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Implications of complex adaptive systems theory for interpreting research about health care organizations.

Publication ,  Journal Article
Jordon, M; Lanham, HJ; Anderson, RA; McDaniel, RR
Published in: Journal of evaluation in clinical practice
February 2010

Data about health care organizations (HCOs) are not useful until they are interpreted. Such interpretations are influenced by the theoretical lenses used by the researcher.Our purpose was to suggest the usefulness of theories of complex adaptive systems (CASs) in guiding research interpretation. Specifically, we addressed two questions: (1) What are the implications for interpreting research observations in HCOs of the fact that we are observing relationships among diverse agents? (2) What are the implications for interpreting research observations in HCOs of the fact that we are observing relationships among agents that learn?We defined diversity and learning and the implications of the non-linear relationships among agents from a CAS perspective. We then identified some common analytical practices that were problematic and may lead to conceptual and methodological errors. Then we described strategies for interpreting the results of research observations.We suggest that the task of interpreting research observations of HCOs could be improved if researchers take into account that the systems they study are CASs with non-linear relationships among diverse, learning agents. Our analysis points out how interpretation of research results might be shaped by the fact that HCOs are CASs. We described how learning is, in fact, the result of interactions among diverse agents and that learning can, by itself, reduce or increase agent diversity. We encouraged researchers to be persistent in their attempts to reason about complex systems and learn to attend not only to structures, but also to processes and functions of complex systems.

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Published In

Journal of evaluation in clinical practice

DOI

EISSN

1365-2753

ISSN

1356-1294

Publication Date

February 2010

Volume

16

Issue

1

Start / End Page

228 / 231

Related Subject Headings

  • Systems Theory
  • Nonlinear Dynamics
  • Learning
  • Humans
  • Health Services Research
  • Health Policy & Services
  • Data Interpretation, Statistical
  • 42 Health sciences
  • 32 Biomedical and clinical sciences
  • 1117 Public Health and Health Services
 

Citation

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Jordon, M., Lanham, H. J., Anderson, R. A., & McDaniel, R. R. (2010). Implications of complex adaptive systems theory for interpreting research about health care organizations. Journal of Evaluation in Clinical Practice, 16(1), 228–231. https://doi.org/10.1111/j.1365-2753.2009.01359.x
Jordon, Michelle, Holly Jordan Lanham, Ruth A. Anderson, and Reuben R. McDaniel. “Implications of complex adaptive systems theory for interpreting research about health care organizations.Journal of Evaluation in Clinical Practice 16, no. 1 (February 2010): 228–31. https://doi.org/10.1111/j.1365-2753.2009.01359.x.
Jordon M, Lanham HJ, Anderson RA, McDaniel RR. Implications of complex adaptive systems theory for interpreting research about health care organizations. Journal of evaluation in clinical practice. 2010 Feb;16(1):228–31.
Jordon, Michelle, et al. “Implications of complex adaptive systems theory for interpreting research about health care organizations.Journal of Evaluation in Clinical Practice, vol. 16, no. 1, Feb. 2010, pp. 228–31. Epmc, doi:10.1111/j.1365-2753.2009.01359.x.
Jordon M, Lanham HJ, Anderson RA, McDaniel RR. Implications of complex adaptive systems theory for interpreting research about health care organizations. Journal of evaluation in clinical practice. 2010 Feb;16(1):228–231.
Journal cover image

Published In

Journal of evaluation in clinical practice

DOI

EISSN

1365-2753

ISSN

1356-1294

Publication Date

February 2010

Volume

16

Issue

1

Start / End Page

228 / 231

Related Subject Headings

  • Systems Theory
  • Nonlinear Dynamics
  • Learning
  • Humans
  • Health Services Research
  • Health Policy & Services
  • Data Interpretation, Statistical
  • 42 Health sciences
  • 32 Biomedical and clinical sciences
  • 1117 Public Health and Health Services