Data Science and Analytics
Data science seeks to gain useful insights from diverse data sets by employing a range of computational analytics and visualization techniques. As part of the Quantitative Science pillar at Stanley Manne Children’s Research Institute, our team of data scientists and report analysts work closely with data engineers and informatics analysts to support innovative pediatric research across Manne Research Institute. Our team brings a rich variety of expertise, including physiological data analytics, machine learning (ML) and artificial intelligence (AI), predictive analytics, remote patient monitoring analytics, natural language processing (NLP), data fusion, and comprehensive support for big data analytics. We specialize in utilizing advanced analytics tools such as Python, MATLAB, R, Databricks and Spark, coupled with sophisticated visualization techniques to elucidate complex biological and clinical phenomena.
Core Services
- Consultation: We love to brainstorm with researchers and provide education about advanced analytical and computational methods. Consultations are free
- Project Services: Our team is also available for well-defined, discrete analytics projects. These services are billed at our hourly rate.
- Grant Development: We encourage researchers to develop a close collaboration early in the process of research design and proposal development. Assuming funded inclusion of our team members or services in the ultimate proposal, these services are free.
Specialty Services
Research data requests involve pulling structured data from various sources, but most commonly from Epic, the electronic health record we use at Lurie Children’s. Our reporting team will work with you to define your query design and pull the data.
Please note you must have an approved IRB to pull any data for a research project.
We provide up to 20 hours of research data request work at no cost. Anything over 20 hours requires funding or resubmitting a request.
Leveraging a rich historical database of critical care bedside monitor data to uncover vital insights into patient health and disease progression. Our data includes 10+ years of continuous raw waveforms, vitals, alarms from Lurie Children’s PICU, NICU, CICU and some NICU beds at Northwestern Medicine's Prentice Women’s Hospital.
Analyzing visible light and other sensor arrays, including video and volumetric techniques that can be used to enrich discrete clinical data for predictive modeling.
Developing and deploying ML models for predicting clinical (and operational) outcomes within the EHR
Employing remote health (and environmental) data to enhance patient monitoring and care delivery.
Extracting and analyzing of valuable information from unstructured text within medical records, literature, and patient feedback using both traditional NLP techniques and advanced large language models
Providing infrastructure and expertise to manage and analyze large-scale healthcare data sets.
Utilizing state-of-the-art analytics tools (Python, MATLAB, R, Spark) for in-depth data analysis and modeling.
Creating intuitive and interactive visual representations of complex data sets to facilitate understanding and decision-making.
Quick Links
Request Services
Please complete the Quantitative Science Service Request form.
Service Rates
View details on our rates for fiscal year 2025.
Contact Us
For help, please email Quantsci@luriechildrens.org.
Our Team
Kyle Honegger, PhD
Associate Director, Data Science
Latasha A. Daniels, MSW, MA
Research Data Analyst Lead
Xavieria "Vera" Vasser, MPH
Research Data Analyst III
Alexa Mendoza, MS
Research Data Analyst II
Ope Blackburn, MS
Research Data Analyst II