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Massachusetts Institute of Technology

Improved access to large medical databases for clinical research and quality improvement

Abstract

dc:description.abstract

Computerized medical databases are now commonplace in healthcare environments. Information is routinely stored for each clinical encounter, be it an inpatient, outpatient, telephone, or even computer-based interaction. In the past, the vast majority of this data concerned the demographic and financial details of the encounter; however, more and more clinically relevant content is now being collected. Along with this increased amount of available data has come promises of improve patient care, easier clinical research studies, and enhanced efficiency and quality of healthcare institutions. In part, these promises have been kept; there are examples in the literature and in real-world medical environments in which care has improved through the use of data stores. The ease by which this information is accessed, displayed, and interpreted remains a significant problem, however. In addition, current data retrieval methods do not foster user "exploration" of the data, and thus limit its potential. The specific aim of this thesis has been the development of a new computer application ("Goldminer"), which provides for enhanced data retrieval, interpretation, and analysis by authorized personnel at large medical institutions. This application also provides for patient data privacy; unique patient identifiers are not disclosed in information requests, and routine logs of Goldminer's usage are kept for analysis by hospital administrative staff. The methods used in this work included the integration and mapping of disparate data sources to one central database, followed by the implementation of a group of simple "atomic" queries, which insulate users from the underlying database complexity. These queries include both population-based and temporal predicates, and are combinable to allow for arbitrarily complex data retrieval. All data have personal identifiers removed before presentation to the user. Goldminer will be deployed within the hospital Intranet as a web-based "point and click" tool, allowing for efficient data analysis and exploration by non-programming healthcare personnel.

Degree

thesis:*
Department dc:contributor.department
Whitaker College of Health Sciences and Technology
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
1999

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Nigrin, Daniel J. (Daniel Joseph), 1965-
Advisor dc:contributor.advisor
  • Isaac S. Kohane and Peter Szolovits.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/9740
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/9740

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Nigrin, Daniel J. (Daniel Joseph), 1965-. Improved access to large medical databases for clinical research and quality improvement. Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/9740