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Assessment of Dependence in Activities of Daily Living Among Older Patients in an Acute Care Unit

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Measuring interdependence in ambulatory care.

David Katerndahl¹, Robert Wood¹, Carlos R Jaen¹

¹Family & Community Medicine, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.

Journal of Evaluation in Clinical Practice

|December 15, 2015

Summary

Network density effectively measures interdependence in complex systems. Binary network density proved more accurate than valued density for assessing healthcare complexity, offering a valid approach for unique settings.

Keywords:

ambulatory care complexity science health services measurement methodology systems science

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Area of Science:

Complex systems analysis
Healthcare informatics
Network science

Background:

Complex systems exhibit nonlinear behavior due to component interdependence.
Quantifying interdependence is crucial for understanding system dynamics and consequences.
Existing measures of healthcare complexity may not fully capture system interdependence.

Purpose of the Study:

To demonstrate network density as a valid measure of interdependence in healthcare.
To assess the concurrent validity of network density against established complexity measures.
To compare the efficacy of valued versus binary network ties in measuring interdependence.

Main Methods:

Secondary analysis of the 2010 National Ambulatory Care Medical Survey data.
Calculation of valued and binary network densities for diagnoses and medications across 14 specialties.
Correlation of network density measures with existing complexity of care metrics, adjusting for diversity.

Main Results:

Significant partial correlations were found between diagnosis density and diagnosis/total input complexity.
Significant partial correlations were observed between medication density and medication/total output complexity.
Adjusted correlations for both diagnosis and medication densities were higher for binary than valued densities.

Conclusions:

Network density is a feasible and valid metric for quantifying interdependence in complex systems.
Binary network density provides a more accurate measure of complexity compared to valued density when adjusted for diversity.
This network density approach offers a complementary method for estimating complexity of care, applicable in diverse settings.