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A Boxwala

Publications and source records attributed to A Boxwala.

9 recordsLinked to original sources
PubMed2001

Sharable computer-based clinical practice guidelines: rationale, obstacles, approaches, and prospects.

Clinical practice guideline automation at the point of care is of growing interest, yet most guidelines are authored in unstructured narrative form. Computer-based execution depends on a formal structured representation, and also faces a number of other challenges at all stages of the guideline lifecycle: modeling, authoring, dissemination, implementation, and update. This is because of the multiplicity of conceptual models, authoring tools, authoring approaches, intended applications, implementation platforms, and local interface requirements and operational constraints. Complexity and time required for development and structure are also huge obstacles. These factors argue for convergence on a common shared model for representation that can be the basis of dissemination. A common model would facilitate direct interpretation or mapping to multiple implementation environments. GLIF (GuideLine Interchange Format) is a formal representation model for guidelines, created by the InterMed Collaboratory as a proposed basis for a shared representation. GLIF currently addresses the process of authoring and dissemination; the InterMed team's major focus now is on tools to facilitate these tasks and the mapping to clinical information system environments. Because of limitations in what can be done by a single team with finite resources, however, and the variety of additional perspectives that need to be accommodated, the InterMed team has determined that further development of a shared representation would be best served as an open process in which the world community is engaged. Under the auspices of the HL7 Decision Support Technical Committee, a GLIF Special Interest Group has been established, which is intended to be a forum for collaborative refinement and extension of a standard representation that can support the needs of the guideline lifecycle. Significant areas for future work will need to include demonstrations of effective means for incorporating guide-lines at point of care, reconciliation of functional requirements of different models and identification of those most important for supporting practical implementation, im-proved means for authoring and management of complexity, and methods for automatically analyzing and validating syntax, semantics, and logical consistency of guidelines.

Artificial Intelligence↗
PubMed1999

A framework and tools for authoring, editing, documenting, sharing, searching, navigating, and executing computer-based clinical guidelines.

With the spread of managed care and integrated delivery networks, an increased emphasis has been placed on the cost-effectiveness of clinical practices. The need has been recognized to use guidelines to support education, and to integrate them into clinical practice. A specification for guideline representation that would facilitate computer-based clinical guideline sharing has been developed by the InterMed Collaboratory. Called GLIF (GuideLine Interchange Format), this specification and its proposed extensions have been the basis for our implementation of a framework and suite of integrated software tools for guideline authoring and editing, packaging in XML, Internet distribution, navigation, eligibility determination, and automatic execution.

Eligibility Determination↗
PubMed1997

Benchmark test cases for evaluation of computer-based methods for detection of setup errors: realistic digitally reconstructed electronic portal images with known setup errors.

PURPOSE: The purpose of this investigation was to develop methods and software for computing realistic digitally reconstructed electronic portal images with known setup errors for use as benchmark test cases for evaluation and intercomparison of computer-based methods for image matching and detecting setup errors in electronic portal images. METHODS AND MATERIALS: An existing software tool for computing digitally reconstructed radiographs was modified to compute simulated megavoltage images. An interface was added to allow the user to specify which setup parameter(s) will contain computer-induced random and systematic errors in a reference beam created during virtual simulation. Other software features include options for adding random and structured noise, Gaussian blurring to simulate geometric unsharpness, histogram matching with a "typical" electronic portal image, specifying individual preferences for the appearance of the "gold standard" image, and specifying the number of images generated. The visible male computed tomography data set from the National Library of Medicine was used as the planning image. RESULTS: Digitally reconstructed electronic portal images with known setup errors have been generated and used to evaluate our methods for automatic image matching and error detection. Any number of different sets of test cases can be generated to investigate setup errors involving selected setup parameters and anatomic volumes. This approach has proved to be invaluable for determination of error detection sensitivity under ideal (rigid body) conditions and for guiding further development of image matching and error detection methods. Example images have been successfully exported for similar use at other sites. CONCLUSIONS: Because absolute truth is known, digitally reconstructed electronic portal images with known setup errors are well suited for evaluation of computer-aided image matching and error detection methods. High-quality planning images, such as the visible human CT scans from the National Library of Medicine, are essential for producing realistic images. Sets of test cases with systematic and random errors in selected setup parameters and anatomic volumes are suitable for use as standard benchmarks by the radiotherapy community. In addition to serving as an aid to research and development, benchmark images may also be useful for evaluation of commercial systems and as part of a quality assurance program for clinical systems. Test cases and software are available upon request.

Computer Simulation↗
PubMed1995

Core-based portal image registration for automatic radiotherapy treatment verification.

PURPOSE: Portal imaging is the most important quality assurance procedure for monitoring the reproducibility of setup geometry in radiation therapy. The role of portal imaging has become even more critical in recent years due to the migration of three-dimensional (3D) treatment planning technology, including high-precision conformal therapy, from the research setting to routine clinical practice. Unfortunately, traditional methods for acquiring and interpreting portal images suffer from a number of deficiencies that contribute to the well-documented observation that many setup errors go undetected, and some persist for a clinically significant portion of the prescribed dose. Significant improvements in both accuracy and efficiency of detecting setup errors can, in principle, be achieved by using automatic image registration for on-line screening of images obtained from electronic portal imaging devices (EPIDs). METHODS AND MATERIALS: This article presents recent developments in a method called core-based image analysis that shows great promise for achieving the desired improvements in error detection. Core-based image analysis is a fundamental computer vision method that is capable of exploiting the full power of EPIDs by providing for on-line detection of setup errors via automatic registration of user-selected anatomical structures. We describe a robust method for automatic portal image registration based on core analysis and demonstrate an approach for assessing both accuracy and precision of registration methods using realistic, digitally reconstructed portal radiographs (DRPRs) where truth is known. RESULTS: Automatic core-based analysis of a set of 20 DRPRs containing known, random field positioning errors was performed for a patient undergoing treatment for prostate cancer. In all cases, the reported translation was within 1 mm of the actual translation with mean absolute errors of 0.3 mm and standard deviations of 0.3 mm. In all cases, the reported rotation was within 0.6 degree of the actual rotation with a mean absolute error of 0.18 degree and a standard deviation of 0.23 degree. CONCLUSION: Our results, using digitally reconstructed portal radiographs that closely resemble clinical portal images, suggest that automatic core-based registration is suitable as an on-line screening tool for detecting and quantifying patient setup errors.

Humans↗
PubMed1995

Three-dimensional reconstruction of a bullet path: validation by computed radiography.

Three-dimensional visualization is an important tool in the evaluation and demonstration of injury. Creating convincing graphics, however, requires strict distinction between illustrative and reconstructive visualizations and a method of validation. We present a case in which we used a radiation-planning tool to provide a 3-dimensional illustrative visualization of a contact gunshot wound to the head, and validated the result by comparing computed radiographs with radiographs taken at autopsy. We discuss the use of visualization tools for data exploration in forensic pathology.

Adult↗
PubMed1995

Multimedia medical case authorship and simulator program.

For the last several years, third and fourth year medical students rotating on the rheumatology/immunology service at the University of North Carolina School of Medicine have been using a laptop computer as a teaching adjunct to their formal training in rheumatology. The laptop contains diagnostic programs, reference management and clinical note generation facilities, remote medline access, and most recently, multimedia case simulations. These simulations have been created by the use of a case authoring and simulation system which is presented in this demonstration. The program is divided into simulator and designer modules and uses graphics and sound to portray such data as physical examination findings, blood smears, radiographs, heart sounds, etc. The simulator module includes diagnostic sections with feedback to the student as well as robust patient management trees with an occasional circuitous route for patient outcome. The student receives a numerical score based on deviations from the correct path and optimal cost as designated by the case designer. The system simulates complete management of a patient from the first encounter until treatment is complete. During each encounter, a student obtains the patient's history, physical examination findings, orders tests and reviews their results, makes a differential diagnosis, and treats the patient. The patient's progress and further treatment options at any time are dependent on the treatment option selected by the student at an earlier stage. Students are given the costs of ancillary tests and hospitalization before they order them. Words or phrases can be marked as hypertext and the student can get more information about the marked words by a mouse click. The designer interface of the program creates the clinical case by prompts and requests for information from the designer who needs no programming skills. The designer is almost always an expert faculty member who bases the simulated case on a real patient. Default and normal values for clinical findings and tests facilitate the case design. Graphics and sound files are easily incorporated into any historical, physical examination or test window. Management trees are automatically generated during the case design and the author is able to rapidly change to a new management scene for editing with a mouse click. Optimal critical path to correct cost effective diagnoses and treatment is designated and used as the standard to which the students' choices are compared. The software runs on PC's with 386 or better processors and is based in either Windows or OS/2 operating environments. The display can be VGA or SVGA, color or monochrome. Sound is played from 8 or 16 bit sound files. It can be readily extrapolated to any clinical medical specialty in the medical school or postgraduate curricula. The capabilities of this system to create unlimited, branched management and multiple clinical scenarios combined with the ease of authorship make this program unique and an excellent teaching tool.

Computer Simulation↗
PubMedDate not supplied

The decision systems group: creating a framework for decision making.

The Decision Systems Group is pursuing a vision in which every available medical resource can be brought together at the point of need. The DSG focuses on the components and tools in specific areas as well as on the models, approaches, and infrastructure that make this type of integration possible. Its academic mission is to train individuals with dual expertise: those who understand and appreciate the issues involved in developing and validating a method or technique, plus the issues of deployment, operation, and interaction in practical environments. Ultimately, the application of this vision can only serve to enhance the current level of healthcare.

Boston↗