NCI's Physician Data Query (PDQ®) cancer information summaries: history, editorial processes, influence, and reach.

In the National Cancer Act of 1971, the Director of the National Cancer Institute (NCI) was given a mandate to "Collect, analyze, and disseminate all data useful in the prevention, diagnosis, and treatment of cancer, including the establishment of an International Cancer Research Data Bank (ICRDB) to collect, catalog, store, and disseminate insofar as feasible the results of cancer research undertaken in any country for the use of any person involved in cancer research in any country" (National Cancer Act of 1971, S 1828, 92nd Congress, 1st Sess (1971)). In subsequent legislation, the audience for NCI's information dissemination activities was expanded to include physicians and other healthcare professionals, patients and their families, and the general public, in addition to cancer researchers. The Institute's response to these legislative requirements was to create what is now known as the Physician Data Query (PDQ®) cancer information database. From its beginnings in 1977 as a database of NCI-sponsored cancer clinical trials, PDQ has grown to include extensive information about cancer treatment, screening, prevention, supportive and palliative care, genetics, drugs, and more. Herein, we describe the history, editorial processes, influence, and global reach of one component of the PDQ database, namely its evidence-based cancer information summaries for health professionals. These summaries are widely recognized as important cancer information and education resources, and they further serve as foundational documents for the development of other cancer information products by NCI and other organizations.

The development of the Medical Literature Analysis and Retrieval System (MEDLARS).

OBJECTIVE: The research provides a chronology of the US National Library of Medicine's (NLM's) contribution to access to the world's biomedical literature through its computerization of biomedical indexes, particularly the Medical Literature Analysis and Retrieval System (MEDLARS). METHOD: Using material gathered from NLM's archives and from personal interviews with people associated with developing MEDLARS and its associated systems, the author discusses key events in the history of MEDLARS. DISCUSSION: From the development of the early mechanized bibliographic retrieval systems of the 1940s and to the beginnings of online, interactive computerized bibliographic search systems of the early 1970s chronicled here, NLM's contributions to automation and bibliographic retrieval have been extensive. CONCLUSION: As NLM's technological experience and expertise grew, innovative bibliographic storage and retrieval systems emerged. NLM's accomplishments regarding MEDLARS were cutting edge, placing the library at the forefront of incorporating mechanization and technologies into medical information systems.

Nurses and PDQ: what's in it for you?

In March 1989, the National Cancer Institute's Physician Data Query (PDQ) celebrated its fifth year. PDQ, a computerized cancer information database, was created to enhance the communication and application of cancer research data to the oncology community. Because of the variety and currency of the information contained within the system, it can be an extremely valuable resource for cancer nurses and patients. Future enhancements of the system will provide nurses with even more material for patient teaching and self-learning. This article discusses the development of PDQ, reviews its content and objectives, and identifies its possible uses for oncology nurses practicing in a variety of patient care settings.

The physician data query (PDQ) cancer information system.

PDQ is an online database that provides information about the prognosis and treatment of all major types of cancer. It represents a major effort by the NCI to communicate advances in cancer treatment using computer technology, and serves as a major component of the Institute's program to reduce cancer mortality nationwide. PDQ utilizes a modern large-scale computer to provide processing speed, a general purpose database management system to provide retrieval and display functions, and commercial telecommunication networks to provide online access to up-to-date information on cancer treatment. A series of user-friendly menus allow searching, browsing, and displaying without having to learn a specialized search language. PDQ is accessible through the National Library of Medicine's computer system via a computer terminal or personal computer and is available to the medical community at over 6,000 medical libraries and centers and through individual access codes. PDQ is also available as an online database under a special license agreement with NCI through two medical information systems produced by commercial database vendors: BRS/Saunders' COLLEAGUE Mead Data Central's MEDIS, and Telmed, a Swiss database.

The Physician Data Query (PDQ) cancer information system.

PDQ is an online database that provides information about the prognosis and treatment of all major types of cancer. It represents a major effort by the NCI to communicate advances in cancer treatment using computer technology, and serves as a major component of the Institute's program to reduce cancer mortality nationwide. PDQ utilizes a modern large-scale computer to provide processing speed, a general purpose database management system to provide retrieval and display functions, and commercial telecommunication networks to provide online access to up-to-date information on cancer treatment. A series of user-friendly menus allow searching, browsing, and displaying without having to learn a specialized search language. PDQ is accessible through the National Library of Medicine's computer system via a computer terminal or personal computer and is available to the medical community at over 2000 medical libraries and centers and through individual access codes. PDQ is also available as an online database under a special license agreement with NCI through two medical information systems produced by commercial database vendors: BRS/Saunders' COLLEAGUE and Mead Data Central's MEDIS.

Automatic query formulations in information retrieval.

Modern information retrieval systems are designed to supply relevant information in response to requests received from the user population. In most retrieval environments the search requests consist of keywords, or index terms, interrelated by appropriate Boolean operators. Since it is difficult for untrained users to generate effective Boolean search requests, trained search intermediaries are normally used to translate original statements of user need into useful Boolean search formulations. Methods are introduced in this study which reduce the role of the search intermediaries by making it possible to generate Boolean search formulations completely automatically from natural language statements provided by the system patrons. Frequency considerations are used automatically to generate appropriate term combinations as well as Boolean connectives relating the terms. Methods are covered to produce automatic query formulations both in a standard Boolean logic system, as well as in an extended Boolean system in which the strict interpretation of the connectives is relaxed. Experimental results are supplied to evaluate the effectiveness of the automatic query formulation process, and methods are described for applying the automatic query formulation process in practice.