Annual Report 2016-2017

The College of Computing and Digital Media has always prided itself on curriculum, creative work, and research that stays current with changes in our various fields of instruction. As we looked back on our 2016-17 academic year, the need to chronicle the breadth and excellence of this work became clear. We are pleased to share with you this annual report, our first, highlighting our accomplishments. Last year, we began offering three new graduate programs and two new certificate programs. We also planned six degree programs and three new certificate programs for implementation in the current academic year. CDM faculty were published more than 100 times, had their films screened more than 200 times, and participated in over two dozen exhibitions. Our students were recognized for their scholarly and creative work, and our alumni accomplished amazing things, from winning a Student Academy Award to receiving a Pulitzer. We are proud of all the work we have done together. One notable priority for us in 2016-17 was creating and strengthening relationships with industry—including expanding our footprint at Cinespace and developing the iD Lab—as well as with the community, through partnerships with the Chicago Housing Authority, Wabash Lights, and other nonprofit organizations. We look forward to continuing to provide innovative programs and spaces this academic year. Two areas in particular we’ve been watching closely are makerspaces and the “internet of things.” We’ve already made significant commitments to these areas through the creation of our 4,500 square foot makerspace, the Idea Realization Lab, and our new cyber-physical systems bachelor’s program and lab. We are excited to continue providing the opportunities, curriculum, and facilities to support our remarkable students. David MillerDean, College of Computing and Digital Mediahttps://via.library.depaul.edu/cdmannual/1000/thumbnail.jp

An ostensive information architecture to enhance semantic interoperability for healthcare information systems

Semantic interoperability establishes intercommunications and enables data sharing across disparate systems. In this study, we propose an ostensive information architecture for healthcare information systems to decrease ambiguity caused by using signs in different contexts for different purposes. The ostensive information architecture adopts a consensus-based approach initiated from the perspective of information systems re-design and can be applied to other domains where information exchange is required between heterogeneous systems. Driven by the issues in FHIR (Fast Health Interoperability Resources) implementation, an ostensive approach that supplements the current lexical approach in semantic exchange is proposed. A Semantic Engine with an FHIR knowledge graph as the core is constructed using Neo4j to provide semantic interpretation and examples. The MIMIC III (Medical Information Mart for Intensive Care) datasets and diabetes datasets have been employed to demonstrate the effectiveness of the proposed information architecture. We further discuss the benefits of the separation of semantic interpretation and data storage from the perspective of information system design, and the semantic reasoning towards patient-centric care underpinned by the Semantic Engine

Cohort Identification Using Semantic Web Technologies: Ontologies and Triplestores as Engines for Complex Computable Phenotyping

Electronic health record (EHR)-based computable phenotypes are algorithms used to identify individuals or populations with clinical conditions or events of interest within a clinical data repository. Due to a lack of EHR data standardization, computable phenotypes can be semantically ambiguous and difficult to share across institutions. In this research, I propose a new computable phenotyping methodological framework based on semantic web technologies, specifically ontologies, the Resource Description Framework (RDF) data format, triplestores, and Web Ontology Language (OWL) reasoning. My hypothesis is that storing and analyzing clinical data using these technologies can begin to address the critical issues of semantic ambiguity and lack of interoperability in the context of computable phenotyping. To test this hypothesis, I compared the performance of two variants of two computable phenotypes (for depression and rheumatoid arthritis, respectively). The first variant of each phenotype used a list of ICD-10-CM codes to define the condition; the second variant used ontology concepts from SNOMED and the Human Phenotype Ontology (HPO). After executing each variant of each phenotype against a clinical data repository, I compared the patients matched in each case to see where the different variants overlapped and diverged. Both the ontologies and the clinical data were stored in an RDF triplestore to allow me to assess the interoperability advantages of the RDF format for clinical data. All tested methods successfully identified cohorts in the data store, with differing rates of overlap and divergence between variants. Depending on the phenotyping use case, SNOMED and HPO’s ability to more broadly define many conditions due to complex relationships between their concepts may be seen as an advantage or a disadvantage. I also found that RDF triplestores do indeed provide interoperability advantages, despite being far less commonly used in clinical data applications than relational databases. Despite the fact that these methods and technologies are not “one-size-fits-all,” the experimental results are encouraging enough for them to (1) be put into practice in combination with existing phenotyping methods or (2) be used on their own for particularly well-suited use cases.Doctor of Philosoph

State Consent Policies and the Meaningful Use of Electronic Health Records Among Nonfederal Acute Care Hospitals in the United States

The less-than-nationwide use of electronic health record (EHR) systems to send, receive, and integrate (SRI) patient summary of care (PSC) records limits the ability of hospital administrators to maximize efficiency and improve quality in the continuum of care. Despite obvious differences in state health information exchange (HIE) consent policies, there is no known research that has determined if and what aspects of state-level HIE legislation affect the use of EHR systems to SRI PSC records. Guided by the unified theory of acceptance and use of technology (UTAUT), the purpose of this quantitative cross-sectional research study was to examine the relationship between one independent variable (type of HIE consent policy) and three dependent variables: percent of nonfederal acute care hospitals that electronically (a)send (b) receive (c) integrate PSC records from and into their EHR from outside providers respectively. Data analysis using multivariate analysis of variance (MANOVA) statistical test found that Opt-in policy states had the lowest percentage of hospitals engaging in the three domains. The study also found that the use of EHR systems was most rampant in states with relatively less stringent HIE policies., there was a non-statistically significant relationship between HIE policy type and the dependent variable. However, the relationship between year (secular trend) and the dependent variable was statistically significant as there was incremental changes in the independent variable between 2015 and 2017. The study contributes to positive social change by providing increased research within the (HIE) field aiming to promote government and private sector investment to understand and address technological, practice, and policy barriers regarding EHR-to-EHR system integrations