News and Events

Chair’s Message

pth-use-this-oneWe are moving toward our vision with a number of activities. We completed the Clinical Informatics Fellowship match and filled our two open positions with two excellent candidates who started July 2018. We completed the interview process for our research focused MS and research focused PhD programs, and have a new cohort who will start in Fall 2018.  Applications are open for our applied on-line MS in Clinical Informatics and Patient Centered Technologies. We are beginning a new overall strategic planning process for all of our Departmental activities in conjunction with preparing for our every 10 year academic program review. We are still actively recruiting new faculty as part of our strategic plan to expand our core faculty by 50%, with 3-4 positions remaining to be filled over the next two years (see link).

Cordially,

Peter Tarczy-Hornoch, MD
Chair and Professor, Department of Biomedical Informatics and Medical Education

Biomedical Informatics and Medical Education Newsletter

March 18-March 22, 2019

UPCOMING MASTER’S DEFENSES

Greg Aeschliman

Friday March 22, 11:00 am, UW SLU C122

Title: A Wireframe Representation of a Prototype Clinical Decision Support Tool For the Management of Cardiometabolic Disorder and Diabetes Type 2

Abstract: Diabetes Mellitus Type 2 is a complex disorder with complex management pathways. This research developed a wireframe representation of a prototype Clinical Decision Support Tool that enables the comprehensive, efficient and efficacious management of patients with Cardiometabolic Disorder and Diabetes Mellitus Type 2.

(The Tool’s development employed user-centered, iterative design principles to create both the user interface and the backend decision support logic.  The design process took place in the context of a cross-functional team of physicians, pharmacists, diabetic nurse educators, care managers and administrators.)

This research developed a wireframe representation of a prototype Clinical Decision Support Tool that

enables the comprehensive, efficient and efficacious management of patients with Cardiometabolic

Disorder and Diabetes Mellitus Type 2.  This research took place in the Eastside Health Network, an

Accountable Care Organization and employed user-centered, iterative design principles to create both

the user interface and the backend decision support logic.  The design process took place in the context

of a cross-functional team of physicians, pharmacists, diabetic nurse educators, care managers and

administrators.

OTHER NEWS

The University of Washington’s graduate and professional degree programs were widely recognized as among the best in the nation, according to U.S. News & World Report’s 2020 Best Graduate School rankings released today.

http://www.washington.edu/news/?utm_source=whitebar&utm_medium=click&utm_campaign=news&utm_term=uwnews

March 11-March 15, 2019

UPCOMING LECTURES AND SEMINARS

BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, March 14, 11:00am-11:50am, UW Medicine South Lake Union, Building C, Room C123AB

(livestream at tcs.slu.washington.edu)

 Speaker: Don Smith, MS

4th Year Biomedical and Health Informatics PhD Student

Title: Uncovering exposures responsible for birth season – disease effects: a global study

Abstract: Birth month and climate have an impact lifetime disease risk. The underlying exposures remain largely elusive and difficult to identify. Uncovering distal risk factors underlying these relationships can be accomplished by probing the relationship between global exposure variance and disease risk variance by birth season. This study utilized electronic health record data from 6 sites representing 10.5 million individuals in 3 countries (United States, South Korea, and Taiwan). We obtained birth month-disease risk curves from each site in a case-control manner and correlated them with each exposure. A meta-analysis was then performed of correlations across sites. This allowed us to identify the most significant birth month-exposure relationships supported by all 6 sites while adjusting for multiplicity.

Our methods identified several culprit exposures that correspond well with the literature in the field. These include a link between first-trimester exposure to carbon monoxide and increased risk of depressive disorder, first-trimester exposure to fine air particulates and increased risk of atrial fibrillation, and decreased exposure to sunlight during the third trimester and increased risk of type 2 diabetes mellitus.

Speaker Bio: Don Smith is a fourth-year Ph.D. student in Biomedical and Health Informatics at the University of Washington. He studied Biology as an undergrad and Health Informatics and Information Management for his Master’s program. Prior to starting the Ph.D. program, Don worked for many years in the federal government, healthcare organizations, and high tech industries in a variety of technical roles. Prior to that, he worked on the clinical side of healthcare as an Emergency Medical Technician and ER Technician. Experiencing both the technical and clinical side of healthcare inspires him to bridge the gap between the two in order to implement systems level quality and process improvements.

Currently, Don works with the Mooney Group headed by Sean Mooney, and is involved in using EHR data to support predictive analytics, clinical decision support tools, and the learning healthcare system. At UW Medicine’s Office of Medical Staff Appointments, Don serves as the IT Systems Operations Manager. In this role, he guides 19 academic departments, 22 divisions, and 4 medical centers in their use of the medical credentialing and privileging systems.

BIME 591B–Developing Your Informatics Career Path

Tuesday, March 12: 12:30pm- 1:20pm, Health Sciences Building, E216

Facilitator: David Masuda 

Faculty Candidate Talk:

Please join us for a faculty candidate talk on Monday, March 11 at 11am!

BIME Faculty Candidate – Ron Li, MD

Monday, March 11, 11:00 a.m., South Lake Union, Orin Smith Auditorium (from off-site connect through Zoom: https://washington.zoom.us/j/222337570)

Speaker: Ron Li, MD

Clinical Informatics Fellow, Stanford Medicine, Palo Alto, CA

Title:  Mining the electronic health record to build a continuously learning ecosystem for clinical decision support

Abstract:  Clinical decision support (CDS), which refers to computerized tools that intelligently deliver information to support workflow and decision making, is a core piece of health information technology (IT) on which health systems rely to improve efficiency, reduce errors, and decrease unwanted care variability.  Nevertheless, CDS is often developed and implemented in a reactive, “top down” manner.  Decisions around CDS deployments tend to be driven by ad hoc requests from institutional leadership with limited ability to systemically determine which points in workflow to target to derive the most value.  Similarly, the determination of deployment success and future CDS iterations often rely on opinions and assumptions with limited insights into the end user experience and real world effects on patient care.  This talk will discuss our recent work on mining the EHR to discover insights into how clinicians are using CDS in the real world setting.  These insights are then leveraged to iterate future designs and implementation strategies as part of a continuously learning ecosystem to further the development of clinician and patient-centered health IT.

UPCOMING DISSERTATION DEFENSE

Abdul Alshammari

Wednesday, March 13, 2019, 10:00am-12:00pm, UW South Lake Union, Room C123A

Title: Developing and Evaluating a Prototype Communicable Disease Web-based Clinical Reporting Tool

Abstract: Reporting reportable diseases within a time-frame is considered a cornerstone of any public health surveillance system. The purpose of surveillance is to empower decision makers to act by providing timely and accurate data. Conducting surveillance requires a cycle of collecting and reporting individual cases by solo healthcare providers or healthcare facilities to the local/public health department. Healthcare providers are familiar with the requirements to report reportable diseases, but compliance is a challenge.

Novel influenza has been a reportable disease since the 2007 legislation. Pandemic influenza is caused by novel influenza that is introduced into a population where some of this population has low immunity to the novel influenza, which increases the mortality rate. In the past 120 years, there have been six well-known international novel influenza spread. The deadliest novel influenza epidemic happened in 1918. That year the Spanish Influenza (H1N1) infected about 500 million people and caused the death of an estimated 20 – 50 million. Other novel infections similarly need to be reported and track. Two examples in the last five years are Middle East Respiratory virus and Zika virus.

I developed a Web-based reporting tool prototype to help healthcare providers in reporting communicable diseases that are required to be tracked such as novel influenza cases to authorities based on the state’s official case report form. The overarching goal was to develop and evaluate this prototype. My aims were: 1) Understanding the problems within the reportable diseases reporting process from healthcare providers to healthcare authorities , 2) Develop and test a prototype Web-based reporting tool to help improving the reporting process,  and 3) Evaluate the prototype Web-based reporting tool .

The result of Aim 1 was identifying gaps between states’ reporting guidelines and states’ case report forms at individual state level and across states. The identified gaps helped to generate a collection of all the data fields used in novel influenza states’ reporting guidelines and states’ case report forms. The identified data fields were ranked based on the most used data fields across all the participated states. The ranked data fields across all the participated states helps healthcare providers and policymakers to get insight into other data fields required by other states to develop future guidelines and case report forms.

The result of Aim 2 was a tool that maps the required data from a database simulating EHRs with a different granularity of data to one or more state’s official case report forms. The tool does this through query mapping and pre-population of as much data into a given state’s case report form as the granularity of a given EHR data permit. This feature helps in reducing the manual data entry and increase the accuracy and completeness of submitted data to authorities. The tool converts the submitted case report form into Clinical Document Architecture (CDA) format, which is a recommended standard by HL7.

For Aim 3, a combination of usability evaluation methods is implemented to evaluate the Web-based reporting tool from Aim 2. The main objectives of the implemented usability evaluation methods are to measure the usability of the tool. The usability refers to the quality of a user’s experience when interacting with the tool and to measure the user’s overall satisfaction.  The Key finding from Aim 3 was that the Web-based reporting tool is an acceptable tool by potential users. The evaluation study generated qualitative and quantitative results. Also, the results generated a list of usability problems for future development and considerations.

UPCOMING GENERAL EXAM

Timothy Bergquist

Friday, March 8, 2019, 2:00-4:00pm, UW South Lake Union, Room E130.

Title: Quality, Trauma, and Competition: Tools for the Learning Healthcare System

Abstract: The process of implementing novel research findings into clinical practice is a key issue facing translational research. The estimated turn around for applying conclusive research results to clinical practice is approximately 17 years. In response to this implementation lag, a theoretical framework has been proposed called the Learning Healthcare System. This framework proposes to treat all healthcare centers as nodes in a network, where these nodes can share clinical data, analyze this accumulated data, and share the results from those studies for implementation into medical practice. This process takes a cyclical approach where implemented methods create new data, that data is assembled and analyzed, the lessons from analysis inform new medical practices, and more data is collected on those new practices. Even if hospitals wish to implement this framework, there is a lack of widely available tools to manage and analyze clinical data, to evaluate the proposed solutions from these studies, and to the return clinically relevant research findings to patients and doctors. Some of these tools have already been developed in one form or another at other institutions, but they aren’t publicly available. Development of new tools and methods is needed to address many of the common data management and research knowledge deployment needs of healthcare institutions. The objective of this proposal is to produce publicly available tools and methods to facilitate integration into the Learning Healthcare System. The aims will be focused on four areas in the Learning Healthcare System: 1. Electronic Health Record data quality and research readiness assessment; 2. Population health analysis with EHR data; 3. Prospective evaluation of predictive analytics; and 4. Return of clinically actionable research results.

PUBLICATIONS AND PRESENTATIONS

Delgado, N. L., Usuyama, N., Hall, A. K., Hazen, R. J., Ma, M., Sahu, S., & Lundin, J. (2019). Fast and accurate medication identification. npj Digital Medicine, 2(1), 10.

Liu X, Sutton PR, McKenna R, Sinanan MN, Fellner BJ, Leu MG, Ewell C. Evaluation of Secure Messaging Applications for a Health Care System: A Case Study. Appl Clin Inform. 2019 Jan;10(1):140-150. doi: 10.1055/s-0039-1678607. Epub 2019 Feb 27.

FACULTY/STUDENT/ALUMNI/STAFF ACTIVITIES

Vikas Rao Pejaver, Moore-Sloan & WRF Innovation in Data Science fellow, Department of Biomedical Informatics and Medical Education and the eScience Institute has received a Pathway to Independence Award (K99/R00) from the National Library of Medicine at the National Institutes of Health for his proposal titled “Integrative data science approaches for rare disease discovery in health records”.

Congratulations to Savitha Sangameswaran and family on the birth of their son, Dhruv on January 13, 2019. Both Mom and baby are doing great!

OTHER EVENTS

BIME is hosting our Prospective Student Visit Days on March 18-19, 2019. We will welcome 22 prospective PhD students during the two-day event.

UNDERGRADUATE INTERNSHIP OPPORTUNITIES

Preparing Patients with Cancer for Goals-of-Care Discussions in the Hospital

The purpose of this project is to develop a digital educational intervention to prepare patients with cancer for a discussion with a clinician about their goals of care.  This is a difficult, emotional, and yet critical discussion.  We are looking for a user experience (UX) research assistant who is interested in developing the digital interface for this intervention with us.  The intervention will be built on a WordPress platform, and you will work with the faculty mentor to select and customize a suitable WordPress theme for this project.  In addition, you will interview patients to obtain feedback on prototypes that we develop along the way.  If you are interested in working on this meaningful project, enjoy and/or would like to work with patients in healthcare settings, and are interested in user-centered design, we would like to hear from you. This is a 10 week paid internship for spring quarter.

To apply: Please send an email describing your interest in the project, along with your resume, to Dr. Annie Chen: atchen@uw.edu

Field testing a digital fitness program for older adults

This paid 10-week internship involves assisting the research team with study administration and data collection for a 6 week field test of a digital fitness program designed to increase walking in older adults.  This is a great opportunity for an undergraduate student interested in health informatics and user research. The digital fitness program is comprised of using Fitbit, a Facebook private group, and having a walking buddy.  The program will be used by up to 20 participants and tested for acceptability, engagement, and preliminary efficacy to improve walking. Internship tasks range from sending materials to study participants, monitoring the Facebook group for user activity, assisting with data collection from surveys, interviews, and Fitbit data pull, and assisting with technical support for participant. There is an opportunity to work with the Facebook APIs using python or Java to extract social media data. The intern will meet regularly with the research team (Thursday mornings 9am-10am) and report to the team lead. The intern must complete the web-based human subjects training through CITI to participate.

To apply: Please email Dr. Andrea Hartzler andreah@uw.edu the following by Friday 3/8/19:  (1) a brief description of why you are interested in this particular opportunity and how you would contribute to the team, (2) your resume, and (3) confirm your availability to meet each TH 9-10am spring quarter for a team meeting at UW Medicine South Lake Union. There is a shuttle to and from campus.

March 4-March 8, 2019

UPCOMING LECTURES AND SEMINARS

BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, March 7, 11:00am-11:50am, UW Medicine South Lake Union, Building C, Room C123AB

(livestream at tcs.slu.washington.edu)

Speakers: Annie T. Chen, MSIS, PhD

Assistant Professor, Department of Biomedical Informatics and Medical Education, University of Washington

Ginger J. Tsai, MS

ABGC Certified Genetic Counselor, Department of Laboratory Medicine, University of Washington

Title: Different Strokes for Different Folks – Eliciting User Feedback and Analyzing Data in Two Genetics-Related Contexts

Abstract: This talk will present two studies involving the analysis of data collected from target and potential user groups, with a focus on eliciting user feedback and analyzing data from these groups. The first study involved a two-part evaluation of AnalyzeMyVariant, an online scientific tool that enabling geneticists to use family pedigree data to calculate pathogenicity likelihood ratios for variants of unknown significance (VUS).  First, we developed and employed a survey instrument focusing on constructs of importance to online scientific tools, to collect data about the use experience of AnalyzeMyVariant from 57 genetic experts and trainees. Second, we conducted semi-structured interviews with six genetics experts to explore work contexts in which users might use the tool and further delve into issues faced in tool use. We found that the needs of genetics professionals, namely, statistical geneticists and genetic counselors, vary considerably, owing to differences in their research and clinical contexts and perspectives.

The second study is based on data collected from relatives participating in patient-driven family studies for reclassification of VUS.  We conducted semi-structured interviews with 55 individuals from 21 different families with clinically identified VUS.  Interviewees were recruited from a set of  individuals who had initially received information about a familial VUS from a proband-relative.  Interviewees had been asked by the proband to participate in a patient-driven VUS reclassification study (FindMyVariant) and had been contacted by study staff for an interview about their study experience. The study examined three main research themes: motivators and deterrents of participation, impacts of participation, and research ethics.

Other than presenting the results of each study, we highlight the main methodological takeaways for each, in terms of eliciting the needs of different user groups in their respective contexts.   These studies are related to the work of Dr. Brian Shirts in the Department of Laboratory Medicine, which focuses on understanding rare genetic variants and communicating the meaning of medically important genetics results with health care providers, patients, and patients’ families.

Speaker Bios: Annie T. Chen is an assistant professor in the Department of Biomedical Informatics and Medical Education.  She maintains an active research program with two methodological areas of emphasis: text and visual analytics and user-centered design.  In addition, she is actively engaged in research concerning the information behavior of individuals with pain-related conditions and health-related interactions in online environments.  Dr. Chen holds a B.A. in Psychology from Harvard University, and M.S.I.S. and Ph.D. degrees in Information Science from the University of North Carolina at Chapel Hill.

Ginger J. Tsai is an ABGC Certified Genetic Counselor licensed in the state of Washington. Her research at the Department of Laboratory Medicine at the University of Washington focuses on genetic variant classification and interpretation. She has an M.S. in Genetic Counseling from the University of Texas Health Science Center at Houston and B.S. in Biomedical Engineering from the Georgia Institute of Technology.

BIME 591B–Developing Your Informatics Career Path

Tuesday, March 5: 12:30pm- 1:20pm, Health Sciences Building, E216

Facilitator: David Masuda 

Faculty Candidate Talk:

Please join us for a faculty candidate talk on Monday, March 11 at 11am!

BIME Faculty Candidate – Ron Li, MD

Monday, March 11, 11:00 a.m., South Lake Union, Orin Smith Auditorium (from off-site connect through Zoom: https://washington.zoom.us/j/222337570)

Speaker: Ron Li, MD

Clinical Informatics Fellow, Stanford Medicine, Palo Alto, CA

Title:  Mining the electronic health record to build a continuously learning ecosystem for clinical decision support

Abstract:  Clinical decision support (CDS), which refers to computerized tools that intelligently deliver information to support workflow and decision making, is a core piece of health information technology (IT) on which health systems rely to improve efficiency, reduce errors, and decrease unwanted care variability.  Nevertheless, CDS is often developed and implemented in a reactive, “top down” manner.  Decisions around CDS deployments tend to be driven by ad hoc requests from institutional leadership with limited ability to systemically determine which points in workflow to target to derive the most value.  Similarly, the determination of deployment success and future CDS iterations often rely on opinions and assumptions with limited insights into the end user experience and real world effects on patient care.  This talk will discuss our recent work on mining the EHR to discover insights into how clinicians are using CDS in the real world setting.  These insights are then leveraged to iterate future designs and implementation strategies as part of a continuously learning ecosystem to further the development of clinician and patient-centered health IT.

UPCOMING DISSERTATION DEFENSE

Abdul Alshammari

Wednesday, March 13, 2019, 10:00am-12:00pm, UW South Lake Union, Room C123A

Title: Developing and Evaluating a Prototype Web-based Reporting Tool

Abstract: TBD

UPCOMING GENERAL EXAM

Timothy Bergquist

Friday, March 8, 2019, 2:00-4:00pm, UW South Lake Union, Room E130.

Title: Quality, Trauma, and Competition: Tools for the Learning Healthcare System

Abstract: The process of implementing novel research findings into clinical practice is a key issue facing translational research. The estimated turn around for applying conclusive research results to clinical practice is approximately 17 years. In response to this implementation lag, a theoretical framework has been proposed called the Learning Healthcare System. This framework proposes to treat all healthcare centers as nodes in a network, where these nodes can share clinical data, analyze this accumulated data, and share the results from those studies for implementation into medical practice. This process takes a cyclical approach where implemented methods create new data, that data is assembled and analyzed, the lessons from analysis inform new medical practices, and more data is collected on those new practices. Even if hospitals wish to implement this framework, there is a lack of widely available tools to manage and analyze clinical data, to evaluate the proposed solutions from these studies, and to the return clinically relevant research findings to patients and doctors. Some of these tools have already been developed in one form or another at other institutions, but they aren’t publicly available. Development of new tools and methods is needed to address many of the common data management and research knowledge deployment needs of healthcare institutions. The objective of this proposal is to produce publicly available tools and methods to facilitate integration into the Learning Healthcare System. The aims will be focused on four areas in the Learning Healthcare System: 1. Electronic Health Record data quality and research readiness assessment; 2. Population health analysis with EHR data; 3. Prospective evaluation of predictive analytics; and 4. Return of clinically actionable research results.

PUBLICATIONS AND PRESENTATIONS

Mueller BU, Neuspiel DR, Stucky Fisher ERS, COQIPS, COHC.  Principles of Pediatric Patient Safety:  Reducing Harm Due to Medical Care.  Pediatrics. 2019: e20183649.  Doi: 10.1542/peds.2018-3649.  PMID: 30670581.

Liu X, Sutton PR, McKenna R, Sinanan MN, Fellner BJ, Leu MG, Ewell C.  Evaluation of Secure Messaging Applications for a Health Care System: A Case Study. Appl Clin Inform 2019; 10(01): 140-150.  DOI: 10.1055/s-0039-1678607.

Chen AT, Swaminathan A, Kearns WR, Alberts NM, Law EF, Palermo TM. (accepted). Understanding user experience: Exploring participants’ messages with an online behavioral health intervention for adolescents with chronic pain. Journal of Medical Internet Research.

Chen AT, Swaminathan A. (accepted). Factors in the building of effective patient-provider relationships in the context of fibromyalgia. Pain Medicine.

Phuong J, Bandaragoda C, Istanbulluoglu E, Beveridge C, Strauch R, Setiawan L, Mooney SD. Automated retrieval, preprocessing, and visualization of gridded hydrometeorology data products for spatial-temporal exploratory analysis and intercomparison. Environmental Modelling & Software. 2019 Feb 20. doi:10.1016/j.envsoft.2019.01.007

FACULTY/STUDENT/ALUMNI/STAFF ACTIVITIES

Professor Jan Carline retired from BIME as of January 9, 2019. He will continue to be active in the department as emeritus faculty. In honor of Dr. Carline’s contributions to our department, the School of Medicine, and the University of Washington, a new award fund has been established: Jan D. Carline Award of Excellence in Scholarship of Education. This is an annual award for medical student independent inquiry (Triple I) projects determined to be the most meritorious in the area of education, including medical education or community education.  You can support the fund from the BIME “Make a Gift” page at http://bime.uw.edu/giving/.

Congratulations to Ahmad Aljadaan and his family on the birth of their baby daughter, Sarah on January 30, 2019. Sarah joins twin siblings, Khalid and Abdullah. Mother Maram and baby Sarah are doing great!

February 25-March 1, 2019

UPCOMING LECTURES AND SEMINARS

BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, February 28, 11:00am-11:50am, UW Medicine South Lake Union, Building C, Room C123AB

(livestream at tcs.slu.washington.edu)

Speaker: Tellen D. Bennett, MD, MS

Associate Professor, Pediatric Critical Care

University of Colorado School of Medicine | Children’s Hospital Colorado

Associate Professor, Biostatistics and Informatics, Colorado School of Public Health (Secondary)

Co-Director, Analytics Core, CU Data Science to Patient Value (D2V, cud2v.org)

Associate Director, Informatics Core, Colorado Clinical and Translational Sciences Institute (CCTSI)

Title: High-risk decisions in critically ill patients: unique challenges for informatics, data science, and clinical decision support

Abstract: Decisions about urgent interventions in critically ill patients must balance morbidity and mortality risk with potentially life-sustaining benefits. In order to make these decisions, clinicians rapidly integrate multiple data streams and recognize evolving patterns based on training and experience. Modern computational systems are well-suited to assist with these tasks, but personalized time-critical clinical decision support development has been limited by gaps in interoperability, model accuracy, efficiency, and interpretability, and end-user engagement. This presentation will review each of these gaps, discuss recent examples of academic and industry tools, and initiate a discussion of how multidisciplinary teams can collaborate to build tools that improve patient outcomes.

Speaker Bio: Tellen D. Bennett, MD, MS is Associate Professor of Pediatrics (primary) and Biomedical Informatics and Personalized Medicine (secondary) at the University of Colorado School of Medicine and Biostatistics and Informatics (secondary) at the Colorado School of Public Health. He is a pediatric intensivist, informaticist, and data scientist. He is board-certified in Pediatrics, Pediatric Critical Care, and Clinical Informatics and serves as an attending physician in the Pediatric Intensive Care Unit at Children’s Hospital Colorado. Dr. Bennett is the Co-Director of the Analytics Core of the Data Science to Patient Value program (D2V) at the University of Colorado and the Associate Director of the Informatics Core of the Colorado Clinical and Translational Science Institute. His research is focused on computational tools to support critical care decision-making and is supported by the NIH and the State of Colorado. Dr. Bennett received a MD from the Johns Hopkins University School of Medicine, completed a Pediatrics residency and Pediatric Critical Care fellowship at the University of Washington/Seattle Children’s Hospital, and received a MS in Epidemiology from the University of Washington School of Public Health. He completed post-doctoral training in Biomedical Data Science at the University of Colorado.

BIME 591B–Developing Your Informatics Career Path

Tuesday, February 26: 12:30pm- 1:20pm, Health Sciences Building, E216

Facilitator: David Masuda 

UPCOMING DISSERTATION DEFENSE

Lucy Lu Wang

Tuesday, February 26, 2019, 1:00 PM, UW Health Sciences T635

Title: Ontology-driven pathway data integration

Abstract: Biological pathways are useful tools for understanding human physiology and disease pathogenesis. Pathway analysis can be used to detect genes and functions associated with complex disease phenotypes. When performing pathway analysis, researchers take advantage of multiple pathway datasets, combining pathways from different pathway databases. Pathways from different databases do not easily inter-operate, and the resulting combined pathway dataset can suffer from redundancy or reduced interpretability.

The Pathway Ontology (PW) is an ontology of pathway terms that can be used to organize pathway data and eliminate redundancy. I generated clusters of semantically similar pathways by mapping pathways from seven databases to classes in the PW. I then produced a typology of differences between pathways by summarizing the differences in content and knowledge representation between databases. Using the typology, I optimized an entity and graph-based network alignment algorithm for aligning pathways between databases. The algorithm was applied to clusters of semantically similar pathways to generate normalized pathways for each PW class. These normalized pathways were used to produce normalized gene sets for gene set enrichment analysis (GSEA). I evaluated these normalized gene sets against baseline gene sets in GSEA using four public gene expression datasets.

Results suggest that normalized pathways can help to reduce redundancy in enrichment outputs. The normalized pathways also retain the hierarchical structure of the PW, which can be used to visualize enrichment results and provide hints for interpretation. Ontology-based organization of biological pathways can play a vital role in improving data quality and interoperability, and the resulting normalized pathways may have broad applications in genomic analysis

UPCOMING GENERAL EXAM

Timothy Bergquist

Friday, March 8, 2019, 2:00-4:00pm, UW South Lake Union, Room E130.

Title: Quality, Trauma, and Competition: Tools for the Learning Healthcare System

Abstract: The process of implementing novel research findings into clinical practice is a key issue facing translational research. The estimated turn around for applying conclusive research results to clinical practice is approximately 17 years. In response to this implementation lag, a theoretical framework has been proposed called the Learning Healthcare System. This framework proposes to treat all healthcare centers as nodes in a network, where these nodes can share clinical data, analyze this accumulated data, and share the results from those studies for implementation into medical practice. This process takes a cyclical approach where implemented methods create new data, that data is assembled and analyzed, the lessons from analysis inform new medical practices, and more data is collected on those new practices. Even if hospitals wish to implement this framework, there is a lack of widely available tools to manage and analyze clinical data, to evaluate the proposed solutions from these studies, and to the return clinically relevant research findings to patients and doctors. Some of these tools have already been developed in one form or another at other institutions, but they aren’t publicly available. Development of new tools and methods is needed to address many of the common data management and research knowledge deployment needs of healthcare institutions. The objective of this proposal is to produce publicly available tools and methods to facilitate integration into the Learning Healthcare System. The aims will be focused on four areas in the Learning Healthcare System: 1. Electronic Health Record data quality and research readiness assessment; 2. Population health analysis with EHR data; 3. Prospective evaluation of predictive analytics; and 4. Return of clinically actionable research results.

PUBLICATIONS AND PRESENTATIONS

Reza Sadeghian

The BUSINESS of Medicine Simplified

SMA’s 2019 Southern Regional Assembly

Birmingham, AL

June 27 – 29

Link to SMA website: https://sma.org/

Link to my page: https://sma.org/reza-sadeghian/

February 18-February 22, 2019

UPCOMING LECTURES AND SEMINARS

BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, February 21, 11:00am-11:50am, NO SEMINAR

BIME 591B–Developing Your Informatics Career Path

Tuesday, February 19: 12:30pm- 1:20pm, Health Sciences Building, E216

Facilitator: David Masuda 

UPCOMING DISSERTATION DEFENSE

Lucy Lu Wang

Tuesday, February 26, 2019, 1:00 PM, UW Health Sciences T635

Title: Ontology-driven pathway data integration

Abstract: Biological pathways are useful tools for understanding human physiology and disease pathogenesis. Pathway analysis can be used to detect genes and functions associated with complex disease phenotypes. When performing pathway analysis, researchers take advantage of multiple pathway datasets, combining pathways from different pathway databases. Pathways from different databases do not easily inter-operate, and the resulting combined pathway dataset can suffer from redundancy or reduced interpretability.

The Pathway Ontology (PW) is an ontology of pathway terms that can be used to organize pathway data and eliminate redundancy. I generated clusters of semantically similar pathways by mapping pathways from seven databases to classes in the PW. I then produced a typology of differences between pathways by summarizing the differences in content and knowledge representation between databases. Using the typology, I optimized an entity and graph-based network alignment algorithm for aligning pathways between databases. The algorithm was applied to clusters of semantically similar pathways to generate normalized pathways for each PW class. These normalized pathways were used to produce normalized gene sets for gene set enrichment analysis (GSEA). I evaluated these normalized gene sets against baseline gene sets in GSEA using four public gene expression datasets.

Results suggest that normalized pathways can help to reduce redundancy in enrichment outputs. The normalized pathways also retain the hierarchical structure of the PW, which can be used to visualize enrichment results and provide hints for interpretation. Ontology-based organization of biological pathways can play a vital role in improving data quality and interoperability, and the resulting normalized pathways may have broad applications in genomic analysis

PUBLICATIONS AND PRESENTATIONS

Wu, D. T. Y., Chen, A. T., Manning, J. D., Levy-Fix, G., Backonja, U., Borland, D., … Gotz, D. (accepted). Evaluating visual analytics for health informatics applications: a systematic review from the American Medical Informatics Association Visual Analytics Working Group Task Force on Evaluation. Journal of the American Medical Informatics Associationhttps://doi.org/10.1093/jamia/ocy190

Gotz, D., Wang, W., Chen, A. T., & Borland, D. (accepted). Visualization model validation via inline replication. Information Visualizationhttps://doi.org/10.1177/1473871618821747

Scott C, Vincenzi F, Smith D, Gorrin K, Trantham J. Mind-Body Skills Elective: A 7-year Follow-up of Health Professions Students. 006 J Complement Med Alt Healthcare. 2019; 9(1): 555750. http://dx.doi.org/10.19080/JCMAH.2019.09.555751

Presentation

Chen, A. T., Andrews, W., Gazula, Y., Liu, C., & Wang, J. (accepted). Re-designing the Svoboda diaries: A user-centered approach. Canadian Society for Digital Humanities / Société Canadienne des Humanités Numériques (CSDH / SCHN) Congress 2019. Vancouver, BC, Canada.

Poster

Zaslavsky, O., Chen, A., Teng, A., Lin, S.-Y., Han, S., Demiris, G. (accepted). Virtual Online Communities for Aging Life Experience (VOCALE). The International Conference on Frailty & Sarcopenia Research (ICFSR 2019). February 20-22, 2019. Miami Beach, USA.

OTHER EVENTS

BIME Happy Hour
Thursday, February 21, 5:00 p.m., South Lake Union, Reception Lounge

Please join us for our monthly departmental BYOB Happy Hour, held every third Thursday of the month. As always, please bring your own beverage; snacks will be provided!

February 11-February 15, 2019

UPCOMING LECTURES AND SEMINARS

BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, February 14, 11:00am-11:50am, UW Medicine South Lake Union, Building C, Room C123A&B

(Also broadcast live and archived at tcs.slu.washington.edu; livestream will have a red dot in the top left hand corner)

Speaker: Stephan D. Fihn MD MPH FACP FAHA

Professor, Departments of Medicine and Health Services

Head, Division of General Internal Medicine

University of Washington

Title: The Difficulty of Integrating AI Applications into Clinical Care – a personal perspective

Abstract:

There is great enthusiasm for integrating AI applications into health care delivery but the literature on successful implementation is very limited.  I will review my own experience conducting trials in this area which highlight some of the difficulties.  I will also review an approach to evaluating AI applications for clinical use and discuss future strategies.

Bio:

Dr. Fihn received his medical training at St. Louis University and completed an internship, residency and chief residency in the Department of Medicine at the University of Washington (UW).  He was a Robert Wood Johnson Clinical Scholar and earned a masters degree in public health at UW where he has been on the faculty since 1979 and presently holds the rank of Professor in the departments of Medicine and Health Services.  He has served as Head of the Division of General Internal Medicine at UW since 1995 (https://gim.uw.edu/)

During his 36-year career with the U.S. Department of Veterans Affairs, Dr. Fihn provided primary and hospital care to veterans and held a number of clinical, research and administrative positions. Early in his career, he directed one of the first primary care clinics in VA at the Seattle VA Medical Center.  From 1993 to 2011, he directed the Northwest VA Health Services Research & Development Center of Excellence at the Seattle VA.  His own research has addressed a broad range of topics related to strategies for improving the efficiency and quality of primary and specialty medical care and understanding the epi¬demiology of common medical problems.  He received the Department of Veteran Affairs Undersecretary’s Award for Outstanding Contributions in Health Services Research in 2002.  He has published more than 300 scientific articles and book chapters.

He also served several national roles within VA that enabled him to apply the principles and findings of health services research to health care delivery.  From 2004-5 he served as Acting Chief Research and Development Officer for the Veterans Health Administration (VHA) and as Chief Quality and Performance Officer from 2007-8.  From 2010 to 2016, he was Director of Analytics and Business Intelligence for VHA and was responsible for supporting high-level analytics and delivery of clinical, performance and business information throughout VHA.  From 2016-17, he was Director of Clinical System Development and Evaluation and was responsible for developing integrated workflow solutions for clinical care and conducting national evaluations of major clinical initiatives.

Dr. Fihn is still an active clinician He co-edited two editions of a textbook entitled Outpatient Medicine and is Deputy Editor of JAMA Network Open (https://sites.jamanetwork.com/jamanetworkopen/index.html).  He is active in several academic organizations including the Society of General Internal Medicine [SGIM] (past-president), the American College of Physicians (fellow), American Heart Association (fellow) and AcademyHealth.  In 2012 he received the Robert J. Glaser Award for outstanding contributions to research, education, or both in generalism in medicine from SGIM.

He is married and has three adult children and one grandchild.

BIME 591- Developing Your Informatics Career Path

Tuesday, February 12: 12:30pm- 1:20pm, Health Sciences Building, E216

Facilitator: David Masuda 

FACULTY/STUDENT/ALUMNI/STAFF ACTIVITIES

Lauren Snyder, PhD student, was awarded the 2019 Steve Lieber Innovator Scholarship from the HIMSS foundation. The Steve Lieber Innovator Scholarship is awarded to a student pursuing a degree from an accredited collegiate undergraduate, graduate, or doctoral academic program. Winning submissions embrace the use of digital health or technology-enabled workflow innovation in support of the HIMSS mission of better health through information and technology. She will accept the award at the HIMSS conference next week in Orlando, FL.

The announcement can be found here: https://www.himssconference.org/updates/celebrating-next-generation-healthcare-leaders

February 4-February 8, 2019

UPCOMING LECTURES AND SEMINARS

BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, February 7, 11:00am-11:50am, Webinar

https://uw-phi.zoom.us/j/2066515416, or dial 1-646-558-8656, 2066515416

Speaker: Patrick Cronin

Title: A Data Scientist Journey

Bio:

After completing a BA in mathematics from Truman State University, Patrick spent 5 years working as an actuary in New York City.  He then earned a MA from Columbia University in Biomedical Informatics, and then spent 6 years at Massachusetts General Hospital (MGH).  There he developed an implemented “Smart-Booking” which algorithmically identified opportunities for double-booking medical appointments and “Smart-Calling” which directed reminder calls at patients at high likelihood of no-showing.  Later worked in the Lab of Computer Science at MGH developing the population management software TopCare and implemented several real-time prediction models for no-shows, readmissions, and mortality.  Current he works for Decision Resources Group as an operations lead developing tools to extract insights from several types of medical data.  He currently resides in Arlington, Massachusetts with his wife Angel and his seven year old daughter Violet.

BIME 591B–Developing Your Informatics Career Path

Tuesday, February 5: Cancelled due to snow day. 

PUBLICATIONS AND PRESENTATIONS

Evaluating the Usefulness of Translation Technologies for Emergency Response Communication: A Scenario-Based Study.

Turner AM, Choi YK, Dew K, Tsai MT, Bosold AL, Wu S, Smith D, Meischke H.

JMIR Public Health Surveill. 2019 Jan 28;5(1):e11171. doi: 10.2196/11171.

FACULTY/STUDENT/ALUMNI/STAFF ACTIVITIES

Trevor Cohen and Meliha Yetisgen will be serving on the Journal of Biomedical Informatics Editorial Board until December 2022.

January 28-February 1, 2019

UPCOMING LECTURES AND SEMINARS

BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, January 31, 11:00am-11:50am, UW Medicine South Lake Union, Building C, Room C123A&B

 (Also broadcast live and archived at tcs.slu.washington.edu; livestream will have a red dot in the top left hand corner)

Speaker: E. Sally Lee, PhD, Manager, Population Health Analytics

UW Medicine Finance, University of Washington

Title: Sensemaking Clinical Data

Bio:

https://www.linkedin.com/in/sallylee/

BIME 591B– BIME 591B– Developing Your Informatics Career Path

Tuesday, January 29, 12:30pm- 1:20pm, Health Sciences Building, E216

Facilitator: David Masuda 

PUBLICATIONS AND PRESENTATIONS

Diane M. Korngiebel, Jennifer M. Zech, Amelia Chappelle, Wylie Burke, Jan D. Carline, Thomas H. Gallagher & Stephanie M. Fullerton (2019) Practice Implications of Expanded Genetic Testing in Oncology, Cancer Investigation, DOI: 10.1080/07357907.2018.1564926

Eric Rose, Integration of Postcoordination Content into a Clinical Interface Terminology to Support Administrative Coding

https://www.thieme-connect.com/products/ejournals/abstract/10.1055/s-0038-1676972

Jimmy PhuongAndrea HartzlerKari StephensSean Mooney, Christina Bandaragoda. Geospatial-temporal information needs and use-cases for population health researchers in hurricane and flood disaster preparedness scenario. American Geophysical Union Fall Meeting. GeoHealth poster session. Washington, D.C., December 10-14, 2018.

Jimmy Phuong, Christina Bandaragoda, Landung Setiawan, Claire Beveridge, Ronda Strauch, Sai Siddhartha Nudurupati, Sean Mooney, Erkan Istanbulluoglu. Observatory for Gridded Hydrometeorology (OGH): a python toolkit to automate access and analysis with gridded data products. American Geophysical Union Fall Meeting. Near Surface Geophysics poster session and lightning talk. Washington, D.C., December 10-14, 2018.

Christina Bandaragoda, Miguel Leon, W. Christopher Lenhardt, Jimmy Phuong, Jeffery Horsburgh, Amber Jones. Operational data provenance and cybersecurity for anticipatory disaster planning. American Geophysical Union Fall Meeting, Earth and Space Science Informatics poster session. Washington, D.C., December 10-14, 2018.

Sara Lucero, Christina Bandaragoda, Lea Shanley, W. Christopher Lenhardt, Veronica Smith, Michael R Burchell, Kelsey Pieper, Lisa Stillwell, Scott Dale Peckham, Lori Peek, Jared Bales, Erkan Istanbulluoglu, Jimmy Phuong, Elaine Faustman, Graciela Ramirez-Toro, Alicia Adcock, Tim Sauder. Building Digital Infrastructure and Communities to Assess Risk of Drinking Water Hazards Caused by Hurricanes Maria and Florence. American Geophysical Union Fall Meeting. Natural Hazards poster session. Washington, D.C., December 10-14, 2018.

FACULTY/STUDENT/ALUMNI/STAFF ACTIVITIES

Jimmy Phuong was awarded an AGU Outstanding Student Presentation Award (OSPA) for the poster presentation within the GeoHealth section at the 2018 American Geophysical Union Fall meeting in Washington, D.C. for his research:

Jimmy PhuongAndrea HartzlerKari StephensSean Mooney, Christina Bandaragoda. Geospatial-temporal information needs and use-cases for population health researchers in hurricane and flood disaster preparedness scenario. American Geophysical Union Fall Meeting. GeoHealth poster session. Washington, D.C., December 10-14, 2018.

INTERNSHIP OPPORTUNITY

2019 Summer Internship in Assessment Science and Psychometrics

https://www.nbme.org/research/internship.html?fbclid=IwAR03YV3WYfKb17hrXNQZphV7ew5_qZvaiPgaKMmBM7L6yXPgm7Ld6GLKiy4

January 14-18, 2019

UPCOMING LECTURES AND SEMINARS

 BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, January 17, 11:00am-11:50am, UW Medicine South Lake Union, Building C, Room C123A&B

(Also broadcast live and archived at tcs.slu.washington.edu; livestream will have a red dot in the top left hand corner)

Speaker: Gang Luo, PhD, Associate Professor, University of Washington

Title:  Predicting Appropriate Hospital Admission of Emergency Department Patients with Bronchiolitis

Abstract: In children below age two, bronchiolitis is the most common reason for hospitalization. Each year in the United States, bronchiolitis causes 287,000 emergency department visits, 32%-40% of which result in hospitalization. Frequently, emergency department disposition decisions (to discharge or to hospitalize) are made subjectively because of a lack of evidence and objective criteria for bronchiolitis management, leading to significant practice variation, wasted healthcare use, and suboptimal outcomes. At present, no operational definition of appropriate hospital admission for emergency department patients with bronchiolitis exists, although such a definition is essential for assessing care quality. Also, no model for predicting appropriate hospital admission exists, although an accurate model predicting this can guide emergency department disposition decisions for bronchiolitis and improve outcomes.

In this talk, we present our recent work filling these two gaps. First, we provided the first operational definition of appropriate hospital admission for emergency department patients with bronchiolitis. We showed that ~6% of emergency department disposition decisions for bronchiolitis were inappropriate at Intermountain Healthcare. Second, we developed the first machine learning model to predict appropriate hospital admission for emergency department patients with bronchiolitis. Our model achieved an accuracy of 91% and an area under the receiver operating characteristic curve of 0.96. With further improvement, our model could serve as a foundation for building decision support tools to guide disposition decisions for children with bronchiolitis presenting to emergency departments.

Speaker Bio: Gang Luo obtained his Ph.D. degree in Computer Science minor in Mathematics at the University of Wisconsin-Madison in 2004. Between 2004 and 2012, he was a Research Staff Member at the IBM T.J. Watson research center. Between 2012 and 2016, he was a faculty member in the Department of Biomedical Informatics at the University of Utah. Gang is currently a faculty member in the Department of Biomedical Informatics and Medical Education of the School of Medicine at the University of Washington. His research interests include health informatics (software system design/development and data analytics), big data, information retrieval, database systems, and machine learning with a focus on health applications. He invented the first method for automatically providing rule-based explanation for any machine learning model’s prediction results with no accuracy loss, the first method for efficiently automating machine learning model selection, the questionnaire-guided intelligent medical search engine iMed, intelligent personal health record, and SQL, compiler, and machine learning progress indicators.

BIME 591B– BIME 591B– Developing Your Informatics Career Path

Tuesday, January 8, 12:30pm- 1:20pm, Health Sciences Building, E216

Facilitator: David Masuda 

UPCOMING DISSERTATION DEFENSE

Ahmad Aljadaan

Wednesday, January 16, 2019, 11:00am, UW Health Sciences Building, BB1602

Title: The Untold Story of Predicting Readmissions for Heart Failure Patients

Abstract: The availability and accessibility of Electronic Health Record (EHR) data create an opportunity for researchers to revolutionize healthcare. The recognition of the importance of secondary use of EHR data has led to the development of research-ready integrated data repositories (IDRs) from EHR data. Analyzing this data can help researchers connect the dots and can lead to critical clinical findings through predictive analytics methods. Unfortunately, poor data quality is a problem that affects the accuracy of such findings. An example of a data quality problem is poor information about the specifics of admission, discharge, and readmission.

Heart Failure (HF) is one of the most common cardiovascular diseases. 5.7 million people in the United States have heart failure with 870,000 new cases annually, and this disease is the leading cause of hospital readmission.

Predicting readmission for heart failure patients has been well-studied. The readmission periods that researchers have studied range between 30 days to one year. However, shorter than 30 days readmission have received less research attention. In my research, I shed light on an overlooked yet important group of readmissions: very early readmissions. Currently, little is known about what causes heart failure patients to come back so quickly. In the long term, my career goal is to predict very early readmission patients before discharge and improve on the discharge decision making. It is a step toward personalized healthcare to improve patient care eventually.

The broad goal of my dissertation is to leverage the availability and accessibility of electronic health data and characterize day 1-30 readmission, more specifically characterizing very early readmissions. My approach to reach my goal went through four major steps: 1) Reviewing the literature to understand the field and how early readmission have been defined, 2) Using retrospective EHR data from UW Medicine to build an accurate visit table for heart failure patients, 3) Using the visit table to build a prediction model to characterize day 1-30 readmissions, 4) Improving on the model by applying different machine learning algorithms and imputation techniques for missing data.

PUBLICATIONS AND PRESENTATIONS

Fathiamini, Safa, Amber M. Johnson, Jia Zeng, Vijaykumar Holla, Nora S. Sanchez, Funda Meric-Bernstam, Elmer V. Bernstam, and Trevor Cohen. “Rapamycin–mTOR+ BRAF=? Using Relational Similarity to Find Therapeutically Relevant Drug-Gene Relationships in Unstructured Text.” Journal of Biomedical Informatics (2019): [epub ahead of print]

INTERNSHIP OPPORTUNITY

2019 Summer Internship in Assessment Science and Psychometrics

https://www.nbme.org/research/internship.html?fbclid=IwAR03YV3WYfKb17hrXNQZphV7ew5_qZvaiPgaKMmBM7L6yXPgm7Ld6GLKiy4

OTHER EVENTS

BIME Happy Hour
Thursday, January 17, 5:00 p.m., South Lake Union, Reception Lounge

Please join us for our monthly departmental BYOB Happy Hour, held every third Thursday of the month. As always, please bring your own beverage; snacks will be provided!

January 7-11, 2019

UPCOMING LECTURES AND SEMINARS

BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, January 10, 11:00am-11:50am, UW Medicine South Lake Union, Room C123A&B

(Also broadcast live and archived at tcs.slu.washington.edu; livestream will have a red dot in the top left hand corner)

Speaker: Paul Nagy, PhD, FSIIM, Associate Professor, Johns Hopkins University School of Medicine,

Russell H. Morgan Department of Radiology

Title: The Johns Hopkins Precision Medical Analytics Platform.  Accelerating clinical research with a secure big data cloud architecture

Abstract: 

In 2016, Johns Hopkins launched the inHealth precision medicine initiative to partner with clinical research groups (Centers of Excellence) to turn clinical data sources into research instruments and constructing the Precision Medicine Analytics Platform (PMAP).  PMAP is a platform for data collection and analysis utilizing a cloud based hadoop architecture ingesting electronic medical records, medical imaging, physiological monitoring, and genomic sequencing.  PMAP was designed in partnership with the Institutional Review Board (IRB) and the JHM Data Trust to rapidly deliver clinical data to researchers in a secure hosted research environment with a large suite of analytical tools.  The twin goals of the initiative are to accelerate biomedical discovery through data science and to leverage those discoveries to improve patient care.

Speaker’s Bio:

Paul Nagy, PhD, FSIIM is an Associate Professor in the Johns Hopkins University School of Medicine Russell H. Morgan Department of Radiology and is faculty in the Division of Health Science Informatics and the Armstrong Institute for Patient Safety and Quality.  He serves as the deputy director of the Johns Hopkins Medicine Technology Innovation Center (TIC) with the goal of partnering with clinical inventors to create novel IT solutions that improves patient care.  This team of designers, developers, and data scientists work with inventors to build, deploy, and evaluate digital health solutions within the Johns Hopkins Medical System.  http://www.jhmtic.org

At Johns Hopkins, Dr. Nagy serves as the program director for year-long multidisciplinary leadership development programs at Johns Hopkins Medicine in precision medicine, clinical informatics, data science and creating commercial ventures.  There have been over 360 faculty and staff that have gone through the programs since 2012.

Dr. Nagy is the past-chair of the Society of Imaging Informatics in Medicine and serves on the Board of the American College of Medical Quality and the Board of Health for Howard County Maryland.  From 2010-2012 he served as the chair of the American Board of Imaging Informatics (ABII) which created the certification for imaging informatics professionals which has over 1,000 diplomates. In 2012, he was inducted into the college of fellows for the Society of Imaging Informatics in Medicine. The Baltimore Business Journal honored him with the 2015 Healthcare Innovation Educator of the year award.

Dr. Nagy received his PhD in Medical Physics from the Medical College of Wisconsin and is the author of over 125 papers in the fields of informatics and implementation science.  https://scholar.google.com/citations?user=tqh1a8sAAAAJ&hl=en

BIME 591B– Developing Your Informatics Career Path

Tuesday, January 8, 12:30pm- 1:20pm, Health Sciences Building, E216

Facilitator: David Masuda

Biomedical Informatics and Medical Education News

December 24-28, 2018

FACULTY/STUDENT/ALUMNI/STAFF ACTIVITIES

Adam Wilcox, PhD, led a committee of thought leaders for AcademyHealth in a response to the “NIH Proposed Provisions for a Future Draft Data Management and Sharing Policy”. Details and the response are here: https://www.academyhealth.org/sites/default/files/academyhealthnihdatasharingresponseweb.pdf

Anne Turner, MD, was voted in as Chair-Elect of the AMIA Academic Forum Executive Committee for 2019 and will serve as Chair of the AMIA Academic Forum Executive Committee in 2020

Peter Tarczy-Hornoch, MD, Professor and Chair of BIME, has been named Chair Elect of the AMIA Academic Leaders Community (ALC) which is the national group of department chairs of Biomedical Informatics programs. He will serve two years as Chair Elect in 2019-20 (and Chair 2021-22, Past-Chair 2023-24).

PUBLICATIONS AND PRESENTATIONS

Lim C, Berry A, Hartzler A, Carrell D, Hirsch T, Bermet Z, Ralston JR. Facilitating Self-reflection about Values and Self-care among Individuals with Chronic Conditions. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI ’19). Accepted for publication in May 2019.

Berry A, Lim C, Hirsch T, Hartzler A, Kiel L, Bermet Z, Ralston JR. Supporting Communication About Values Between People with Multiple Chronic Conditions and their Providers, Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI ’19). Accepted for publication in May 2019.

December 17-21, 2018

FACULTY/STUDENT/ALUMNI/STAFF ACTIVITIES

Dr. Uba Backonja, BIME Adjunct Assistant Professor, was nominated for the Distinguished Teaching Award for Innovation with Technology

http://www.washington.edu/teaching/innovation/teaching-awards/nominees-award-recipients/new-teaching-award-nominees/

Winners will be announced in spring 2019.

BIME faculty Trevor Cohen received a R01 award from the NLM for a project entitled “Robust Inference from Observational Data with Distributed Representations of Conceptual Relations” (total costs $1,500,000 over three years), with sub awards to collaborators Devika Subramanian at Rice University, and Sahiti Myneni at the University of Texas Health Science Center in Houston. This is a renewal of a previous R01 grant concerning the development and evaluation of methods through which knowledge extracted from the biomedical literature can be leveraged in support of post-marketing drug surveillance using distributed representations of biomedical concepts (concept embeddings). The renewal will focus on the integration of these methods with models of large stores of empirical data, including the Food and Drug Administration’s repository of adverse event reports, and data extracted from the Electronic Health Record.

PUBLICATIONS AND PRESENTATIONS

G. Luo, B.L. Stone, F.L. Nkoy, S. He, and M.D. Johnson. Predicting Appropriate Hospital Admission of Emergency Department Patients with Bronchiolitis: Secondary Analysis. JMIR Medical Informatics.

R. Sadeghian, The Feasibility and Satisfaction of Using Telemedicine to Provide Tertiary Pediatric Obesity Care. Journal of the International Society for Telemedicine and EHealth.

J.A. Thomas‡, A Perez-Alday EA‡ Junell A, Newton K, Hamilton C, Li-Pershing Y, et al. Vectorcardiogram in athletes: The Sun Valley Ski Study. Ann Noninvasive Electrocardiol. 2018 Nov 7;e12614. (‡) equal contribution. https://rdcu.be/baVe3

S. Haldar, SR Mishra, M Khelifi, AH Pollack, W Pratt. Beyond the Patient Portal: Supporting Needs of Hospitalized Patients. Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI ’19). Accepted for publication in May 2019.

OTHER NEWS

T. Payne attended a briefing on Capitol Hill on “Unlocking Patient Data”

HIPAA Modernization Needed, Experts Say | AMIA

AMIA-AHIMA Hill Briefing on Strikingly

December 10-14, 2018

UPCOMING MASTER’S DEFENSES

Wenjun Song

Thursday December 13, 10:00 am, UW SLU C123A

Title:  Immune Correlates Analysis of RhCMV/SIV Vaccine Efficacy

Abstract:

In the past 30 years, HIV vaccine studies on traditional CD8+ T cell-targeted HIV vaccines were frustrated by the ineffectiveness of mediating immediate vaccinal interception upon infection acquisition prior to the explosive viral amplification. As the most important lesson of past HIV vaccine researches, the first hours to days immediately after viral infection might be the only vulnerable time period for immunologic interceptions. With this regard, immunologists started a novel research on employing Cytomegelovirus (CMV) as vaccine vector in early 2000s, to exploit CMV vectors’ unique ability on eliciting and maintaining abundant functional T cell responses at all potential HIV infection sites. Recent CMV-based vaccine research, demonstrated by Louis Picker and colleagues, with statistical support by Dr. Edlefsen, manifests a remarkable infection control and clearance on ~50% of HIV-acquired rhesus macaques (RM) vaccinated by Simian immunodeficiency virus (SIV) inserted rhesus cytomegalovirus (CMV) vaccine. This promising protection pattern motivates further immunologic correlates analysis on vaccine efficacy to investigate potential immunological mechanisms of the partial protection. This presentation will show a preliminary immunologic correlates model with strategic informatics interpretations.

December 3-7, 2018

UPCOMING LECTURES AND SEMINARS

BIME 591B– Write the Good Write

Tuesday, December 4, 11:30am- 12:20pm, Health Sciences Building, T530

Facilitators: Wanda Pratt, PhD and Sonali Mishra

See course website for details.

UPCOMING DISSERTATION DEFENSE

Tim Wu
Thursday, December 6; 9:30-10:30 AM; South Lake Union Building C259

Title: Bicluster-Based Identification of Gene Sets Through Multivariate Meta-Analysis (MVMA)

Abstract:

Omics technologies have transformed biology and medicine by generating massive amount of high-resolution data. Much of the data have been made publicly available but have not been fully explored or utilized. The current study aims to mine public gene expression to discover gene sets that may correspond to biological pathways. The challenges with using public data include data heterogeneity, high dimensionality, and small sample sizes. The overall research questions include: (1) what is the data mining method best suited for finding gene sets; and (2) how best to utilize multiple datasets in order to increase statistical strength. Aim 1 is to determine optimal method for constructing bicluster stacks. Aim 2 is to determine suitability of meta-analysis techniques to pool biclusters and assess performance, and Aim 3 is to assess potential utility of gene sets identified in Aim 2 using pathway analyses.

In Aim 1, we demonstrate the technique of biclustering in gene set identification, based on a number of key advantages of biclustering over the traditional clustering methods. In addition, we show that synthesis of summary statistics (biclusters in this case) is a better approach for utilizing multiple datasets compared to simply aggregating the source datasets together.  For Aim 2, we adapt the framework of multivariate meta-analysis (MVMA), and a previously published two-step procedure to tackle the issue of high dimensionality with an improvement that involves a sparse estimate for the between-study covariance matrix using the graphical lasso algorithm. The improvement leads to a significant increase in the performance of MVMA in classifying real genes from background genes. In Aim 3, the gene sets found to be significant according to MVMA are further investigated by knowledge-based pathway analyses. The results suggest that the overall effect sizes are a predictor of biological relevance of the gene sets, which is the most significant finding of the study.

NEW FACULTY ANNOUNCEMENT

We are delighted to announce that Dr. Matthew Cunningham will be joining our faculty as an Assistant Professor starting January 2019. Dr. Cunningham received a Ph.D. from the Neurobiology & Behavior graduate program at the University of Washington in 2003. He then transitioned away from biomedical research and into educational evaluation in the UW Biology department, where he completed a certificate program in Program Evaluation. In 2009, he landed in his current role in BIME managing the testing service for the UW School of Medicine, where he has played a large role in moving the Medical School to fully computerized testing, among other things. Starting in January 2019 in addition to joining our faculty, Dr. Cunningham will take on the role of Director of Educational Evaluation (previously held by Dr. Carline).

FACULTY/STUDENT/ALUMNI/STAFF ACTIVITIES

Thomas Payne, MD (GIM), Adjunct Professor in BIME; Fuki Hisama, MD, PhD (Medical Genetics); and Lue-Ping Zhao, PhD (Fred Hutchinson Cancer Research Center) were awarded a 2018 Catalytic Collaborations granting program from the Brotman Baty Institute for their proposal “Using EHR Content to Prevent Breast and Ovarian Cancer.”  Dr. Payne will serve as Principal Investigator.

PUBLICATIONS AND PRESENTATIONS

Relational concurrency, stages of infection, and the evolution of HIV set point viral load” Steven M Goodreau, Sarah E Stansfield, James T Murphy, Kathryn C Peebles, Geoffrey S Gottlieb, Neil F Abernethy, Joshua T Herbeck, John E Mittler Virus Evolution, Volume 4, Issue 2, 1 July 2018, vey032, Published: 21 November 2018

Feld LG, Neuspiel DR, Foster BA, Leu MG, Garber MD, Austin K, Basu RK, Conway EE, Fehr JJ, Hawkins C, Kaplan RL, Rowe EV, Waseem M, Moritz ML, Subcommittee on Fluid and Electrolyte Therapy.  Clinical Practice Guideline:  Maintenance Intravenous Fluids in Children.  Pediatrics. 2018 Nov 21. doi:  10.1542/peds.2018-3083.

JOB OPENINGS

Undergraduate Teaching Assistant Position for BIME 498 “Informatics in Healthcare” (Winter 2019)

We are seeking an undergraduate teaching assistant for our new undergraduate course in clinical informatics, BIME 498 “Informatics in Healthcare”. This paid position requires a maximum of 15 hours per week winter quarter. The iSchool administers recruitment and hiring. Contact Andrea Hartzler with any questions andreah@uw.edu. Applications are due 12/3/18: https://jobs.ischool.uw.edu/posting/306

 

November 26 – November 30, 2018

UPCOMING LECTURES AND SEMINARS

BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, November 29, 4:00pm-5:00pm, UW Medicine South Lake Union, Room C123A&B

(Also broadcast live and archived at tcs.slu.washington.edu; livestream will have a red dot in the top left hand corner)

Title:  Reproducible Research with R

Speaker: Kara Woo, MLIS, Research Scientist, Sage Bionetworks

Abstract: 

Reproducibility (or lack thereof) of research findings is a growing concern, but fortunately there are many tools and resources to aid analysts in developing transparent and reproducible projects. Kara will discuss the landscape of some of these tools, and how the rOpenSci community is advancing open, reproducible science through software and community.

Speaker’s Bio:

Kara Woo is a research scientist at Sage Bionetworks where she develops tools to help researchers manage and share their data. She is active in the R community through rOpenSci, R-Ladies, and as a core developer of ggplot2.

BIME 591B– Write the Good Write

Tuesday, November 27, 11:30am- 12:20pm, Health Sciences Building, T530

Facilitators: Wanda Pratt, PhD and Sonali Mishra

See course website for details.

UPCOMING GENERAL EXAM

Jimmy Phuong

Friday November 30, 1:00-3:00 p.m., UW Health Sciences, T498

Title:  Enhancing Secondary-use of Electronic Health Records for Population Health Research using Spatiotemporal Analytical Methods

Abstract: For almost three decades, the United States Department of Human and Health Services, Center for Disease Control, and the World Health Organization have recognized social and environmental determinants of health account for the majority of population health. While genetics and personal behavior may predispose an individual to be in a healthy status, community- and population-scale health status are determined in large by factors of socioeconomic status, physical environmental ecology, and access to healthcare services. Hence, the geographic environment and the accessibility to resources are critical components towards understanding and promoting health, by ways such as enacting policy interventions. In disastrous times, spatiotemporally-relevant information escalate in importance as the health system respond to emergent concerns, pre-existing needs, disruption in access to prior resources, and migration among affected populations. Hospital and clinic Electronic Health Record systems (EHRs) contain a richness and diversity of information about where healthy and unhealthy patients are. In disaster preparedness, EHRs could potentially inform where and how to prepare for population-level patient needs in future scenarios with a timely, equitable, and data-driven approach; however, for operational and ethical reasons, the ability to apply EHR-enabled spatiotemporal reasoning and analytics has remained an underrepresented capacity. Moreover, it is unknown how data gaps and changing standards within EHRs may challenge inferential interpretations. This proposal will investigate three areas for building capacities to address population health uses with spatiotemporal analytical methods. The specific aims of this work include: 1) design spatiotemporal use-case workflows to survey trends and anomalies for regional areas using gridded hydrometeorological data products, a surrogate for structured multivariate datasets, 2) assess information needs and high-value use-cases for population health research in hydrologic disaster preparedness, and 3) develop and evaluate spatiotemporal inferential statistics through secondary-use of patient diagnostics within EHRs. These research aims align with recent funding priorities with United States National Institutes of Health, National Science Foundation, World Health Organization, and multi-national Ministries of Health for integrative disaster research and population health initiatives.

UPCOMING DISSERTATION DEFENSE

Sean Mikles
Friday, November 30, 2pm, UW Health Sciences Building, T359

Title: No Wrong Door: Designing Health Information Technology to Support Interprofessional Collaboration Around Child Development Work

Abstract:

Child development refers to children gaining the skills they need to succeed in life, consisting of abilities in different overlapping domains such as speech, motor, social, and cognition. Developmental disabilities are chronic delays in gaining such skills, and if they are not addressed in a timely manner a child can experience negative outcome throughout their life. Responsibilities for identifying and treating developmental delays and disabilities are spread across many stakeholders in the community, including not only parents but an interprofessional collection of service providers such as pediatricians, early educators, childcare providers, providers of home visiting services, and community groups. Regardless of who is involved in a child’s care, there must be ‘no wrong door’ into the ecosystem of development support services. Unfortunately, these stakeholders operate in silos, leading to a fractured system of services that parents struggle to navigate. This often leads to delays in the receipt of necessary services and uncoordinated care. Various researchers and policy leaders such as the American Academy of Pediatrics have suggested that health information technology (HIT) could be an important tool to help stakeholders collaborate in a child’s care management. Current biomedical informatics literature, however, provides little practical guidance on how to design HIT systems to support such interprofessional collaboration.

This dissertation presents four studies that aim to address this design gap by drawing upon the extensive corpus of literature on collaborative practice and the user-centered design framework. These studies demonstrate the use of qualitative methods in conjunction with theoretical concepts to assess the needs of a heterogeneous collection of stakeholders in regards to collaborative work with the goal of deriving design implications for future creators of collaborative HIT systems. The first study demonstrates the utility of using concepts from the collaboration literature to uncover actionable design implications for collaborative systems using previously-collected interview data from an interprofessional collection of stakeholders. The second and third studies utilize the methods of the first study to explore interprofessional work processes and interprofessional trust, respectively, with new original interview data. Building upon the third study, the last study provides practical guidance for designing interprofessional collaborative systems to support the creation of trust between stakeholders of heterogeneous backgrounds. This is achieved through eliciting the information that people use to judge trustworthiness, and then creating and testing prototype information webpages listing the noted information. This research will provide concrete methodological guidance for designers of future systems to support collaborative work as well as concrete design implications for such systems.

PUBLICATIONS AND PRESENTATIONS

Thomas JA‡, Perez-Alday EA‡, Hamilton C, Kabir MM, Park EA, Tereshchenko LG. The utility of routine clinical 12-lead ECG in assessing eligibility for subcutaneous implantable cardioverter defibrillator. Computers in Biology and Medicine. 2018 Nov 1;102:242–50. (‡) equal contribution. https://doi.org/10.1016/j.compbiomed.2018.05.002

Chan EKH, Edwards TC, Haywood K, Mikles SP, Newton L. Implementing patient-reported outcome measures in clinical practice: a companion guide to the ISOQOL user’s guide. Quality of Life Research. 2018. Epub ahead of print. doi: 10.1007/s11136-018-2048-4

Luo G, A Roadmap for Semi-automatically Extracting Predictive and Clinically Meaningful Temporal Features from Medical Data for Predictive Modeling. Global Transitions, 2019.

 

November 19 – November 21, 2018

UPCOMING LECTURES AND SEMINARS

BIME 591B– Write the Good Write

Tuesday, November 20, 11:30am- 12:20pm, Health Sciences Building, T530

Facilitators: Wanda Pratt, PhD and Sonali Mishra

See course website for details.

 

BIME 590A – Biomedical & Health Informatics Lecture Series

No session, Thanksgiving Holiday

UPCOMING GENERAL EXAMS

Abhishek Pratap
Wednesday November 21, 2:30 p.m., UW Health Sciences, T360

Title:  Using Technology-enabled Services to Improve our Capacity to Assess and Intervene in Depression

Abstract: When it comes to mental health, no country is considered developed. The recent 2018 report from Lancet commission on global mental health highlights the global burden of disease linked to mental disorders has risen in all countries with increasing socioeconomic disparities in timely diagnosis and access to evidence-based treatments. We still don’t fully understand the underlying cause or mechanism behind the mental disorders. To date, there is no objective test to measure the severity of mental health symptoms, and clinical diagnoses are routinely based on subjective expressed symptoms which makes it difficult to manage what we cannot measure. Technology-enabled services offer an incredible opportunity to bridge the gap in mental health care by building objective assessment and symptom tracking tools along with digital psychological interventions that are more accessible and potentially less stigmatizing and can be offered either in conjunction or independently of local mental health services. This digital ecosystem has a realistic potential to address all corners of IOM’s triple aim, i.e. improve mental health at the population level, enhance patient satisfaction and reduce overall costs. In this regard my Aim I is to learn the clinical utility of active and passive digital data collected fully remotely through smartphones for assessing symptoms of the major depressive disorder (MDD) and the feasibility of developing robust digital biomarkers that could potentially identify underlying substructure of depression symptomatology. In Aim II, I propose to investigate the nationwide depression trends using data from > 1.5 million web-based screenings for MDD for the years 2015-2017 and evaluate the impact of environmental factors such as weather, air pollution, and social determinants of health on MDD symptoms. Finally, in Aim III, I will determine the feasibility of using past web-based searches to learn individual-level risk factors and context leading to a suicide attempt; a condition well known to be linked with severe depression. The proposed research aims are also aligned with the NIMH strategic research priorities and are directed toward enabling a digital framework that can help early detection and deployment of tailored interventions at the population level particularly in low resource settings and marginalized populations.

November 12 – November 16, 2018

UPCOMING LECTURES AND SEMINARS

 BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, November 15, 4:00pm-5:00pm, UW Medicine South Lake Union, Room C123A&B

 (Also broadcast live and archived at tcs.slu.washington.edu; livestream will have a red dot in the top left hand corner)

Title:  The Implementation of Genetic Medicine

Speaker: David Crosslin, PhD, Associate Professor, Biomedical Informatics and Medical Education

Abstract: 

Dr. Crosslin will chronicle the National Human Genome Research Institute’s genetic medicine research efforts, mainly through the Electronic Medical Records & Genomics (eMERGE) Network.  This will include current opportunities and trends with the implementation of genetic medicine.

Speaker’s Bio:

Dr. Crosslin’s research program focuses on translational bioinformatics with a combination of bioinformatics, statistical association analyses, and computational tools development for applied research.  Specifically, his research focuses on integrating genetic data into the electronic health record for clinical decision support.  All efforts will advance the national electronic health information infrastructure in support of personalized medicine.

BIME 591B– Write the Good Write

Tuesday, November 13, 11:30am- 12:20pm, Health Sciences Building, T530

Facilitators: Wanda Pratt, PhD and Sonali Mishra

See course website for details.

BIME ACTIVITIES AT AMIA

Mikles, S. P., Haldar, S., Yin, S.-Y., Kientz, J. A., & Turner, A. M. (2018). Trust and Sharing in an Interprofessional Environment: A Thematic Analysis From Child Development Support Work in the Community. Presented at the AMIA 2018 Annual Symposium, San Francisco, CA.

FACULTY/STUDENT/ALUMNI/STAFF ACTIVITIES

Congratulations to Daniel Capurro, Fellow of AMIA!

Daniel Capurro, MD, PhD, Affiliate Assistant Professor of BIME, was included in the inaugural class of 130 Fellows in the newly established FAMIA Applied Informatics Recognition Program, a new program meant to recognize AMIA members who apply informatics skills and knowledge within their professional setting, who have demonstrated professional achievement and leadership, and who have contributed to the betterment of the organization. Mike Leu, MD, Associate Professor of BIME and Director of the Clinical Informatics Fellowship, and Paul Sutton, MD, Adjunct Associate Professor of BIME, were also honored as Fellows of FAMIA (see 11/2/18 BIME News for more information).

New Fellows of AMIA are authorized to use the letters FAMIA in connection with their professional activities. A formal induction ceremony will be held at the AMIA 2019 Clinical Informatics Conference in Atlanta, April 30 – May 2, 2019. Click here for the list of the inaugural class of Fellows.

Congratulations to Reza Sadeghian!

Reza Sadeghian, MD, Clinical Informatics Fellow, has joined Southern Medical Association Faculty team for their online Healthcare Tech Webcast.

https://sma.org/smarter-healthcare-tech-webcasts/

November 5 – November 9, 2018

UPCOMING LECTURES AND SEMINARS

BIME 590A – Biomedical & Health Informatics Lecture Series

Thursday, November 8, 4:00pm-5:00pm, UW Medicine South Lake Union, Building E, Room E130AB

(Also broadcast live and archived at tcs.slu.washington.edu; livestream will have a red dot in the top left hand corner)

Title:  Using Predictive Analytics in Healthcare

Speaker: James Perkins, MD, FACS, MSDS, FACMQ, Professor of Transplant and Surgery and Vice Chair of Surgery, University of Washington

Abstract: 

The field of predictive analytics has many interrelated terms including artificial intelligence, machine learning, big data, natural language processing, and others.  After reviewing these terms, the areas in healthcare where predictive analytics is being used will be explored with some common examples in each area. Finally, a brief overview of a standard method to develop predictive analytic models and pitfalls to avoid will be reviewed.

Speaker’s Bio:

Dr. Perkins obtained his medical degree at the University of Arkansas in 1979. He completed a residency in General Surgery at the University of Kansas in 1984. He became a fellow in renal transplantation at the University of Utah and later in liver transplantation at the Mayo Clinic from 1984 to 1986. He came to the University of Washington as the Division Chief for Abdominal Transplantation from 1989 to 2002. He has been the Vice-Chairman for Quality in the Department of Surgery from 2002 until the present. In 2009, he completed the 10 X 10 Medical Informatics course from Oregon Health and Science University. In 2010, he received certification from the University of Washington in Database Administration. He obtained a Master of Science degree in Data Science in 2016 from Northwestern University. Since 2010, he has been the Director of the Clinical and Bio-Analytics Transplant Laboratory (CBATL) in the Department of Surgery. CBATL is a think tank for improving transplant patient care through: predictive analytics, genomic analysis, microsimulation modeling, and outcomes research.

BIME 591B– Write the Good Write

Tuesday, November 6, 11:30am- 12:20pm, Health Sciences Building, T530

Facilitators: Wanda Pratt, PhD and Sonali Mishra

See course website for details.

BIME ACTIVITIES AT AMIA

Uba Backonja, PhD, RN, BIME Adjunct Assistant Professor, is co-organizer for the Citizen Science workshop (W3, Saturday 11/3/2018 at 8:30 AM–12:00 PM Nov 3, 2018   Franciscan B).

Shefali Haldar, PhD Candidate, will be presenting the following paper on behalf of her co-authors in S40-Patient Engagement and Safety (Monday 11/5 1:45pm-3:15pm, Plaza A): Exploring the Design of an Inpatient Peer Support Tool: Views of Adult Patients.

Lauren Snyder, PhD Candidate, will be presenting the following poster in Poster Session 2 (Tuesday, 11/6 5-6:30pm): Business Process Analysis to Understand Health Policy Information Needs in South Africa.  Full author list: Snyder LE, Lane JP, Katz A, Turner AM

Peter Tarczy-Hornoch, MD, Professor and Chair will be presenting a poster on behalf of BIME PhD student Ahmad Aljadaan (Tuesday, 11/6 5-6:30pm): Counting Readmissions: Surprisingly Difficult. Full author list: Aljadaan A, Tarczy-Hornoch P, Wilcox A, Dardas T, Gennari J

Anne Turner, MD, BIME Professor, is presenting S103: Oral Presentation – Patient and Family Participation (Wed. 11/7 8:30-10:00am): A closer look at health information seeking in older adults and involved family and friends.

UPCOMING DISSERTATION DEFENSES

Graham Kim
Friday, November 9, 1pm, UW Medicine SLU, Building E, Room E130A

Title: Secondary Usage of Electronic Health Record Data for Patient-Specific Modeling

Abstract:

Translational research has become an important bridge that moves findings from basic science research to patients’ bedside and to the clinical community. Unfortunately, this notion of translational research seems to be unidirectional in that basic research is translated into clinical research and practice, but basic science research does not seem to benefit as much from clinical medicine.

In my dissertation, I leverage the availability of retrospective EHR data and use them with biosimulation models to translate data from clinical medicine to benefit biosimulation modeling. Biosimulation models are mathematical representations of biological systems, and they can help with mechanistic understanding of physiology and predict the dynamics of a biological system. Using clinical data with biosimulation models has the potential to benefit both the biosimulation modelers, as well as clinicians.

The abundance of retrospective clinical data available for research is a promising alternative to the traditional method of validating models by conducting resource-intensive prospective studies. These models can then be made patient-specific to simulate the physiology of individuals. When used in the clinical setting, these patient-specific models have the potential to be used by clinicians to better understand the underlying pathophysiology of the patient.

In my research, I first conduct a scoping review of model in the literature to quantify model reproducibility and discover the abysmal status of model source code availability in publications. Then using a published hemodynamics model, I demonstrate using retrospective clinical dataset from right heart catheterizations to optimize and validate the model without needing to conduct burdening prospective studies, and explore potential clinical applications of patient-specific modeling. Finally, I describe an ontological approach to extend the data-model connection to be systematic and scalable. I demonstrate this approach by connecting cardiology data and lab results data with a hemodynamics model and several nephrology models, respectively.

FACULTY/STUDENT/ALUMNI/STAFF ACTIVITIES

Congratulations to Mike Leu, MD and Paul Sutton, MD, Fellows of AMIA!

Mike Leu, MD, Associate Professor of BIME and Director of the Clinical Informatics Fellowship, and Paul Sutton, MD, Adjunct Associate Professor of BIME, have been recognized by being included in the inaugural class of 130 Fellows in the newly established FAMIA Applied Informatics Recognition Program, a new program meant to recognize AMIA members who apply informatics skills and knowledge within their professional setting, who have demonstrated professional achievement and leadership, and who have contributed to the betterment of the organization.

FAMIA was established in May 2018, following several months of deliberation by an interdisciplinary Advisory Group of AMIA members to define the FAMIA Eligibility Criteria. These deliberations reaffirmed that the FAMIA Applied Informatics Recognition Program be inclusive – balancing the needs of physicians, nurses, pharmacists, and others within clinical informatics, with the needs of public health, clinical researchers, and others who apply informatics to their practice.

FAMIA recognizes professionals who apply informatics skills and knowledge towards the goals of enhanced personal and population health, improved organizational performance and learning, and individual empowerment in their health, care, and research.

New Fellows of AMIA are authorized to use the letters FAMIA in connection with their professional activities. A formal induction ceremony will be held at the AMIA 2019 Clinical Informatics Conference in Atlanta, April 30 – May 2, 2019. Click here for the list of the inaugural class of Fellows.

PUBLICATIONS AND PRESENTATIONS

Conference paper:

Stephens, K. A., Osterhage, K. P., Fiore-Gartland, B., Lovins, T. L., Keppel, G. A., & Kim, K. K. (in press). Examining the Needs of Patient Stakeholders as Research Partners in Health Data Networks for Translational Research. AMIA Summits Translational Science Proceedings, Mar 27, 2019.

2 Conference abstracts:

Bergquist, T., Estiri, H., Prosser, J., & Stephens, K. A. (2018, December). A Data Quality Testing Tool for Cross-institutional OMOP Electronic Health Record Data Repositories. Abstract and oral presentation presented at International Society for Computational Biology Rocky 2018 Bioinformatics Conference, Aspen, CO.

 Stephens, K. A., Wilcox, A., Payne, Ph., Morrison, J. Sprecher, J., Mussa, R., Foraker, R., Biber, S., & Mooney, S. D. (2018, December). Governance Innovations for Promoting Cross-institutional Electronic Health Data Sharing. International Society for Computational Biology Rocky 2018 Bioinformatics Conference, Aspen, CO.