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School of Health and
Rehabilitation Sciences

Overview

As the demand for quality health care rises, so does the need for accurate and reliable patient data. Pitt’s Department of Health Information Management is a leader in providing students with high quality education and immersive internships that prepare them to meet future data management challenges across the ever-changing landscape of health care.

Our faculty are committed to developing the next generation of health information professionals. They serve at the highest levels of regional, national and international HIM professional associations and conduct research that advances the quality of care for patients. Collaboration with other health care disciplines allows them to successfully research and develop new tools and technologies, including mobile health applications, classification systems and other data management solutions.

Outcomes

The Master of Science in Health Informatics program is in Candidacy Status, pending accreditation review by the Commission on Accreditation for Health Informatics and Information Management Education (CAHIIM).

This data was collected for the time period of September 1, 2023 – August 31, 2024.

  • Average time to degree completion: 16-24 months (depending on full-time or part-time enrollment status)
  • Percent employed post-program completion: 94.3% employed post-graduation
  • Program graduation rate: 98.7%
  • Retention Rate: 91.9%
  • Student Satisfaction: Based on an optional Student Satisfaction Survey, 95.2% of respondents would recommend the MSHI program to others.

The HI (Health Informatics) baccalaureate degree program is in Candidacy Status, pending accreditation review by the Commission on Accreditation for Health Informatics and Information Management Education (CAHIIM).

All inquiries about the program’s accreditation status should be directed by mail to CAHIIM, 200 East Randolph Street, Suite 5100, Chicago, IL, 60601; by phone at (312) 235-3255; or by email at info@cahiim.org.

For the class of 2024:

  • Graduation Rate: 100%
  • Retention Rate: 100%
  • Students Employed or Continuing Education 6 months post-graduation: 94%

Programs

Health Informatics (MS)

On-campus, Online

Duration:

Full-time:
12-16 months
(3-4 terms, including 1 summer term)

Part-time:
2 years
(6 terms, including 2 summer terms)

Program Start:

On-Campus
Fall start (August)

Online
Fall start (August)
Spring start (January)
Summer start (May)

Application Closes:

On-campus:
August 1, 2025
The deadline for international student applications (F-1 students) is May 1.

Online:

  • Summer 2025 term – April 20, 2025
  • Fall 2025 term – August 20, 2025
  • Spring 2026 term – December 10, 2025

Health Informatics (BS)

On-campus

Duration:

2 years
(4 terms)

Program Start:

Fall term (August)

Application Closes:

March 1, 2025

Application extended through August 1, 2025

Scholarships

AI Summer School

Students sitting in a computer lab with desktop computers, listening to someone give a lecture.

What is this program?

Our Artificial Intelligence (AI) Summer School organized by the Pitt HexAI Research Laboratory and in collaboration with the Computational Pathology & AI Center of Excellence (CPACE), the School of Health and Rehabilitation Sciences and IEEE Computer Society, aims to provide a stimulating unique, and all expense paid opportunity to dive into the fascinating world of AI and its application in medical imaging informatics.

Medical imaging informatics leverages AI-driven computer vision to analyze and interpret medical images for better diagnosis and treatment. A key area of focus is object detection and localization, where AI systems identify and locate relevant features within medical images.

This program was established in 2023 and occurs annually.

Who is this for?

The program hosts 35 students. There are 20 seats for in-person and 15 seats available to attend online via Zoom.

This program is available to students in grades 11 and 12 (high school) and community college students with a keen interest in advanced technology, health care informatics and artificial intelligence (AI). Students from all backgrounds and levels of experience are encouraged to apply.

Students must be familiar with Basic Python Programming. If not familiar with this prerequisite, you can learn more by following the link here.

Student Testimonials

Read what past participants have to say about their experience at the AI Summer School.

“Everything was just so interesting and I feel like I have found something new that I might want pursue in the future, and I think Dr. Tafti and all the other instructors were very helpful and really just facilitated like the entire learning process. And I found that AI and all these really hard things that I always thought were really complicated were actually quite easy to to understand.” – Katherine

“After coming here I learned a lot as I didn’t know a huge lot about AI before coming here, but after coming here know I have learned about like machine learning and like deep learning, the differences between that and I just feel like AI is such a big like broad topic that can really be implemented into anything.” – Sophia

“I was so glad that I signed up because there is so many opportunities and so much to learn from this program, and you can meet a lot of guest speakers and we have a great teacher Dr. Tafti and he will teach you so much about AI and medical imaging.” – Zoe

 

When and where is the program?

The AI Summer School is a week-long program. It starts on Monday, June 9 and goes to Friday, June 13, 2025.

Every day, the registered students will meet from 9 a.m. – 3 p.m. in Forbes Tower at the University of Pittsburgh on Main Campus in Pittsburgh, PA, or online.

What will I do?

This program will dive into these techniques, teaching participants how to apply them using Python programming. Through lectures, hands-on exercises and collaborative projects, attendees will gain practical skills in AI-powered medical image analysis, preparing them to tackle real-world challenges in the field.

  • Begin with foundational concepts, including an introduction to AI, computer vision and digital image operations, followed by hands-on practice with Python and Google Colab.
  • Explore advanced topics such as deep learning, convolutional neural networks (CNNs) and object detection techniques like “You-Only-Look-Once” (YOLO) and “Single-Shot Detector (SSD).
  • Attend lectures from esteemed University of Pittsburgh faculty
  • Participate in hands-on coding exercises
  • Listen to guest speakers and talks from AI researchers in academia and industry
  • Gain practical experience in medical image annotation, image filtering and object localization, utilizing tools like PyTorch, ITK-SNAP and Liner.ai

At the end of the week, students will cap their experience with a collaborative team project, where students apply their knowledge to real-world challenges, followed by team presentations.

Certification: Upon successful completion of the summer school, students will receive a certificate of participation, recognizing their dedication and achievement in AI-powered medical imaging informatics.

Join us!
Registration opens soon.

Thank you to all our AI Summer School Alumni!

  • Alan
  • Alexandra
  • Airah
  • Amber
  • Amulya
  • Arthur
  • Bhavika
  • Chuhan
  • Darren
  • Delia
  • Ethan
  • Fae
  • Katherine
  • Leah
  • Neil
  • Rachel
  • Samuel
  • Saharsha
  • Saniya
  • Sara
  • Sohan
  • Sophia
  • Sophia
  • Thomas
  • Ziqian
  • Zoe

Research

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
  • Clinical Decision Support System utilizing the electronic health record
  • Development of Clinical Alert systems
  • Personal Health Record development in mobile applications
  • Data Analytics in healthcare
  • Development of best practices in Privacy and Security in telehealth

Active Research Labs and Projects

 

Past 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.

People

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Mervat Abdelhak

Emeritus Professor

abdelhak@pitt.edu
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Turki Alotaibi

PhD Student

tsa48@pitt.edu
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Bayu Aryoyudanta

PhD Student

baa181@pitt.edu
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Page Babbit

Adjunct Assistant Professor

pbabbit@pitt.edu
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Bailey Cassidy

Administrative Coordinator

bmc205@pitt.edu
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Yong Choi

Assistant Professor

yong.choi@pitt.edu
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Taylor Cronauer

Assistant Professor, Clinical Education Coordinator

tah241@pitt.edu
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Dilhari DeAlmeida

Vice Chair for Education, Director of the Health Informatics (BS) Program and Associate Professor

drd7@pitt.edu
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Made Dhanar Indhira Yoga

Web and Mobile Programmer

made.yoga@pitt.edu
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Ashley Gruszkowski

Adjunct Instructor

ang258@pitt.edu
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Haomin Hu

Research Scientist

hah90@pitt.edu
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Firdaus Indradharmaya

PhD Student

fai14@pitt.edu
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Rajendra Khanal

Adjunct Faculty

rak153@pitt.edu
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Min Gu Kwak

Machine Learning Research Scientist

mik414@pitt.edu
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Tania Lyon

Adjunct Instructor

tlyon@pitt.edu
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Gina McKernan

Assistant Director of Data Science at HERL

gina.mckernan@pitt.edu
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Steve Moeini

Adjunct Instructor

ssm70@pitt.edu
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Samantha Olsen

Academic Programs Administrator

smo73@pitt.edu
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Ryan Osal

PhD Student

rbo8@pitt.edu
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Suzanne Paone

Adjunct Assistant Professor

spaone@pitt.edu
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Bambang Parmanto

Chair for the Department, Professor

parmanto@pitt.edu
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Kimberly Peterson

Assistant Professor

kap141@pitt.edu
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Vayu Putraadinatha

PhD Student

vap93@pitt.edu
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Andi Saptono

Assistant Professor

ans38@pitt.edu
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Agus Setiawan

Research Scientist

made.agus@pitt.edu
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Ahmad Tafti

Director of the Pitt HexAI Lab, Assistant Professor

tafti.ahmad@pitt.edu
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William Thomson

Adjunct Instructor

wrt1@pitt.edu
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Ed Tony

Adjunct Instructor

ent33@pitt.edu
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August Turano

Adjunct Associate Professor

amt18@pitt.edu
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Juliana Vazquez

Adjunct Instructor

jmv111@pitt.edu
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Ann Vinski

Department and Financial Administrator

anv60@pitt.edu
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Yanshan Wang

Vice Chair for Research, Assistant Professor

yanshan.wang@pitt.edu
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Valerie Watzlaf

Emeritus Professor

valgeo@pitt.edu
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Michael Westfall

Adjunct Instructor

wcm23@pitt.edu
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Justin A. Wetzel

Adjunct Instructor

jaw451@pitt.edu
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Xizhi Wu

PhD Student

xiw183@pitt.edu
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Yi Xu

PhD Student

yix95@pitt.edu
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Maria Yuliana

PhD Student

mgy9@pitt.edu
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Leming Zhou

Program Director of Master of Science in Health Informatics (MSHI), Associate Professor

lzhou1@pitt.edu
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Drake “Yuxuan” Zhou

PhD Student

yuz211@pitt.edu

Student Groups

SHRS Affinity Groups
SHRS Student Advisory Board
Health Informatics Student Association
Health Informatics Graduate Society
Interprofessional Studies Student Group

Resources

Current Student Hub

Students can find access to program and school materials in the Current Student Resource Hub. Pitt Passport is required.

Current Students can also find answers to commonly asked questions and connect with valuable resources and contacts. This resource helps students locate academic guidance, professional development, or support for each individual’s wellbeing including things like counseling or study resources.

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