David A. Trace

Intelligent medical record-entry (IMR-E)

This paper describes an automated medical record designed to allow providers to enter patient data at the point of care. The system runs on PCs and Macintoshes and uses a graphical user interface and object-oriented programming to take advantage of current mouse and pen technologies. The provider acquires all relevant patient data by pointing and clicking at selections on input screens, many of which contain anatomical drawings to help the provider quickly and accurately describe patient findings. The system also generates a grammatically correct progress note using the problem-oriented structure. Furthermore, items identified in the assessment and plans portion of the program can be ported to expert systems for medical decision assistance or to billing systems. The system allows the provider to obtain the necessary information on a focused patient visit in less than 5 min or to enter a complete history and physical.

Recommending tests in a multimembership Bayesian diagnostic expert system

A computerized test selection module for a multimembership Bayesian diagnostic expert system built to recommend tests to further refine the differential diagnosis is described. The output of the program includes recommendations for individual tests, for groups of tests to be administered in sequence, and for groups of parallel tests. The original set of available tests is large. This generates a large number of groups of tests, any of which could possibly provide the most valuable information. Selection of the proper subset of tests from the original set is critical. A smaller proper subset of tests improves the systems response time by avoiding unnecessary calculation.<<ETX>>

A complete, hypermedia medical decision analysis support system

A treatment risk analysis system was developed and presented by the MEDAS project group. Now, a risk analysis system for medical tests has also been developed to form a complete medical decision support system. Moreover, the current system (a combined treatment and test system) has been redesigned and developed using an object-oriented hypermedia programming language, called Spinnaker Plus, running on the MS-Windows environment. The system has already been used to analyze several neurological problems.<<ETX>>

A Knowledge Engineering System for MEDAS

This paper introduces a Knowledge Engineering System, the Disorder Toolbox (DT), which assists physicians to build, test, and verify the knowledge base for the Medical Emergency Decision Assistance System (MEDAS). DT is designed using a hypertext/hypermedia system and gives physicians an intelligent and user-friendly tool to streamline the disorder pattern creation process. DT reads the Portable Patient File (PPF) generated by the Intelligent Medical Record Entry (IMR-E) System, and allows the medical expert to enter prior and conditional probabilities, and test the posterior probabilities for disorders during the knowledge creation time. After building the disorder patterns, the physician can load a PPF and produce a differential diagnosis using the multimembership Bayesian inference engine. The process of building the Disorder Toolbox and its use are described.<<ETX>>

Extending the feature dictionary to support sophisticated feature interaction and classification

The feature dictionary of a Bayesian diagnostic system is expanded to include feature interactions to support test selection and treatment protocols. The feature interactions required to provide this flexibility are drug side effects and allergic reactions, contraindications to tests and treatment, and drug interactions. Although the primary use of the dictionary is to store the feature information to be used by the MEDAS (Medical Emergency Decision Assistance System) diagnostic system, adding further functionality allows other applications, both inside and outside of MEDAS, to be supported. Generic and brand names of drugs appear as synonyms in the dictionary. This widens the ability to translate data from one system to another.<<ETX>>

An Interactive System for Generating Hospital Progress Notes

Research has shown that physicians find a medical expert system much more attractive if the system can provide in addition to diagnostic support some relief from the heavy burden of responsibility for daily record keeping required in hospital practice. This paper introduces a sophisticated interactive system for generating daily progress notes designed to function as an integral part of MEDAS (the Medical Emergency Decision Assistance System). MEDAS is a pattern-recognition expert system, using multi-membership Bayesian inference. At hospital admission, the MEDAS diagnosis module and severity module produce a problem list and assign a severity code to each problem. In many hospitals, physicians are expected to provide daily progress notes discussing the patients condition with respect to each problem area. For each problem, they need to consider subjective and objective information, assessment and make a plan for handling the problem. The items to be considered depend on the specific problem: remembering these items is a huge memory load; writing it all down is very time-consuming. Our system presents the physician with a series of problem-specific menus, making data entry easy and rapid. Finally, it automatically generates the necessary output for the patient record.

A relational database design in support of standard medical terminology in multi-domain knowledge bases

Relational database techniques have been used to create knowledge bases for a medical diagnostic consultant system. Known as MEDAS (Medical Emergency Decision Assistance System), this expert system, using disorder patterns consisting of features such as symptoms and laboratory results, is able to diagnose multiple disorders. Database technology has been used in MEDAS to develop knowledge engineering tools, called the TOOL BOX, which permit domain experts to create knowledge without the assistance of a knowledge engineer. In the process of knowledge development with the TOOL BOX a standardization of terms was needed. This led us to design a Feature Dictionary and a grammar to support a standardized format for features. A common dictionary of features will allow us to merge knowledge bases, translate between multi-domain bases, and compare competing expert systems. In addition, standard terminology will assist communication across domains The Feature Dictionary has the following attributes Long forms of the feature name (White Blood Count) and short forms (WBC) as well as a three line description of the feature. The type, binary (Abdominal Pain), continuous-valued (WBC), or derived (pulse pressure = systolic - diastolic) is also kept for each feature For value features the appropriate unit (cc, kg, etc.) as well as range limits are stored so that these can be used as a form of quality control on input. The permanence (Y/N) of each feature is kept so it is possible to automatically include permanent features in future encounters. In addition, for each feature three separate “cost” parameters are kept. Risk measures the danger to the patient from no risk such as taking a blood pressure to highly invasive proceedings such as a liver biopsy. Time measures whether results can be expected in minutes, hours, or days. Money measures the actual cost to the patient FD-Equivalents stores the synonyms and antonyms of each feature. These are used to translate between knowledge bases using different terminology. Features were first classified in terms of a Problem Oriented Medical Record. We have added an anatomical reclassification in terms of body systems. Experts will be able to add new kinds of feature classifications. MEDAS, a multi-membership Bayesian model, needs binary representations for its inference. These Binary Features are created by the expert physician in the given disorder patterns. For example, “WBC > 50,000”, or “Age > 2 & Female & Hematocrit > 42” are binary features that might appear in a disorder pattern. Laboratory results often lead to a multiplicity of binary features (such as “WBC ≤ 3,000”, or 3,000 ≤ WBC ≤ 10,000, etc.). Our design allows the user to enter the value of such a feature and have the system set of all the corresponding binary features. This intelligent user interface is controlled by a grammar that allows us to parse the binary features and generate rules for them. The knowledge base for a particular problem domain such as OB/GYN is organized as a collection of disorder patterns. Each of these is represented as a list of binary features and associated probabilities. The domain knowledge base contains only the features relevant to that domain. Experience with the Feature Dictionary has convinced us that there are many advantages in using a DBMS to store the knowledge base for an expert system. The TOOL BOX, originally in ACCENT-R, was rewritten in dBase III for the PC. The knowledge bases created on the PC were then ported to the mainframe. As the number of domains supported by MEDAS grew, it became evident that we needed a DBMS that could function in both environments so we are in the process of converting to ORACLE.

Educational patient simulation in MEDASPC

Describes the patient simulation program that we created for the MEDASPC system. The program provides the patient file with different features that were randomly chosen by the computer or allows the user to set the features individually. We can use the program to create a multi-encounter patient file that corresponds to the way patients and physicians often interact. For the first encounter, we choose the setting of and the physical examination features. Then, for the second encounter, we set laboratory and radiology tests results, etc. By using simulated patient files, medical students can learn and make mistakes without taking risks with real patients.<<ETX>>

A productive user environment for generating progress notes

Describes the implementation methodology of an intelligent progress note system which is designed to support physicians in writing problem-oriented progress notes. The authors are currently developing their system on PCs in Microsoft Windows 3.0 by using Spinnaker Plus. The conversion of the system from a PC base to Macintosh or OS/2 has proven to be easy. The design applies cognitive models of memory as well as hypermedia to provide a creative and productive environment for the physician. The basis of the work is observation of practicing physicians writing progress notes in todays paper-driven world. The hope is to simulate some of the more routine parts of the thinking processes that physicians devote to producing the progress note, to save time, and to provide useful reminders, so that the users can concentrate on the more complex parts of the task.<<ETX>>

MEDRIS: the hypermedia approach to medical record input-software engineering techniques for developing a hypermedia system

A medical record input system (MEDRIS) that makes use of hypermedia technology to provide a clinical tool for physicians to input patient data in a simple manner is described. The design of MEDRIS focuses on providing a natural working environment for the physicians. Physicians can easily learn to use MEDRIS since it eliminates the use of command-level entries and special function keys. MEDRIS comprises the following modules: history (chief complaints, review of systems, family history, etc), physical examination, laboratory, and medication. The chief complaint and the physical examination modules are discussed in detail. The software techniques adopted in building this system are explained. MEDRIS produces an immediate report of the data entered and an encounter file containing all the patient data collected during the current visit, which is added to the portable patient file.<<ETX>>