Effects of Pain Management Clinical Decision Support in an Inpatient Setting for Patients Experiencing Abdominal Pain

Disorganization of pain-management-related information in an EMR may limit clinicians’ ability to consider clinical factors comprehensively. A clinical decision support (CDS) system for pain management was developed and deployed at University of Missouri Healthcare.  CDS effects were examined for inpatients with diagnoses of diverticulitis, pancreatitis, and abdominal pain.  Statistically significant differences were found in the average NRS-11 self-reported pain scores with a mean reduction of 0.7, and number of pain related medications prescribed, with a mean reduction of 1.2 pain medication orders per day. No statistical correlation was found between the use of the CDS and prescription of different classes of pain medications at discharge, nor…

Use of Powerful Tools for Meaningful Conclusions from Sparse Data

At any given time, over 10 million women are pregnant or lactating in the United States, about 80% of these pregnancies result in a normal pregnancy and life birth. The remaining are associated with a wide range of pregnancy related diseases, an even lower percent of patients present with complications not related to the pregnancy itself. The size of the data is at first glance exciting for the informatics researcher however, the low incidence of positive cases of each type of disease results in sparse data difficult to analyze resulting in less than ideal models for data mining and knowledge…

Using Social Network Analysis and Natural Language Processing to Describe Communication Practices of Interdisciplinary Teams in Primary Care

The Electronic Medical Record (EMR) serves different purposes including documentation of care and billing. One part of the EMR at the University of Missouri Hospital and Clinics is the Message Center. Many people, including healthcare providers, nurses, social workers, therapists, office staff, and nurse care managers (known as the interdisciplinary team, or IDT) work together to deliver healthcare. This research examines how the Message Center is used in primary care by nurse care managers to document care coordination activities, including communication between patients, patient identified family or significant other, and the IDT. Care coordination activities, and the focus of those activities…

Seasonal Influenza Vaccine: Not easy shot to get

During the past nearly 50 years, antigenic variants of subtype H3N2 influenza A viruses have frequently emerged, causing significant public health challenges. The manner in which these variants emerge and their patterns of spread are not well understood. We identified 15 antigenic drift events with 16 antigenic variants during 1968–2016 by using a novel genomic sequence–based antigenicity inference method on ~40,000 H3N2 viruses. New antigenic variants were shown to emerge from certain locations in other continents rather than from Asia alone, and variants emerged year-round and took <2 months to spread across multiple continents. The uncertainty of the location of…

REDESIGN: RDF-based Differential Signaling Framework for Precision Medicine Analytics

Pathway-based analysis holds promise to be instrumental in precision and personalized medicine analytics. However, the majority of pathway-based analysis methods utilize “fixed” or “rigid” data sets that limit their ability to account for complex biological inter-dependencies. Here, we present REDESIGN: RDF-based Differential Signaling Pathway informatics framework. The distinctive feature of the REDESIGN is that it is designed to run on “flexible” ontology-enabled data sets of curated signal transduction pathway maps to uncover high explanatory differential pathway mechanisms on gene-to-gene level. The experiments on two morphoproteomic cases demonstrated REDESIGN’s capability to generate actionable hypotheses in precision/personalized medicine analytics.

Genetic targets for autism spectrum disorder identified by MU team

COLUMBIA, Mo. – Autism is a spectrum of closely related symptoms involving behavioral, social and cognitive deficits. Early detection of autism in children is key to producing the best outcomes; however, searching for the genetic causes of autism is complicated by various symptoms found within the spectrum. Now, a multi-disciplinary team of researchers at the University of Missouri created a new computational method that has connected several target genes to autism. Recent discoveries could lead to screening tools for young children and could help doctors determine correct interventions when diagnosing autism. Unlocking the genetic causes of autism requires data-intensive computations.

MU-LOC: A Deep Neural Network Method for Predicting Mitochondrially Localized Proteins in Plants

Targeting and translocation of proteins to the appropriate subcellular compartments is crucial for cell organization and function. Newly synthesized proteins are transported to mitochondria with the assistance of complex targeting sequences containing either an N-terminal pre-sequence or a multitude of internal signals. Compared with experimental approaches, computational predictions provide an efficient way to infer subcellular localization of a protein. However, it is still challenging to predict plant mitochondrially localized proteins accurately due to various limitations. Consequently, the performance of current tools can be improved with new data and new machine-learning methods. We present MU-LOC, a novel computational approach for large-scale…

An Analysis of Diabetes Mobile Applications Features Compared to AADE7TM: Addressing Self-Management Behaviors in People with Diabetes

Diabetes Self-management (DSM) applications (apps) have been designed to improve knowledge of diabetes and self-management behaviors. However, few studies have systematically examined if diabetes apps followed the American Association of Diabetes Educators (AADE) Self-Care BehaviorsTM guidelines. The purpose of this study was to compare the features of current DSM apps to the AADE7TM guidelines. In two major app stores, we used three search terms to capture a wide range of diabetes apps. Apps were excluded based on five exclusion criteria. A multidisciplinary team analyzed and classified the features of each app based on the AADE7TM. We conducted interviews with six…

Collaborations across disciplines: MU Thyroid Nodule Electronic Database (MU-TNED), a multidisciplinary informatics approach

Thyroid nodules are common findings and thyroid cancer is projected to be one of the leading causes of cancer in women. The EHR includes the necessary data needed to connect clinical research with patient outcomes. The objective for this project was to develop and validate a usable informatics tool for clinicians and researchers to record, analyze, and be able to manipulate the clinical and research data to benefit all collaborators. The tool was specifically designed to enable follow-up in a longitudinal manner to support multiple aspects of research. The informatics tool MU-TNED was designed with a multidisciplinary team including the…