Photo of Min Jung  Kim, Ph.D.

Min Jung Kim, Ph.D.

Assistant Professor of Medicine
Academic Office Location:
Pat and Jim Calhoun Cardiology Center
UConn Health
263 Farmington Avenue
Farmington, CT 06030
Education
DegreeInstitutionMajor
B.S.Chung-Ang UniversityMathematics and Statistics
M.Sc.Pennsylvania State UniversityIndustrial Engineering with Option in Operation Research
Ph.D.Pennsylvania State UniversityIndustrial Engineering
PostdocUniversity of MarylandMechanical Engineering

Awards
Name of Award/HonorAwarding Organization
Center for Integrated Healthcare Delivery System Research FellowshipPennsylvania State University
Center for Integrated Healthcare Delivery System ScholarshipPennsylvania State University
Excellent Honors ScholarshipChung-Ang University

My research interests lie in health care system development, specifically applying statistical engineering methodologies to improve the syndromic surveillance, chronic disease monitoring, and clinical information system. Throughout my research and academic coursework, I have maintained a strong interest in how statistical engineering approaches can address challenges in the complex health care system and promote continuous improvement in the health care system. Prior research has proved that a strong background in operation research techniques (optimization, decision making, stochastic modeling, process/quality control and multivariate statistics) and system engineering (system development, system dynamics, and risk management) could be essential keys to unravel complexities in the health care system.

In particular, I currently focus on identifying the main components and interpreting the dynamics in the chronic care management system. Using data in healthcare system, it can define key variables and functions explaining between all the parts of a system. Using system analytics, it can account for how those relationships influence the behavior of the system over time. Thereby, when the system engineering is adopted in chronic disease management system, it can contribute to 1) better understanding how changes in one area will affect the function in another area within the system, 2) better predicting secondary effects stemming from the complicatedly interrelated nature of the system elements, and 3) better decision making by projecting how alternative course of changes can impact the system over time. 

Journal Articles

Book Chapters

  • Real Option-based Analysis in Pharmaceutical Partnerships for Research and Development
    Min Jung Kim Real Options in Engineering Design, Operations and Management 2010 Oct;

Abstracts

Conference Papers

  • Predicting Patients Vulnerable to Short-Term Readmission.
    Kim, M., Tabtabai S. 2019 May;
Title or AbstractTypeSponsor/EventDate/YearLocation
A Dedicated Guideline Directed Medical Therapy Clinic Improves Quality of Care and Outcomes In Patients with Heart Failure and Reduced Ejection FractionPoster2020Annual HFSA meeting
Achievement of Target Doses of Guideline-Directed Medical Therapy Prior to Cardiac Resynchronization Therapy is SuboptimOtherJournal of Cardiac Failure2019
Assessment of Cardiac Abnormalities in Sickle Cell Disease Patients Using EchocardiographOtherBlood2019
Differential impact of Apnea Hypopnea Index and Nocturnal Oxygen Desaturation on Cardiac Dysfunction in Patients with Sleep Disordered BreathingOtherJournal of the American College of the Cardiology2019
Predicting Patients Vulnerable to Short-Term ReadmissionPosterBiomedical Health Informatics2019Chicago
Development of UCONN Health Heart Failure Mobile ApplicationPoster3rd Annual UConn Center for mHealth and Social Media Conference2018Storrs, CT
Circulating Caspase-3 p17 Fragment as a Novel Marker for Cardiac Apoptosis During CardioplegiaPosterAmerican Society for Investigative Pathology Annual Meeting2018San Diego, CA
The Lower the Better-Intensive Systolic Blood Pressure Control is associated with Better Diastolic FunctionPosterConnecticut Chapter of the American College of Cardiology2017Monroe, CT
Modeling Patient Adherence Trends Using Markov ChainsTalkIndustrial and Systems Engineering Research Conference 2014Montreal, CA,
Multivariate Statistical Process Control to Monitor Hypertensive PatientsTalk13. European Network for Business and Industrial Statistics Meeting (ENBIS13)2013Ankara, Turkey
A Polynomial Regression based Framework for Constructing Longitudinal Data from Cross-Sectional Data: A Case Study using NHANES Data on Hypertensive PatientsTalk13th Biennial Symposium on Statistical Methods (CDC)2011Decatur, GA
Chronic care intervention strategiesTalk2010 Center for integrated Healthcare Delivery System Workshop2010State College, PA