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PubMed1994

Measuring physician attitudes toward cost, uncertainty, malpractice, and utilization review.

OBJECTIVE: To develop a reliable measure of physician attitudes postulated to influence resource utilization. DESIGN: Statements related to attitudes that may influence resource use were culled from the literature and informal discussions with physicians. SETTING: Academic medical center. PARTICIPANTS: All faculty and housestaff in internal medicine, pediatrics, family medicine, and surgery at an academic medical center were surveyed. The response rate was 59% (n = 428). RESULTS: Exploratory factor analysis of all internal medicine surveys revealed four prominent domains. These closely corresponded with our a-priori hypothesized domains and were interpreted as cost-consciousness, discomfort with uncertainty, fear of malpractice, and annoyance with utilization review. A replication of the analysis using 25 survey items and conducted on the remainder of the data (surgeons, pediatricians, and family practitioners) revealed a similar four-factor solution. Scales were constructed for each of the four domains. Cronbach's alpha ranged from 0.66 to 0.88. Discomfort from uncertainty and fear of malpractice were moderately correlated (r = 0.42); other scale-scale correlations were modest. Of the four attitude measures, only cost-consciousness was associated with lower self-estimates of resource use. Both annoyance with utilization review and fear of malpractice increased as the proportion of time spent in patient care increased. CONCLUSIONS: Although various physician attitudes and beliefs have been hypothesized to influence health services resource use, reliable and valid measures for most of these have not been developed. The authors developed a 19-item survey instrument designed to measure these attitudes reliably. The four scales developed in this study may help identify physician attitudes that are important determinants of physician decision making and help foster a better understanding of physicians' reactions and acculturation to different practice environments.

Academic Medical Centers↗
PubMedDate not supplied

Brain dynamics, psychophysiological uncertainty and behavioral learning.

The present paper takes a first step toward the integration of recent findings on brain dynamics and learning into established fields of psychophysiological science. Leading-edge studies of brain dynamics have shown that the brain manifests an inherent variability and that, when new stimuli (i.e., "problems") are presented to the organism, brain chaos increases. Similarly, many previous studies using a wide variety of physiological and behavioral measures have shown that "psychophysiological uncertainty" is associated with novel stimuli, novice behavioral performance, and new stimulus-stimulus and response-stimulus contingencies. Such uncertainty may ultimately be resolved through some form of learning. Along with the general changes in physiological and behavioral activity, increases in brain chaos may usher the organism into an exploratory mode which serves as a catalyst for learning.

Animals↗
PubMed2002

Resolution of uncertainty of a four-stage sequential extraction procedure using analysis of variance.

Sequential extraction procedures are mostly applied to soils and sediments. Investigations were made for testing the applicability of a selected extraction scheme on spoil pile material. Therefore, different spoil pile samples from uranium mining were extracted into four steps (exchangeable, reducible, oxidizable, and aqua regia soluble phase) and the contents of the elements Cr, Cu, Fe, K, Ni, and Zn were analyzed. To substitute the sequential extraction by a sequence of single extractions and thus keep uncertainties of extraction on a low level, both procedures were compared regarding conformity of their results. The effects of sample handling as well as those of analysis on the measured metal contents were determined by means of analysis of variance and sources of uncertainties were discussed.

Journal Article↗
PubMed2004

New advances in method validation and measurement uncertainty aimed at improving the quality of chemical data.

The implementation of quality systems in analytical laboratories has now, in general, been achieved. While this requirement significantly modified the way that the laboratories were run, it has also improved the quality of the results. The key idea is to use analytical procedures which produce results that fulfil the users' needs and actually help when making decisions. This paper presents the implications of quality systems on the conception and development of an analytical procedure. It introduces the concept of the lifecycle of a method as a model that can be used to organize the selection, development, validation and routine application of a method. It underlines the importance of method validation, and presents a recent approach based on the accuracy profile to illustrate how validation must be fully integrated into the basic design of the method. Thanks to the beta-expectation tolerance interval introduced by Mee (Technometrics (1984) 26(3):251-253), it is possible to unambiguously demonstrate the fitness for purpose of a new method. Remembering that it is also a requirement for accredited laboratories to express the measurement uncertainty, the authors show that uncertainty can be easily related to the trueness and precision of the data collected when building the method accuracy profile.

Journal Article↗
PubMed2001

Meeting the measurement uncertainty and traceability requirements of ISO/AEC standard 17025 in chemical analysis.

The new laboratory accreditation standard, ISO/IEC 17025, reflects current thinking on good measurement practice by requiring more explicit and more demanding attention to a number of activities. These include client interactions, method validation, traceability, and measurement uncertainty. Since the publication of the standard in 1999 there has been extensive debate about its interpretation. It is the author's view that if good quality practices are already in place and if the new requirements are introduced in a manner that is fit for purpose, the additional work required to comply with the new requirements can be expected to be modest. The paper argues that the rigour required in addressing the issues should be driven by customer requirements and the factors that need to be considered in this regard are discussed. The issues addressed include the benefits, interim arrangements, specifying the analytical requirement, establishing traceability, evaluating the uncertainty and reporting the information.

Journal Article↗
PubMed2004

Uncertainty assessment for management of soil contaminants with sparse data.

In order for soil resources to be sustainably managed, it is necessary to have reliable, valid data on the spatial distribution of their environmental impact. However, in practice, one often has to cope with spatial interpolation achieved from few data that show a skewed distribution and uncertain information about soil contamination. We present a case study with 76 soil samples taken from a site of 15 square km in order to assess the usability of information gleaned from sparse data. The soil was contaminated with cadmium predominantly as a result of airborne emissions from a metal smelter. The spatial interpolation applies lognormal anisotropic kriging and conditional simulation for log-transformed data. The uncertainty of cadmium concentration acquired through data sampling, sample preparation, analytical measurement, and interpolation is factor 2 within 68.3 % confidence. Uncertainty predominantly results from the spatial interpolation necessitated by low sampling density and spatial heterogeneity. The interpolation data are shown in maps presenting likelihoods of exceeding threshold values as a result of a lognormal probability distribution. Although the results are not deterministic, this procedure yields a quantified and transparent estimation of the contamination, which can be used to delineate areas for soil improvement, remediation, or restricted area use, based on the decision-makers' probability safety requirement.

Data Collection↗
PubMed2000

Stochastic aspects and uncertainties in the prechemical and chemical stages of electron tracks in liquid water: a quantitative analysis based on Monte Carlo simulations.

A new physical module for the biophysical simulation code PARTRAC has recently been developed, based on newly derived electron inelastic-scattering cross-sections in liquid water. In the present work, two modules of PARTRAC describing the production, diffusion and interaction of chemical species were developed with the specific purpose of quantifying the role of the uncertainties in the parameters controlling the early stages of liquid water radiolysis. A set of values for such parameters was identified, and time-dependent yields and frequency distributions of chemical species produced by electrons of different energies were calculated. The calculated yields were in good agreement with available data and simulations, thus confirming the reliability of the code. As the primary-electron energy decreases down to 1 keV, the *OH decay kinetics were found to get faster, reflecting variations in the spatial distribution of the initial energy depositions. In agreement with analogous works, an opposite trend was found for energies of a few hundred eV, due to the very small number of species involved. The spreading effects shown at long times by *OH frequency distributions following 1 keV irradiation were found to be essentially due to stochastic aspects of the chemical stage, whereas for 1 MeV tracks the physical and pre-chemical stages also were found to play a significant role. Relevant differences in the calculated e(aq) -yields were found by coupling the physics of PARTRAC with descriptions of the pre-chemical and chemical stages adopted in different models. This indicates a strict interrelation of the various stages, and thus a strong dependence of the parameter values on the assumptions made for the preceding and subsequent stages of the process. Although equally acceptable results can be obtained starting from different assumptions, it is necessary to keep control of such uncertainties, since they can significantly influence the modeling of radical attack on DNA and, more generally, radiobiological damage estimation. This study confirms the need for new, independently derived data on specific steps of water radiolysis, to be included in comprehensive biophysical simulation codes.

Algorithms↗
PubMed2000

Projection of cancer risks from the Japanese atomic bomb survivors to the England and Wales population taking into account uncertainty in risk parameters.

Generalized relative risk models, with adjustments to the relative risk for time after exposure and age at exposure and incorporating a linear-quadratic dose response, were fitted to the latest (Life Span Study Report 12) Japanese atomic bomb survivor cancer mortality data using Bayesian Markov Chain Monte Carlo methods, taking account of random errors in the DS86 dose estimates. The resulting uncertainty distributions in the relative risk model parameters were used to derive uncertainties in population cancer risks for a current UK population. Following an assumed administered dose of 1 Sv, leukaemia mortality risks were estimated to be 1.93x10(-2) Sv(-1) (95% CI 1.14, 3.38), or 0.44 years of life lost Sv(-1) (95% CI 0.22, 0.94). Following an assumed administered dose of 1 Sv, solid cancer mortality risks were calculated to be 10.36x10(-2) Sv(-1) (95% CI 8.41, 12.42), or 1.38 years of life lost Sv(-1) (95% CI 1.11, 1.68). In general, solid cancer risks were very similar to those predicted by classical likelihood-based methods; however, leukaemia risks were somewhat higher, by 10-35%, than those predicted by classical likelihood-based methods. This is so in both cases, irrespective of whether or not adjustments are made in these likelihood-based fits for the effects of measurement errors, and the discrepancy for leukaemia tends to be greater at higher doses. Overall, cancer risks predicted by Bayesian Markov Chain Monte Carlo methods are similar to those derived by classical likelihood-based methods and which form the basis of established estimates of radiation-induced cancer risk.

Bayes Theorem↗
PubMed2005

Uncertainty analysis in pharmacokinetics and pharmacodynamics: application to naratriptan.

PURPOSE: The aim of the study was to predict pain relief of migraine in patients following naratriptan oral (tablet) administration by using uncertainty analysis. The analysis was based on phase I pharmacokinetic naratriptan data, sumatriptan pharmacodynamic data, and naratriptan preclinical (animal) potency information, together with general knowledge as to how migraine affects oral absorption. METHODS: A previously developed pharmacokinetic (PK)/pharmacodynamic (PD) model for naratriptan disposition and effect was used. The uncertain parameters in the model, which were associated with absorption and scaling between first-in-class compound sumatriptan and naratriptan, were modeled using fuzzy sets theory. Global sensitivity analysis was then used to investigate the impact of each PK/PD parameter on the responses. RESULTS: Acknowledging parametric uncertainty did not improve prediction of the probability of pain relief. Global sensitivity analysis demonstrated that predictions were heavily influenced by interindividual variability in pharmacodynamics, as the dose response relationship was relatively insensitive to the pharmacokinetics. CONCLUSIONS: To predict the probability of pain relief following oral (tablet) administration of naratriptan, a simple dose response, instead of the PK/PD model, would have yielded very similar predictions. The naratriptan PK/PD model may be improved by either refining the PD model or better still by specifying the interindividual error by additional data collecting with an improved design.

Algorithms↗
PubMed1980

A formalism for the assignment of uncertainties to clinical probabilities of hypothyroidism, euthyroidism, and hyperthyroidism.

A formalism for the optimal estimation of the probabilities of hypothyroidism, euthyroidism, and hyperthyroidism is outlined. The scheme provides a means for assigning uncertainties to the estimates. These uncertainties can be used to determine whether or not the difference between two probabilities is statistically significant. Clinical data are utilized to illustrate the method.

Computers↗
PubMed1990

Incorporating prior parameter uncertainty in the design of sampling schedules for pharmacokinetic parameter estimation experiments.

An experiment design procedure is proposed for nonlinear parameter estimation studies that formally incorporates prior parameter uncertainty. The design criterion derives from information theory considerations and involves an asymptotic interpretation of the expected posterior information provided by an experiment. A pharmacokinetic sample schedule design problem is used to illustrate and evaluate this information theoretic design strategy. The model considered is commonly used to describe the plasma concentration of a drug following its oral administration. The limitations and advantages of the proposed design procedure are discussed in relation to other previously reported design techniques for incorporating parameter uncertainty.

Administration, Oral↗
PubMed1996

The efficiency of different cue types for reducing spatial-frequency uncertainty.

Detection experiments reveal that performance is decreased when the signal's spatial frequency varies unpredictably across trials compared with conditions where it is held constant. However, this effect can more or less be compensated by presenting cues shortly before each trial. To investigate the efficiency of different sensory and symbolic cue types a signal-detection experiment with spatial-frequency uncertainty was carried out. The inter-stimulus interval between cue and signal as well as for the sensory cue types, the spatial overlap between cue and signal, was varied. The results reveal appreciable efficiency differences. While some cues were only of little help, others reduced uncertainty almost entirely. However, the efficiency of cues which were identical to the signals was severely restricted by forward-masking effects when they were presented at the same position as the signal.

Adult↗
PubMed1993

Uncertainty and health care spending by the poor: the health capital model revisited.

This short theoretical paper examines health care utilization by the poor in the context of Grossman's (1972) health capital model. Earlier work has shown that uncertainty can reduce the attractiveness to the poor of health capital investments. This paper demonstrates that uncertainty can also have precisely the opposite effect. That is, while there may be cases in which it is excessively risky for the poor to invest in their health, there may also be cases in which the poor can ill-afford the risks that arise from not making timely investments in their health.

Attitude to Health↗
PubMed1996

Randomized clinical trials in the presence of diagnostic uncertainty: implications for measures of efficacy and sample size.

Diagnostic uncertainty, particularly prior to the receipt of test results, is common in medicine. When randomized trials are being conducted to evaluate therapies in these situations, patients must be randomized in the absence of a definitive diagnosis. This article explores some of the implications of diagnostic uncertainty for the design and analysis of randomized clinical trials, using specific therapeutic examples to illustrate the important points.

Diagnosis↗
PubMed1994

Uncertainties in current estimates of emissions of ammonia in the United Kingdom.

Estimates of the emissions of ammonia have previously concentrated on animal husbandry sources from agricultural systems. Animal husbandry sources still constitute the major fraction of emissions of ammonia, but we have also considered the potential magnitude of other 'minor' sources, which may include coal combustion, waste incineration, road vehicles, sewage treatment plants, fertiliser manufacture and application, vegetation senescence and crop emissions, domestic pets, and human sources. Where possible, a provisional estimate of UK emissions from each of these sources is given. It is concluded that the potential magnitude of emissions from these 'minor' sources may make a significant contribution to the total emissions of ammonia to the atmosphere. On the basis of the available data, and the application of a range of emission factors to the UK situation, an additional annual emission potential lying in the range of approximately 80-140 ktonne year(-1) over and above that from animal husbandry has been calculated. The uncertainties in the emission estimates and instances in which a better resolution of sources is required are discussed. The emission factors used for animals in various inventories are reviewed and applied to the main UK agricultural animal populations. By using this approach, estimates of emissions from these sources range between 113 and 647 ktonne year(-1), which illustrates the uncertainties involved. It is suggested that our knowledge of the sources of ammonia, and their distribution, is far from complete.

Journal Article↗
PubMed1983

Regulatory history and experimental support of uncertainty (safety) factors.

A synthesis of available literature on uncertainty (safety) factors which are used to estimate acceptable daily intakes (ADIs) for toxicants is presented. This synthesis reveals reasonable qualitative biological premises, as well as specific biological data that support both the use and choice of these factors. A suggestion is made in order to derive a range of ADI. Research needs in various areas of uncertainty are also identified.

Animals↗
PubMed1990

Uncertainty in health risk assessments.

Considerable scientific evidence has accumulated in the area of risk assessment. Using physiologically based pharmacokinetic models and biologically based dose-response models, more precise estimates of risk are becoming available. Uncertainty analysis performed at three steps of the process will enhance a clearer understanding of the assumptions being made regarding a public health decision. Recommendations are made on how uncertainty in risk assessments can be addressed and the types of future research that are required to this end.

Animals↗
PubMed1982

Professional uncertainty and the problem of supplier-induced demand.

This paper discusses the puzzling problem of large differences in per capita use of certain common surgical procedures among neighboring populations, which by all available measures are quite similar in need for and access to services. The evidence reviewed here supports the hypothesis that variations occur to a large extent because of differences among physicians in their evaluation of patients (diagnosis) or in their belief in the value of the procedures for meeting patient needs (therapy). This hypothesis, which we call the professional uncertainty hypothesis, is germane to current controversies concerning the nature and extent of supplier influence on the demand for medical services. It is also important because of its implications for health regulatory policy. Our plan is to (1) review the relevance of the hypotheses for the supplier-induced demand controversy; (2) review the epidemiologic evidence on the nature and causes of variation; (3) examine patterns of use of common surgical procedures to illustrate the importance of supplier influence on utilization; and (4) consider some of the implications of the professional uncertainty hypotheses for public policy.

Behavior↗