FREE HL7 FHIR Tutorial for Students during HL7 Working Group Meeting in Atlanta, GA

WHAT: “Starting from Scratch: A Recipe for Students Using HL7 Standards Including HL7 FHIR”

WHEN: Wednesday, September 18 — 1:45-3:00 pm

WHERE: HL7 33rd Annual Plenary and Working Group Meeting (WGM) — Atlanta Marriott Marquis, Atlanta, GA

HOW: Registration is required, students can register for this FREE tutuorial at: http://www.hl7.org/events/tutorial/2019/.

This free tutorial is an opportunity for students to learn about HL7, its legacy standards and FHIR. A major focus of this presentation will be an introduction to FHIR and how a knowledge of HL7 standards will give these students a competitive edge in the job market.

MCBIOS & MAQC Announce Joint Conference in April 2020 at SAS

The Midsouth Computational Biology & Bioinformatics Society (MCBIOS) is holding its 17th Annual Meeting, Precision Public Health – A 2020 Vision, April 6-8, 2020 in Cary, NC at the SAS Institute.  There are a variety of opportunities to participate.  See MCBIOS2020 for more information.

 

Richesson Co-Chair of Second Annual MCBK Meeting, July 18 & 19, 2019

The Mobilizing Computable Biomedical Knowledge (MCBK) 2019 second annual meeting was held  at the National Institutes of Health (NIH) in Bethesda, MD July 18-19, 2019. MCBK, a diverse group including clinicians, researchers, biomedical informaticians, librarians, and policy-makers was formed as a means to use computable knowledge representation to accelerate the use of biomedical knowledge. The co-chairs of the MCBK Community are Charles Friedman, PhD, Department Chair of Learning Health Sciences and Professor of Medical Education at the University of Michigan, and Rachel Richesson, PhD, Associate Professor in the Duke School of Nursing.

Computable Biomedical Knowledge (CBK) is explicit and machine-executable, and includes the standards and mathematical approaches required to represent biomedical knowledge in a computable FAIR (findable, accessible, interoperable, and reusable) format. Work to date has included outlining MBCK’s vision and goals and the standards, technical infrastructure, governance, policies, and stakeholders central to advancing the use of Computable Biomedical Knowledge.

Key speakers for the meeting included Patty Brennan, RN, PhD, Director of the National Library of Medicine; Don Rucker, MD, National Coordinator for Health Information Technology (ONC); and Dipak Kalra, PhD, President of the European Institute for Innovation through Health Data (i-HD). In addition to co-chair Rachel Richesson, PhD, Duke was represented at the meeting by Davera Gabriel, RN from DCRI and Vivian West, PhD, MBA, RN, the Associate Director of DCHI.

Gabriel appointed to HIMSS Interoperability & HIE Committee for FY 20-21

DCRI Senior Informaticist Davera Gabriel has been selected by HIMSS for a two year appointment to the Interoperability & Health Information Exchange (I&HIE) Committee.  The purpose of the committee is to promote standards-based interoperability and new information technologies for secure and accessible health information exchange that leads to improving care while lowering costs. The committee supports HIMSS’ activities on both national and global levels.

In her role, Davera hopes to leverage her “boots on the ground standards and data harmonization implementation experience to support HIMSS’ efforts to bridge the data divide between the healthcare and clinical research enterprises it serves, to maximize benefits of interoperable data envisioned for Learning Health Organizations.” See the HIMSS website for additional information.

And the Winner is….Duke Breathe FHIR Team!

Duke Breathe FHIR team members  (l-r) Yifei Wang, Allison Young and Brinnae Bent with their faculty mentor Dr. Ed Hammond. Members of the team not pictured:  Sa Cheng, Ruiqi Wang and Daniel Witt.
HL7 Student Track Cup Redmond 2019.
Duke Breathe FHIR team members  (l-r) Allison Young, Brinnae Bent and Yifei Wang present their project. Members of the team not pictured:  Sa Cheng, Ruiqi Wang and Daniel Witt.

Student teams from all over the world competed in an Online Hackathon for the HL7 Student Track Cup Redmond 2019.

Duke’s team was one of three finalists, winning 3-day passes to the HL7 FHIR Development Days Conference.  Three team members and their mentor, Dr. Ed Hammond traveled to Redmond, WA to compete against McMaster University from Hamilton, Ontario and Georgia Institute of Technology in Atlanta, GA.  Each team was given 10 minutes to present their work to a panel of FHIR experts who judged the projects based on the effective use of standards, originality of their solution and their presentation.

As a final project for their Data Representation and Standards course, the six students under the guidance of Dr. Ed Hammond created SPiRE: A Smart Phone App for Managing Adolescent Asthma.

Tenenbaum selected as new N.C. Health Agency Chief Data Officer

Jessie Tenenbaum, PhD, Assistant Professor in the Department of Biostatistics and Bioinformatics, Division of Translational Biomedical Informatics, has been appointed to succeed Aaron McKethan, PhD, as the chief data officer for the North Carolina Department of Health & Human Services.  In an article in Healthcare Innovation, David Raths discusses the transition and collaborative initiatives of both Drs. Tenenbaum and McKethan.  Dr. Tenenbaum will retain her faculty appointment and affiliation with Duke University.

 

MIDS Program Class Project Selected as Finalist at HL7 FHIR Developer Days Conference

Daniel Witt, Brinnae Bent, Allison Young, Dr. Ed Hammond, PhD, Sa Cheng, Ruiqi Wang and Yifei Wang – Members of the Breathe FHIR Team

Students in the Master of Interdisciplinary Science (MIDS) program, Data Representation and Standards course offered in the Biomedical Informatics concentration are headed to Redmond, WA June 10-12, 2019. Their team project, SPiRE: A Smart Phone App for Managing Adolescent Asthma  was selected as one of three finalists in the HL7 FHIR Dev Days 2019 Student Track Competition. Members of the team are noted in the photo and caption above.

The course, taught by Dr. Ed Hammond, DCHI Director, focuses on data representation that is essential for interoperability and the sharing and intellectual use of data across the health care spectrum. The course investigates the current world of healthcare data representation –controlled terminologies such as SNOMED-CT, LOINC, ICD10, RxNorm, DSM-5, MedDRA, CPT, and MeSH; ontologies as a data representation; existing common data element sets; and attributes to make the data element provide meta knowledge. The course also focuses on data transport standards, including HL7 International standards; Standards Developing Organizations such as IEEE, X12, ASTM, NCPDP, DICOM, IHE, ISO TC 215, CEN TC 251; and standards such as Clinical Decision Support standards, Genomic standards, and SMART app standards.

 

 

Second Edition of Clinical Research Informatics is published

Rachel Richesson, PhD, Associate Professor in the Duke School of Nursing, together with James Andrews, PhD, University of South Florida are co-editors of the second edition of Clinical Research Informatics recently published by Springer International Publishing.   The edition reviews how clinical research informatics has evolved and the challenges in a constantly evolving clinical research environment.  The book includes two chapters co-authored by other Duke faculty: James Tcheng, MD, Professor of Medicine/Cardiology (Patient Registries for Clinical Research) and W. Ed Hammond, PhD, Professor of Community and Family Medicine (Developing and Promoting Data Standards for Clinical Research).

Healthcare Data Scientist Qualifications, Skills, and Job Focus: A Content Analysis of Job Postings

Melanie A Meyer

Journal of the American Medical Informatics Association, Volume 26, Issue 5, May 2019, Pages 383–391, https://doi.org/10.1093/jamia/ocy181

Published: 01 March 2019

Abstract

Objective

Growth in big data and its potential impact on the healthcare industry have driven the need for more data scientists. In health care, big data can be used to improve care quality, increase efficiency, lower costs, and drive innovation. Given the importance of data scientists to U.S. healthcare organizations, I examine the qualifications and skills these organizations require for data scientist positions and the specific focus of their work.

Materials and Methods

A content analysis of U.S. healthcare data scientist job postings was conducted using an inductive approach to capture and categorize core information about each posting and a deductive approach to evaluate skills required. Profiles were generated for 4 job focus areas.

Results

There is a spectrum of healthcare data scientist positions that varies based on hiring organization type, job level, and job focus area. The focus of these positions ranged from performance improvement to innovation and product development with some positions more broadly defined to address organizational-specific needs. Based on the job posting sample, the primary skills these organizations required were statistics, R, machine learning, storytelling, and Python.

Conclusions

These results may be useful to organizations as they deepen our understanding of the qualifications and skills required for data scientist positions and may aid organizations in identifying skills and knowledge areas that have been overlooked in position postings.

 

Duke well represented at the AMIA 2019 Annual Summit

This year, Duke was well represented at the AMIA 2019 Informatics Summit  with over thirty faculty, staff and students from the University, Health System, School of Medicine, Duke Clinical Research Institute, Duke Health and Technology Solutions and Duke Forge.

Duke Participants:

Scientific Program Committee

Davera Gabriel, RN, Senior Informaticist at Duke Clinical Research Institute, Vice Chair, Data Science Track

Benjamin Goldstein, PhD School of Medicine, Data Science Scientific Program Committee

Julian C. Hong, MD, MS, Duke University, Clinical Research Informatics Scientific Program Committee

Birds-of-a-Feather session

Davera Gabriel, RN – 3D Data

Special, late-breaking AMIA Summit SPC Chair Alumni Supersession

Dr. Jessie Tenenbaum, PhD Assistant Professor, Duke Translational Medicine Institute; TBI, 2013

Scientific Panel

Dr. Jessie TenenbaumPhD Assistant Professor

S32: Panel – Mental health research in the open science era: special issues in sharing sensitive behavioral health data

Scientific Papers, Podium Presentations

Allison Dunning, Senior Biostatistician at Duke Clinical Research Institute

Board 10 – An Interactive Data Visualization Tool Developed from Deep Learning Implementation to Electronic Health Record Notes

Note coauthors: Qi Liu, Duke University, Azalea Kim, Duke Forge, Julie Childers, Duke University Health System, Shelley Rusincovitch, Duke Forge, Ursula Rogers, Duke Forge, Ricardo Henao, Duke University

Andy MacKelfresh, Project Leader at Duke Clinical Research Institute

Surgical Critical Care Initiative: Multi-Site Data Collection, Harmonization, and Analytics to Generate Clinical Decision Support Tools

Matthew Phelan, Biostatistician at Duke Clinical Research Institute

Mitigating Bias Due to Informative Visit Process in Electronic Health Records Data

Note coauthors: Sarah Peskoe, Duke University, Neha Pagidipati, DCRI, Benjamin Goldstein, Duke Clinical Research Institute

Laura Qualls, Project Leader at Duke Clinical Research Institute

Evaluating Foundational Data Quality and Fitness for Use in the National Patient-Centered Clinical Research Network (PCORnet®)

Note coauthors: Sujung Choi, Duke Clinical Research Institute, Allison Haufler, Duke Clinical Research Institute, Darcy Louzao, Duke Clinical Research Institute, Stephanie Poley, Duke Clinical Research Institute, Keith Marsolo, Cincinnati Children’s Hospital (now Duke University)

Prof. Ryan Shaw, Associate Professor at Duke University

Diabetes Mobile Care: Aggregating and Visualizing Data from Multiple Mobile Health Technologies

Note coauthors: Eleanor Wood, Duke University, Qing Yang, Duke University, Dori Steinberg, Duke University, Angel Barnes, Duke University, Jacqueline Vaughn, Duke University, Matthew Crowley, Duke University, Craig Henriquez, Duke University, Martin Streicher, Duke University, Daniel Bass Blue, Duke University, Susie Choi, Duke University

Dr. Azalea Kim, MD, MBA, MPA, Medical Director, Applied Health Data Science at Duke University

Finding Needles in the EHR Haystack: Design and Early Results for a Natural Language Processing Model to Identify Clinical Notes Relevant to a Patient’s Goals of Care

Note coauthors: Allison Dunning, Duke University, Shelley Rusincovitch, Duke University, Andrew Olson, Duke University, Julie Childers, Duke University Health System, Erich Huang, Duke University, Ursula Rogers, Duke University, Brian Griffith, Duke University Health System, Lawrence Mumm, Duke University Health System, Qi Liu, Duke University, Matias Benitez, Duke University, Jared Lowe, Duke University Health System, Ricardo Henao, Duke University, David Casarett, Duke University Health System

Debra Harris, Assoc Dir, HSR at Duke University – Duke Clinical Research Institute

From Encounters to Endpoint: Method of Developing Clinical Trial Endpoint Dataset from EHR, Claims, and Patient-Reported Events

Note co-authors: Bradley Hammill, Duke University, Lisa Eskenazi, Duke University, Mary Williams, Duke University, W. Jones, Duke University , Jennifer White, Duke University, Holly Robertson, Duke University

Bilikis Akindele, Team Lead Clinical Research Informatics/Analytics at DUHS

Monitoring the Monitors: Data-Driven Alarm Management Strategies for Clinical Devices at Duke Health

Note co-author: Tracey Hughes, Duke University Health System

Nrupen Bhavsar, Assistant Professor at Duke University School of Medicine

Is the health of a neighborhood improving or are healthier people displacing long term residents: – a case study of gentrification in Durham County

Note co-authors: Matthew Phelan, Duke Clinical Research Institute, Megan Sheperd-banigan, Duke University School of Medicine,Joseph Lunyera, Duke University School of Medicine, Benjamin Goldstein, Duke University School of Medicine,Clarissa Diamantidis, Duke University School of Medicine, Ebony Boulware, Duke University School of Medicine

Scientific Posters

Bilikis Akindele, Team Lead Clinical Research Informatics/Analytics at Duke University Health Systems

Board 01 – Towards reproducibility and quality in EHR-enabled data science – Methods and Strategy

Note coauthors: Bhargav Adagarla, Duke Clinical Research Institute, Brian McCourt, Duke Clinical Research Institute, Matthew Harker, Duke University Health System

Ursula Rogers, Senior Informaticist at Duke University School of Medicine

Board 40 – Data Management Considerations using Electronic Health Record (EHR) Clinical Notes

Note coauthors: Shelley Rusincovitch, Duke University, Allison Dunning, Duke Clinical Research Institute, Ryan Craig, Duke Health Technology Systems

Zhecheng Sheng, Duke University School of Medicine

Board 42 – Analyzing the association of time-varying vital signs with in-hospital mortality & ICU transfer.

Note co-authors: Armando Bedoya, School of Medicine, Duke University, Cara O’Brien, School of Medicine, Duke University, Sheng Luo, School of Medicine, Duke University, Benjamin Goldstein, School of Medicine, Duke University

 Zidi Xiu, Duke University

Board 51 – Adversarial Learning in Time-to-Event Prediction

Note coauthors: Yue Liang, Duke University, Cara O’Brien, Duke University, Armando Bedoya, Duke University, Benjamin Goldstein, Duke University, Ricardo Henao, Duke University

 Zhong Huang , Duke University

Board 18 – Constructing Clinical Profiles of Rare Diseases Through Latent Dirichlet Allocation

Note co-authors: Nishant Iyengar, Duke University, James Moody, Duke University, Rachel Richesson, Duke University School of Nursing

 Lisa Eskenazi, MHA Clinical Data Operations Manager at Duke Clinical Research Institute

Board 12 – I’ve Got a Golden Ticket! How the ADAPTABLE Study Uses Invitation Codes as a Gateway for Patients to Enroll Through the ADAPTABLE Patient Portal.

Note coauthors: William S. Jones, Duke Clinical Research Institute, Bradley G. Hammill, Dr PH Duke Clinical Research Institute, Debra F. Harris, Duke Clinical Research Institute, Holly R. Robertson, PhD Duke Clinical Research Institute, Shelley Rusincovitch, MMCi Duke Forge

Yue Liang, Student at Duke University

Board 24 – Predictive Performance of Deep Learning Models using Longitudinal Electronic Health Records Data

Note coauthors: Zidi Xiu, Duke University , Cara O’Brien, Duke University, Armando Bedoya, Duke University, Ricardo Henao, Duke University, Benjamin Goldstein,PhD  Duke University