We propose to develop a semantically driven, web-based IT framework that will (a) allow comparison of organizational structures of trauma centers and trauma systems and (b) collect data about the organization of trauma centers and trauma systems. Our first goal is to enable representatives of trauma care environments and verification/consultation bodies to use our framework for computer-assisted assessment of trauma care organizations. Our second goal is to support public health researchers by providing them access to the knowledge accumulated through verification and consultation processes. Currently, little is known about which structures and processes of trauma systems and trauma centers lead to optimal care for the injured patient, yet the role of structure in influencing performance has been widely recognized in the healthcare industry. One reason for this gap in knowledge is that, despite a strong regulatory framework, we lack unified, machine- interpretable models of the organization of trauma centers and trauma systems to foster comparability between different instances of each type of organization. Our proposed web services will be based on such a machine- interpretable model, which we propose to develop as an ontology of trauma center and trauma system organization under Aim 1. Within the domain of biomedicine, issues related to comparability have already been successfully addressed with ontologies-logical models of the components of a domain and their interrelations that are coded in a machine-interpretable language.
Under Aim 2 we will develop the technical means to integrate the ontology in a web service infrastructure.
Aim 3 is to create the infrastructure to be used by those seeking and those providing trauma care assessment and to enable comparison of organizational structures of trauma care environments. In the process of comparing organizational structures of trauma centers and trauma systems, data will be collected from the user and stored in our data repository. Thus, while running the service, we will also be creating a data source about organization of trauma centers and trauma systems, which we will make available to those conducting comparative research on the impact of organizational structures of trauma care facilities on patient outcomes under Aim 4. The interrelation between organizational structures and patient outcome is known in the public health literature, but we lack tools to explore its effects on trauma care environments in a computer-assisted manner; our project will provide an IT framework resolving this lack. It will contribute to information and knowledge processing, advanced information retrieval, and incorporation of machine intelligence into decision processes. By providing a common schema, it will also contribute to the integration of heterogeneous data types. Our project will impact the work of organizations that assess, verify, or designate trauma care environments, as well as organizations interested in self-assessing their own organization. Supporting comparison of these organizations will not only affect assessment or certification but also add to the comparability of patient outcome data by linking it to specific organizational components.

Public Health Relevance

We will develop an IT framework accessible on the Internet that facilitates and optimizes verification of trauma centers and consultation of trauma systems and fosters comparability between trauma care environments with different organizational structures and under different legislations. Making these structures more comparable will not only benefit those who provide verification or consultation to trauma care environments, it will also allow organizations unable to acquire assessment through third parties to do in-house assessments based on data collected through best-practice assessments for the benefits of the patients. In providing these services, our framework will collect data on the organization trauma care environments, and our framework will make that data available for researchers interested in comparative studies.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM111324-05
Application #
9649217
Study Section
Biomedical Computing and Health Informatics Study Section (BCHI)
Program Officer
Somers, Scott D
Project Start
2015-03-05
Project End
2019-08-08
Budget Start
2019-03-01
Budget End
2019-08-08
Support Year
5
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of Arkansas for Medical Sciences
Department
Miscellaneous
Type
Schools of Medicine
DUNS #
122452563
City
Little Rock
State
AR
Country
United States
Zip Code
72205
Utecht, Joseph; Brochhausen, Mathias; Judkins, John et al. (2017) Formalizing Evidence Type Definitions for Drug-Drug Interaction Studies to Improve Evidence Base Curation. Stud Health Technol Inform 245:960-964
Judkins, John; Utecht, Joseph; Brochhausen, Mathias (2016) Easy Extraction of Terms and Definitions with OWL2TL. CEUR Workshop Proc 1747:
Hicks, Amanda; Hanna, Josh; Welch, Daniel et al. (2016) The ontology of medically related social entities: recent developments. J Biomed Semantics 7:47
Utecht, Joseph; Judkins, John; Otte, J Neil et al. (2016) OOSTT: a Resource for Analyzing the Organizational Structures of Trauma Centers and Trauma Systems. CEUR Workshop Proc 1747:
Utecht, Joseph; Brochhausen, Mathias (2015) Measuring the Usability of Triple Stores for Knowledge Management on Trauma Care Organizations. CEUR Workshop Proc 1546:241-242