Cost-effectiveness of screening for hereditary hemochromatosis.

BACKGROUND: Recent studies have estimated the prevalence of hereditary hemochromatosis to be 3 to 8 per 1000. Early detection and treatment can prevent disease manifestations and normalize life expectancy. We used decision analysis techniques to determine whether screening the population at large for hereditary hemochromatosis would be cost-effective. METHODS: We constructed a model to compare the cost and outcome of a strategy of performing screening transferrin saturation tests on cohorts of 30-year old men with that of awaiting symptomatic disease. Baseline estimates of disease prevalence and complication rates were based on the published literature. Costs of treatment were estimated based on prevailing local costs. Sensitivity analyses were then conducted to determine which variables had the most significant impact on the decision to screen. RESULTS: At our baseline estimates, the decision to screen was found to be a dominant strategy and resulted in cost saving. Sensitivity analysis showed that four variables had the most significant impact on the decision to screen: (1) the prevalence of hereditary hemochromatosis, (2) the probability of developing disease manifestations, (3) the cost of the screening test, and (4) the discount rate. Screening was a dominant strategy for asymptomatic men provided that the prevalence of hereditary hemochromatosis was at least 3 per 1000, the probability of developing disease manifestations was greater than 0.4, the test cost was less than $12, and the discount rate was less than 3%. Using more pessimistic estimates, the cost per life year saved was still less than that considered acceptable for many common medical interventions. CONCLUSION: Screening for hereditary hemochromatosis has a favorable cost-effectiveness ratio over a wide range of assumptions. We recommend that practitioners consider including a serum transferrin saturation test in their routine screening for asymptomatic white men.

Psychopharmacological characterisation of the successive negative contrast effect in rats.

RATIONALE: Successive negative contrast (SNC) describes a change in the behaviour of an animal following a downshift in the quantitative or qualitative value of an expected reward. This behavioural response has been hypothesised to be linked to affective state, with negative states associated with larger and/or prolonged shifts in behaviour. OBJECTIVE: This study has investigated whether different psychopharmacological treatments have dissociable actions on the SNC effect in rats and related these findings to their actions on different neurotransmitter systems and affective state. METHODS: Animals were trained to perform a nose-poke response to obtain a high-value food reward (four pellets). SNC was quantified during devalue sessions in which the reward was reduced to one pellet. Using a within-subject study design, the effects of acute treatment with anxiolytic, anxiogenic, antidepressant and dopaminergic drugs were investigated during both baseline (four pellets) or devalue sessions (one pellet). RESULTS: The indirect dopamine agonist, amphetamine, attenuated the SNC effect whilst the D1/D2 antagonist, alpha-flupenthixol, potentiated it. The antidepressant citalopram, anxiolytic buspirone and anxiogenic FG7142 had no specific effects on SNC, although FG7142 induced general impairments at higher doses. The α2-adrenoceptor antagonist, yohimbine, increased premature responding but had no specific effect on SNC. Results for the anxiolytic diazepam were mixed with one group showing an attenuation of the SNC effect whilst the other showed no effect. CONCLUSIONS: These data suggest that the SNC effect is mediated, at least in part, by dopamine signalling. The SNC effect may also be attenuated by benzodiazepine anxiolytics.

The value of diagnostic information to patients with suspected multiple sclerosis. Rochester-Toronto MRI Study Group.

OBJECTIVE: To determine the value of diagnostic information to patients with suspected multiple sclerosis (MS). Because treatment choices would be only minimally affected by earlier diagnosis for most patients with this clinical problem, this study assessed the "nondecisional" value of diagnosis. DESIGN: Prospective survey of patients before and after diagnostic workup, including imaging with magnetic resonance scanning. We assessed the effect of diagnostic information on patients' sense of well-being, as well as direct measures of the utility of information (using time trade-off and willingness-to-pay techniques). SETTING: Patients referred from primary care practices for diagnostic workup for suspected MS to neurology clinics and practices. PATIENTS: Sixty-eight individuals, mean age 37.5 years, 53 female and 15 male. Thirty-one patients were classified as having "probable MS," and 37 were classified as having "possible MS" by the examining neurologist before workup. MEASUREMENTS: Present and future health perception, uncertainty about diagnosis-prognosis, and level of anxiety. Willingness to pay for diagnostic information, quality of life as measured by the time trade-off technique, and psychological state of the patient before and after diagnosis. RESULTS: Diagnostic uncertainty fell significantly as a result of the diagnostic workup. Most patients (59/62) said that they were better off having received diagnostic information. Although anxiety seemed to be reduced by testing, overall anxiety levels did not decrease as much as anticipated. Patients also became less optimistic about their future health after testing. On average, patients were willing to forgo 4.5 quality-adjusted life days to receive an earlier diagnosis and their quality of life after diagnosis improved slightly. Subgroups of patients differed in their response to diagnostic information. Those in whom no definitive diagnosis emerged tend to be more anxious rather than being reassured by the "negative" workup. Individuals with "positive" workups became less anxious and expressed favorable feelings about the diagnostic workup even though they often faced a chronic disease. CONCLUSIONS: Overall, the diagnostic workup seemed to benefit patients and improve their sense of well-being. However, whether the effects were beneficial or not depended on the results of the diagnostic workup itself. In clinical practice the decision to undergo testing in situations in which definitive treatment is unavailable should be individualized. The potential for negative as well as positive consequences should be recognized.

Cystic fibrosis carrier screening: knowledge and attitudes of prenatal care providers.

We are conducting a trial of population carrier screening for cystic fibrosis (CF), targeting pregnant and nonpregnant patients of prenatal care providers. We first enlisted providers by presenting a description of the trial to the obstetrical staffs of the five Rochester, New York, hospitals having delivery services. Of the 124 prenatal care providers (111 obstetricians and 13 family practitioners) with delivery privileges at the five hospitals, only 81 (65%) attended one of our presentations. Providers who attended lacked knowledge about CF screening and counseling and expressed divergent attitudes about prenatal diagnosis for carrier women having test-negative partners. Of the 79 providers completing an attitude questionnaire, 68 (86%) were willing to offer carrier screening to all their patients if educational materials, testing, and counseling were all provided without charge. After visiting participating physicians' offices to orient their staff, we reached two additional conclusions. First, in considering whether to offer CF carrier screening to their patients, prenatal care providers are less concerned about imperfect test sensitivity, false reassurance of those testing negative, or discrimination against those testing positive than about time required to answer patients' questions if they screen and about legal liability if they do not. Second, some providers are more resistant to offering screening to nonpregnant patients than to pregnant patients, not because they believe that the timing is less appropriate, but because nonpregnant patients do not routinely receive an advance mailing, have phlebotomy, or return for follow-up. Our experience raises concerns about the willingness and capability of prenatal care providers to translate advances in molecular medicine into prenatal screening services.

Death and taxes. An opportunity for substitution.

The risks of fatal vehicle crash for young drivers rise precipitously with more drinking, reaching a 100-fold increase in risk for youths with 6+ drinks. Considerable external damage arises from drunk driving, providing firm logic for government intervention. If the 'cost' of an alcohol tax is the foregone consumer surplus of drinkers, then the cost per life saved using higher alcohol taxes is less than +10,000 per life at low taxes, even ignoring the lives of the drinking drivers. Thus, alcohol taxes are one of the cheapest possible life saving techniques available. Preliminary evidence suggests that youthful drinking drivers badly under-perceive the risks of their own behavior. This increases the measure of 'external damage' and hence the optimal tax for alcoholic beverages. It may be impossible to administer an 'optimal tax' on alcohol, but 'second-best' taxes appear to lie in the range of 25 to 40 percent or more.

Regulatory intensity and hospital cost growth.

This article parameterizes and examines the regulatory intensity of New York's all-payer rate setting system. The model, using hospital level data, compares the effects of specific features of rate-setting designed to promote cost containment. Two indicators measuring regulatory intensity were examined; the extent of hospital-specific disallowances, and how frequently the base year was adjusted (the degree of prospectivity). The results indicate that both the degree of prospectivity and the extent of disallowances importantly affect cost growth. Hospitals, when constrained, primarily achieved cost savings through reductions in non-medical personnel.

Economic foundations of cost-effectiveness analysis.

To address controversies in the applications of cost-effectiveness analysis, we investigate the principles underlying the technique and discuss the implications for the evaluation of medical interventions. Using a standard von Neumann-Morgenstern utility framework, we show how a cost-effectiveness criterion can be derived to guide resource allocation decisions, and how it varies with age, gender, income level, and risk aversion. Although cost-effectiveness analysis can be a useful and powerful tool for resource allocation decisions, a uniform cost-effectiveness criterion that is applied to a heterogeneous population level is unlikely to yield Pareto-optimal resource allocations.

Good technologies gone bad: how and why the cost-effectiveness of a medical intervention changes for different populations.

Cost-effectiveness (CE) ratios vary considerably, not only across interventions, but within single interventions. Using a simple decision-tree model of the treat-vs no-treat decision to organize the analysis, four potential errors leading to these within-treatment differences in CE ratios are identified. These errors arise from estimates relating to 1) prior probabilities of disease; 2) treatment efficacies; 3) costs of treatment; and 4) patient preferences. Systematic biases, where present, suggest overuse of medical interventions. For diagnostic tests, two additional potential sources of error are considered (using a simple decision tree incorporating both test and treat decisions). These involve 5) sensitivity and specificity of the diagnostic test and 6) inappropriate choice of "cutoff" to determine abnormal patients, in part arising from errors in estimating prior probability of disease.

Estimating diagnostic test accuracy using a "fuzzy gold standard".

This study uses Monte Carlo methods to analyze the consequences of having a criterion standard ("gold standard") that contains some error when analyzing the accuracy of a diagnostic test using ROC curves. Two phenomena emerge: 1) When diagnostic test errors are statistically independent from inaccurate ("fuzzy") gold standard (FGS) errors, estimated test accuracy declines. 2) When the test and the FGS have statistically dependent errors, test accuracy can become overstated. Two methods are proposed to eliminate the first of these errors, exploring the risk of exacerbating the second. Both require a probabilistic (rather than binary) gold-standard statement (e.g., probability that each case is abnormal). The more promising of these, the "two-truth" method, selectively eliminates those cases where the gold standard is most ambiguous (probability near 0.5). When diagnostic test and FGS errors are independent, this approach can eliminate much of the downward bias caused by FGS error, without meaningful risk of overstating test accuracy. When the test and FGS have dependent errors, the resultant upward bias can cause test accuracy to be overstated, in the most extreme cases, even before the offsetting "two-truth" approach is employed.

Focusing technology assessment using medical decision theory.

Combining medical decision theory and epidemiologic information, the authors have developed a strategy to assess diagnostic technologies. For any patient, patient utilities with new diagnostic information are compared with the preferred fallback action absent that diagnostic information. After determination of whether the expected value of diagnostic information (EVDI) justifies its cost, the method adds across the eligible population to determine whether the global EVDI justifies the technology's deployment, employing a screen (Hurdle 1) that assumes that the diagnostic device has perfect accuracy. This preliminary evaluation relies on published data on treatment efficacy, population probabilities of illness, etc., but not on new clinical trials. If the technology is not sufficiently cost-effective, even with this optimistic assumption, the strategy recommends against its use. Otherwise, the next step is Hurdle II, in which the critical clinical studies, identified by the decision-theory model, are undertaken. These commonly include measuring the actual diagnostic accuracy of a device, with which the cost-effectiveness is recalculated. These studies in general do not require randomized controlled trials.

Targeting assessments of magnetic resonance imaging in suspected multiple sclerosis.

Decision-analytic methods can be valuable for targeting research in technology assessment. They can indicate whether further evaluation of a technology is warranted, and if so, which variables are key determinants of its clinical utility and cost-effectiveness. This approach was tested on a salient issue--whether magnetic resonance imaging (MR) should be used in evaluating patients with mild neurologic symptoms who might have multiple sclerosis (MS). The authors developed a decision-analytic model to assess the expected utility and costs associated with immediately using MR in this situation, compared with waiting for further symptoms to emerge before testing. Sensitivity analyses demonstrated that priorities for technology assessment research include estimating the value of information to patients in resolving uncertainty, evaluating the impact on patients of being labeled with a diagnosis of MS, and measuring the test characteristics of MR.

The association between interdisciplinary collaboration and patient outcomes in a medical intensive care unit.

We prospectively studied the relationship between interdisciplinary collaboration and patient outcomes in the medical intensive care unit (MICU) using nurses' and residents' reports of amount of collaboration involved in making decisions about transferring patients from the MICU to a unit with a less intense level of care. Either readmission to the MICU or death was considered a negative patient outcome. Nurses' reports of collaboration were significantly (p = 0.02) and positively associated with patient outcome, controlling for severity of illness. Patient predicted risk of negative outcome decreased from 16%, when the nurse reported no collaboration in decision making, to 5% when the process was fully collaborative. There was an interaction of collaboration with availability of alternative choices in the transfer decision-making situation. When alternatives were available, collaboration was more strongly associated with patient outcome. There was no significant relationship between residents' reports of collaboration and patient outcomes. The correlation between amount of collaboration reported by nurses and residents about the same decisions was quite low (r = 0.10).

Bug/drug resistance. Sometimes less is more.

Increased use of antibiotics in any community increases the risks that future bacterial strains will resist the effects of current antibiotics. The consequences of a resistant bacterial strain include costs for more expensive and powerful drugs, additional hospital days, and on rare occasion, death. A key to understanding the importance of this problem is better knowledge about the rate that resistance increases and persists as antibiotic use rates increase. Using the scant evidence available in the literature, this study conducts a sensitivity analysis to calculate the unrecognized costs of antibiotic use annually in the United States under various possible circumstances. For the estimated 150 million annual antibiotic prescriptions, the unrecognized costs appears to be at least $.1 billion, and they may exceed $30 billion in the worst case. The estimates of the burden caused by bacterial resistance to antibiotics depend heavily on unknown parameters, including the rate that resistance occurs, the dose-resistance patterns through time, the frequency of inappropriate use of antibiotics, and the frequency with which death occurs due to a resistant bacterial infection. New studies in each of these areas are needed to improve our understanding of the extent of the resistance problem.