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Biomedical subjects

R N Shiffman

Publications and source records attributed to R N Shiffman.

28 records · Page 2Linked to original sources
PubMed1992

Rule set reduction using augmented decision table and semantic subsumption techniques: application to cholesterol guidelines.

Clinical practice guidelines must comprehensively address all logically possible situations, but this completeness may result in sizable and cumbersome rule sets. We applied rule set reduction techniques to a 576-rule set regarding recommendations for medication treatment of hypercholesterolemia. Using decision tables augmented with information regarding test costs and rule application frequencies, we sorted the rule sets prior to identifying irrelevant tests and eliminating unnecessary rules. Alternatively, we examined the semantic relationships among risk factors in hypercholesterolemia and applied a subsumption technique to reduce the rule set. Both methodologies resulted in substantial rule set compression (mean, 48-70%). Subsumption techniques proved superior for compacting a large rule set based on risk factors.

Adult↗
PubMed1991

Composing user models through logic analysis.

The evaluation of tutorial strategies, interface designs, and courseware content is an area of active research in the medical education community. Many of the evaluation techniques that have been developed (e.g., program instrumentation), commonly produce data that are difficult to decipher or to interpret effectively. We have explored the use of decision tables to automatically simplify and categorize data for the composition of user models--descriptions of student's learning styles and preferences. An approach to user modeling that is based on decision tables has numerous advantages compared with traditional manual techniques or methods that rely on rule-based expert systems or neural networks. Decision tables provide a mechanism whereby overwhelming quantities of data can be condensed into an easily interpreted and manipulated form. Compared with conventional rule-based expert systems, decision tables are more amenable to modification. Unlike classification systems based on neural networks, the entries in decision tables are readily available for inspection and manipulation. Decision tables, descriptions of observations of behavior, also provide automatic checks for ambiguity in the tracking data.

Decision Making↗
PubMed1991

Use of augmented decision tables to convert probabilistic data into clinical algorithms for the diagnosis of appendicitis.

Decision table techniques have been shown to be useful for ensuring logical completeness, eliminating ambiguity, and optimizing the translation of logic into flowcharts or computer programs. Nevertheless, they have not been widely applied in medicine. We have used decision table techniques to demonstrate the derivation of two sets of rules for determining whether to operate on patients with suspected appendicitis based on patterns of observed signs and symptoms. One rule set is based on a diagnostic threshold whereby morbidity is minimized; the other rule set minimizes mortality. For this purpose, we have developed an augmented decision table format that allows the incorporation of probability and utility data.

Algorithms↗
PubMedDate not supplied

Representation of clinical practice guidelines in conventional and augmented decision tables.

OBJECTIVE: To develop a knowledge representation model for clinical practice guidelines that is linguistically adequate, comprehensible, reusable, and maintainable. DESIGN: Decision tables provide the basic framework for the proposed knowledge representation model. Guideline logic is represented as rules in conventional decision tables. These tables are augmented by layers where collateral information is recorded in slots beneath the logic. RESULTS: Decision tables organize rules into cohesive rule sets wherein complex logic is clarified. Decision table rule sets may be verified to assure completeness and consistency. Optimization and display of rule sets as sequential decision trees may enhance the comprehensibility of the logic. The modularity of the rule formats may facilitate maintenance. The augmentation layers provide links to descriptive language, information sources, decision variable characteristics, costs and expected values of policies, and evidence sources and quality. CONCLUSION: Augmented decision tables can serve as a unifying knowledge representation for developers and implementers of clinical practice guidelines.

Decision Support Techniques↗
PubMedDate not supplied

A design model for computer-based guideline implementation based on information management services.

Clinical practice guidelines must be implemented effectively if they are to influence the behavior of clinicians. The authors describe a model for computer-based guideline implementation that identifies eight information management services needed to integrate guideline-based decision support with clinical workflow. Recommendation services determine appropriate activities in specific clinical circumstances. Documentation services involve data capture. Registration services integrate demographic and administrative data. Explanation services enhance the credibility of automated recommendations by providing supportive evidence and rating the quality of evidence. Calculation services measure time intervals, suggest medication dosages, and perform other computational tasks. Communication services employ standards for information transfer and provide data security. Effective presentation services facilitate understanding of complex data, clarify trends, and format written materials (including prescriptions) for patients. Aggregation services associate outcomes with specific guideline interventions. The authors provide examples of the eight services that make up the model from five evidence-based practice parameters developed by the American Academy of Pediatrics.

Decision Support Systems, Clinical↗
PubMedDate not supplied

Computer-based guideline implementation systems: a systematic review of functionality and effectiveness.

In this systematic review, the authors analyze the functionality provided by recent computer-based guideline implementation systems and characterize the effectiveness of the systems. Twenty-five studies published between 1992 and January 1998 were identified. Articles were included if the authors indicated an intent to implement guideline recommendations for clinicians and if the effectiveness of the system was evaluated. Provision of eight information management services and effects on guideline adherence, documentation, user satisfaction, and patient outcome were noted. All systems provided patient-specific recommendations. In 19, recommendations were available concurrently with care. Explanation services were described for nine systems. Nine systems allowed interactive documentation, and 17 produced paper-based output. Communication services were present most often in systems integrated with electronic medical records. Registration, calculation, and aggregation services were infrequently reported. There were 10 controlled trials (9 randomized) and 10 time-series correlational studies. Guideline adherence improved in 14 of 18 systems in which it was measured. Documentation improved in 4 of 4 studies.

Decision Making, Computer-Assisted↗
PubMedDate not supplied

GEM: a proposal for a more comprehensive guideline document model using XML.

OBJECTIVE: To develop a guideline document model that includes a sufficiently broad set of concepts to be useful throughout the guideline life cycle. DESIGN: Current guideline document models are limited in that they reflect the specific orientation of the stakeholder who created them; thus, developers and disseminators often provide few constructs for conceptualizing recommendations, while implementers de-emphasize concepts related to establishing guideline validity. The authors developed the Guideline Elements Model (GEM) using XML to better represent the heterogeneous knowledge contained in practice guidelines. Core constructs were derived from the Institute of Medicine's Guideline Appraisal Instrument, the National Guideline Clearinghouse, and the augmented decision table guideline representation. These were supplemented by additional concepts from a literature review. RESULTS: The GEM hierarchy includes more than 100 elements. Major concepts relate to a guideline's identity, developer, purpose, intended audience, method of development, target population, knowledge components, testing, and review plan. Knowledge components in guideline documents include recommendations (which in turn comprise conditionals and imperatives), definitions, and algorithms. CONCLUSION: GEM is more comprehensive than existing models and is expressively adequate to represent the heterogeneous information contained in guidelines. Use of XML contributes to a flexible, comprehensible, shareable, and reusable knowledge representation that is both readable by human beings and processible by computers.

Algorithms↗
PubMedDate not supplied

Information technology for children's health and health care: report on the Information Technology in Children's Health Care Expert Meeting, September 21-22, 2000.

In September 2000, the Agency for Healthcare Quality and Research and the American Academy of Pediatrics Center for Child Health Research sponsored a meeting of experts and knowledgeable stakeholders to identify 1) the special information needs of pediatric care and 2) health service research questions related to the use of information technology in children's health care. Technologies that support the care of children must address issues related to growth and development, children's changing physiology, and the unique diseases of children and interventions of pediatric care. Connectivity and data integration are particular concerns for child health care workers. Consumer health information needs for this population extend beyond the needs of one individual to the needs of the family. Recommendations of the attendees include rapid implementation of features in electronic health information systems that support pediatric care and involvement of child health experts in policy making, standards setting, education, and advocacy. A proposed research agenda should address both effectiveness and costs of information technology, with special consideration for the needs of children, the development and evaluation of clinical decision support in pediatric settings, understanding of the epidemiology of iatrogenic injury in childhood, supplementation of vocabulary standards with pediatrics-specific terminology, and improvement in health care access for children, using telemedicine.

Child↗
PubMedDate not supplied

Improving clinical guidelines with logic and decision-table techniques: application to hepatitis immunization recommendations.

Clinical practice guidelines can be clarified, verified, and simplified by the use of logical analysis and the application of decision-table techniques. This methodology is applied to a CDC guideline for the prevention of perinatal transmission of hepatitis B by immunization. Relevant clinical variables are identified and possible values for each variable are defined. An exhaustive enumeration of value combinations is generated. Logically impossible combinations are identified and eliminated. The guideline's recommendations are next translated into a set of rules and compared with the remaining value combinations. Variable combinations that are not covered by guideline recommendations represent incomplete guideline specifications. Inconsistency can be identified by finding identical condition sets in two or more rules. The procedure demonstrates that the hepatitis guideline is incomplete. Logical analysis can improve the quality of clinical practice guidelines by assuring comprehensiveness and consistency.

Decision Support Techniques↗