. https://doi.org/10.1080/17441690903213774
  • Kerber KJ, et al. Continuum of care for maternal, newborn, and child health: from slogan to service delivery. Lancet. 2007;370(9595):1358–69. https://doi.org/10.1016/S0140-6736(07)61578-5
  • Khan KS, et al. WHO analysis of causes of maternal death: a systematic review. Lancet. 2006; 367(9516): 1066–74. https://doi.org/10.1016/S0140-6736(06)68397-9
  • Khanal V, et al. Utilization of maternal and child health services in western rural Nepal: a cross-sectional community-based study. Indian Journal of Public Health. 2014;58(1):27–33. https://doi.org/10.4103/0019-557X.128162 [doi]
  • Koh HC, Tan G. Data mining applications in healthcare. Journal of Healthcare Information Management. 2005;19(2):64–72.
  • Lavrač N, et al. Data mining and visualization for decision support and modeling of public health-care resources. Journal of Biomedical Informatics. 2007; 40(4): 438–47. https://doi.org/10.1016/j.jbi.2006.10.003
  • Ministry of Health and Family Welfare. Government of India. (2013). A strategic approach to reproductive, maternal, newborn, child, and adolescent health (RMNCH+A) in India.
  • Raghupathy S. Education and the use of maternal health care in Thailand. Social Science & Medicine. 1996;43(4):459–71. https://doi.org/10.1016/0277-9536(95)00411-4
  • Rajaratnam JK, et al. Neonatal, postneonatal, childhood, and under-5 mortality for 187 countries, 1970-2010: a systematic analysis of progress towards Millennium Development Goal 4. Lancet. 2010;375(9730):1988–2008. https://doi.org/10.1016/S0140-6736(10)60703-9
  • Saha P. Decision Support System to Develop Evidence-based Policies for Inequity Reduction in Maternal and Child Health Care. Journal of Health Management. 2019;21(1):53–84.
  • Simon, H. The New Science of Management Decision. Prentice Hall. 1977.
  • Singh A, et al. Socio-economic inequalities in the use of postnatal care in india. PLoS ONE. 2012;7(5). https://doi.org/10.1371/journal.pone.0037037
  • Singh PK, Kumar C, Ra, RK, Singh L.. Factors associated with maternal healthcare services utilization in nine high focus states in India: A multilevel analysis based on 14 385 communities in 292 districts. Health Policy and Planning. 2014;29(5):542–59. https://doi.org/10.1093/heapol/czt039
  • Solar O, Irwin A. A Conceptual Framework for Action on the Social Determinants of Health. In World Health Organization. 2010. https://doi.org/ISBN 978 92 4 150085 2
  • UNICEF. 2006. The state of the world’s children 2007: Women and children: The double dividend of gender equality (Vol. 7). Unicef.
  • United Nations. The Millennium Development Goals Report 2013.
  • Victora CG, et al. How changes in coverage affect equity in maternal and child health interventions in 35 Countdown to 2015 countries : an analysis of national surveys. Lancet. 2012;380:1149–56. https://doi.org/10.1016/S0140-6736(12)61427-5
  • Victora CG, et al. How changes in coverage affect equity in maternal and child health interventions in 35 Countdown to 2015 countries: an analysis of national surveys. The Lancet. 2012;380(9848):1149–56.
  • WHO. 2007. Everybody’s business: strengthening health systems to improve health outcomes: WHO’s framework for action. Production, 1–56. https://doi.org/10 July 2012
  • Wojciechowski J, Hopkins AM, Upton RN. Interactive Pharmacometric Applications Using R and the hiny Package. The R Journal. 2015;6(2):146–59.
  • Yuan B, et al. What interventions are effective on reducing inequalities in maternal and child health in low- and middle-income settings? A systematic review. BMC Public Health. 2014;14(1):634. https://doi.org/10.1186/1471-2458-14-634
  • Zeng Y, Cai Y, Jia P, Jee H. Development of a webbased decision support system for supporting integrated water resources management in Daegu city, South Korea. Expert Systems with Applications. 2012; 39(11): 10091– 102. https://doi.org/10.1016/j.eswa.2012.02.065
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