BIME Research Projects

Sorted by Project Name

2016- 2017 University of Washington Race & Equity Initiative (R&EI) Award

Faculty Lead(s)

Janice A. Sabin

Keywords

Clinical & Leaarning Environment
Implicit Bias
Implicit Bias Workshop
Strategies to Reduce Impact of Implicit Bias

Project Summary

The UW School of Medicine developed an online course on implicit bias in health care aimed at clinical faculty who train medical students across the WWAMI region (Sabin, lead content expert). The course addresses three core learning objectives regarding implicit bias. The Learning Objectives of the course state that by the end of the course learners will be able to: 1. define implicit bias and how it is manifested in health care, 2. recognize how implicit bias may be operating in the clinical setting and learning environment, and 3. apply strategies that can be used to minimize impact of implicit bias. The course begins with students voicing their real world experiences as recipients of bias based upon their background. With funding from the Race & Equity Initiative (R&EI), we propose to develop implicit bias workshop materials for faculty and trainees to extend use of the course to a workshop format to address the topic of implicit bias in health care more in-depth. A menu of real-time and longitudinal evaluation metrics will be developed for use with the workshop based upon the Kirkpatrick Model of Evaluation.


Bias in Physician-Patient Communication

Faculty Lead(s)

Annie Chen
Janice A. Sabin

BIME Student(s)

ChungKei Wilson Lau

Keywords

Bias
Physician-Patient Communication

Project Summary

This research employs text mining techniques to study communication patterns in physician-patient interactions.  In particular, we are interested in the effect that unconscious biases may have on the outcomes of clinical interactions.


Body Listening Project

Faculty Lead(s)

Annie Chen

Keywords

Body Awareness
Body Listening
Collective Tagging
Folksonomies
Knowledge Organization

Project Summary

Being in tune with and and being able to read one’s body can be invaluable in management of one’s health.  The Body Listening Project is a collaborative effort to create a public repository of people’s experiences of body listening and body awareness.  The repository will be used to develop patient education programs, knowledge resources on body listening, and a novel system featuring innovative visual interfaces for browsing and exploring content.  The Body Listening Project research team is comprised of faculty and students from the University of Washington, the University of North Carolina, Chapel Hill, and University at Buffalo; as well as industry collaborators and independent researchers.


Clinical sequencing in cancer: Clinical, ethical, and technological studies

Faculty Lead(s)

Peter Tarczy-Hornoch

Faculty

Sean Mooney
David Crosslin

BIME Student(s)

Wayne Liang, MD

Project Summary

The informatics work on this project centers on the integration of whole exome sequence data into the Electronic Health Record. Subprojects include a) working on and with variant annotation databases, b) integrating reports on exome sequencing into the EHR, and c) integrating computable variant data into the EHR for automated decision support with an emphasis on pharmacogenomics and ACMG panel testing.

The overall project is part of NHGRI Clinical Sequencing and Exploratory Research (CSER) initiative. The overall project proposes a randomized controlled trial of usual care vs. the addition of exome analysis in University of Washington Medical Genetics Clinic patients who have clinical indications for colorectal cancer/polyposis (CRCP) genetic testing. We will evaluate the effectiveness of this technology for the identification of clinically relevant CRCP gene mutations, cost, and patient derived measures. After deliberations by experts to indentify variants that are incidental findings that should be returned, we will also return CLIA certified results to the participants. We will obtain structured feedback from subjects in both the usual care and exome arms of the RCT to evaluate their experiences. We will further consider the input of referring physicians and patients using focus groups. We will investigate the legal basis of the need to return CLIA certified research results. An important component of our work is determination of not only which results to return, but how best to incorporate these genomic data into the medical record. Finally, we will perform CRCP gene discovery studies for families without identifiable CRCP mutations; such novel gene discovery can impact prevention and treatment.


COmmuNity-engaged SimULation Training (CONSULT) for Cultural Competence

Faculty Lead(s)

Janice A. Sabin

Keywords

Bias Assessment
Community Engaged Research
Community Engagement
Provider Implicit Bias
Training Intervention

Project Summary

December 01, 2017 through November 30, 2022, NIH, NIMHD, Scored 1st Percentile

PI: Jennifer Tjia, MD, UMass Medical School

Project Summary: CONSULT is a training intervention being developed by UMass Medical School that features community-members from racial, ethnic, and socioeconomic disadvantaged populations as high-fidelity standardized patients (actors trained to portray patients in simulations). The goal of CONSULT is to train early-stage clinicians to develop awareness and communication skills that can overcome sociocultural differences between patients and providers, and the effects of these differences on communication and clinical outcomes. The CONSULT investigator team is based at the UMass Special Populations Resource Center, a NIH-CTSA funded center of academic and community partners who work together to develop rigorous, respectful, and impactful community-engaged research. Janice Sabin is the lead content expert on measures of implicit bias. Dr. Sabin, in collaboration with Dr. Tjia, will bring her expertise in implicit bias to the project. Her activities will include; serving as Project Implicit lead contact, guiding analysis for bias assessment and bias awareness, monitoring data collection and IAT participation, contributing to interpretation of analysis, findings and manuscript writing, and problem solving with Project Implicit as needed.


Conceptual Framework for Simulation Intervention

Faculty Lead(s)

Anne Turner

Keywords

Public Health Informatics

Project Summary

Self-efficacy Theory and Adult Learning theory

The goal of this AHRQ funded project is to develop a simulation-based training intervention for 911 dispatchers based on Self-efficacy Theory and Adult Learning Theory. The randomized controlled trial will test whether simulated instruction can improve the recognition and response of cardiac arrest calls by 911 dispatchers in King County, Washington.


Critical Illness Phenotype Extraction (DECIPHER) Project

Faculty Lead(s)

Meliha Yetisgen

Keywords

Clinical Informatics

Project Summary

Clinical and translational research involving critical illness phenotypes relies heavily on the identification of clinical syndromes defined by consensus definitions (e.g. pneumonia, sepsis, acute lung injury). The overall goal of this project is to apply natural language processing, machine learning, and network analysis to develop an automated screening tool that accurately identifies critical illness phenotypes and their interactions among ICU patients.


Decision Making in Radiation Oncology

Faculty Lead(s)

John Gennari

Keywords

Clinical Informatics

Project Summary

In collaboration with Prof. Mark Phillips, I am exploring a couple of approaches to improving decision making in the radiation oncology setting.

First, we are exploring the ability of Bayesian Nets to detect incorrect, or sub-optimal radiation treatment plans. Our approach is novel, in that we are exploring the ability to create and modify the topology of these Bayes nets automatically, as new information and data become available.

Second, in the follow-up setting for radiation treatment patient, we are looking to improve decision making for those patients who may need additional imaging or treatment. As an example domain, we focus on CNS disease, such as brain cancers, or brain metastases. Our approach here is patient-centered; we plan to provide a smart-phone app for patients to log self-reported symptoms and standard neurological test that assess cognitive and motor skills. These results can then be transmitted as needed to the clinical decision maker for followup. Our approach is in contrast to the current standard of care, where the followup patient is scheduled for visits every 3 months to assess symptoms.


Discovering the Analytic Potential of EHR Data

Faculty Lead(s)

Adam Wilcox

Faculty

Sean Mooney

Project Summary

With increasing availability of electronic health data from EHRs, there has been expanding interest in using this data to identify populations for targeted health interventions. With a small proportion of patients using a majority of healthcare resources, the potential benefit of predicting high cost patients is clear, though early efforts have delivered few gains.

This project involves a manual review of a set of high-cost patients to characterize the ability of electronic health data to appropriately predict high utilization. Patient records will be reviewed for indications of declining health to provide an estimate of potential benefit for risk prediction. Information for prediction will also be characterized for its availability in structured electronic form. This project will be critical to inform one of the most invested areas of healthcare analytics.

Project can provide research opportunities for interested graduate students and post-docs.


Education-Practice Partnership to Improve Advanced Heart Failure (AHF) Training and Outcomes for Rural and Underserved Populations in an Accountable Care Organization (ACO)

Faculty Lead(s)

Brenda Zierler

Faculty

Janice A. Sabin

Keywords

Implicit Bias
Interprofessional Education
Rural & Underserved Communities

Project Summary

Grant: 1 D09 HP 28670-01-00,  Health Research Services Administration,  2015-2017

The proposed project enhances a partnership among UW SoN, UWMC’s RHC, and UWMC’s Institute for Simulation and Interprofessional Studies (ISIS). The project will provide clinical education and training for graduate nursing students in an ACO which uses advanced clinical information technology (IT) to provide evidence-based clinical services for rural, diverse, and medically underserved (MU) patients with AHF from five states (WA, WY, AK, MT, ID; WWAMI). SoN and UW RHC to oversee: curricular enhancements and clinical training of graduate nursing students within an ACO; preceptor recruitment/training; site development and field placements in rural and/or MU areas; Health IT that includes using technologies and approaches for engaging and monitoring AHF patients; evaluation of the innovative clinical training model;  2) 3) Create a Preceptor Training Toolkit that includes effective teaching strategies for adult learners with training on facilitation, providing effective feedback, coaching and mentoring; unconscious bias in rural and underserved communities; and methods and tools for measuring preceptor competencies and student clinical competencies and readiness to practice; 4) Establish a Regional AHF Collaborative for referring PCPs and future preceptors; offer weekly TeleAHF Conferences and online training modules to improve AHF care.


Effectiveness of Patient-Centered Technology on Medication Errors During Intensive Chemotherapy Treatment

Keywords

Chemotherapy
Medication Error
Patient Self-Care

Project Summary

This project will develop, pilot test, and evaluate a patient-centered self-monitoring/documentation system to track the accuracy of dosages and frequency of drug administrations that patients receive during complex, intensive, in-patient chemotherapy treatment regimens in an effort to reduce potential medication administration errors. In addition, the project will record and document patient reported medication reactions and side effects, as well as evaluate patients’ and providers’ (physicians, nurses) opinions and satisfaction with a patient-centered treatment tracking system that is intended to accurately track treatment and reactions, and to prevent potential errors.

Collaborators: Clinical faculty at UWMC/Seattle Cancer Care Alliance (SCCA)

Project can provide research opportunities for interested graduate students and post-docs.


Electronic Medical Records and Genomics (eMERGE) Network Coordinating Center

Faculty Lead(s)

David Crosslin

BIME Student(s)

Wayne Liang, MD
Jared Erwin
Taryn Hall, PhD

Keywords

Bioinformatics
Electronic Health Records
Genetics
Genomics

Project Summary

The Coordinating Center will remain responsible for cross-study functions, conducting quality control analyses of sequencing data, harmonizing data across studies, and supporting cross-study analyses. The University of Washington team, led by Drs. Crosslin, will manage the genomic data for the eMERGE III Coordi-nating Center as a sub-contract with the parent grant at Vanderbilt University. Our group has extensive expertise in providing sequencing data production and analysis support for many both sequencing and genotyping studies. Specifically, we will develop and manage an efficient genomic information workflow to support clinical decision mak-ing for the 25, 000+ eMERGE participants.


Electronic Medical Records and Genomics (eMERGE) Network, Phase III Study Investigators

Faculty Lead(s)

Gail Jarvik
Eric Larson

Faculty

David Crosslin

BIME Student(s)

Wayne Liang, MD
Jared Erwin
Taryn Hall, PhD

Keywords

Bioinformatics
Electronic Health Records
Genetics
Genomics
Phenotype

Project Summary

We will develop policies and practices for individualized evidence-based medical practice, add to the database of variant classifications, accomplish discovery through sequencing of clinically significant genes, and improve the linking of high-throughput genomic methods to data extracted from electronic health records for regional and national “mega-epidemiology”, focusing on colorectal cancer/polyposis, triglycerides, and neutrophil count.


Epigenetics and Transcription in Leishmania

Faculty Lead(s)

Peter Myler

Keywords

Bioinformatics
Genomics
Parasite Molecular Biology

Project Summary

The very first cosmid clone from the Leishmania major genome that we sequenced at Seattle Biomed in 1997 offered insight into the unusual gene organization of trypanosomatid genomes – it contained a divergent strand-switch region (as it turned out, the only one on all of chromosome 1). Over the next 10 years, my laboratory was at the forefront in defining the genomic elements and chromatin modifications involved in transcription initiation in Leishmania, as well as defining many of the protein components of the RNA polymerase II and III initiation and elongation complexes. After a brief hiatus in the late 2000s, these activities have been re-kindled by my involvement (in collaboration with the Borst group in Amsterdam) in showing that the trypanosomatid-specific modified DNA base J plays an important role in transcription termination in Leishmania. I am now PI on an NIAID grant investigating the sequence elements and protein machinery involved J insertion and maintenance, as well as the molecular mechanism(s) underlying its involvement in transcription termination.

  1. Martínez-Calvillo S, Yan S, Nguyen D, Fox M, Stuart K, Myler PJ. (2003) Transcription of Leishmania major Friedlin chromosome 1 initiates in both directions within a single region. Mol Cell, 11:1291-9. PubMed: 12769852.
  2. van Luenen HG, Farris C, Jan S, Genest PA, Tripathi P, Velds A, Kerkhoven RM, Nieuwland M, Haydock A, Ramasamy G, Vainio S, Heidebrecht T, Perrakis A, Pagie L, van Steensel B, Myler PJ, Borst P. (2012) Glucosylated hydroxymethyluracil, DNA base J, prevents transcriptional readthrough in Leishmania. Cell, 150:909-21. PubMed: 22939620; PubMed Central: PMC3684241.
  3. Sekar A, Merritt C, Baugh L, Stuart K, Myler PJ. (2014) 10.6900 encodes the glucosyltransferase involved in synthesis of base J in Trypanosoma brucei. Mol Biochem Parasitol, 196:9-11. PubMed: 25064607; PubMed Central: PMC4206709
  4. Genest PA, Baugh L, Taipale A, Zhao W, Jan S, van Luenen HG, Korlach J, Clark T, Luong K, Boitano M, Turner S, Myler PJ, Borst P. (2015) Defining the sequence requirements for the positioning of base J in DNA using SMRT sequencing. Nucl Acids Res, 43:2102-15. PubMed: 25662217; PubMed Central: PMC4344527.


Ethically responsible Clinical Decision Support for Lynch Syndrome Screening

Faculty Lead(s)

Diane M. Korngiebel

Faculty

Jan Carline
Peter Tarczy-Hornoch

Keywords

Decision Support
Genomic Medicine
Implementation Science

Project Summary

This project’s end deliverable is a computerized Clinical Decision Support tool for Lynch Syndrome screening that would tackle a health-care system-wide issue of tailoring routine clinical care to accommodate local needs, reflect a nationally developing standard of practice for universal colorectal cancer tumor testing for Lynch Syndrome, and address bioethical issues of informed consent and returning findings to patients and their families concerning heritable colorectal cancer. The aims are: 1. Identify through interviews with key content experts and decision-makers the critical health system elements and decision points for adaptation of colorectal tumor testing in two patient care settings; 2. Identify through interviews and targeted surveys of geneticists and non-geneticists the barriers, facilitators, and priorities for successfully deploying a local clinical decision support tool for diagnostic genetic tests that leverages the Electronic Medical Record; and 3. Test the decision support tool to evaluate clinical utility and appropriateness through evidence-based usability methods The improvement in care and information conveyance could, ultimately, save lives and deliver on the promise of personalized genomic medicine.

There are potential opportunities for students to assist in creating and testing a decision support prototype with partner clinics.


Foundational Model of Anatomy

Faculty Lead(s)

James Brinkley

Project Summary

The Foundational Model of Anatomy Ontology (FMA) is an evolving computer-based knowledge source for biomedical informatics; it is concerned with the representation of classes or types and relationships necessary for the symbolic representation of the phenotypic structure of the human body in a form that is understandable to humans and is also navigable, parseable and interpretable by machine-based systems. Specifically, the FMA is a domain ontology that represents a coherent body of explicit declarative knowledge about human anatomy. Its ontological framework can be applied and extended to all other species. http://www.si.washington.edu/projects/fma


HEALTH-E

Faculty Lead(s)

George Demiris

BIME Student(s)

Yong Choi
Laura Kneale
Savitha Sangameswaran

Keywords

Aging
Clinical Informatics
Consumer Informatics
Patient Engagement

Project Summary

The aim of this project is to utilize an informatics platform to assess multiple components of wellness for community dwelling older adults and visualize health related information to support shared decision making.

Project URL:http://www.health-e.info


Hospice Caregiving Research Network

Faculty Lead(s)

George Demiris

BIME Student(s)

Yong Choi

Keywords

Caregiving
Clinical Informatics
Consumer Informatics
Hospice

Project Summary

The aim of this project is to explore the use of informatics s tools as a platform for the delivery of interventions aiming to support hospice caregivers. Such initiatives aim to reduce caregiver anxiety and increase the participation of patients and caregivers in interdisciplinary team meetings in hospice.

Project URL: http://www.hospice-research.org


Identifying Variation for Applying Process and Quality Improvement

Faculty Lead(s)

Adam Wilcox

Project Summary

As part of its clinical process improvement efforts, UW Medicine has started efforts to identify areas of variation for high-cost patients, in order to suggest focused quality improvement processes. To perform this analysis successfully, electronic data must be extracted that can characterize different areas of care and variation in costs, and also to identify subpopulations within the high-cost services.   This project will work closely with the clinical process improvement leaders to appropriately extract and represent clinical data for variation analysis, as well as develop reports for subpopulation analysis.  This is a practical project involving healthcare analytics, where appropriate research and analytics methods can facilitate the data query, analysis and interpretation.

Project can provide research opportunities for interested graduate students and post-docs.


Information Behaviors in the Context of Chronic Illness

Faculty Lead(s)

Annie Chen

BIME Student(s)

Aarti Swaminathan

Keywords

Chronic Illness
Chronic Pain
Cognitive Representation
Fibromyalgia
Information Behaviors
Self-Management

Project Summary

Patients who have a chronic condition, or multiple chronic conditions, encounter information and develop knowledge and skills to manage their condition better over time.  Over the course of illness, patients may initiate and/or experience differences in aspects of their health management, including patient-provider interaction, information seeking behaviors, treatment choices and lifestyle changes.  This project focuses on how patients with chronic conditions, particularly fibromyalgia and other pain conditions, learn to manage their health over the course of illness, and particularly, the role that information plays in this process.


Information Extraction from Clinical Records

Faculty Lead(s)

Meliha Yetisgen

Keywords

Clinical Informatics

Project Summary

Accessibility to patient data available in EMR systems is critical to improve health care process. However most patient information is represented in free-text form and textual information is difficult for automated approaches to reliably access. A representation step is required to convert the unstructured information available in free-text into a structured format so that the automated approaches can work on. In this project, we focus on extraction of medical entities (e.g. medical problem, treatments, tests), temporal phrases, and their relations.


Information Resources and Information Quality for Complementary and Integrative Health

BIME Student(s)

Lisa Taylor-Swanson, PhD

Keywords

Complementary & Integrative Health (CIH)
Health Information Quality

Project Summary

In their search for effective health management strategies, patients with chronic conditions often seek out and employ complementary and integrative health (CIH) treatments.  We can find abundant information about CIH treatments, therapies, and modalities online, and though there is some extant research concerning the quality and reliability of this information, there is much that we still do not know.  Because people may encounter this information and potentially act upon it, it is important for health care providers and researchers to have a better understanding of what is available online about CIH modalities.  The aim of this project is to characterize the topography of online CIH information and develop better ways of organizing and delivering CIH information to consumers.


Interactive Visual Analytics of Narrative and Textual Data for Internet Interventions

Faculty Lead(s)

Annie Chen

BIME Student(s)

William Kearns

Keywords

Cognitive Behavioral Therapy
Interactive Visual Analytics
Narrative Data
Text Mining

Project Summary

In recent years, we have seen a dramatic increase in Internet interventions.  The data from these interventions often includes a free text component such as chat messages, text messages, or a discussion forum.  This data can be a rich source of qualitative information for understanding study participants’ experiences with the intervention, which can in turn be used to improve their experience, as well as increase the effectiveness of the intervention.  The narrative form of this data, coupled with its serial nature, makes it both a challenge and particularly worthy of study.  This project is focused on developing a platform that facilitates visual exploration of free text data from health behavior interventions, with a particular emphasis on interventions employing cognitive behavioral therapy (CBT).  This project is in collaboration with Seattle Children’s Research Institute.


Investigating New Technologies to Facilitate Communication Between EMS Providers and Limited English Proficiency Individuals

Project Summary

The purpose of this community-based Medic One Foundation research is to test the potential use of new translation technologies to improve communication between firefighters and individuals with limited English proficiency (LEP). The project evaluates and compares a commercially available translation software tool designed specifically for EMS response with the more generic online statistical machine translation tool, Google Translate. We use evidence-based scenarios and conduct mock EMS response sessions with King County firefighters and Chinese and Spanish speaking LEP individuals. We aim to evaluate the accuracy and perceived usefulness of the two different translation technologies in assisting communications between firefighters and non-English speaking community members.


Investigating the Health Information Management of Older Adults

Faculty Lead(s)

Anne Turner

BIME Student(s)

Yong Choi

Keywords

Public Health Informatics

Project Summary

This five year AHRQ funded project involves an in-depth investigation of the health information needs and management of a diverse group of older adults and their caregivers.  Based on the results of extensive qualitative studies (interviews, focus groups, and surveys), we will develop a model of health information management for older adults. The model will help identify key design principles for the future design of information systems to facilitate the successful management of health information by older adults. This project involves collaboration between faculty from the UW Schools of Public Health, Medicine, Nursing and Engineering and King County community agencies serving older adults.


Local Public Health Information Workflow

Faculty Lead(s)

Anne Turner

Keywords

Public Health Informatics

Project Summary

Public Health Department Information Workflow

I am involved in several projects using detailed qualitative ethnographic methods (interviews, focus groups, and observations) to investigate the information workflow of public health activities of local health departments throughout the Northwest. Areas of local public health practice research have included communicable disease reporting, emergency preparedness, business continuity planning, chronic disease prevention and the creation of health education materials.


Machine Translation for Health Informatics

Faculty Lead(s)

Anne Turner

Keywords

Public Health Informatics

Project Summary

Machine Translation to Improve Access to Multilingual Health Information

The goal of this research study is to investigate current public health translation processes and increase the availability of multilingual public health information for limited English proficiency (LEP) populations through advancing domain-specific machine translation (MT) technology. This project involves 1) investigating the information needs and workflow of public health professionals involved in creating multilingual health materials and 2) developing a novel domain-specific machine translation tool that fits with public health workflow and 3) evaluating the potential impact of using machine translation technology to assist with the production of multilingual consumer health materials. The long term goal of this project is to develop cost effective methods to expand the availability of health information for LEP populations while maintaining accurate and readable content.


Motivations, Contexts and Effects of Tobacco Use

Faculty Lead(s)

Annie Chen

Keywords

Electronic Cigarettes
Hookah
Smoking Cessation
Text Mining
Tobacco Use

Project Summary

In recent years, we have seen increased use of electronic cigarettes and hookah, and there is currently a need to understand more about the use experience of these tobacco products. This project focuses on investigating the motivations, contexts and effects of tobacco use, particularly from social media sources, and employing text mining and visualization techniques. This work is in collaboration with the University of Utah and the University of California, San Diego.


NLP Detection of Critical Radiology Recommendations

Faculty Lead(s)

Meliha Yetisgen

Keywords

Clinical Informatics

Project Summary

Communication of recommendations and abnormal test results is prone to error. If important imaging findings and recommendations are not systematically identified and promptly communicated to referrers, poor patient outcomes can result. In this project, we investigate NLP and supervised classification approaches to identify critical recommendation sentences in radiology reports.


Precision Medicine Informatics Group

Faculty Lead(s)

Peter Tarczy-Hornoch
Sean Mooney
David Crosslin

Faculty

Beth Devine
Diane M. Korngiebel
Brian Shirts
Neil Abernethy

BIME Student(s)

Maher Khelifi
Shuyang Wu
Dae Lee
Taryn Hall, PhD
Chia-Ju Lee

Keywords

Bioinformatics
Clinical Informatics
Consumer Informatics
Decision Support
Genetics
Genomic Medicine
Genomics
Machine Learning
Patient Engagement
Physician-Patient Communication
Precision Medicine
Translational Bioinformatics

Project Summary

The Precision Medicine Informatics Group is an umbrella research group that brings together multiple students and faculty interested broadly in the domain of precision medicine and translational bioinformatics. The group meets weekly to discuss and get feedback on the research projects of faculty, student and postdoctoral students who are members of the group. The discussions include discussions of relevant journal articles, RFAs, grants, dissertation proposals, dissertation projects, etc. The two broad areas of focus are a) Precision Medicine in the context of Genomic Medicine, and b) Precision Medicine in the context of predictive analytics using EHR data plus/minus genotype or other biomarker type data. Projects include machine learning for prediction of biological pathways, machine learning for prediction of clinical outcomes, using the EHR to phenotype patients, developing knowledge bases of clinical genomic knowledge, development and implementation of genomic decision support, shared patient/provider genomic decision support. Major research projects include the UW faculty working on the informatics aspects of the UW CSER and eMERGE grants and the eMERGE bioinformatics data coordinating center and the CSER coordinating center informatics core. For more information on specific projects led by faculty and students please see Research Projects Grouped by Faculty or click on the name of a faculty or student in PMIG.


Predicting Appropriate Admission of Bronchiolitis Patients in the Emergency Room

Faculty Lead(s)

Gang Luo

Keywords

Decision Support
Forecasting
Machine Learning

Project Summary

Bronchiolitis is the most common illness leading to hospitalization in young children. For children under age two, bronchiolitis incurs an annual total inpatient cost of $1.73 billion. Each year in the U.S., 287,000 emergency department (ED) visits occur because of bronchiolitis, with a hospital admission rate of 32-40%. Due to a lack of evidence and objective criteria for managing bronchiolitis, ED disposition decisions (hospital admission or discharge to home) are often made subjectively resulting in significant practice variation. Studies reviewing admission need suggest that up to 29% of admissions from the ED are unnecessary. About 6% of ED discharges for bronchiolitis result in ED returns with admission. These inappropriate dispositions waste limited healthcare resources, increase patient and parental distress, expose patients to iatrogenic risks, and worsen outcomes.

Clinical guidelines are designed to reduce practice variation and improve clinicians’ decision making. Existing guidelines for bronchiolitis offer limited improvement in patient outcomes. Methodological shortcomings include that the guidelines provide no specific thresholds for ED decisions to admit or to discharge, have an insufficient level of detail, and do not account for differences in patient and illness characteristics including co-morbidities.

Predictive models are frequently used to complement clinical guidelines, reduce practice variation, and improve clinicians’ decision making. Used in real time, predictive models can present objective criteria supported by historical data for an individualized disease management plan and guide admission decisions. However, existing predictive models for bronchiolitis patients in the ED have limitations, including low accuracy and the assumption that the actual ED disposition decision was appropriate. To date, no operational definition of appropriate admission exists. No model has been built based on appropriate admissions, which include both actual admissions that were necessary and actual ED discharges that were unsafe.

To fill the gap, the proposed project will: (1) Develop an operational definition of appropriate hospital admission for bronchiolitis patients in the ED. (2) Develop and test the accuracy of a new model to predict appropriate hospital admission for a bronchiolitis patient in the ED. (3) Conduct simulations to estimate the impact of using the model on bronchiolitis outcomes. The project will produce a new predictive model that can be operationalized to guide and improve disposition decisions for bronchiolitis patients in the ED. Broad use of the model would reduce iatrogenic risk, patient and parental distress, healthcare use, and costs and improve outcomes for bronchiolitis patients. If the model proves to be accurate and associated with improved outcomes, future study will test the impact of using it in a randomized controlled trial following its implementation into an existing electronic medical record to facilitate real-time decision making.


Rapid Development of an Analytics Repository Library

Faculty Lead(s)

Adam Wilcox

Project Summary

The UW Medicine analytics infrastructure includes data from two different electronic health records (EHRs) distributed across four institutions and multiple ambulatory sites of care. With that data distribution, there has been significant variation in systems, some related to differences in patient mix and some due to differences in EHR implementation.  As a result, the analytics data can be difficult to harmonize across system and sites of care.

The analytics challenge of this project is to apply informatics principles to create a harmonized analytics repository and library of common concepts.  Harmonization will use standardized data models with value sets mapping to clinical concepts.  Areas for informatics research are the development and application of machine learning, statistics and language processing tools to automate data harmonization or identify areas where it could be harmonized. This is a real-world application of informatics that will have a direct impact on the access and use of data at UW Medicine.

Project can provide research opportunities for interested graduate students and post-docs.


Semantics for Biological Processes

Faculty Lead(s)

John Gennari

BIME Student(s)

Karam Kim
Lucy Wang

Keywords

Bioinformatics
Translational Informatics

Project Summary

In this project, we pursue ontology-based informatics research that focuses on the representation and use of process knowledge within biomedical applications. Our primary driving use case is with bio-simulation systems. We collaborate closely with bioengineers who build simulation models of biology ranging from blood flow to pathway-level molecular processes.

A primary work product has been the Ontology of Physics for Biology, as published in the BioPortal collection of biological ontologies. See our project home page for more information, including our project’s publications to date.

John Gennari and Daniel Cook co-lead this project.


Structural Genomics of Infectious Disease

Faculty Lead(s)

Peter Myler

Keywords

Bioinformatics
Drug Development
Structural Biology

Project Summary

In 2001, I began working in the field of structural genomics, being Co-PI on the NIGMS-funded Structural Genomics of Pathogenic Protozoa (SGPP) project headed by Wim Hol and the University of Washington. Because of my involvement in the TriTryp genome sequencing projects, my group performed all Target Selection for SGPP. I am currently PI and Director of the Seattle Structural Genomics Center for Infectious Disease (SSGCID), which has been funded under a contract from NIAID since 2007. The mission of SSGCID is to use X-ray crystallography and NMR spectroscopy to solve the structure of proteins targets in emerging and re-emerging infectious disease organisms, primarily to facilitate development of new therapeutics using structure-based drug design, and toward this goal we have solved ~800 protein structures. SSGCID is extremely collaborative; providing clones, purified protein and structures to over 200 investigators around the world. Several of these collaborations have resulted in additional funding from sources such as NIH, BMGF and NATO. One particular success is the Structure Guided Drug Design Consortium (SDDC), which works closely with MMV and the TB Alliance to generate hit-to-lead compounds for malaria and TB.

  1. Myler PJ, Stacy R, Stewart L, Staker BL, Van Voorhis WC, Varani G, Buchko GW. (2009) The Seattle Structural Genomics Center for Infectious Disease (SSGCID). Infect Disord Drug Targets, 9:493-506. PubMed: 19594426; PubMed Central: PMC2857597.
  2. Yamada S, Hatta M, Staker BL, et al. (2010) Biological and structural characterization of a host-adapting amino acid in influenza virus. PLoS Pathog, 6:e1001034. PubMed: 20700447; PubMed Central: PMC2916879
  3. Baugh L, Phan I, Begley DW, et al. (2015) Increasing the structural coverage of tuberculosis drug targets. Tuberculosis (Edinb), 95:142-8. PubMed: 25613812; PubMed Central: PMC4361283.
  4. Staker BL, Buchko GW, Myler PJ (2015) Recent contributions of structure-based drug design to the development of antibacterial compounds. Curr Opin Microbiol, 27:133-8. PubMed: 26458180 PMC4659754 (Available on 10/1/2016)


Synthetic Biology Open Language (SBOL)

Faculty Lead(s)

John Gennari

Keywords

Bioinformatics

Project Summary

In collaboration with Herbert Sauro (bioengineering), and building from the success of the SBOL development, we have begun a four year project extending the SBOL standard and building a user community of synthetic biology researchers and informaticians. The SBOL standard provides an interaction language for describing and sharing synthetic biology designs and components, and it’s goals include promoting reuse and modularity in design. The goals of this project are to strengthen and broaden the standard, develop validation services, and demonstrate successful storing of knowledge sharing and design interoperation. We also plan a series of workshops and outreach programs to grow the community and user base.


Systematic Evidence Review and Meta-Analysis of Asthma Self Management Interventions

Keywords

Asthma Education
Meta-Analysis
Systematic Reviews

Project Summary

This project will update a Cochrane Collaboration systematic evidence review and meta-analysis (SR/MA) of randomized and controlled clinical trials of asthma self-management education programs for children and adolescents, results of which were published in the British Medical Journal (BMJ). The effectiveness of these asthma self-management education programs are evaluated to estimate their effects on four types of health outcomes in children and adolescents: 1) Lung function (FEV1 and Peak Flow), 2) Asthma morbidity (asthma exacerbations, days of school absence, days of restricted activity, nights disturbed by asthma, asthma severity), 3) Health care utilization (physician and emergency department visits, hospitalizations), and 4) Self-reported perceptions of self-care abilities (self-efficacy). This updated SR/MA will allow us to incorporate newer evidence to perform more valid and reliable subgroup analyses that are potentially important in designing new programs, such as effectiveness related to 1) Degree of asthma severity, 2) Time of enrollment in the intervention, 3) Type of self-management strategy, 4) Intervention type (individual vs. group), 5) Intensity of intervention  (single vs. multiple sessions), and 6) Study quality.

Collaborators: Cyril Grum, MD, University of Michigan; James Guevara, MD, University of Pennsylvania

Project can provide opportunities for interested graduate students and post-docs.


Systems Biology of Leishmania Differentiation

Faculty Lead(s)

Peter Myler

Keywords

Bioinformatics
Genomics
Parasite Molecular Biology

Project Summary

In 2003, I began collaborating with Dan Zilberstein at the Technion – Israel Institute of Technology to utilize the rapidly emerging tools available for genome-wide elucidation of changes in gene expression occurring during Leishmania promastigote-to-amastigote differentiation, using an axenic system that his group had established. The collaboration has proven remarkably fruitful, as we used a USI-BSF grant to support microarray and LC-MS/MS analysis and show that there is a well-coordinated program involved changes in mRNA and protein abundance of several hundred genes during this differentiation process – challenging the dogma at the time, which held that trypanosomatid gene expression was generally constitutive. This work as continued with the introduction of new technologies, such as RNA-seq, ribosome profiling (in collaboration with Marilyn Parsons at CID Research) and phosphoproteomic analyses, to generate the extensive datasets needed for a true systems approach to understanding the molecular processes involved in Leishmania differentiation. I have also collaborated with other Leishmania researchers to extend these analyses to identify the regulatory networks underlying the response to other environmental stimuli, and we are now on the brink of being able to test some of these hypotheses experimentally.

  1. Saxena A, Lahav T, Holland N, Aggarwal G, Anupama A, Huang Y, Volpin H, Myler PJ, Zilberstein D. (2007) Analysis of the Leishmania donovani transcriptome reveals an ordered progression of transient and permanent changes in gene expression during differentiation. Mol Biochem Parasitol, 152:53-65. PubMed: 17204342; PubMed Central: PMC1904838.
  2. Lahav T, Sivam D, Volpin H, Ronen M, Tsigankov P, Green A, Holland N, Kuzyk M, Borchers C, Zilberstein D, Myler PJ. (2011) Multiple levels of gene regulation mediate differentiation of the intracellular pathogen Leishmania. FASEB J, 25:515-525. PubMed: 20952481
  3. Mittra B, Cortez M, Haydock A, Ramasamy G, Myler PJ, Andrews NW. (2013) Iron uptake controls the generation of Leishmania infective forms through regulation of ROS levels. J Exp Med. 210:401-16. PubMed PMID: 23382545; PubMed Central PMCID: PMC3570109.
  4. Martin JL, Yates PA, Soysa R, Alfaro JF, Yang F, Burnum-Johnson KE, Petyuk VA, Weitz KK, Camp DG 2nd, Smith RD, Wilmarth PA, David LL, Ramasamy G, Myler PJ, Carter NS. (2014) Metabolic reprogramming during purine stress in the protozoan pathogen Leishmania donovani. PLoS Pathog, 10:e1003938. PubMed PMID: 24586154; PubMed Central PMCID: PMC3937319.


The Ontology of Craniofacial Development and Malformation (OCDM)

Faculty Lead(s)

James Brinkley

Faculty

Linda Shapiro

Project Summary

The Ontology of Craniofacial Development and Malformation (OCDM) is a mechanism for representing knowledge about craniofacial development and malformation, and for using that knowledge to facilitate integrating craniofacial data obtained via multiple techniques from multiple labs and at multiple levels of granularity. The OCDM is a project of the NIDCR-sponsored FaceBase Consortium, whose goal is to promote and enable research into the genetic and epigenetic causes of specific craniofacial abnormalities through the provision of publicly accessible, integrated craniofacial data. However, the OCDM should be usable for integrating any web-accessible craniofacial data, not just those data available through FaceBase. The OCDM is based on the Foundational Model of Anatomy (FMA), our comprehensive ontology of canonical human adult anatomy, and includes modules to represent adult and developmental craniofacial anatomy in human, mouse and zebrafish, mappings between homologous structures in the different species, and associated malformations. We suggest that the OCDM can be useful not only for integrating craniofacial data, but also for expressing new knowledge gained from analyzing the integrated data. Project link: http://www.si.washington.edu/projects/ocdm


Trypanosomatid Genomics and Bioinformatics

Faculty Lead(s)

Peter Myler

Keywords

Bioinformatics
Genomics

Project Summary

Beginning in the late 1980s, I started leading the efforts in Ken Stuart’s laboratory Seattle Biomedical Research Institute to sequence trypanosomatid mitochondrial (maxicircle and minicircle) and viral (LRV1) genomes, as well small circular and linear amplified DNA elements of Leishmania. This culminated in my taking a leading role in the worldwide consortium (Seattle Biomed, Wellcome Trust Sanger Institute, The Institute for Genome Research and Uppsala University/Karolinska Institute) to sequence the TriTryp genomes (Leishmania major, Trypanosoma brucei and Trypanosoma cruzi), which were (largely) completed and published in 2005. Since that time my group has maintained an active involvement in the sequence, annotation and curation of more trypanosomatid genomes, and I was co-PI on the original BMGF grant to establish and maintain TriTrypDB (the definitive database for trypanosomatid genomics data). During this time, my team has developed a number of software pipelines for genome annotation and analysis, and continues to be one of the leaders in this effort for these specialized genomes. More recently, this has extended to data generation and analysis using several new sequencing platforms (Illumina, PacBio, MinIon).

  1. El-Sayed NM, Myler PJ, et al. (2005) Comparative genomics of trypanosomatid parasitic protozoa. Science, 309:404-409. PubMed: 16020724.
  2. El-Sayed NM, Myler PJ, et al. (2005) The genome sequence of Trypanosoma cruzi, etiologic agent of Chagas disease. Science. 309:409-415. PubMed: 16020725.
  3. Ivens AC, Peacock CS, et al. (2005) The genome of the kinetoplastid parasite, Leishmania major. Science, 309:436-442. PubMed: 16020728; PubMed Central: PMC1470643.
  4. Myler PJ. (2008) Searching the Tritryp genomes for drug targets. Adv Exp Med Biol, 625:133-140. PubMed: 18365664.


University of Washington, Seattle Children’s Hospital, Pediatric Pulmonary Center

Faculty Lead(s)

Gregory Redding

Faculty

Janice A. Sabin

Keywords

Family Centered Care
Health Equity Curriculum
Interprofessional Education
Leadership Training
Pediatric Pulmonary

Project Summary

Grant: T72 MC 00007-15, 2009 – 2019, Maternal and Child Health Bureau

The Pediatric Pulmonary Center (PPC) Leadership Training Grant funds multidisciplinary training in postgraduate work for physicians, nurses, social workers and nutritionists. Our goal as faculty on the grant is to train leaders in family centered, community based, culturally competent and interdisciplinary care. The training focuses on a balance of inpatient hospital practice and the opportunity to develop leadership roles in advocacy, policy, research, and public health contexts for this work.  Leadership training consists of required interdisciplinary clinical and advocacy activities that culminate in a trainee capstone project.


Visualizing Smart Home Sensor Data to Support Aging in Place

Faculty Lead(s)

George Demiris

BIME Student(s)

Yong Choi
Abhishek Pratap

Keywords

Aging in Place
Behavioral Sensing
Consumer Informatics
Smart Homes

Project Summary

The aim of this project is to collect behavioral sensing data from community dwelling older adults and develop inference mechanisms to extract information that can be visualized and inform shared decision making.