Data Science Commons^™

Clinical Decision Support Capabilities Of Commercially-Available Clinical Information Systems, Adam Wright, Dean F Sittig, Joan S Ash, Sapna Sharma, Justine E Pang, Blackford Middleton

Faculty, Staff and Student Publications

BACKGROUND: The most effective decision support systems are integrated with clinical information systems, such as inpatient and outpatient electronic health records (EHRs) and computerized provider order entry (CPOE) systems. Purpose The goal of this project was to describe and quantify the results of a study of decision support capabilities in Certification Commission for Health Information Technology (CCHIT) certified electronic health record systems.

METHODS: The authors conducted a series of interviews with representatives of nine commercially available clinical information systems, evaluating their capabilities against 42 different clinical decision support features.

RESULTS: Six of the nine reviewed systems offered all the applicable …

Artificial Intelligence – Ii: Anomaly Detection In Data Streams Using Fuzzy Logic, Muhammad Umair Khan

International Conference on Information and Communication Technologies

Unsupervised data mining techniques require human intervention for understanding and analysis of the clustering results. This becomes an issue in dynamic users/applications and there is a need for real-time decision making and interpretation. In this paper we will present an approach to automate the annotation of results obtained from data stream clustering to facilitate interpreting that whether the given cluster is an anomaly or not. We use fuzzy logic to label the data. The results will be obtained on the basis of density function & the number of elements in a certain cluster.

Data Mining: Assessment Of Features Quality Of Class Discrimination Using Arif Index And Its Application To Physiological Datasets, Dr. Muhammad Arif, A. Fida

International Conference on Information and Communication Technologies

Quality of features determines the maximum achievable accuracy by any arbitrary classifier in pattern classification problem. In this paper, we have proposed an index that can assess the quality of features in discrimination of patterns in different classes. This index is in-sensitive to the complexity of boundary separating different classes if there is no overlap among features of different classes. Proposed index is model free and requires no clustering algorithm to discover the clustering structure present in the feature space. It is only based on the information of local neighborhood of feature vectors in the feature space. This index can …

Data Mining: Analyzing Impact Of Outliers' Detection And Removal From The Test Sample In Blind Source Extraction Using Multivariate Calibration Techniques, S. R. Naqvi, F. Rehman, S. S. Naqvi, A. Amin, I. Qayyum, S. Khan, W. A. Khan

International Conference on Information and Communication Technologies

Blind source extraction (BSE) may be an essential but a challenging task where multiple sources are convolved and/or time delayed. In this article we discuss the performance of multivariate calibration techniques that comprise of classical least square (CLS), inverse linear regression (ILS), principal component regression (PCR) and partial least square regression (PLS) in achieving this task in robust speech recognition systems with varying signal-to-noise ratios (SNR). We specifically analyze two methods for identifying and removing outliers from the sample, namely; outlier sample removal (OSR) and descriptor selection (DS) for classical least square and factor Based regression respectively, which results in …

Artificial Intelligence – I: A Two-Step Approach For Improving Efficiency Of Feedforward Multilayer Perceptrons Network, Shoukat Ullah, Zakia Hussain

International Conference on Information and Communication Technologies

An artificial neural network has got greater importance in the field of data mining. Although it may have complex structure, long training time, and uneasily understandable representation of results, neural network has high accuracy and is preferable in data mining. This research paper is aimed to improve efficiency and to provide accurate results on the basis of same behaviour data. To achieve these objectives, an algorithm is proposed that uses two data mining techniques, that is, attribute selection method and cluster analysis. The algorithm works by applying attribute selection method to eliminate irrelevant attributes, so that input dimensionality is reduced …

Improving Clinical Quality Indicators Through Electronic Health Records: It Takes More Than Just A Reminder, Dean F Sittig, Jonathan M Teich, Jerome A Osheroff, Hardeep Singh

Faculty, Staff and Student Publications

No abstract provided.

The Storm 2.0 Project Next Generation Hurricane Data Collection, Santhana Krishnan Balaji

Honors Capstones

No abstract provided.

Use Of Instructional Video To Prepare Parents For Learning Infant Cardiopulmonary Resuscitation, Timothy S. Brannon, Lisa A. White, Julie N. Kilcrease, Lashawn D. Richard, Jana G. Spillers, Cynthia L. Phelps

Faculty, Staff and Student Publications

Parents of premature infants often receive infant cardiopulmonary resuscitation (CPR) training prior to discharge from the hospital, but one study showed that 27.5% of parents could not demonstrate adequate CPR skills after completing an instructor-led class. We hypothesized that parents who viewed an instructional video on infant CPR before attending the class would perform better on a standardized skills test than parents who attended the class with no preparation. Parents randomized to the intervention (video) group viewed the video within 48 hours of the CPR class. Parents in the control group attended the class with no special preparation. All parents …

Sensitivity Analysis Framework For Large And Complex Simulation Models, Ghaith Rabadi, Shannon Bowling, Charles Keating, Resit Unal

Engineering Management & Systems Engineering Faculty Publications

In this paper, a framework for conducting Sensitivity Analysis (SA) on large and complex simulation models is introduced. The framework consists of components that are designed to make the SA a systematic process that is easy to manage and follow by simulation analysts and practitioners. Unlike local SA (one-variable-at-a-time SA), the method presented here is variance-based and it is rooted in the field of Design of Experiments (DoE) where Input Variables are varied and Output Variables are measured. Based on the DoE results, a risk scoring system is developed to identify the sensitivity of the Input Variables, and as a …

Information Brokerage - A New Approach Using Knowledge Management, Robert Loew

Theses

Traditional knowledge management attempts to store the total enterprise knowledge into IT related structures, but knowledge management strategies should focus also on people and organisations and not just on technology.

This can be addressed in part by communicating knowledge between people, in and across organisations. Such communication focuses on the development and exchange of people’s experience.

This thesis introduces a hybrid knowledge management solution consisting of an automated system that includes people: employees, experts and Knowledge Brokers (KB). The hybrid concept supports the identification of suitable people for certain topics of discussion. Further, it supports the knowledge communication process by …

Taxonomy Development And Knowledge Representation Of Nurses' Personal Cognitive Artifacts, Sharon Mclane, James P Turley

Faculty, Staff and Student Publications

Nurses prepare knowledge representations, or summaries of patient clinical data, each shift. These knowledge representations serve multiple purposes, including support of working memory, workload organization and prioritization, critical thinking, and reflection. This summary is integral to internal knowledge representations, working memory, and decision-making. Study of this nurse knowledge representation resulted in development of a taxonomy of knowledge representations necessary to nursing practice.This paper describes the methods used to elicit the knowledge representations and structures necessary for the work of clinical nurses, described the development of a taxonomy of this knowledge representation, and discusses translation of this methodology to the cognitive …

Improving Follow-Up Of Abnormal Cancer Screens Using Electronic Health Records: Trust But Verify Test Result Communication, Hardeep Singh, Lindsey Wilson, Laura A Petersen, Mona K Sawhney, Brian Reis, Donna Espadas, Dean F Sittig

Faculty, Staff and Student Publications

BACKGROUND: Early detection of colorectal cancer through timely follow-up of positive Fecal Occult Blood Tests (FOBTs) remains a challenge. In our previous work, we found 40% of positive FOBT results eligible for colonoscopy had no documented response by a treating clinician at two weeks despite procedures for electronic result notification. We determined if technical and/or workflow-related aspects of automated communication in the electronic health record could lead to the lack of response.

METHODS: Using both qualitative and quantitative methods, we evaluated positive FOBT communication in the electronic health record of a large, urban facility between May 2008 and March 2009. …

Ontology Driven Integration Platform For Clinical And Translational Research, Parsa Mirhaji, Min Zhu, Mattew Vagnoni, Elmer V. Bernstam, Jiajie Zhang, Jack W. Smith

Faculty, Staff and Student Publications

Semantic Web technologies offer a promising framework for integration of disparate biomedical data. In this paper we present the semantic information integration platform under development at the Center for Clinical and Translational Sciences (CCTS) at the University of Texas Health Science Center at Houston (UTHSC-H) as part of our Clinical and Translational Science Award (CTSA) program. We utilize the Semantic Web technologies not only for integrating, repurposing and classification of multi-source clinical data, but also to construct a distributed environment for information sharing, and collaboration online. Service Oriented Architecture (SOA) is used to modularize and distribute reusable services in a …

Enhancing The Collection Process For The Delphi Technique, Petros Katsioloudis, John Brocato (Ed.)

STEMPS Faculty Publications

The purpose of this manuscript is to describe a process that enhances the data collection process for a Delphi technique. The approach consists of online platforms to expedite the process and reinforce the validity of the Delphi technique. The context of the study was the identification of quality indicators for visual-based learning material development for Technology Education programs for grades 7-12.

Computerized Provider Order Entry Adoption: Implications For Clinical Workflow, Emily M. Campbell, Kenneth P. Guappone, Dean F. Sittig, Richard H. Dykstra, Joan S. Ash

Faculty, Staff and Student Publications

OBJECTIVE: To identify and describe unintended adverse consequences related to clinical workflow when implementing or using computerized provider order entry (CPOE) systems. METHODS: We analyzed qualitative data from field observations and formal interviews gathered over a three-year period at five hospitals in three organizations. Five multidisciplinary researchers worked together to identify themes related to the impacts of CPOE systems on clinical workflow. RESULTS: CPOE systems can affect clinical work by 1) introducing or exposing human/computer interaction problems, 2) altering the pace, sequencing, and dynamics of clinical activities, 3) providing only partial support for the work activities of all types of …

Object Reuse And Exchange, Michael L. Nelson, Carl Lagoze, Herbert Van De Sompel, Pete Johnston, Robert Sanderson, Simeon Warner, Jürgen Sieck (Ed.), Michael A. Herzog (Ed.)

Computer Science Faculty Publications

The Open Archives Object Reuse and Exchange (OAI-ORE) project defines standards for the description and exchange of aggregations of Web resources. The OAI-ORE abstract data model is conformant with the Architecture of the World Wide Web and leverages concepts from the Semantic Web, including RDF descriptions and Linked Data. In this paper we provide a brief review of a motivating example and its serialization in Atom.