Overview
The Department of Health Information Management is at the forefront of revolutionizing health care through advanced technology and research. It encompasses a wide array of research domains, including mHealth (mobile health) and digital health, which leverage mobile and telecommunications technology to remotely deliver healthcare services and information, enhancing accessibility and efficiency.
The department's exploration into the natural language processing (NLP) of unstructured Electronic Health Records (EHRs) aims to harness critical data from clinical notes, improving patient care and supporting informed clinical decisions. Additionally, it focuses on medical imaging, utilizing machine learning and deep learning techniques to enhance the analysis of clinical images for more precise diagnoses and treatment plans. Our research is currently focusing on artificial intelligence (AI) in health and health care, aiming to transform patient care, diagnostics, treatment plans and health care management through AI algorithms and models. These efforts are complemented by the development of digital interventions, which employ digital platforms to implement therapeutic strategies for disease management and prevention.
By integrating AI, the department is not only innovating health care practices but also paving the way for a future where care is more personalized, predictive and preventive. Through its comprehensive research efforts, the department contributes significantly to the growth and evolution of health informatics, striving to improve patient outcomes and health care systems worldwide.
Research Areas
- mhealth (mobile health)
- digital health
- artificial intelligence in health and health care
- natural language processing
- medical imaging informatics
Publications
Research Opportunities
HIM Research Labs
Health and Rehabilitation Informatics (HARI) LabFaculty: Research Focuses:
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Health and Explainable AI Research Laboratory (HexAI)Faculty: Ahmad P. Tafti Research Focuses:
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Clinical Natural Language Processing and Artificial Intelligence Innovation Laboratory (PittNAIL)Faculty: Yanshan Wang Research Focuses:
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Zhou LabFaculty: Leming Zhou Research Focuses:
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Choi LabFaculty: Yong K. Choi Research Focuses:
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Prior Labs and Projects
A Curriculum for Security Assurance Health (SAHI), NSF
Investigators will develop an integrated curriculum on (SAHI) to develop multiple SAHI tracks with curriculum components focused on Healthcare IT (HIT) within the IST programs and a track focused on Healthcare Security and Privacy (HS&P) and will develop a curriculum that fosters research and doctoral students in SAHI areas.
SmartCAT: Using Smartphone to Enhance Skill Development in CBT for Child Anxiety, NIH R34
Investigators with expertise in Ecological Momentary Assessment, Cognitive Behavioral therapy, Mobile Health Technology, and Skill Acquisition & Utilization will integrate these domains in an investigation of an Ecological Momentary Intervention (SmartCAT) that may be helpful increasing skill acquisition and utilization for youth with childhood anxiety disorders.
Promoting Independence & Self-Management using mHealth (DRRP), NIDILRR, ACL-HHS
Investigators will develop and implement mobile health (mHealth) tools to support self-management and aid youth with brain and spinal anomalies (BSA) in their transition to adulthood.
From Cloud to Smartphone: Accessible and Empowering ICT-RERC, NIDILRR, ACL-HHS
The objectives of this Center are to mitigate barriers to ICT access for Persons with Disabilities (PwDs) and to harness the power of ICT to improve health and function, social participation, and employment among PwDs.
Aphasic Comprehension: Conflict Resolution and Short-Term Memory, Dept. of Veteran Affairs
Investigators will create a structural equation model to determine the relationship among conflict resolution, short-term memory, and language processing. The data is obtained from 120 participants with aphasia.
Enhanced Aural Rehabilitation for Cochlear Implant Users via Telerehab Technology, Gallaudet University
Investigators will develop a telerehab system tailored to support aural rehabilitation using the VISYTER system. This effort will include optimizing the VISYTER system for aural rehabilitation, testing audio-video synchronization under various settings, and developing techniques to improve audio-video synchronizations to support lip-reading.
Data Analytics, ICD-10, Patient Care Engagement and Leadership in HIM Initiatives, CIOX Health
To conduct research that focuses on the objectives of the CioxinnoLab which includes research on ICD-10-CM/PCS inpatient coding productivity trends over time, examining the differences in organization and management of clinical data abstraction functions in health care facilities, assess the utilization of the cancer registry across healthcare facilities from the perspective of the physician, nurse, administrator and researcher, and examine coding quality databases in order to effectively mine the
Evaluating the Effectiveness of the Acute Kidney Injury (AKI) Alert Project
This project is in collaboration with the Department of Critical Care Medicine and UPMC. The AKI alert has been developed and implemented in the initial phase and we care currently involved with monitoring and evaluating the data, refining the alert, evaluating other possible outcomes in order to detect early stages of AKI. The alert is currently utilized in the Cerner Electronic Health Record (EHR) system at UPMC.
Genomics and Personalized Medicine
The development of high-throughput biotechnologies that makes personal genomes accessible, which can then be applied into personalized medicine. In this field, the researcher develops methods, algorithms, and software programs to analyze genomic data, associate genetic information with specific diseases, and create applications to facilitate personalized health care.
Biomedical Modeling
The project involves the creation of models with multiple methods (statistical, equation-based, network-based, and agent-based modeling) to simulate the development and treatment of various diseases, especially cardiovascular disease and obesity.