A soft systems approach to construct an information system to organise knowledge production and dissemination, in Mexico’s General Hospital.

Macías-Chapula, C.A., Rodea-Castro, I.P., Gutiérrez-Carrasco, A. and Mendoza-Guerrero, J.A. A soft systems approach to construct an information system to organise knowledge production and dissemination, in Mexico’s General Hospital., 2005 . In International Conference of Information Management in a Knowledge Society, Mumbai (India), 21-25 February 2005. [Conference paper]

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English abstract

Purpose The purpose of this work is to present the preliminary results of a research in progress on the development of an information system and model so as to organise and disseminate the knowledge production in Mexico’s General Hospital (MGH). The final goal is to support decision making processes related to science policy and public communication of science results. Method MGH is a major teaching hospital in Mexico. Located in Mexico city, MGH provides health care services to un-insured population through 36 medical specialties, 6400 staff, and 931 hospital beds. Seventy researchers conduct basic and applied health research throughout 160 registered protocols on a yearly basis. While productivity of this research is being monitored in MEDLINE, no clear picture exists as to the impact of this production; its interaction with other hospital outcome indicators; and the dissemination of this production at the local and institutional level. The above was perceived as a problem situation by the head of the research unit at MGH. A soft systems approach (Checkland and Scholes, 1990) was used to construct a rich image of the situation so as to identify the elements involved and to take action. Donabedian’s (1988) model to quality of health approach was used to identify the levels of resolution of the model and to identify the quantitative and qualitative indicators involved. Quantitative indicators included MGH statistical rates, and bibliometric indicators of the scientific production. A literature search was conducted in six local and international databases so as to identify the visibility and impact of MGH production. Qualitative indicators will be obtained through semi-structured interviews to researchers. Results Preliminary results included a rich image of the situation, indicating information flows, interactions, and lack of communication of subsystems at different levels of the model. Bibliometric indicators identified the impact of the production at the local, regional and international levels; and helped to nourish the construction of a model of communication of science in the health field (Macías-Chapula, 2002; Macías-Chapula, et al, 2004). Results will support the development of the ad-hoc information system for the research unit of MGH; and will help to define the science policy lines that the hospital will take in the near future. The authors will discuss the implications of this study in a knowledge society context.

Item type: Conference paper
Keywords: Soft systems methodology; Systems analysis; Models; Information systems; Bibliometric studies; Indicators; Scientific production; Bibliographic databases; Mexico; Mexico’s General Hospital; Knowledge organisation; Knowledge society; Information management.
Subjects: B. Information use and sociology of information > BH. Information needs and information requirements analysis.
Depositing user: PhD Jose Antonio Mendoza-Guerrero
Date deposited: 10 Apr 2020 11:11
Last modified: 10 Apr 2020 11:11
URI: http://hdl.handle.net/10760/34497

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References

Arderson, J., & Aydin, C. (1997). Evaluating the impact of the health care information systems. Communications of the ACM, 40, 83-90.

Alavi M., & Leidner, D.E. (2001) Review: knowledge management and knowledge management systems: conceptual foundations and research issues. MIS Quarterly, 25, 107–136.

Bose, Ranjit. (2003). Knowledge management enabled health care management systems: capabilities, infrastructure, and decision-support. Expert Systems with Applications, 24, 59-71

Checkland, P., & Scholes, J. (1990). Soft systems methodology in action. Chichester: Wiley & Sons.

Davenport, T.H., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Boston MA: Harvard Business School.

Donabedian, A. (1988). The quality of health. How can it be assessed? JAMA, 260,:1743-1748

Donabedian, A.(1990). The seven pillars of Quality. Arch. Phatol. Lab. Med, 14, 1115-8

Ergas, H. (1986). Does technology policy matter? In: Guile, B., Brooks, H. (Eds.), Technology and Global Industry: Companies and Nations in the World Economy (pp. 191-245). Washington, DC: National Academy Press pp. 191–245.

Freeman, C., (1987). Technology Policy and Economic Performance: Lessons from Japan. London: Pinter.

Gibbons, M .(1999). Science’s new social contract with society. Nature 402, 82-84.

Haux, Reinhold; Ammenweth, Elske; Herzog, Werner; Knaup, Petra. (2002). Health care in the information society. A prognosis for the year 2013. International Journal of Medical Informatics, 66, 3-21.

Hibbard, J. (1997). Knowledge management-knowing what we know. Information Week, October.

Holsapple, C. W. & Singh, M. (2001). The knowledge chain model: activities for competitiveness. Expert Systems with Applications.201, 77–98.

Jadad, A.R.; Haynes, R. B.; Hunt, D.; Browman, G. P. (2000). The Internet and evidence-based decision-making: a needed synergy for efficient knowledge management in health care. CMAJ, 162, 362–365.

R. Kohli, J.K. Tan, F.A. Piontek, D.E. Ziege and Groot H. (1999). Integrating cost information with health management support system: an enhanced methodology to assess healthcare quality drivers. Topics in Health Information Management, 20, 80–95.

Lemola, Tarmo. (2002). Convergence of national science and technology policies: the case of Finland. Research Policy, 31, 1481-1490.

Liebowitz, J., (2000). Building organizational intelligence—A knowledge management primer. Boca Raton, FL: CRC Press.

Lundvall, B.-Å. (1992). National Systems of Innovation: Towards a Theory of Interactive. London: Learning. Pinter.

Macías-Chapula, C.A. (2002). Exploratory model on the construction of a science communication model in the health field. In: Research on science communication: A multidisciplinary approach. (pp. 55-68) Ed. By Margarita Almada de Ascencio, et al., México: UNAM.

Macías-Chapula, C.A.; Rodea-Castro, I.P.; EguíaLis-Marques, J.; Gutiérrez-Carrasco, A. (2004). Institutional Scientific production and national benchmarking: The case of Mexico’s General Hospital. Internal report 2004.

Nelson, R., & Winter, S., (1982). An Evolutionary Theory of Economic Change. Cambridge, MA: Harvard University Press.

Nelson, R. (Ed.), (1993). National Innovation Systems. New York: Oxford University Press.

Nonaka, I. and Takeuchi, H. (1995). The knowledge-creating company. New York: Oxford University Press.

Quinn P, Anderson., & Finkelstein. S. (1998). Harvard Business Review on Knowledge Management Harvard Business Review on Knowledge Management. Boston, MA: Harvard Business School Press.


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