Participant: PROMISE AGEP Research Symposium, 2014
Department: Computer Science
Institution: University of Maryland, Baltimore County (UMBC)
Electronic Health Records Impact on Safety and Efficacy
The use of information technology in healthcare provision has increased significantly over the last decade. New regulations require healthcare providers utilize certain levels of technology. Technology in healthcare has been used in various ways including clinical decision support, prescribing of medication, validation of clinical data, genome mapping, etc. Several concerns such as privacy of patient data, confidentiality, clinical workflow interruption, and data ownership have been raised in various implementations of technology in healthcare. In particular, electronic health records (EHRs) have been adapted by many providers with the aim of improving the quality of care. However, not much research has been done in determining the impact of EHRs on clinical outcomes. This paper does a survey of clinical institutions that have adapted EHRs and the implications on safety and efficacy. A distinction is made between the direct and indirect impacts, and a connection is made between this impact and observed clinical outcomes.
Isaac Mativo earned his Bachelor of Science degree in Computer Science from University of Maryland Baltimore County in 2000. He received his Master of Science degree in Computer Science from University of Maryland Baltimore County in 2011. In 2012, he joined the doctoral program in Computer Science in at the University of Maryland Baltimore County.
Mr. Mativo has over 8 years work experience in various positions in the Information Technology industry. Employers he has worked for include Computer Sciences Corporation and CareFirst BlueCross BlueShield. While pursuing his graduate degree, Mr. Mativo has worked as a Teaching Assistant in Computer Science. Mr. Mativo is currently works as a Research Associate at the University of Maryland Center for Integrative Medicine.
Mr. Mativo has been a recipient of several honors and awards including a certificate of outstanding achievement at Computer Sciences Corporation. Mr. Mativo is a member of the American Medical Informatics Association (AMIA), Upsilon Pi Epsilon Computer Science Honor Society, Golden Key Honor Society, and University of Maryland Baltimore County Honors College.
Mr. Mativo’s research area is in the field of clinical informatics, and specifically on personalized medicine and clinical decision support systems. He is interested in the use of genome data to help predict clinical outcomes, as well as utilization of technology in healthcare including at the point of care.
Mr. Mativo lives in Columbia Maryland with his wife and three children. He is a marathoner and an active volunteer in his community.
GENERAL SUMMARY OF GRADUATE RESEARCH
My master’s paper was on the technology used in healthcare, specifically focusing on electronic medical records (EMRs). In that work, I identified the role EMRs play in healthcare provision as well as the barriers that exist for their adaption. I also assessed their actual usefulness and design considerations. I then identified key elements that needed to be considered in a successful EMR design and implementation. I wrote a paper on personal health records (PHR) where I surveyed several implementations. I analyzed the integration of PHRs and EMRs and identified technological challenges including secure messaging, authentication, and privacy.
I have done a literature survey on technology utilization on patient-centered medical homes (PCMH). PCMHs attempt to provide better healthcare based on collaboration between a team of providers and the patient. Integration of the electronic health records (EHRs) and the PHR, as well as the self-reported items by the patient become important things to consider. I have done a survey of informatics related media articles and scored them based on their relevance to informatics. These results were part of a presentation Media in Review done at the American Medical Informatics Association (AMIA) national conference in 2013.
My current research focuses on personalized medicine. This includes the use of genome data (SNPs) to help predict healthcare outcomes using machine learning techniques. This also includes the use of Big Data techniques to analyze trends and identify patterns.
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