Brief Bio

Dr. Kim is Associate Professor at the Duke University School of Nursing. Dr. Kim received a PhD in Health Informatics from the University of Minnesota at Twin Cities, completed a post-doctoral fellowship in the Decision Systems Group at the Brigham and Women’s Hospital in Boston. After the post-doctoral training, she joined the Clinical Informatics Research and Development group of Partner’s Healthcare as a nurse informatician, where she was heavily involved in analyzing and designing nursing documentation system. Dr. Kim came to Duke from UC San Diego’s School of Medicine, Division of Biomedical Informatics where she was an associate professor. She was also associate director of the T15 training program on biomedical informatics funded through the National Library of Medicine. Her research interests in data standardization, consumer informatics, and nursing decision support complement the school’s research areas of excellence. The overall goal of Dr. Kim’s research is to facilitate the reuse of biomedical data via standardization and effective representations. Data standardization encompasses standardized terminologies, metadata generation and information modeling, which are critical foundations for any informatics solutions that deal with biomedical data. Dr. Kim’s work has particular focuses on the reuse of clinical data to support patient care and she have demonstrated the impact of data reuse by developing prototype nursing clinical decision support tools and algorithms for acuity estimation, pressure ulcer risk assessment, and pain assessment. Dr. Kim is also experienced in developing infrastructure for data standardization to support big data analyses through two NIH funded projects. In these projects, Dr. Kim led development of a data standardization tool and standardization of the metadata extracted from various biomedical datasets. Dr. Kim’s data standardization and representation work also expands to the area of consumer health informatics, Dr. Kim’s research in consumer focus data representation includes use of pictograms in health communication and assessing/improving the readability of various health texts. Dr. Kim’s latest consumer oriented informatics research aims to empower patients by providing a means to indicate their preference on sharing health data for research. Presenting a wide range of health data in such a way that help patients determine the level of data sharing is also critical component in this project.

Academic Program Affiliations

Master of Science in Nursing Program
PhD in Nursing Program

Education

PhD	University of Minnesota at Twin Cities
MPH	Seoul National University
BSN	Seoul National University

Research Interests

Data standardization Nursing decision support system Consumer informatics Health disparity

Awards and Honors

• 2017 Daniel T. O’Connor Memorial Award, UC San Diego, CTRI

• 2012 Best poster award, Healthcare Informatics, Imaging and Systems Biology

• 2010 Harriet H. Werley Award, American Medical Informatics Association

• 2007 Working Group Student Award, American Medical Informatics Association Nursing Informatics

Areas of Expertise

• Standardized data representation

Representative Publications

• 2017 -- Pubmed # 28430977 Zong, N., Kim, H., Ngo, V., Harismendy, O. Deep mining heterogeneous networks of biomedical linked data to predict novel drug-target associations. Bioinformatics. August 1, 2017; 33(15); 2337-2344

• 2017 -- Pubmed # 28585923 Sansone, S., Gonzalez-Beltran, A., Rocca-Serra, P., Alter, G., Grethe, J. S., Xu, H., Fore, I. M., Lyle, J., Gururaj, A. E., Chen, X., Kim, H., Zong, N., Li, Y., Liu, R., Ozyurt, I. B., Ohno-Machado, L. DATS, the data tag suite to enable discoverability of datasets. Sci Data. June 6, 2017; 4 170059 PMCID: PMC5460592

• 2017 -- Pubmed # 28546571 Ohno-Machado, L., Sansone, S., Alter, G., Fore, I., Grethe, J., Xu, H., Gonzalez-Beltran, A., Rocca-Serra, P., Gururaj, A. E., Bell, E., Soysal, E., Zong, N., Kim, H. Finding useful data across multiple biomedical data repositories using DataMed. Nat Genet. May 26, 2017; 49(6); 816-819

• 2017 -- Pubmed # 28207198 Sitapati, A., Kim, H., Berkovich, B., Marmor, R., Singh, S., El-Kareh, R., Clay, B., Ohno-Machado, L. Integrated precision medicine: the role of electronic health records in delivering personalized treatment. Wiley Interdiscip Rev Syst Biol Med. May 1, 2017; 9(3); PMCID: PMC5400726

• 2017 -- Pubmed # 27589942 Kim, H., Bell, E., Kim, J., Sitapati, A., Ramsdell, J., Farcas, C., Friedman, D., Feupe, S. F., Ohno-Machado, L. iCONCUR: informed consent for clinical data and bio-sample use for research. J Am Med Inform Assoc. March 1, 2017; 24(2); 380-387 PMCID: PMC5391727

Grant Funding (selected)

• Informed Consent for Clinical Data and Bio-sample Use for Research  
  NIH/NHGRI
  R01HG008802-02
  09/2015-06/2018
  Project Goal: The goal of this project is to incorporate genetic test data produced at the laboratories outside UCSD Medical center to the clinical data warehouse at UCSD to promote reuse of the genetic test data for research and patient treatment.

• bioCADDIE: biomedical and healthcare data discovery and indexing engine center  
  NIH/NIAID
  U24AI117966-05
  09/2014-08/2017
  Role: Co-I
  Project Goal: The goal of this project is to promote the development of realistic, minimal, and user-friendly metadata specifications and annotation for biomedical and healthcare data and corresponding tools for automated indexing to facilitate reuse of biomedical big data.

• Phenotype discovery NHLBI genomic studies (PhD)  
  NIH/NHLBI
  UH3HL108785
  07/2011-09/2015
  Project Goal: The goal of this project is to develop a defined metadata model and build an integrated system that enables researchers to query and find genomic studies of interest in public repositories as well as upload new data into our database (sdGaP), in a standardized manner.

• iDASH – integrating data for analysis, anonymization, and sharing  
  NLH/NHLBI
  HL108460
  09/2010-06/2017
  Role: Co-I
  Project Goal: The goal of this project is to create IDASH, a national center for biomedical computing that will develop new algorithms, open-source tools, computational infrastructure and services that will enable biomedical and behavioral researchers nationwide to integrate Data for Analysis, Anonymization, and Sharing, IDASH will address fundamental challenges to research progress by providing a secure, privacy-preserving environment in which researchers can analyze genomic, transcriptomic and highly annotated phenotypic data.

• SCANNER – scalable national network for effectiveness research  
  AHRQ
  R01HS19913
  09/2010-09/2013
  Role: CO-I
  Project Goal: The goal of this project is to develop a distributed network infrastructure for comparative effectiveness research that provides flexibility to participant sites in the means for data sharing.

• Global health knowledge collective – a collaborative toolkit for global health  
  NIH/FIC, NIH/OD
  R24TW008805
  09/2010-08/2012
  Role: CO-I
  Project Goal: The goal of this project is to promote efficient health care services in resource-poor settings in low-to-middle income countries with knowledge collectives implemented on low cost computing device.

• San Diego biomedical informatics education & research  
  NIH/NLM
  T15LM11271
  07/2012-06/2021
  Role: Core faculty (associate director)
  Project Goal: The biomedical informatics training program at UC San Diego provides biomedical informatics training and research opportunities through pre-doctoral and post-doctoral levels.