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CDA 07-022 – HSR Study

 
CDA 07-022
The Role of Complexity Science in Improving Clinical Microsystems
Luci Leykum, MD MBA MSc
South Texas Health Care System, San Antonio, TX
San Antonio, TX
Funding Period: April 2008 - March 2013
BACKGROUND/RATIONALE:
We believe that health care organizational research has not been grounded in the theoretical model that represents the clinical microsystems in which care is delivered. Growing evidence suggests that these systems are complex adaptive systems, characterized by nonlinear dynamics between inputs and outputs. This lack of proportionality makes prediction of outcomes more difficult, and introduces an inherent level of uncertainty that cannot be eliminated with planning or process reengineering. We hypothesize that an implication of this uncertainty may be that interventions that improve individuals' ability to make sense of what is happening ("sensemaking") will be more effective in improving outcomes than those that do not. We propose a career development award that will be a first step in understanding the ways in which conceptualizing clinical settings as complex adaptive systems changes the way we intervene in such systems.

OBJECTIVE(S):
The purpose of the proposed research will be to apply techniques from other fields to health care settings in an effort to observe and measure characteristics of complex systems in health care, and to allow us to analyze the non-linear data that will result from such observations. In this award, we propose the following specific objectives, which we plan to carry out in inpatient medical settings:

Objective # 1a: To use observation, interview and survey techniques to observe and describe the non-linear phenomena of self-organization and co-evolution in clinical microsystems.
Objective # 1b: To use observation, interview and survey techniques to observe and describe sense-making in clinical microsystems.

Objective # 2: To explore the use of existing non-linear data analysis techniques, including agent-based modeling, multiscale analysis, and phase-space plots to healthcare settings, in order to:
a.compare these settings on the activities (was dimensions) of self-organization, co-evolution, and sensemaking
b. relate performance of these activities to process indicators and clinical outcomes

METHODS:
Data collection on this project has been completed. Data entry and initial analyses have been completed. Initial analyses explore the association between physician team relationships and length of stay, unnecessary length of stay, and complication rates. A manuscript based on these analyses is almost complete. Additional analyses examining differences in sensemaking among teams is also underway.

FINDINGS/RESULTS:
Not yet available.

IMPACT:
Our analyses suggest that improving provider relationships may be an important strategy for improving the care of hospitalized Veterans. We will be resubmitting a VA grant proposal of an intervention to improve physician sensemaking as a strategy to improve patient outcomes as an outcome of this work.



External Links for this Project

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PUBLICATIONS:

None at this time.


DRA: Health Systems
DRE: Treatment - Observational
Keywords: none
MeSH Terms: none

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