Temporal and Atemporal Provider Network Analysis in a Breast Cancer Cohort from an Academic Medical Center (USA)

Journal Title: Informatics - Year 2018, Vol 5, Issue 3

Abstract

Social network analysis (SNA) is a quantitative approach to study relationships between individuals. Current SNA methods use static models of organizations, which simplify network dynamics. To better represent the dynamic nature of clinical care, we developed a temporal social network analysis model to better represent care temporality. We applied our model to appointment data from a single institution for early stage breast cancer patients. Our cohort of 4082 patients were treated by 2190 providers. Providers had 54,695 unique relationships when calculated using our temporal method, compared to 249,075 when calculated using the atemporal method. We found that traditional atemporal approaches to network modeling overestimate the number of provider-provider relationships and underestimate common network measures such as care density within a network. Social network analysis, when modeled accurately, is a powerful tool for organizational research within the healthcare domain.

Authors and Affiliations

Bryan D. Steitz and Mia A. Levy

Keywords

Related Articles

Real-Time and Embedded Detection of Hand Gestures with an IMU-Based Glove†

This article focuses on the use of data gloves for human-computer interaction concepts, where external sensors cannot always fully observe the user’s hand. A good concept hereby allows to intuitively switch the interac...

Detecting Transitions in Manual Tasks from Wearables: An Unsupervised Labeling Approach†

Authoring protocols for manual tasks such as following recipes, manufacturing processes or laboratory experiments requires significant effort. This paper presents a system that estimates individual procedure transition...

Exploiting Rating Abstention Intervals for Addressing Concept Drift in Social Network Recommender Systems

One of the major problems that social networks face is the continuous production of successful, user-targeted information in the form of recommendations, which are produced exploiting technology from the field of recom...

Opening up the Black Box of Sensor Processing Algorithms through New Visualizations

Vehicles and platforms with multiple sensors connect people in multiple roles with different responsibilities to scenes of interest. For many of these human–sensor systems there are a variety of algorithms that transfo...

Data Provenance for Agent-Based Models in a Distributed Memory

Agent-Based Models (ABMs) assist with studying emergent collective behavior of individual entities in social, biological, economic, network, and physical systems. Data provenance can support ABM by explaining individual...

Download PDF file
  • EP ID EP44149
  • DOI https://doi.org/10.3390/informatics5030034
  • Views 255
  • Downloads 0

How To Cite

Bryan D. Steitz and Mia A. Levy (2018). Temporal and Atemporal Provider Network Analysis in a Breast Cancer Cohort from an Academic Medical Center (USA). Informatics, 5(3), -. https://europub.co.uk/articles/-A-44149