Integrated Information Visualization to Support Decision Making for Health Promotion in Chonburi, Thailand

Authors

  • Puangrat JINPON Information Technology and Educational Media Center, Southern College of Technology, Nakhon Si Thammarat 80110
  • Mullica JAROENSUTASINEE Center of Excellence for Ecoinformatics, School of Science, Walailak University, Nakhon Si Thammarat 80160
  • Krisanadej JAROENSUTASINEE Information Technology and Educational Media Center, Southern College of Technology, Nakhon Si Thammarat 80110

DOI:

https://doi.org/10.48048/wjst.2019.2181

Keywords:

Integrated information visualization, data visualization, integrated information system, clinical informatics, clinical research informatics

Abstract

A visualization of comprehensive data on health care enhances performance of decision-making in health promotion programs. We describe the design and prototype of a Dashboard Decision Support System (DDSS) as a web-based advanced tool for executives and health officers to plan and generate effective programs in health promotion and disease prevention. Data were obtained from 10 communities surrounding oil refinery, using Family and community Assessment Program (FAP), in operation since 2010. The system was developed using web-based technology and open standards, i.e., MySQL, PHP, Highcharts JS, and Google Maps. Perception of the system and its effectiveness were evaluated using a questionnaire after participants had had an approximately one month period of experience of using the system. The responses to the questionnaire were positive about the system features and system process. Using the DDSS, executives and health officers can deploy effective and appropriate programs to enhance health care in their communities.

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References

JA Jacobs, E Jones, BA Gabella, B Spring and RC Brownson. Tools for implementing an evidence-based approach in public health practice. Prev. Chronic Dis. 2012; 9, 110324.

World Health Organization. The Ottawa charter of health promotion, Available at: http://www.who.int/healthpromotion/conferences/previous/ottawa/en, accessed February 2015.

GS Guldan. Obstacles to community health promotion. Soc. Sci. Med. 1996; 43, 689-95.

C Merzel and JD Afflitti. Reconsidering community-based health promotion: Promise, performance, and potential. Am. J. Public Health 2003; 93, 557-74.

The International Union for Health Promotion and Education (IUHPE). Available at: http://www.iuhpe.org/images/PROJECTS/ACCREDITATION/EHP_part1.pdf, accessed February 2015.

AF Simpao, LM Ahumada, JA Galvez and MA Rehman. A review of analytics and clinical informatics in health care. J. Med. Syst. 2014; 38, 45.

M Seah, MH Hsieh and P Weng. A case analysis of Savecom: The role of indigenous leadership in implementing a business intelligence system. Int. J. Inform. Manag. 2010; 30, 368-73.

P Jinpon, M Jaroensutasinee and K Jaroensutasinee. Business intelligence and its applications in the public healthcare system. Walailak J. Sci. Tech. 2011; 8, 97-110.

LM Sibley and HY Seow. Developing a dashboard to help measure and achieve the triple aim: A population based cohort study. BMC Health Serv. Res. 2014; 14, 363.

R Miniati, F Dori, G Cecconi, R Gusinu, F Niccolini and GB Gentili. HTA decision support system for sustainable business continuity management in hospitals: The case of surgical activity at University Hospital in Florence. Tech. Health Care 2013; 21, 49-61.

PY Benhamou. Improving diabetes management with electronic health records and patients' health records. Diabetes Metab. 2011; 37, S53-S56.

T Carlson, S York and J Primomo. The utilization of geographic information systems to create a site selection strategy to disseminate an older adult fall prevention program. Soc. Sci. J. 2011; 48, 159-74.

S Ahmed, SJ Bartlett, P Ernst, G Paré, M Kanter, R Perreault, R Grad, L Taylor and R Tamblyn. Effect of a web-based chronic disease management system on asthma control and health-related quality of life: Study protocol for a randomized controlled trial. Trials 2011; 12, 260.

Thaioil Group. Communities Surrounding the Refinery. Available at: http://www.thaioilgroup.com/ home/content.aspx?id=144, accessed July 2015.

P Wasi. Community Health System Development. Available at: http://www.prawase.com/images/ book/060800_PW_PB09.pdf, accessed July 2015.

S Wibulpolprasert. Thailand Health Profile 2005-2007. Available at: http://www.moph.go.th/ops/ health_50, accessed July 2015.

U Jaraeprapal. Pakpoon Subdistrict Administration Organisation with Community Well-Being development. Available at: http://resource.thaihealth.or.th/library/hot/12846, accessed July 2015.

K Hachisuka, S Saeki, Y Tsutsui, H Chisaka, H Ogata, N Iwata and S Negayama. Gender-related differences in scores of the Barthel Index and Frenchay activities index in randomly sampled elderly persons living at home in Japan. J. Clin. Epideminol. 1999; 52, 1089-94.

B Zuberbuhler, P Galloway, A Reddy, M Saldana and R Gale. A web-based information system for management and analysis of patient data after refractive eye surgery. Comput. Meth. Prog. Bio. 2007; 88, 210-6.

MS Hutton, S Azevedo, R Beeler, R Bettenhausen, E Bond, A Casey, J Liebman, A Marsh, T Pannell and A Warrick. Experiment archive, analysis, and visualization at the National Ignition Facility. Fusion Eng. Des. 2012; 87, 2087-91.

ISO 9241-11. Ergonomic Requirements for Office Work with Visual Display Terminals, Part 11: Guidance on Usability. Available at: https://www.iso.org/obp/ui/#iso:std:iso:9241:-11:ed-1:v1:en, accessed July 2015.

J Preece, Y Rogers and H Sharp. In: Proceeding of the Interaction Design: Beyond Human-Computer Interaction, New York, 2002, p. 169-82.

N Amek, P Vounatsou, B Obonyo, M Hamel, F Odhiambo, L Slutsker and K Laserson. Using health and demographic surveillance system (HDSS) data to analyze geographical distribution of socio-economic status: An experience from KEMRI/CDC HDSS. Acta Trop. 2015; 144, 24-30.

L Botetzagias, AF Dima and C Malesios. Extending the theory of planned behavior in the context of recycling: The role of moral norms and of demographic predictors. Resour. Conservat. Recycl. 2015; 95, 58-67.

J Forsman, N Anani, A Eghdam, M Falkenhav and S Koch. Integrated information visualization to support decision making for use of antibiotics in intensive care: Design and usability evaluation. Inform. Health Soc. Care 2013; 38, 330-53.

ST Hawley, B Zikmund-Fisher, P Ubel, A Jancovic, T Lucas and A Fagerlin. The impact of the format of graphical presentation on health-related knowledge and treatment choices. Patient Educ. Couns. 2007; 73, 448-55.

MA Thomas, PR Narayan and C Christian. Mitigating gaps in reproductive health reporting in outlier communities of Kerala, India: A mobile phone-based health information system. Health Pol. Tech. 2012; 1, 69-76.

Gapminder. About Gapminder. Available at: http://www.gapminder.org/about-gapminder, accessed June 2015.

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Published

2017-10-31

How to Cite

JINPON, P., JAROENSUTASINEE, M., & JAROENSUTASINEE, K. (2017). Integrated Information Visualization to Support Decision Making for Health Promotion in Chonburi, Thailand. Walailak Journal of Science and Technology (WJST), 16(8), 551–560. https://doi.org/10.48048/wjst.2019.2181

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