Data visualization for truth maintenance in clinical decision support systems

Abstract

Background and objectivesThe goal is to inform proactive initiatives to expand the knowledge base of clinical decision support systems.Design and settingWe describe an initiative in which research informationists and health services researchers employ visualization tools to map logic models for clinical decision support within an electronic health record.Materials and methodsWe mapped relationships using software for social network analysis: NodeXL and CMAP. We defined relationships by shared observations, such as two Arden rules within medical logic modules that consider the same clinical observation, or by the presence of common keywords that were used to label rules according to standardized vocabularies.ResultsWe studied the Child Health Improvement through Computer Automation (CHICA) system, an electronic medical record that contains 170 unique variables representing discrete clinical observations. These variables were used in 300 medical logic modules (MLM's) that prompted health care providers to deliver preventive counseling or otherwise served as clinical decision support. Using data visualization tools, we generated maps that illustrate connections, or lack thereof, between clinical topics within CHICA's MLMs.ConclusionsThe development of such maps may allow multiple disciplines commonly interacting over EMR platforms, and various perspectives (clinicians, programmers, informationists) to work more effectively as teams to refine the EMR by programming logic routines to address co-morbidities or other instances where domains of medical knowledge should be connected.

GenomicsKG: A Knowledge Graph to Visualize Poly-Omics Data

“…It will also help respondents to improve their prospective therapeutic options. In any clinical visualization and reporting system, 29 'truth maintenance' is essential. GenomicsKG tried to achieve this by integrating and linking multiple reliable patient data cohorts, as well as easy to use visual readabilities and generating customized report based on requirement of cancer type.…”

The Full Knowledge of Big Data in the Integration of Inter-Organizational Information

“…Rudolph, Savikhin, & Ebert (2009) developed FinVIs, a call tool that the user can use to perform a visual analysis in the financial scenario, assisting the decision maker to adopt alternatives with better results. In health area, Liu et al (2015) From what was previously exposed, we can identify that visual analysis tools facilitate decision making in the context of the real world (Shneiderman & Plaisant, 2015). From the perspective of big data, the decision making process is based on information gathered in the data repository, and through visualization techniques, decision makers can analyze the information through search and analysis tools (Zhang & Huang, 2014).…”

Innovative reflection on oral cancer research priorities: the contribution of social network analysis

“…These basic centrality measures have been used extensively in the healthcare literature to quantify the network positions of individual actors in networks. 9,10,11 The network analysis approach could represent an important contribution for scholars interested in oral cancer, as it identifies research gaps based on the strength of connections between keywords. The main goal of this study was to present a social network analysis of keywords used in studies in the field of oral cancer prevention.…”