Biomedical subjects

R L Winkler

Publications and source records attributed to R L Winkler.

4 recordsLinked to original sources

PubMed2001

Why Bayesian analysis hasn't caught on in healthcare decision making.

The objective of this paper is to discuss why Bayesian statistics is not used more in healthcare decision making and what might be done to increase the use of Bayesian methods. First, a case is made for why Bayesian analysis should be used more widely. Serious weaknesses of commonly used frequentist methods are discussed and contrasted with advantages of Bayesian methods. Next, the question of why Bayesian methods are not used more widely is addressed, considering both philosophical differences and practical issues. Contrary to what some might think, the practical issues are more important in this regard. Finally, some steps to encourage increased use of Bayesian methods in healthcare decision making are presented and discussed. These ideas are straightforward but are by no means trivial to implement, largely because it is difficult to fight tradition and make major paradigm shifts quickly. The primary needs are improved Bayesian training at the basic level (which means textbooks and other materials as well as training of those who teach at the basic level), procedures to make Bayesian analysis easier to understand and use (better software and standard methods for displaying and communicating Bayesian outputs will help here), and the education of decision makers about the advantages of Bayesian methods in important healthcare decision-making problems.

Bayes Theorem↗

PubMed2000

The first positive: computing positive predictive value at the extremes.

Computing the positive predictive value (PPV) of a wellknown test for a relatively common disease is a straight-forward exercise. However, in the case of a new test for a rare disorder; the extreme numbers involved-the very low prevalence of the disorder and the lack of previous false-positive results--make it difficult to compute the PPV. As new genetic tests become available in the next decade, more and more clinicians will have to answer questions about PPVs in cases with extreme prevalence, sensitivity, and specificity. This paper presents some tools for thinking about these calculations. First, a standard PPV calculation with rough estimates of the prevalence, sensitivity, and specificity is reviewed. The "zero numerator" problem posed by not having seen any false-positive results is then discussed, and a Bayesian approach to this problem is described. The Bayesian approach requires specification of a prior distribution that describes the initial uncertainty about the false-positive rate. This prior distribution is updated as new evidence is obtained, and the updated expected false-positive rate is used to calculate PPVs. The Bayesian approach provides appropriate and defensible PPVs and can be used to estimate failure rates for other rare events as well.

Bayes Theorem↗

PubMed1990

Are two (inexperienced) heads better than one (experienced) head? Averaging house officers' prognostic judgments for critically ill patients.

Inexperienced physicians may make prognostic judgments and management decisions about acutely ill patients in the absence of supervision. We hypothesized that mathematically combining judgments of junior and senior house officers might yield aggregate judgments as good as those made by experienced critical care attending physicians. We obtained independent quantitative assessments of the likelihood of in-hospital survival for 269 sequential intensive care unit admissions from the patient's intern or resident and the critical care fellow and attending physician on duty within 24 hours of admission, and compared these judgements with mortality data. By logistic regression, the residents' and fellows' judgments added independent prognostic information to each other (likelihood ratio chi 2, 7.6; df = 1). The junior house officers' and fellows' assessments were significantly less reliable than the attending physicians' by calibration curves, and by Brier scores, 0.126 and 0.127 vs 0.119. All physicians had good discriminating ability (receiver operating characteristic areas [SE] were 0.83 [0.03], 0.85 [0.03], 0.86 [0.03], respectively). A simple average of the residents' and fellows' judgments was slightly but significantly more reliable by calibration curve and by Brier score, 0.117, and as discriminating (ROC area = 0.85, SE = 0.03) as the attending physicians' judgments. Nonmedical studies have shown that averaging independent judgments may compensate for people's tendency to make extreme estimates, and may take advantage of their complementary abilities. This first medical application of this technique suggests that this form of voting by secret ballot may prove useful for health care teams making other judgments and decisions.

Clinical Competence↗

PubMed1983

Progression of myopia in youth: age of cessation.

Patient records of young myopes were collected from three optometry practices. An index of the age at which increases of myopia in young people cease was derived using four different graphical and statistical methods. The results suggest that myopia stops increasing earlier in females than in males. There is, however, a great deal of individual variability in cessation age. Some implications for clinical practice and clinical research are discussed.

Adolescent↗