Distributed, Modular Grid Software for Management and Exploration of Data in Patient-Centric Healthcare IT

Andrew Hart (NASA Jet Propulsion Laboratory), David Kale (Children's Hospital Los Angeles), Heather Kincaid (NASA Jet Propulsion Laboratory)
Location: F151
Average rating: ***..
(3.75, 4 ratings)


This presentation will discuss past and present work by engineers from the NASA Jet Propulsion Lab (JPL) to apply their open source Object Oriented Data Technology (OODT) to health care domains. Andrew Hart of JPL will give a 30 minute talk that focuses on the technology of OODT and introduces two distinct applications of OODT to health care: the Early Detection Research Network, a collaboration with the National Cancer Institute (NCI), for sharing of cancer biomarker data; and ongoing work with the Laura P. and Leland K. Whittier Virtual Pediatric Intensive Care Unit (Whittier VPICU) at Children’s Hospital Los Angeles (CHLA) to create a grid-based data management system for intensive care data. After the talk, Heather Kincaid of JPL and David Kale of CHLA will join Andrew for a 15 minute question-and-answer panel about these projects.

The talk will follow this rough outline:

  • Lay out the challenges of managing health data, for research and decision support (proprietary schema, fragmented across multiple stores, new data added continuously)
  • Introduction to JPL’s OODT
  • Fundamental technologies and strategies of OODT framework and paradigm
  • Brief overview of EDRN, a successful and mature deployment of OODT to the problem of sharing biomarker data nationally
  • More detailed description of ongoing OODT deployment at CHLA, including comprehensive ontology and national data-sharing network involving multiple PICUs
  • Q&A

Importance of our project

Existing health care data standards are often proprietary, complex, or designed with billing, not research or sharing, in mind. There are also a variety of efforts underway to make health care data more portable, but most of these efforts focus on personal health care records. These efforts are important and valuable, but they do not address the issue of making massive stores of granular clinical data easier to share and analyze in clinical and research settings. Our work is focused on this latter issue, with the goal of enabling the next generation of data-driven decision support tools by combining data from disparate data sources and across multiple institutions. The pediatric intensive care unit (PICU) is the perfect setting for this, as PICUs have a higher rate of adoption of electronic health records (EHRs) and information systems and are used to collaborating on a national level.

Extended abstract for our project

Modern health care information is highly heterogeneous, distributed, and difficult to leverage in downstream analyses that are critical to quality of patient care, including diagnosis, treatment, and outcome prediction. There are many data types to deal with (medical flowsheets, free text notes, lab results, measurements recorded by clinicians and automatically captured by instruments, waveforms) and a variety of competing standards and formats for organizing and transmitting this data (HL7, SNOWMED, ICD-9, UMLS) – not to mention proprietary and vendor-specific stores. The information landscape is growing at a rapid pace, but medical informatics nevertheless lags far behind other domains in its ability to leverage massive amounts of data to improve service and build effective data-driven tools. One of the largest obstacles to a medical information revolution is inaccessible data locked in proprietary silos, unavailable to clinicians, researchers, and information systems alike. Any progress will require that this information be unlocked from independent systems that collect and manage it.

NASA’s Jet Propulsion Laboratory (JPL) and the Whittier Virtual Pediatric Intensive Care Unit (Whittier VPICU) group at Children’s Hospital Los Angeles have been collaborating since 2003 in the development of open source grid software for the description, organization, management, sharing, and analysis of highly granular data from pediatric intensive care units (PICUs). We are leveraging one of NASA’s flagship grid software technologies, the Object Oriented Data Technology (OODT) framework, to assist in this regard. OODT is hosted at the Apache Software Foundation (ASF) and is a podling within the Apache Incubator. OODT provides a set of loosely coupled components for data capture, discovery, access, and distribution that can be instantiated and connected via modern web protocols and data formats (REST, RDF, etc.) for a particular deployment in a domain. The OODT framework enables CHLA clinicians, researchers, and software to access large amounts of data from a variety of proprietary sources (e.g., hospital-wide EHR systems, bedside monitors, unit-specific applications, homegrown databases) in a unified manner and can be extended readily to enable sharing of data between institutions.

Besides OODT, our project plans to utilize other open source software, including search technologies from Apache Lucene (Solr, Tika, etc.), and common platforms (Ubuntu, Redhat, etc.) as a means for building reliable, value-added software at low cost. We also have begun development of a common semantic architecture for describing similar data from disparate sources, and we plan to continue expanding this into a comprehensive ontology for all PICU clinical data and to share it as a free, open standard.

Our long-term goal is to construct a national distributed data-sharing network to drive the next generation of research into data-driven decision support tools and comparative effectiveness and outcomes analysis. Whittier VPICU and JPL both have experience in building such national collaborative networks: CHLA helped to develop a network of over 80 PICUs that share limited datasets for performance evaluation; JPL has used OODT to construct a variety of scientific data sharing networks, including the National Cancer Institute’s Early Detection Research Network (EDRN).

In this talk, we will discuss the current state of OODT and its successful deployment in projects such as EDRN, the motivation for its use as a means of unlocking and unifying health data at CHLA and across other institutions, and our experiences in leveraging open source software to provide a foundation for building advanced data-driven clinical decision support systems to improve the quality of pediatric intensive care going forward.

Listen to a podcast interview with Chris Mattmann about objected-oriented data technology (OODT) and health IT on O’Reilly Radar.

Photo of Andrew Hart

Andrew Hart

NASA Jet Propulsion Laboratory

Andrew is a staff software engineer at the NASA Jet Propulsion Laboratory (JPL) where he works in the Data Management Systems and Technologies group. He brings his computer science background and creative talents to the design and development of data management components and web interfaces for a wide range of projects including an informatics infrastructure for the National Cancer Institute’s Early Detection Research Network (EDRN), data modeling and architectural support for the Laura P. and Leland K. Whittier Virtual Pediatric Intensive Care Unit (Whittier VPICU) at Children’s Hospital Los Angeles, and web services for JPL’s Airborne Cloud Computing Environment (ACCE). He is also an active contributor to the Object Oriented Data Technology (OODT) project currently incubating at the Apache Software Foundation.

Photo of David Kale

David Kale

Children's Hospital Los Angeles

Dave is a research engineer in the Laura P. and Leland K. Whittier Virtual Pediatric Intensive Care Unit (Whittier VPICU) group at Children’s Hospital Los Angeles, where he brings to bear his background in computer science and artificial intelligence to develop next-generation clinical decision support systems that are data-driven, patient-centered, and personalized. He recently became a contributor to JPL’s Object Oriented Data Technology (OODT) as a part of the Apache Incubator.

Heather Kincaid

NASA Jet Propulsion Laboratory

Heather works for Northup Grumman Corporation as a consultant and operations lead for the Early Detection Research Network (EDRN) Informatics Center at the Jet Propulsion Laboratory. In this capacity, she is responsible for working with the Principal Investigators and the Data Management and Coordinating Center to annotate and curate the data acquired from validation studies of cancer biomarkers. Heather works with the software development team using the EDRN Knowledge Environment and associated tools to build and link the EDRN results into a distributed, semantically-linked database. Prior to arriving at JPL in 2007, Heather worked as the IT Manager for the Data Management and Coordinating Center of the EDRN at the Fred Hutchinson Cancer Research Center.

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