Characteristics of consumer terminology for health information retrieval.

OBJECTIVES: As millions of consumers perform health information retrieval online, the mismatch between their terminology and the terminologies of the information sources could become a major barrier to successful retrievals. To address this problem, we studied the characteristics of consumer terminology for health information retrieval. METHODS: Our study focused on consumer queries that were used on a consumer health service Web site and a consumer health information Web site. We analyzed data from the site-usage logs and conducted interviews with patients. RESULTS: Our findings show that consumers' information retrieval performance is very poor. There are significant mismatches at all levels (lexical, semantic and mental models) between the consumer terminology and both the information source terminology and standard medical vocabularies. CONCLUSIONS: Comprehensive terminology support on all levels is needed for consumer health information retrieval.

Toward a representation format for sharable clinical guidelines.

Clinical guidelines are being developed for the purpose of reducing medical errors and unjustified variations in medical practice, and for basing medical practice on evidence. Encoding guidelines in a computer-interpretable format and integrating them with the electronic medical record can enable delivery of patient-specific recommendations when and where needed. Since great effort must be expended in developing high-quality guidelines, and in making them computer-interpretable, it is highly desirable to be able to share computer-interpretable guidelines (CIGs) among institutions. Adoption of a common format for representing CIGs is one approach to sharing. Factors that need to be considered in creating a format for sharable CIGs include (i) the scope of guidelines and their intended applications, (ii) the method of delivery of the recommendations, and (iii) the environment, consisting of the practice setting and the information system in which the guidelines will be applied. Several investigators have proposed solutions that improve the sharability of CIGs and, more generally, of medical knowledge. These approaches can be useful in the development of a format for sharable CIGs. Challenges in sharing CIGs also include the need to extend the traditional framework for disseminating guidelines to enable them to be integrated into practice. These extensions include processes for (i) local adaptation of recommendations encoded in shared generic guidelines and (ii) integration of guidelines into the institutional information systems.

Sharable representation of clinical guidelines in GLIF: relationship to the Arden Syntax.

Clinical guidelines are intended to improve the quality and cost effectiveness of patient care. Integration of guidelines into electronic medical records and order-entry systems, in a way that enables delivery of patient-specific advice at the point of care, is likely to encourage guidelines acceptance and effectiveness. Among the methodologies for modeling guidelines and medical decision rules, the Arden Syntax for Medical Logic Modules and the GuideLine Interchange Format version 3 (GLIF3) emphasize the importance of sharing encoded logic across different medical institutions and implementation platforms. These two methodologies have similarities and differences; in this paper we clarify their roles. Both methods can be used to support sharing of medical knowledge, but they do so in complementary situations. The Arden Syntax is suitable for representing individual decision rules in self-contained units called Medical Logic Modules (MLMs), which are usually implemented as event-driven alerts or reminders. In contrast, GLIF3 is designed for encoding complex multistep guidelines that unfold over time. As a consequence, GLIF3 has several mechanisms for complexity management and additional constructs that may require overhead unnecessary for expressing simple alerts and reminders. Unlike the Arden Syntax, GLIF3 encourages a top-down process of guideline modeling consisting of three levels that are created in order: Level 1 comprises a human-readable flowchart of clinical decisions and actions. Level 2 comprises a computable specification that can be verified for logical consistency and completeness; and Level 3 comprises an implementable specification that includes information required for local adaptation of guideline logic as well as for mapping guideline variables onto institutional medical records. A major emphasis of the current GLIF3 development process has been to create the computable specification that formally represents medical decision and eligibility criteria. We based GLIF3's formal expression language on the Arden Syntax's logic grammar, making the necessary extensions to the Arden Syntax's data structures and operators to support GLIF3's object-oriented data model. We discuss why the process of generating a set of MLMs from a GLIF-encoded guideline cannot be automated, why it can result in information loss, and why simple medical rules are best represented as individual MLMs. We thus show that the Arden Syntax and GLIF3 play complementary roles in representing medical knowledge for clinical decision support.

Handling expressiveness and comprehensibility requirements in GLIF3.

Clinical guidelines are aimed at standardizing patient care and improving its quality and cost effectiveness. Guidelines represented in a computer-interpretable (CI) format can be used to provide automatic decision support applied to individual patients during the clinical encounter. The process of creating computer-interpretable guidelines (CIG) re-moves ambiguities contained in paper-based guidelines, thus making the guideline more comprehensible. For these reasons, CIGs may have a larger impact on clinician behavior than paper-based guidelines. Since much effort goes into creating guidelines in a CI format, it is desirable that different institutions and software systems share them. In a guideline representation workshop hosted by the InterMed Collaboratory in March 2000, the need for a standard representation format for sharable CIGs was recognized. As a first step towards achieving this goal, we proposed a set of functional requirements for sharable CIGs. The requirements encompass the entire life cycle of a CIG: development, implementation, use and maintenance. In this paper we discuss requirements that are important during the development stage of a CIG. We have abstracted the requirements into two groups: expressiveness--the ability to ex-press the knowledge content of different types of guidelines--and comprehensibility--the ability to manage complexity, facilitate coherence, and visualize a guideline model to aid in human comprehension. The Guideline Interchange For-mat version 3 (GLIF3) is a language for structured representation of CIGs. It is under development to facilitate sharing CIGs among different institutions and systems. We illustrate how GLIF3 meets the specified development requirements.

Using features of Arden Syntax with object-oriented medical data models for guideline modeling.

Computer-interpretable guidelines (CIGs) can deliver patient-specific decision support at the point of care. CIGs base their recommendations on eligibility and decision criteria that relate medical concepts to patient data. CIG models use expression languages for specifying these criteria, and define models for medical data to which the expressions can refer. In developing version 3 of the GuideLine Interchange Format (GLIF3), we used existing standards as the medical data model and expression language. We investigated the object-oriented HL7 Reference Information Model (RIM) as a default data model. We developed an expression language, called GEL, based on Arden Syntax's logic grammar. Together with other GLIF constructs, GEL reconciles incompatibilities between the data models of Arden Syntax and the HL7 RIM. These incompatibilities include Arden's lack of support for complex data types and time intervals, and the mismatch between Arden's single primary time and multiple time attributes of the HL7 RIM.

Guideline classification to assist modeling, authoring, implementation and retrieval.

The National Guideline Clearinghouse (NGC) and its guideline classification system are significant contributions to the study of clinical practice guidelines (CPGs) and their incorporation into routine clinical care. The NGC classification system is primarily designed to support guideline retrieval. We believe that a guideline classification system should also support identification of features that relate to incorporation of executable CPGs into computer-based applications for sharing and delivering guideline-based advice. We have developed a proposed expansion of the NGC guideline classification for this purpose. The axes of the proposed scheme have implications for designing formal models and structures for representing and authoring CPGs. This scheme also has implications for future research.

GLIF3: the evolution of a guideline representation format.

The Guideline Interchange Format (GLIF) is a language for structured representation of guidelines. It was developed to facilitate sharing clinical guidelines. GLIF version 2 enabled modeling a guideline as a flowchart of structured steps, representing clinical actions and decisions. However, the attributes of structured constructs were defined as text strings that could not be parsed, and such guidelines could not be used for computer-based execution that requires automatic inference. GLIF3 is a new version of GLIF designed to support computer-based execution. GLIF3 builds upon the framework set by GLIF2 but augments it by introducing several new constructs and extending GLIF2 constructs to allow a more formal definition of decision criteria, action specifications and patient data. GLIF3 enables guideline encoding at three levels: a conceptual flowchart, a computable specification that can be verified for logical consistency and completeness, and an implementable specification that can be incorporated into particular institutional information systems.

Decision support for clinical trial eligibility determination in breast cancer.

We have developed a system for clinical trial eligibility determination where patients or primary care providers can enter clinical information about a patient and obtain a ranked list of clinical trials for which the patient is likely to be eligible. We used clinical trial eligibility information from the National Cancer Institute's Physician Data Query (PDQ) database. We translated each free-text eligibility criterion into a machine executable statement using a derivation of the Arden Syntax. Clinical trial protocols were then structured as collections of these eligibility criteria using XML. The application compares the entered patient information against each of the eligibility criteria and returns a numerical score. Results are displayed in order of likelihood of match. We have tested our system using all phase II and III clinical trials for treatment of metastatic breast cancer found in the PDQ database. Preliminary results are encouraging.

Architecture for a multipurpose guideline execution engine.

Integration of guideline knowledge into the clinical workflow is essential, for improving adherence to guidelines. Guidelines in structured formats can be utilized by computer programs to provide decision support in clinical information systems, as well as to facilitate workflow. We have designed an architecture for a flexible guideline execution engine that can be utilized in clinical decision support applications. The engine may be utilized for other applications such as referral management, medical education, and conducting clinical trials. The engine executes guidelines that are defined in an extension of the Guideline Interchange Format (GLIF). GLIF was extended to support representation of constructs that are essential to the execution of the guideline. A prototype of the engine was implemented based on this architecture. The engine is being utilized in two clinical applications that draw on guidelines for decision support. The engine was also used for developing an educational application aimed at testing knowledge of guideline recommendations.

Comparison of computer workstation with light box for detecting setup errors from portal images.

PURPOSE: Observer studies were conducted to test the hypothesis that radiation oncologists using a computer workstation for portal image analysis can detect setup errors at least as accurately as when following standard clinical practice of inspecting portal films on a light box. METHODS AND MATERIALS: In a controlled observer study, nine radiation oncologists used a computer workstation, called PortFolio, to detect setup errors in 40 realistic digitally reconstructed portal radiograph (DRPR) images. PortFolio is a prototype workstation for radiation oncologists to display and inspect digital portal images for setup errors. PortFolio includes tools for image enhancement; alignment of crosshairs, field edges, and anatomic structures on reference and acquired images; measurement of distances and angles; and viewing registered images superimposed on one another. The test DRPRs contained known in-plane translation or rotation errors in the placement of the fields over target regions in the pelvis and head. Test images used in the study were also printed on film for observers to view on a light box and interpret using standard clinical practice. The mean accuracy for error detection for each approach was measured and the results were compared using repeated measures analysis of variance (ANOVA) with the Geisser-Greenhouse test statistic. RESULTS: The results indicate that radiation oncologists participating in this study could detect and quantify in-plane rotation and translation errors more accurately with PortFolio compared to standard clinical practice. CONCLUSIONS: Based on the results of this limited study, it is reasonable to conclude that workstations similar to PortFolio can be used efficaciously in clinical practice.

Portfolio: a prototype workstation for development and evaluation of tools for analysis and management of digital portal images.

PURPOSE: The purpose of this investigation was to design and implement a prototype physician workstation, called PortFolio, as a platform for developing and evaluating, by means of controlled observer studies, user interfaces and interactive tools for analyzing and managing digital portal images. The first observer study was designed to measure physician acceptance of workstation technology, as an alternative to a view box, for inspection and analysis of portal images for detection of treatment setup errors. METHODS AND MATERIALS: The observer study was conducted in a controlled experimental setting to evaluate physician acceptance of the prototype workstation technology exemplified by PortFolio. PortFolio incorporates a windows user interface, a compact kit of carefully selected image analysis tools, and an object-oriented data base infrastructure. The kit evaluated in the observer study included tools for contrast enhancement, registration, and multimodal image visualization. Acceptance was measured in the context of performing portal image analysis in a structured protocol designed to simulate clinical practice. The acceptability and usage patterns were measured from semistructured questionnaires and logs of user interactions. RESULTS: Radiation oncologists, the subjects for this study, perceived the tools in PortFolio to be acceptable clinical aids. Concerns were expressed regarding user efficiency, particularly with respect to the image registration tools. CONCLUSIONS: The results of our observer study indicate that workstation technology is acceptable to radiation oncologists as an alternative to a view box for clinical detection of setup errors from digital portal images. Improvements in implementation, including more tools and a greater degree of automation in the image analysis tasks, are needed to make PortFolio more clinically practical.

A virtual repository approach to clinical and utilization studies: application in mammography as alternative to a national database.

A national mammography database was proposed, based on a centralized architecture for collecting, monitoring, and auditing mammography data. We have developed an alternative architecture relying on Internet-based distributed queries to heterogeneous databases. This architecture creates a "virtual repository", or a federated database which is constructed dynamically, for each query and makes use of data available in legacy systems. It allows the construction of custom-tailored databases at individual sites that can serve the dual purposes of providing data (a) to researchers through a common mammography repository and (b) to clinicians and administrators at participating institutions. We implemented this architecture in a prototype system at the Brigham and Women's Hospital to show its feasibility. Common queries are translated dynamically into database-specific queries, and the results are aggregated for immediate display or download by the user. Data reside in two different databases and consist of structured mammography reports, coded per BIRADS Standardized Mammography Lexicon, as well as pathology results. We prospectively collected data on 213 patients, and showed that our system can perform distributed queries effectively. We also implemented graphical exploratory analysis tools to allow visualization of results. Our findings indicate that the architecture is not only feasible, but also flexible and scaleable, constituting a good alternative to a national mammography database.

Acceptability and usage patterns of an image analysis workstation.

Critical to the successful deployment and use of new computer systems is the acceptance of the system by the users, i.e., the clinicians. We describe a study which evaluated, in an experimental setting, the potential acceptability of an image analysis workstation for radiation therapy. The acceptability and usage patterns were measured using semi-structured questionnaires and maintaining logs of user interactions. The results of the study showed that the radiation oncologists, who were the subjects for the study, perceived the workstation as acceptable. The results also suggested several areas for improvement of workstation that could increase its acceptance in the clinical setting.

Verifying radiotherapy treatment setup by interactive image registration.

Digital image analysis techniques can be used to assist the physician in diagnostic or therapeutic decision making. In radiation oncology, portal image registration can improve the accuracy of detection of errors during radiation treatment. Following a discussion of the general paradigm of interactive image registration, we describe PortFolio, a workstation for portal image analysis.

Retrospective reconstruction of three-dimensional radiotherapy treatment plans of the thorax from two dimensional planning data.

PURPOSE: A method for the retrospective reconstruction of three-dimensional (3-D) radiotherapy treatment plans from two-dimensional (2-D) planning data is detailed in this paper. METHODS AND MATERIALS: With these techniques the user can register an arbitrarily shaped portal on a simulation film with a diagnostic computed tomography study of the patient and then generate the resultant 3-D dose distribution or dose-volume histogram. Seven treatment plans were reconstructed of patients who had previously undergone 3-D treatment planning for fields involving the thorax and who had had a diagnostic computed tomography (CT) scan. The dose-volume histograms and the spatial positions of the beams on the reconstructed plans were then compared to those of the original 3-D plan, which until then, were not made available to the investigators. RESULTS: The dose-volume histograms of the reconstructed plans did not differ from those of the original plans by more than 3% except in the low dose region. The error in positioning the beam in the reconstructed plan was determined to be approximately 5 mm. CONCLUSION: The technique of 3-D treatment plan reconstruction can be used, through retrospective studies, to obtain better assessments of normal tissue complication probabilities and tumor control probabilities.