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Management Information Systems of Public Health Behaviors based on Evidence in Medicine and Health Management

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  • Joanna Holub-Iwan

Abstract

Purpose: The article shows the method of modeling population segments on health behavior of patients in Poland and the possibility of including this module in decision-making processes in public health management. Design/methodology/approach: Healthcare systems in different countries are different. However, in each of them it is important to make the right decisions. Health protection is a specific area, quick and right decisions can save health and life. Making decisions based on evidence, facts and research should be a standard. The development of information technology makes it possible to collect and process a big data registered in various systems. Findings: Patient behavior models can be created and they should be part of the MIS. On this basis can be created better predictive models for managers' decision making. Analysis based on a representative research sample of 1067 people. Practical Implications: Institutions responsible for analyzing health care systems report that the use of databases to make decisions about treatment is much more frequent than the use of databases to make decisions about public health management. Doctors use the bases more often than managers. However, doctors do not analyze the health behavior of the population. Healthcare managers should be very interested in creating good and integrating databases. Originality/Value: There are tele-medical devices monitoring the health of people. They should be interested in the integration of databases administered by various institutions, not only medical services providing. In public health Management Information Systems (MIS), can and even need to be included modules related to health behavior of the population. Health behaviors concern preventive health, behavior in health and in illness. The area of health behavior of the population is very large. It is also the influence of the environment on people's decisions - health promotion, pharmaceutical marketing, etc.

Suggested Citation

  • Joanna Holub-Iwan, 2021. "Management Information Systems of Public Health Behaviors based on Evidence in Medicine and Health Management," European Research Studies Journal, European Research Studies Journal, vol. 0(Special 1), pages 623-643.
  • Handle: RePEc:ers:journl:v:xxiv:y:2021:i:special1-part1:p:623-643
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    References listed on IDEAS

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    1. Peter S. Fader & Bruce G. S. Hardie & Ka Lok Lee, 2005. "“Counting Your Customers” the Easy Way: An Alternative to the Pareto/NBD Model," Marketing Science, INFORMS, vol. 24(2), pages 275-284, August.
    2. Alain Bultez & Philippe Naert, 1988. "SH.A.R.P.: Shelf Allocation for Retailers' Profit," Marketing Science, INFORMS, vol. 7(3), pages 211-231.
    3. Kass, N.E., 2001. "An ethics framework for public health," American Journal of Public Health, American Public Health Association, vol. 91(11), pages 1776-1782.
    4. Huw T.O. Davies & Sandra M. Nutley, 1999. "The Rise and Rise of Evidence in Health Care," Public Money & Management, Taylor & Francis Journals, vol. 19(1), pages 9-16, January.
    5. Raymond R. Burke & Arvind Rangaswamy & Jerry Wind & Jehoshua Eliashberg, 1990. "A Knowledge-Based System for Advertising Design," Marketing Science, INFORMS, vol. 9(3), pages 212-229.
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    More about this item

    Keywords

    Management Information Systems (MIS); Marketing Information Systems (MkIS); public health; model of patients' health behavior.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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