A Context-Sensitive Teleconsultation Infrastructure
Project Number1R01EB002247-01
Contact PI/Project LeaderKANGARLOO, HOOSHANG
Awardee OrganizationUNIVERSITY OF CALIFORNIA LOS ANGELES
Description
Abstract Text
DESCRIPTION (provided by applicant): Consultation with appropriate specialists improves the quality of healthcare, particularly in patients with complicated cases or chronic illnesses. And for the majority of such patients, specialists use imaging studies (e.g., MR, CT) to objectively document the disease process (e.g., a cancer patient on chemotherapy). However, specialists are generally not available in all communities, tending to be concentrated in academic/specialty centers. Thus, to facilitate the routine use of teleconsultations for patients when specialists are not locally present: 1) the images captured to document the patient's condition must be incorporated into the medical record to enable proper review; and 2) the remote consultant should only receive pertinent parts of the medical record to streamline the consultation process. This proposal is focused on developing and testing a "context-sensitive" telehealth infrastructure based on: 1) automated incorporation of clinical context (patient presentation and referring physician hypothesis) to focus the consultation process; 2) a knowledge-base derived from data mining of natural language processing (NLP) results, mapping patient presentation to select an appropriate imaging study based on anatomical region and imaging parameters; and 3) automated selection of key anatomical structures in the acquired imaging study through the use of a contrast-customizable atlas and rigid body/deformable registration algorithms. Collectively, these technologies will allow context-sensitive, automated summarization of medical records for telehealth in a real-world environment. The proposed technologies will be implemented for neurological and musculoskeletal domains, two areas that are MR imaging intensive.
Technical evaluation will be performed with experts serving as the reference standard and will focus on measuring: 1) the accuracy of the corpus based, NLP-guided knowledge-base in selecting relevant anatomical structures; and 2) the accuracy of anatomical structure delineation using the customizable atlas registration methods. Clinical evaluation will be conducted in a real-world teleconsultation environment in a before/after study design using two performance metrics: 1) the time required for consultations; and 2) the effect on the quality of the consultations.
Public Health Relevance Statement
Data not available.
NIH Spending Category
No NIH Spending Category available.
Project Terms
anatomyclinical researchcomputer assisted diagnosiscomputer assisted medical decision makingcomputer assisted patient carecomputer data analysiscomputer graphics /printingcomputer system design /evaluationdiagnosis quality /standardhealth care qualityhealth care referral /consultationhuman dataimage enhancementimage processingmagnetic resonance imagingmusculoskeletal disordernervous system disorderstatistics /biometrytelemedicine
National Institute of Biomedical Imaging and Bioengineering
CFDA Code
286
DUNS Number
092530369
UEI
RN64EPNH8JC6
Project Start Date
30-September-2003
Project End Date
31-July-2008
Budget Start Date
30-September-2003
Budget End Date
31-August-2004
Project Funding Information for 2003
Total Funding
$383,268
Direct Costs
$314,797
Indirect Costs
$68,471
Year
Funding IC
FY Total Cost by IC
2003
National Institute of Biomedical Imaging and Bioengineering
$383,268
Year
Funding IC
FY Total Cost by IC
Sub Projects
No Sub Projects information available for 1R01EB002247-01
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Outcomes
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No Outcomes available for 1R01EB002247-01
Clinical Studies
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