Apparatus and method for managing interaction-based services
Technology #200804
Application
This new system provides an effective way to capture and manage interaction-based services, specifically, in areas like medicine where there can be multiple parties involved in the care of a single patient.
Problem
Over $59 million dollars is spent on using and managing patient records within a hospital over a 5-year period. In addition to the extra work and resources required to manage substantial amounts of paperwork, one study noted that only 62% of prescriptions written on paper by physicians were complete when received. That not only demands additional time by the pharmacist and physician, but also poses a huge liability if the incorrect medication is dispensed. These reasons are among the few that have pushed healthcare providers to seek out a superior alternative, such as systems that collect and manage patient interactions.
Technology
The interaction management system is made up of a storage medium that is able to retrieve records that correspond to individuals. From there, the system is able to asses any health risks, receive additional interaction data. It then compares the interaction data against interaction criteria and determines a healthcare plan for the patient.
Competitive Advantage
Compared to traditional paper patient files, this system is able to consolidate a patient history into one digital file, eliminating the probability for errors and increasing the efficiency of the healthcare organization.
Additionally, rather than simply collecting information this interaction management system uses a series of algorithms that are able to compare and validate patient interactions, further limiting the scope for error. This functionality is also capable of creating a treatment plan for the patient based on their health history, saving valuable time and resources in the healthcare system.
Opportunity
In 2009 the Health Information Technology for Economical and Clinical Health Act was mandated, pushing healthcare providers into the digital era of health records, or electronic medical records (EMR). This legislative push has created a $23.2 billion global market and a projected annual growth of 9.3%.
The adoption rate of EMR has also been staggering within a typically sluggish healthcare market, leaping from 12% to 59% since the healthcare mandate. This has forced many healthcare providers to find systems that have a wide range of functionalities and ensure a smooth transition.
Stage of Development
There have been extensive models built, both numerical and conceptual, to prove the effectiveness and viability of a system that manages patient interactions. Moving forward, the team is looking to make a prototype that can validate the effectiveness of the system within the medical community.
Patent Status
The Florida Atlantic University team has been granted a patent and would be interested in partnering or licensing with them to further the development of the technology.
Publication Date: August 5, 2014
U.S. Patent Application: US8799017 B2
Researchers
Marilyn E. Parker, PhD, RN, FAAN, is a part time clinical professor. She teaches online and participates with PhD, DNP and Master’s students on dissertations, capstone and other research and practice projects. She welcomes graduate students to join her program of nursing language research. Most recently Dr. Parker was Professor of Nursing at Florida Atlantic University in Boca Raton. Most recently, the third edition of Dr. Parker’s book, Nursing Theories and Nursing Practice, was published.
Dr. Abhijit Pandya is a Professor at Florida Atlantic University in the department of computer and electrical engineering and computer science. He received his Ph.D. at Syracuse University. His research focuses on neural network algorithms, VLSI implementation of neural networks, digital circuit design, and layout and verification.
Dr. Sam Hsu is a professor in the department of computer science and engineering at Florida Atlantic University. He has published over 70 papers and reviews on his research. His research interests include web technologies, computer internetworking, and web-based distance learning.
Shihong Huang is an Associate Professor in the Department of Computer Science & Engineering at Florida Atlantic University. She joined FAU in 2004 after obtaining her Ph.D. from the Computer Science and Engineering Department at the University of California, Riverside. Her research interests include reverse engineering for program understanding, program redocumentation, information visualization, technology assessment, and Web Systems evolution.
Field
Medicine, Information Technology, Computer Science
