Distributed, intelligent, interactive visualization and exploration of time-oriented clinical data and their abstractions.

OBJECTIVES: We present KNAVE-II, an intelligent interface to a distributed architecture specific to the tasks of query, knowledge-based interpretation, summarization, visualization, interactive exploration of large numbers of distributed time-oriented clinical data, and dynamic sensitivity analysis of these data. KNAVE-II main contributions to the fields of temporal reasoning and intelligent user interfaces are: (1) the capability for interactive computation and visualization of domain specific temporal abstractions, supported by ALMA--a computational engine that applies the domain knowledge base to the clinical time-oriented database. (2) Semantic (ontology-based) navigation and exploration of the data, knowledge, and temporal abstractions, supported by the IDAN mediator, a distributed architecture that enables runtime access to domain-specific knowledge bases that are maintained by expert physicians. METHODS AND MATERIALS: KNAVE-II was designed according to 12 requirements that were defined through iterative cycles of design and user-centered evaluation. The complete architecture has been implemented and evaluated in a cross-over study design that compared the KNAVE-II module versus two existing methods: paper charts and an Excel electronic spreadsheet. A small group of clinicians answered the same queries, using the domain of oncology and a set of 1000 patients followed after bone-marrow transplantation. RESULTS: The results show that users are able to perform medium to hard difficulty level queries faster and more accurately by using KNAVE-II than paper charts and Excel. Moreover, KNAVE-II was ranked first in preference by all users, along all usability dimensions. CONCLUSIONS: Initial evaluation of KNAVE-II and its supporting knowledge based temporal-mediation architecture, by applying it to a large data base of patients monitored several years after bone marrow transplantation (BMT), has produced highly encouraging results.

A framework for distributed mediation of temporal-abstraction queries to clinical databases.

OBJECTIVE: The specification and creation of a distributed system that integrates medical knowledge bases with time-oriented clinical databases; the goal is to answer complex temporal queries regarding both raw data and its abstractions, such as are often required in medical applications. METHODS: (1) Specification, design, and implementation of a generalized access method to a set of heterogeneous clinical data sources, by using a virtual medical-record interface and by mapping the local terms to a set of standardized medical vocabularies; (2) specification of a generalized interface to a set of knowledge sources; (3) specification and implementation of a service, called ALMA that computes complex time-oriented medical queries that include both raw data and abstractions derivable from it; (4) design and implementation of a mediator, called IDAN, that answers raw-data and abstract queries by integrating the appropriate clinical data with the relevant medical knowledge and uses the computation service to answer the queries; (5) an expressive language that enables definition of time-dependent medical queries, which are referred to the mediator; (6) evaluation of the effect of the system, when combined with a new visual interface, called KNAVE-II, on the speed and accuracy of answering a set of complex queries in an oncology sub domain, by a group of clinicians, compared to answering these queries using paper or an electronic spreadsheet. RESULTS: We have implemented the full IDAN architecture. The IDAN/KNAVE-II combination significantly increased the accuracy and speed of answering complex queries about both the data and their abstractions, compared to the standard tools. CONCLUSION: The implemented architecture proves the feasibility of the distributed integration of medical knowledge sources with clinical data of heterogeneous sources. The results suggest that the proposed IDAN modular architecture has potential significance for supporting the automation of clinical tasks such as diagnosis, monitoring, therapy, and quality assessment.

Interactive visualization and exploration of time-oriented clinical data using a distributed temporal-abstraction architecture.

KNAVE-II is a system for visualization and exploration of large amounts of time-oriented clinical data and of multiple levels of clinically meaningful abstractions derivable from these data. KNAVE-II uses a distributed temporal-abstraction architecture that integrates a set of knowledge services, each interacting with a domain-specific knowledge source, a set of data-access services, each interacting with a clinical data source, and a computational service for deriving knowledge-based abstractions of the data.

A Web-Based system for interactive visualization and exploration of time-oriented clinical data and their abstractions.

In this theater-style demonstration, the speakers will demonstrate KNAVE-II, a Web-based distributed system for interactive visualization and exploration of large amounts of time-oriented clinical data from multiple sources, and of clinically meaningful concepts (abstractions) derivable from these data. The KNAVE-II system and its complete underlying architecture provide a solution to the data overload problem.