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Biomedical subjects

L A Lenert

Publications and source records attributed to L A Lenert.

At least 19 recordsLinked to original sources
PubMed1999

Associations between health status and utilities implications for policy.

BACKGROUND: If shape of a person's utility function is associated with his health status, as is predicted by Prospect Theory, the use of utilities from the healthy could result in 'de facto' discrimination against the sick. OBJECTIVES: To determine if patients' utilities for hypothetical states and for their current health were associated with their health status. DESIGN: A cross-sectional study of the health and values of patients with depressive illnesses. SETTING: Patients from three large primary care practices with various medical illnesses complicated by symptoms of depression. MEASURES: Short-Form 12 health status measurements, standard gamble, and visual analog scale preference measurements for patients' current health and for three hypothetical states. RESULTS: One hundred and forty nine patients enrolled in the study and 139 patients completed the survey. Utilities for the best and worst states were similar across different levels of health status; however, standard gamble utilities for intermediate health states were higher for patients in poorer health than patients in better health (P = 0.019,) suggesting utility functions with radically different shapes. Utilities for patients' current health were also associated with their health status. Patients in poor health tended to overvalue their current health relative to the most similar hypothetical state; whereas, patients in good health tended undervalue their current health state (P = 0.036). CONCLUSIONS: In patients with depressive illnesses, there were significant interactions between health and values, that were consistent with the predictions of Prospect Theory, and that could result in systematic under valuation of the health effects of treatments that primarily benefit more severely patients ill.

Adult↗
PubMed1999

Clustering and the design of preference-assessment surveys in healthcare.

OBJECTIVE: To show cluster analysis as a potentially useful tool in defining common outcomes empirically and in facilitating the assessment of preferences for health states. DATA SOURCES: A survey of 224 patients with ventricular arrhythmias treated at Kaiser Permanente of Northern California. STUDY DESIGN/METHODS: Physical functioning was measured using the Duke Activity Status Index (DASI), and mental status and vitality using the Medical Outcomes Study Short Form-36 items (SF-36). A "k-means" clustering algorithm was used to identify prototypical health states, in which patients in the same cluster shared similar responses to items in the survey. PRINCIPAL FINDINGS: The clustering algorithm yielded four prototypical health states. Cluster 1 (21 percent of patients) was characterized by high scores on physical functioning, vitality, and mental health. Cluster 2 (33 percent of patients) had low physical function but high scores on vitality and mental health. Cluster 3 (29 percent of patients) had low physical function and low vitality but preserved mental health. Cluster 4 (17 percent of patients) had low scores on all scales. These clusters served as the basis of written descriptions of the health states. CONCLUSIONS: Employing a clustering algorithm to analyze health status survey data enables researchers to gain a data-driven, concise summary of the experiences of patients.

Adult↗
PubMed1998

Empirically defined health states for depression from the SF-12.

OBJECTIVE: To define objectively and describe a set of clinically relevant health states that encompass the typical effects of depression on quality of life in an actual patient population. Our model was designed to facilitate the elicitation of patients' and the public's values (utilities) for outcomes of depression. DATA SOURCES: From the depression panel of the Medical Outcomes Study. Data include scores on the 12-Item Short Form Health Survey (SF-12) as well as independently obtained diagnoses of depression for 716 patients. Follow-up information, one year after baseline, was available for 166 of these patients. METHODOLOGY: We use k-means cluster analysis to group the patients according to appropriate dimensions of health derived from the SF-12 scores. Chi-squared and exact permutation tests are used to validate the health states thus obtained, by checking for baseline and longitudinal correlation of cluster membership and clinical diagnosis. PRINCIPAL FINDINGS: We find, on the basis of a combination of statistical and clinical criteria, that six states are optimal for summarizing the range of health experienced by depressed patients. Each state is described in terms of a subject who is typical in a sense that is articulated with our cluster-analytic approach. In all of our models, the relationship between health state membership and clinical diagnosis is highly statistically significant. The models are also sensitive to changes in patients' clinical status over time. CONCLUSIONS: Cluster analysis is demonstrably a powerful methodology for forming clinically valid health states from health status data. The states produced are suitable for the experimental elicitation of preference and analyses of costs and utilities.

Chi-Square Distribution↗
PubMed1998

Extending contemporary decision support system designs to patient-oriented systems.

Decision support systems for patients can benefit from adopting knowledge engineering-based architectures. In this paper, we describe how decision support systems for patients differ from decision support systems for health professionals and knowledge engineering principles that can be used to improve the efficiency of developing patient support systems. We discuss a five-step process model for patient-computer dialogue and its incorporation into an architecture based on knowledge engineering ontologies. The architecture's components are grouped into transient and persistent application layers that support a general framework for patient decision support. The implementation of the object-based model using a relational database management system is also discussed.

Artificial Intelligence↗
PubMed1997

Method of Medicare reimbursement and the rate of potentially ineffective care of critically ill patients.

CONTEXT: The worst outcome of critical care may not be death itself; rather, the worst may be an extended death process in which a patient's and his or her family's suffering has been prolonged by services that are ultimately impotent. We have previously used potentially ineffective care (PIC) as a proxy measure for this type of care. OBJECTIVE: To determine if PIC is delivered less often to Medicare patients enrolled in health maintenance organizations (HMOs) than those in traditional fee-for-service health plans. PATIENTS: All Medicare patients hospitalized in intensive care units in California during fiscal year 1994. OUTCOME: Potentially ineffective care was defined as the concurrence of in-hospital death or death within 100 days of hospital discharge and resource use (total hospital costs) above the 90th percentile. METHODS: Hospital costs were adjusted for institution-specific cost-to-charge ratios and local wage indices derived from Health Care Financing Administration cost reports. A multivariate regression model adjusted PIC rates for age, sex, race, elective admission to the hospital, Charlson index diseases, the 15 most common diagnosis related groups for death by 100 days, intensive care unit size, and number of residents at the hospital. RESULTS: A total of 3914 (4.8%) of 81 494 patients experienced PIC and used 21.6% of total intensive care unit resources. The occurrence of PIC was less common among HMO members (adjusted odds ratio, 0.75; 95% confidence interval, 0.65-0.87). However, HMO members were not more likely to experience in-hospital death (adjusted odds ratio, 0.99; 95% confidence interval, 0.91-1.07) and only slightly more likely to experience death by 100 days after hospital discharge (adjusted odds ratio, 1.08; 95% confidence interval, 1.01-1.15). CONCLUSIONS: Patients who experience PIC outcomes are not uncommon in the Medicare population, and patients experiencing this outcome consume a disproportionate amount of medical resources. Medicare beneficiaries in HMO practice settings had a lower risk of experiencing PIC outcomes after adjusting for age, sex, diagnosis, comorbid conditions, and characteristics of the treating hospital. This suggests that HMO practices may be better at limiting or avoiding injudicious use of critical care near the end of life.

Adult↗
PubMed1997

The effect of assessment method and respondent population on utilities elicited for Gaucher disease.

Measured preferences have been reported to vary with the method of elicitation and respondent population surveyed. We elicited utilities for Gaucher disease using a multimedia implementation of the time trade-off, standard gamble, and a conceptually different, largely untested approach, the risk-risk trade-off, from those who are healthy, those with a chronic illness and those with Gaucher disease. The risk-risk trade-off produced significantly lower utilities than the other two preference assessment methods and had the poorest test-retest reliability. The respondent's self-rated current health state utility was the most important determinant of utility values elicited by the time trade-off and standard gamble for the hypothetical health states. Our results do not support the use of our implementation of the risk-risk trade-off method. In eliciting preferences for hypothetical health states from the general population, the subjective rating of a respondent's own health state should be considered in determining representative population groups.

Adult↗
PubMed1997

Measurement of the validity of utility elicitations performed by computerized interview.

OBJECTIVES: The authors evaluate a measure of the validity of utility elicitations and study the potential effects of invalid elicitations on population utility values. METHODS: The authors used a computerized survey to describe and measure preferences for three common side-effects of anti-psychotic drugs (tardive dyskinesia [TD], akathesia [AKA], pseudo-parkinsonism). The authors compared the validity of elicitations in 41 healthy volunteers to 22 schizophrenic patients. Preferences were measured using visual analog scale (VAS), pair-wise comparison (PWC), and the Standard Gamble (SG) methods. To assess the validity of each groups' responses, the authors compared the consistency of subjects' rank-order of the desirability of states across methods of preferences assessment (CAMPA). RESULTS: All healthy volunteers and 82% of patients completed the computer survey; of these subjects, 97% of healthy volunteers and 70% of patients indicated they thought they understood the task required of them. However, only 78% of healthy subjects and 44% of patients had a consistent rank ordering of preferences among VAS and PWC ratings; only 80% and 61%, respectively, had a consistent rank ordering preferences among SG and PWC ratings. For two of the three health states, inconsistent subjects had statistically higher SG utilities (for TD, 0.94 versus 0.87, and for AKA 0.92 versus 0.86; P < 0.05). CONCLUSIONS: The CAMPA test can identify potentially invalid preference ratings. Potentially invalid preference ratings may bias the "population" utilities for health states.

Adolescent↗
PubMed1997

Studying ulcerative colitis over the World Wide Web.

OBJECTIVES: The Internet may provide a cost-effective means to collect outcomes data needed to improve the quality and efficiency of medical care. We explored the feasibility and methodology of a longitudinal outcomes study of Internet users who have ulcerative colitis (UC). METHODS: We created an open-enrollment electronic survey of Internet users who have UC and recorded the number of respondents, their demographics, and their willingness to participate. RESULTS: In a 2-month period, 582 users browsed the survey, 172 (30%) completed the questionnaire, and 162 (95%) reported willingness to enroll this study. Eighty-three percent were willing to release their medical records to verify their diagnosis. Most (> 70%) had the same E-mail address over 2 yr, suggesting that long-term follow-up could be performed electronically. In comparison with the male predominance of Internet users, respondents had gender distribution similar to that of patients who have UC. In comparison with the general population, respondents have higher education and higher household income. CONCLUSIONS: The Internet community could serve as a resource for general population outcome studies. Selection bias due to limited availability and use of the networked computers may affect results. The Internet community, however, is expanding rapidly, so it should become more representative of the general population.

Adult↗
PubMed1997

Willingness-to-pay utility assessment: feasibility of use in normative patient decision support systems.

The authors developed an automated patient interviewing tool to elicit individuals' willingness-to-pay (WTP) utilities under conditions of uncertainty and examined the reliability of this method and its potential usefulness in clinical decision support. We tested this method in 52 healthy volunteers using a computer-based interview that trained subjects in standard gamble (SG) and WTP methods, and elicited preferences for moderate Gaucher disease using WTP and SG. We assessed the validity of the WTP method by calculating the cost-effectiveness threshold implied by subjects' WTP and SG utilities; we also assessed subjects' understanding and comfort with using WTP for decision making by a questionnaire. The WTP method had good test-retest reliability (r = 0.796), and produced a cost-effectiveness ratio and ratings for understanding and clarity that support its validity. Moreover, many subjects felt that WTP was a reasonable (83%) method for therapeutic decision making and expressed comfort (62%) in using the method for their own health care decisions. These results suggest that a probabilistic method for WTP utility assessment is potentially useful for acquiring patient preferences for use in normative decision support systems.

Adult↗
PubMed1997

SecondOpinion: interactive Web-based access to a decision model.

In this paper, we describe a computer architecture, which we call SecondOpinion, designed for automated, normative patient decision support over the World Wide Web. SecondOpinion custom tailors the discussion of therapy options for patients by eliciting their preferences for relevant health states via an interactive WWW interface and then integrating those results in a decision model. The SecondOpinion architecture uses a Finite State Machine representation to track the course of a patient's consultation and to choose the next action to take. The consultation has five distinct types of interactions: explanation of health states, assessment of preferences, detection and correction of errors in preference elicitations, and feedback on the implications of preference. A linear "summary model" speeds calculations of predictions from the decision model and makes it possible to dynamically calculate 95% confidence intervals for the marginal utility of each treatment option. Preferences for states are assessed in the order of their variance contribution to the models predictions in an iterative fashion. Only the states required to obtain a 95% Confidence Interval (CI) that excludes zero are assessed. In Monte Carlo simulation studies, the average number of utility assessments required for the 95% CI to exclude zero in an individual was 4.24 (SD = 1.97) out of 8 relevant health states. the SecondOpinion architecture provides an efficient, "discussion-like" experience leading to an individual-specific treatment recommendation. It may be a cost-effective approach to bring decision analytic advice to the bedside.

Computer Communication Networks↗
PubMed1996

Computer-assisted quality of life assessment for clinical trials.

A patient's quality of life is difficult to assess. Most methods designed to evaluate quality of life for clinical trials are time consuming, subject to varied interpretation among patients and assessors, and apply scales with only a limited relationship to utility theory. We have developed a HyperCard program, incorporating animated graphics, to (1) improve the speed of collection and collation of data, (2) improve understanding between patients and assessors, and (3) incorporate utility theory-based assessments. We assessed the quality of life of 25 patients with end-stage renal disease receiving hemodialysis using a traditional paper-based presentation and, eight months later, repeated the assessment with a computer-assisted presentation. Each presentation incorporated five techniques for evaluating quality of life: the Campbell Index of Well-being, the Kaplan-Bush Index of Well-being, categorical scaling, standard gamble, and time tradeoff. The computer program improved the speed of collation of data for statistical analysis, provided a consistent interface among patients for utility assessments, and showed stable reporting of patient's well-being. These findings suggest that further development of computer-assisted assessments of patients' quality of life for clinical trials is warranted.

Clinical Trials as Topic↗
PubMed1995

IMPACT: an object-oriented graphical environment for construction of multimedia patient interviewing software.

This paper describes our software for rapid construction of multimedia computer interviews. The program, which we call IMPACT, was designed to measure preferences for health outcomes using the standard gamble and other decision analytic techniques. IMPACT is also a multimedia shell program that allows researchers to interactively construct patient interviewing instruments without programming or scripting. It supports the integration of text, graphics, synthesized speech, digital sound and QuickTime movies into interviewing instruments through a point-and-click interface. IMPACT also supports branching logic and randomizing the presentation order of materials within an instrument. This allows customization of the presentation based on patient responses and facilitates experimental designs. Validation studies show that preference assessments performed using IMPACT have high test-retest reliability (r = 0.83, n = 96). Post-test surveys (n = 52) show that most subjects understand valuation methods (86%) and believe that the explanations provided were clear (96%) and that methods were reasonable (80%). The majority of subjects thought the preference assessment methods were not difficult to use (53%) and would have been comfortable using such methods for medical decisions (53%).

Computer Graphics↗
PubMed1993

Monitoring free-text data using medical language processing.

In this paper, we describe a software system for automated monitoring of free-text data in a medical information system that we call RadTRAC (Radiology Text Report Analyzer and Classifier). RadTRAC uses a medical language processing tool and rules derived from statistical analysis of a database to process free-text chest X-ray (CXR) reports and identify reports that describe new or expanding neoplasms for the purpose of monitoring the follow-up of these patients. To evaluate the RadTRAC system, we examined a set of 470 consecutive radiology reports at the Veterans Administration Medical Center, Palo Alto, CA. We compared RadTRAC classification of CXR reports with retrospective expert classification of the reports and with clinical classification from CXR films as recorded in a logbook while the films were being read. The RadTRAC system had a sensitivity of 90% and a specificity of 82% using the logbook as the gold standard. This was similar to the performance of expert radiologists (sensitivity, 92%; specificity, 90%). We then reviewed the charts, appointment schedule, and subsequent X-ray reports of cases either in the logbook or that were identified by RadTRAC as needing follow-up. Two cases in the logbook could have potentially benefited from an automatic monitoring system to ensure follow-up. RadTRAC identified six confirmed new tumors or new metastatic lesions that were not in the logbook. Six other cases were identified by the RadTRAC system with suspicious X-ray findings that had either no follow-up or no further mention of the X-ray lesion in medical records. This suggests that a reminder system based on the RadTRAC technology would be potentially useful.

Abstracting and Indexing↗
PubMed1993

The side effects of antipsychotic drugs and patients' quality of life: patient education and preference assessment with computers and multimedia.

Determining the relative value of novel antipsychotics such as clozapine requires measures of the utility of their different side-effect profiles. Many of these side effects (SE) are complex and difficult to describe adequately. Schizophrenic patients are also difficult to interview reliably. Even in normal subjects, utility assessment can be tedious, inconsistent, and difficult for subjects to understand. We addressed these challenges by developing a multimedia patient education and utility assessment tool. SE were described using short video sequences accompanied by digitized voice descriptions. Patients' preferences were assessed using visual analog scales, pairwise comparisons, and standard gambles. These assessment techniques were carefully explained and logically integrated. Instructions were presented both by digitized voice and in print, and, if necessary, were clarified by a moderator. Animated displays were used to graphically display probability. Reminder pictures, comprehension tests and validation questions were used throughout the survey. Thirty-three patients from VA and public clinic inpatient and outpatient settings took the survey. Five psychiatrists were surveyed as a reference group. Patients understood the SE and the survey (92% mean comprehension) and their answers were internally valid and consistent (74% internal consistency). The standard gamble disutilities for the SE were substantial, ranging from 12-20% decrease in their quality of life. Computer-based, multimedia techniques are useful in conducting utility assessment and evaluating its validity. They allow effective patient education and elicitation of useful values, even in subjects with cognitive impairments.

Adult↗
PubMed1993

Automated linkage of free-text descriptions of patients with a practice guideline.

The process of applying a practice guideline to a patient requires a great deal of clinical data. AAPT (Appropriateness-Assessment Processing from Text) is an experimental computer program that can assess the appropriateness of coronary-artery bypass grafting surgery (CABG) in patients with coronary-artery disease (CAD) and chronic stable angina from the admission summaries of those patients. The AAPT architecture combines natural-language processing (NLP) and probabilistic inference. The NLP module identifies single clinical concepts of interest in the free-text document. The probabilistic inference module, a Bayesian belief network, estimates values for variables not specifically mentioned. AAPT produces a patient's summary of CAD that is similar to a manually generated clinical summary. Work is ongoing to improve AAPT and evaluate it as a tool to assist in the dissemination of guidelines and as a tool to encourage adherence to practice guidelines.

Angina Pectoris↗