Children's Hospital Informatics Program

WELCOME

The Children's Hospital Informatics Program (CHIP) is a multidisciplinary applied research and education program at Boston Children's Hospital. CHIP investigators work at the intersection of information science, healthcare and biomedical discovery, advancing the state-of-the-art in functional genomics, personalized medicine, biomedical research collaboration and public health.

Since 1995, CHIP researchers have worked to set the highest standards for patient autonomy and privacy. Our "Instrumenting the Healthcare Enterprise" initiatives focus on accelerating collaborative research across institutions, and on providing tools and services directly to patients, allowing them to be become more active, engaged participants in both their own healthcare and the broader research community.

New Website

CHIP has launched a new website

More at our Blog.

Macrobiology

There is an enormous trove of prior knowledge gleaned in the biological sciences. Macrobiology leverages this prior knowledge in the interpretation of whole physiologies (and pathologies) using empirical grounding offered by high-throughput, comprehensive measurements.

Intelligent Health Laboratory

Our group studies the application of medical informatics, computer science, epidemiology, and biostatistics to improve public health and clinical practice.

SMART Platforms the "App Store" for health

Substitutable Medical Apps, reusable technologies
A platform with substitutable apps constructed around core services is a promising approach to driving down healthcare costs, supporting standards evolution, accommodating differences in care workflow, fostering competition in the market, and accelerating innovation.

Health Map

HealthMap brings together disparate data sources to achieve a unified and comprehensive view of the current global state of infectious diseases and their effect on human and animal health. This freely available Web site integrates outbreak data of varying reliability, ranging from news sources (such as Google News) to curated personal accounts (such as ProMED) to validated official alerts (such as World Health Organization). Through an automated text processing system, the data is aggregated by disease and displayed by location for user-friendly access to the original alert. HealthMap provides a jumping-off point for real-time information on emerging infectious diseases and has particular interest for public health officials and international travelers.

Tuanalyze

TuAnalyze supports consented collection, sharing and display of biomedical and behavioral diabetes data. The application stores user-entered data in an Indivo PCHR, allowing for strict user control of data sharing and access. TuAnalyze provides a biosurveillance-derived display of live, aggregate, geo-referenced data back to the community for benchmarking and to incent ongoing engagement.

Health Information Technology for Health Care Transitions

This initiative is focused on advancing care of chronically ill youth using patient- and family-centered health information technologies. We are conducting research to refine the PCHR approach to capture information about self-care, social roles, transition readiness, health risk behaviors and psychosocial problems. Our goal is to improve the quality and safety of care systems and health as youth move from pediatric to adult internal medicine. In the CHB Diabetes Program we are developing longitudinal systems for monitoring the health of diabetes-affected adolescents over transitional periods and evaluating youth engagement with the PCHR platform and enriched PCHR supported care systems that involve case management and social network-based surveillance and reporting. This project is supported by grants from the Program on Patient Safety and Quality at Boston Children's Hospital, and by the Harvard Clinical and Translational Sciences Center (CTSC).

Computational Epidemiology Group

The Computational Epidemiology Group aims to evolve the traditional paradigm of public health practice and surveillance through innovative multi-disciplinary epidemiologic research. The overall goal is to show how emerging technologies can help clarify patterns of disease and promote public health. Our mission has materialized in a diverse set of projects that include describing the emergence of West Nile virus in New York City using satellite data, predicting patterns of Lyme disease based on climate change, analyzing patterns of influenza epidemics, finding new ways to identify problem medications using electronic medical records, understanding the geographic patterns of substance abuse, describing the impact of pollution on chronic disease, and most recently the first documented use of mobile smartphones as public health surveillance tools for both outbreak and post-marketing surveillance.

Indivo

Indivo is the original personally controlled health record (PCHR) system. A PCHR enables an individual to own and manage a complete, secure, digital copy of her health and wellness information. Indivo integrates health information across sites of care and over time.

AEGIS

Automated Epidemiologic Geotemporal Integrated Surveillance System
The AEGIS System performs automated, real-time surveillance for bioterrorism and naturally occurring outbreaks. It is the syndromic surveillance system for the Massachusetts Department of Public Health, enabling real time population health monitoring.

Biomedical Cybernetics Lab

The Biomedical Cybernetics Laboratory is an interdisciplinary program of the Harvard Medical School - Partners Healthcare Center for Personalized Genetic Medicine, affiliated with the Children's Hospital Informatics Program and the Harvard-MIT Division of Health Sciences and Technology. Our laboratory brings together researchers from computer science, engineering, artificial intelligence, epidemiology and statistics to develop novel methods for the integrated analysis of biomedical systems.

Self - Scaling Registries

The Self Scaling Registry project is an open source software platform aimed to simplify multi-institutional patient registry collaboration. Built upon existing successful open source projects i2b2 and SHRINE, the Self Scaling Registry project empowers researchers to form their own data sharing networks, manage data use, and build on top of existing datasets. Our initial deployment of this platform is supporting the CARRA network, a group of pediatric rheumatologists participating from 60 medical institutions, in forming a patient registry to be the basis for future research work, comparative effectiveness studies, and post marketing surveillance.

Computational Genomics

We are a bioinformatics group interested in understanding chromatin structure and function in a variety of systems using high-throughput sequencing techniques. We specialize in analysis of ChIP-seq and nucleosome profiling data but also work with RNA-seq, whole-genome sequencing, and other data types. We collaborate with a number of experimental labs, both in the Harvard Medical area and around the world.

Gene Partnership

TGP is the only knowledge-base powering research that has an “informed cohort” of research subjects who can actively participate in the discovery of solutions to disease. By allowing participants to be partners in their own research, we have the ability to capture more data and create powerful studies.
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