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Biomedical subjects

Mary Goldstein

Publications and source records attributed to Mary Goldstein.

5 recordsLinked to original sources

Patient-derived health state utilities for gastroesophageal reflux disease.

BACKGROUND AND AIMS: Gastroesophageal reflux disease is a chronic disease that adversely affects health-related quality of life. The purpose of this study was to derive health state utilities for patients with chronic heartburn symptoms. METHODS: We used a custom-designed computer program in order to elicit utilities with the time-tradeoff and standard-gamble techniques. Patients with chronic (more than 6 months) symptoms of gastroesophageal reflux disease entered the study. Two interviews were performed in random sequence either initially on medications for heartburn that adequately controlled symptoms, or off of medications for 1 wk while the patient was symptomatic. We also collected data using visual-analog scales, quality of life in reflux and dyspepsia (QOLRAD), and Gastrointestinal Symptom Rating Scale (GSRS) scores. RESULTS: We invited 222 patients to participate; 158 (71%) patients (129 men, 29 women) completed the study. Barrett's esophagus was present in 40 (25%), erosive disease in 17 (11%), and 118 (74%) had comorbid conditions. The mean (+/-SD) utility ratings were 0.94 +/- 0.09 on medical therapy and 0.90 +/- 0.12 off medications for patients with reflux alone using time tradeoff (p= 0.004), and 0.94 +/- 8.0 both on and off of antireflux medications with standard-gamble assessment (p= 0.96). Mean time-tradeoff scores were also significantly lower off of medications for patients with other comorbid conditions (p= 0.002). There was no significant difference between mean utility scores for patients with or without Barrett's esophagus or erosive disease. CONCLUSION: Gastroesophageal reflux disease adversely affects health-related quality of life. Time-tradeoff utility for patients with reflux disease is substantially higher when patients are on medication than off medications.

Adult↗

Treadmill scores in elderly men.

OBJECTIVES: This study seeks to further characterize the role of exercise testing in the elderly for prognosis and diagnosis of coronary artery disease. BACKGROUND: Recent exercise testing guidelines have recognized that statements regarding the elderly do not have an adequate evidence-based quality because the studies they are based on have limitations in sample size and design. The Duke Treadmill Score has been recommended for risk stratification, but recent evidence has suggested that it does not function in the elderly. METHODS: The study population consisted of male veterans (1872 patients >or=65 years; 3798 patients <65 years) who underwent routine clinical exercise testing with a mean follow-up of six years. A subset who underwent coronary angiography as clinically indicated (elderly, n = 405; younger, n= 809) were included. The primary outcome for all subjects was cardiovascular mortality with coronary angiographic findings as the outcome in those selected for angiography. RESULTS: In survival analysis, exercise-induced ST depression was prognostic in both age groups only when cardiovascular death was considered as the end point. Peak metabolic equivalents were the most significant predictor for both age groups only when all-cause death was considered as the end point. New age-specific prognostic scores were developed and found to be predictive for cardiovascular mortality in the elderly. Moreover, in the angiographic subset of the elderly, a specific diagnostic score provided significantly better discrimination than exercise ST measurements alone. For any new score, there is a need for validation in another elderly population. CONCLUSIONS: The mortality end point affected the choice of prognostic variables. This study demonstrates that exercise test scores can be helpful for the diagnosis and prognosis of coronary disease in the elderly.

Aged↗

Developing quality indicators and auditing protocols from formal guideline models: knowledge representation and transformations.

Automated quality assessment of clinician actions and patient outcomes is a central problem in guideline- or standards-based medical care. In this paper we describe a model representation and algorithm for deriving structured quality indicators and auditing protocols from formalized specifications of guidelines used in decision support systems. We apply the model and algorithm to the assessment of physician concordance with a guideline knowledge model for hypertension used in a decision-support system. The properties of our solution include the ability to derive automatically context-specific and case-mix-adjusted quality indicators that can model global or local levels of detail about the guideline parameterized by defining the reliability of each indicator or element of the guideline.

Algorithms↗

A distributed, collaborative, structuring model for a clinical-guideline digital-library.

The Digital Electronic Guideline Library (DeGeL) is a Web-based framework and a set of distributed tools that facilitate gradual conversion of clinical guidelines from free text, through semi-structured text, to a fully structured, executable representation. Thus, guidelines exist in a hybrid, multiple-format representation The three formats support increasingly sophisticated computational tasks. The tools perform semantic markup, classification, search, and browsing, and support computational modules that we are developing, for run-time application and retrospective quality assessment. We describe the DeGeL architecture and its collaborative-authoring authorization model, which is based on (1) multiple medical-specialty authoring groups, each including a group manager who controls group authorizations, and (2) a hierarchical authorization model based on the different functions involved in the hybrid guideline-specification process. We have implemented the core modules of the DeGeL architecture and demonstrated distributed markup and retrieval using the knowledge roles of two guidelines ontologies (Asbru and GEM). We are currently evaluating several of the DeGeL tools.

Computer Communication Networks↗

A framework for evidence-adaptive quality assessment that unifies guideline-based and performance-indicator approaches.

Automated quality assessment of clinician actions and patient outcomes is a central problem in guideline- or standards-based medical care. In this paper we describe a unified model representation and algorithm for evidence-adaptive quality assessment scoring that can: (1) use both complex case-specific guidelines and single-step population-wide performance-indicators as quality measures; (2) score adherence consistently with quantitative population-based medical utilities of the quality measures where available; and (3) give worst-case and best-case scores for variations based on (a) uncertain knowledge of the best practice, (b) guideline customization to an individual patient or particular population, (c) physician practice style variation, or (d) imperfect reliability of the quality measure. Our solution uses fuzzy measure-theoretic scoring to handle the uncertain knowledge about best-practices and the ambiguity from practice variation. We show results of applying our method to retrospective data from a guideline project to improve the quality of hypertension care.

Algorithms↗