The Chronus II temporal database mediator

Proceedings / the ... Annual Symposium on Computer Application [sic] in Medical Care. Symposium on Computer Applications in Medical Care, 1992

We are developing a database implementation to support temporal data management for the T-HELPER physician workstation, an advice system for protocol-based care of patients who have HIV disease. To understand the requirements for the temporal database, we have analyzed the types of temporal predicates found in clinical-trial protocols. We extend the standard relational data model in three ways to support these querying requirements. First, we incorporate timestamps into the two-dimensional relational table to store the temporal dimension of both instant- and interval-based data. Second, we develop a set of operations on timepoints and intervals to manipulate timestamped data. Third, we modify the relational query language SQL so that its underlying algebra supports the specified operations on timestamps in relational tables. We show that our temporal extension to SQL meets the temporal data-management needs of protocol-directed decision support.

Proceedings : a conference of the American Medical Informatics Association / ... AMIA Annual Fall Symposium. AMIA Fall Symposium, 1996

Due to the ubiquitous and special nature of time, specially in clinical datábases there's the need of particular temporal data and operators. In this paper we describe S-WATCH-QL (Structured Watch Query Language), a temporal extension of SQL, the widespread query language based on the relational model. S-WATCH-QL extends the well-known SQL by the addition of: a) temporal data types that allow the storage of information with different levels of granularity; b) historical relations that can store together both instantaneous valid times and intervals; c) some temporal clauses, functions and predicates allowing to define complex temporal queries.

Journal of the American Medical Informatics Association, 2000

A b s t r a c t Most health care databases include time-stamped instant data as the only temporal representation of patient information. Many previous efforts have attempted to provide frameworks in which medical databases could be queried in relation to time. These, however, have required either a sophisticated database representation of time, including time intervals, or a time-stamp-based database coupled with a nonstandard temporal query language. In this work, the authors demonstrate how their previously described data retrieval application, DXtractor, can be used as a database querying application with expressive power close to that of temporal databases and temporal query languages, using only standard SQL and existing timestamp-based repositories. DXtractor provides the ability to compose temporal queries through an interface that is understood by nonprogramming medical personnel. Not all temporal constructs are easily implemented using this framework; nonetheless, DXtractor's temporal capabilities provide a significant improvement in the temporal expressivity accessible to clinicians using standard time-stamped clinical databases.

Proceedings / AMIA ... Annual Symposium. AMIA Symposium, 1999

Clinical databases typically contain a significant amount of temporal information, information that is often crucial in medical decision-support systems. Most recent clinical information systems use the relational model when working with this information. Although these systems have reasonably well-defined semantics for temporal queries on a single relational table, many do not fully address the complex semantics of operations involving multiple temporal tables. Such operations can arise frequently in queries on clinical databases. This paper describes the issues encountered when joining a set of temporal tables, and outlines how such joins are far more complex than non-temporal ones. We describe the semantics of temporal joins in a query management system called Chronus II, a system we have developed to assist in evaluating patients for clinical trials.

Proceedings / the ... Annual Symposium on Computer Application [sic] in Medical Care. Symposium on Computer Applications in Medical Care, 1995

There is a need for managing temporal clinical information given at different levels of granularity. Different time granularities are also needed in querying clinical databases. In this paper, we describe GCH-OSQL (Granular Clinical History--Object Structured Query Language), an object-oriented temporally-oriented extension of SQL. GCH-OSQL is based on an object-oriented temporal data model. It allows storage of clinical information at different and mixed granularities. GCH-OSQL deals with the valid time of clinical information. GCH-OSQL offers also a graphical user-interface. It guides different end users, from expert to naive, to formulate expressive and correct queries.

1999

The ability to reason with time-oriented data is central to the practice of medicine. Monitoring clinical variables over time often provides information that drives medical decision making (e.g., clinical diagnosis and therapy planning). Because the time-oriented patient data are often stored in electronic databases, it is important to ensure that clinicians and medical decision-support applications can conveniently find answers to their clinical queries using these databases. To help clinicians and decision-support applications make medical decisions using time-oriented data, a database-management system should (1) permit the expression of abstract, time-oriented queries, (2) permit the retrieval of data that satisfy a given set of time-oriented data-selection criteria, and (3) present the retrieved data at the appropriate level of abstraction. We impose these criteria to facilitate the expression of clinical queries and to reduce the manual data processing that users must undertake to decipher the answers to their queries. We describe a system, Tzolkin, that integrates a general method for temporal-data maintenance with a general method for temporal reasoning to meet these criteria. Tzolkin allows clinicians to use SQL-like temporal queries to retrieve both raw, time-oriented data and dynamically generated summaries of those data. Tzolkin can be used as a standalone system or as a module that serves other software systems. We implement Tzolkin with a temporaldatabase mediator approach. This approach is general, facilitates software reuse, and thus decreases the cost of building new software systems that require this functionality.

IEEE Transactions on Information Technology in Biomedicine, 1997

The need to manage temporal information given at different levels of granularity or with indeterminacy is common to many application areas. Among them, we focus on clinical data management. Different time granularities and indeterminacy are also needed in querying temporal databases. In this paper, we describe GCH-OSQL (Granular Clinical History-Object Structured Query Language), an object-oriented/temporally-oriented extension of SQL. GCH-OSQL is based on an object-oriented temporal data model, GCH-OODM. GCH-OODM allows storage of clinical information at different and mixed granularities or with temporal indeterminacy. GCH-OSQL deals with the valid time of clinical information. The temporal extension of the SELECT construct includes the addition of the TIME-SLICE and MOVING WINDOW clauses, and the capability to reference the temporal dimension of objects in the WHERE and SELECT clauses. Using object-oriented technologies, a system prototype for GCH-OSQL and GCH-OODM has been implemented and applied to data management of follow-up patients after coronary angioplasty intervention.

1998

The ability to reason with time-oriented data is central to the practice of medicine. Monitoring clinical variables over time often provides information that drives medical decision making (e.g., clinical diagnosis and therapy planning). Because the time-oriented patient data are often stored in electronic databases, it is important to ensure that clinicians and medical decision-support applications can conveniently find answers to their clinical queries using these databases. To help clinicians and decision-support applications make medical decisions using time-oriented data, a database-management system should (1) permit the expression of abstract, time-oriented queries, (2) permit the retrieval of data that satisfy a given set of time-oriented data-selection criteria, and (3) present the retrieved data at the appropriate level of abstraction. We impose these criteria to facilitate the expression of clinical queries and to reduce the manual data processing that users must undertake to decipher the answers to their queries. We describe a system, Tzolkin, that integrates a general method for temporal-data maintenance with a general method for temporal reasoning to meet these criteria. Tzolkin allows clinicians to use SQL-like temporal queries to retrieve both raw, time-oriented data and dynamically generated summaries of those data. Tzolkin can be used as a standalone system or as a module that serves other software systems. We implement Tzolkin with a temporaldatabase mediator approach. This approach is general, facilitates software reuse, and thus decreases the cost of building new software systems that require this functionality.

Artificial Intelligence in …, 2005

In the area of Medical Informatics, there is an increasing realization that temporal information plays a crucial role, so that suitable database models and query languages are needed to store and support it. In this paper we show that current approaches developed within the database field have some limitations even from the point of view of the data model, so that an important class of temporal medical data cannot be properly represented. We propose a new three-sorted model and a query language that overcome such limitations.

1995