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Biomedical subjects

J Lipscomb

Publications and source records attributed to J Lipscomb.

50 records · Page 3Linked to original sources
PubMed1982

A political economic theory of the dental care market.

A theory of the dental care market is introduced which proposes that the vertically integrated (local/state/national) structure of the profession services as an organizational vehicle both for intra-professional debate and for developing provider-oriented dental care policy. We suggest that a special relationship exists between professionalism and professional regulation. Such regulation has functioned simultaneously to limit competition and to foster a prized consumption commodity for providers: professionalism and professional esteem. The organized pursuit of this commodity inherently dampens competition. Professionalism itself plays a crucial role in: 1) securing for organized dentistry a form of state regulation in which the providers themselves are the principal decision-makers; and 2) influencing provider and consumer market behavior in several significant respects, the net result being the formation of maintenance of a type of "leadership cartel" in the local market. Thus, a political-economic theory of the dental care market formally acknowledges professionalism as valued by established dentists and recent graduates as a central determining influence. Traditional models of pure competition and monopoly emerge as special, extreme cases of the general theory. Hypotheses are offered regarding consumer and provider behavior, market dynamics, and health policy and regulation.

Dental Health Services↗
PubMed1975

Impact of expanded-duty assistants on cost and productivity in dental care delivery.

Data from an experimental dental program are used to develop a linear programming model of dental care delivery that the authors use to examine the economic implications of introducing expanded-duty dental assistants (EDDA's) in three types of dental practices. The authors examine the changes in productivity and profitability that result from hiring one or more EDDAs and conclude that a dentist in solo practice can more than double his net revenue by hiring one EDDA but will not increase his productivity further by hiring additional EDDAs. Two- and three-dentist groups also can increase revenue by hiring EDDAs, but, beyond a certain point, an inverse relationship exists between the number of auxiliaries hired and net revenue generated.

Cost-Benefit Analysis↗
PubMedDate not supplied

Hydrogeologic assessment of exposure to solvent-contaminated drinking water: pregnancy outcomes in relation to exposure.

We recently concluded that exposure to solvent-contaminated drinking water was an unlikely explanation for observed excesses of adverse pregnancy outcomes during 1980-1981 in the Los Paseos neighborhood of Santa Clara County, California, because these excesses were not observed in an adjacent exposed area. The validity of this conclusion depends on the assumption that the two areas had comparable exposure. Using quantitative methods to model movement of the solvent leak plume and water flow within the distribution system, we estimated that women with adverse outcomes were no more likely to have received contaminated water than women with normal live births. These results strengthen the conclusion that exposures to water from the contaminated well were not responsible for the excess of adverse outcomes observed in the Los Paseos area.

Abnormalities, Drug-Induced↗
PubMedDate not supplied

Cytologic nuclear grade of malignant breast aspirates as a predictor of histologic grade. Light microscopy and image analysis characteristics.

OBJECTIVE: To determine if cytologic nuclear grade characteristics combined with image analysis assessment of morphometric nuclear parameters (1) correlate with the modified Scarff-Bloom-Richardson grading system and (2) discriminate between low and high nuclear grades of invasive ductal carcinoma. STUDY DESIGN: Fifty-four fine needle aspiration biopsies (FNABs) of breast carcinoma were evaluated for five morphologic nuclear grade characteristics. In addition, four morphometric, standardized object measurements were analyzed by an image analysis system. Corresponding biopsies of invasive ductal carcinoma (46 cases) were independently evaluated with the Scarff-Bloom-Richardson grading system, modified into low (scores 3-6) and high (scores 7-9) grades. RESULTS: An overall agreement of 82% was reached by three of four cytopathologists for each of five morphologic characteristics. There was a strong correlation (r = .8059, P < .0001) between cytologic nuclear grade and modified histologic grade. Only pleomorphism, nucleoli and sum optical density retained their statistical significance in distinguishing low from high grade ductal carcinomas. These three characteristics also had the strongest correlation with cytologic nuclear grade. CONCLUSION: Cytologic nuclear grade from aspirates of ductal carcinoma can be a predictor of the modified histologic grades of Scarff, Bloom and Richardson. Nuclear morphology reinforced by image morphometry may separate these tumors into low and high nuclear grade categories.

Biopsy, Needle↗
PubMedDate not supplied

Assessing uncertainty in cost-effectiveness analyses: application to a complex decision model.

A framework for quantifying uncertainty about costs, effectiveness measures, and marginal cost-effectiveness ratios in complex decision models is presented. This type of application requires special techniques because of the multiple sources of information and the model-based combination of data. The authors discuss two alternative approaches, one based on Bayesian inference and the other on resampling. While computationally intensive, these are flexible in handling complex distributional assumptions and a variety of outcome measures of interest. These concepts are illustrated using a simplified model. Then the extension to a complex decision model using the stroke-prevention policy model is described.

Bayes Theorem↗
PubMedDate not supplied

Predicting the cost of illness: a comparison of alternative models applied to stroke.

Predictions of cost over well-defined time horizons are frequently required in the analysis of clinical trials and social experiments, for decision models investigating the cost-effectiveness of interventions, and for macro-level estimates of the resource impact of disease. With rare exceptions, cost predictions used in such applications continue to take the form of deterministic point estimates. However, the growing availability of large administrative and clinical data sets offers new opportunities for a more general approach to disease cost forecasting: the estimation of multivariable cost functions that yield predictions at the individual level, conditional on intervention(s), patient characteristics, and other factors. This raises the fundamental question of how to choose the "best" cost model for a given application. The central purpose of this paper is to demonstrate how to evaluate competing models on the basis of predictive validity. This concept is operationalized according to three alternative criteria: 1) root mean square error (RMSE), for evaluating predicted mean cost; 2) mean absolute error (MAE), for evaluating predicted median cost; and 3) a logarithmic scoring rule (log score), an information-theoretic index for evaluating the entire predictive distribution of cost. To illustrate these concepts, the authors conducted a split-sample analysis of data from a national sample of Medicare-covered patients hospitalized for ischemic stroke in 1991 and followed to the end of 1993. Using test and training samples of about 500,000 observations each, they investigated five models: single-equation linear models, with and without log transform of cost; two-part (mixture) models, with and without log transform, to directly address the problem of zero-cost observations; and a Cox proportional-hazards model stratified by time interval. For deriving the predictive distribution of cost, the log transformed two-part and proportional-hazards models are superior. For deriving the predicted mean or median cost, these two models and the commonly used log-transformed linear model all perform about the same. The untransformed models are dominated in every instance. The approaches to model selection illustrated here can be applied across a wide range of settings.

Cerebrovascular Disorders↗