OBJECTIVE: To determine the value of conjunctival pallor in ruling in or ruling out the presence of severe anemia (hemoglobin < or = 90 g/L) and to determine the interobserver agreement in assessing this sign. DESIGN: Patients were prospectively assessed for pallor by at least one of three observers. All observations were made without information of the patient's hemoglobin value or of another observer's assessment. SETTING: Tertiary-care, university-affiliated teaching hospital. PATIENTS: Three hundred and two medical and surgical inpatients. MEASUREMENTS AND MAIN RESULTS: Likelihood ratios (LRs) calculated for conjunctival pallor present, borderline, and absent were as follows: pallor present, LR 4.49 (95% confidence interval [CI] 1.80, 10.99); pallor borderline, LR 1.80 (95% CI 1.18, 2.62); pallor absent, LR 0.61 (95% CI 0.44, 0.80). Kappa scores of interobserver agreement between paired observers were 0.75 and 0.54. CONCLUSIONS: The presence of conjunctival pallor, without other information suggesting anemia, is reason enough to perform a hemoglobin determination. The absence of conjunctival pallor is not likely to be of use in ruling out severe anemia. With well-defined criteria, interobserver agreement is good to very good.
The authors evaluated the accuracy of clinical impressions and Mini-Mental State Exam scores for assessing patient capacity to consent to major medical treatment, relative to expert psychiatric assessment. Consecutive medical inpatients (N = 63) facing a decision about major medical treatment received a clinical impression of capacity from their treating physician and the Standardized Mini-Mental State Exam (SMMSE); 48 received independent psychiatric assessment of capacity. Analyses revealed that both clinical impressions and SMMSE scores were generally inaccurate in determining capacity, although all 23 participants with a clinical impression of "definitely capable" were found capable by the psychiatrist. Given the importance of assessing capacity to consent to major medical treatment, better approaches to the clinical assessment of capacity are required. Several strategies are discussed.
OBJECTIVES: To examine funding priorities assigned by health ministry officials when choosing between clinical programs that offer similar overall benefits distributed in different ways (e.g. large gains for a few versus small gains for many), and to compare the relative magnitude of any distributional bias to age biases. METHODS: A survey consisting of paired hypothetical health care programs was mailed to the 135 most senior officials of the Health Ministry in Ontario, Canada (population 11.5 million). Respondents were asked to assume they were members of a panel allocating a fixed sum of money to one of two programs in each pair. All program descriptions included the number of persons affected each year by a given disease and the average survival gains from the hypothetical programs. Some scenarios also mentioned the side-effects associated with programs and/or the average age of the beneficiaries. RESULTS: Four respondents had retired/died. Of 131 eligible respondents, 80/131 (61%) provided usable responses. Asked to choose between providing large benefits to a few citizens and small benefits to a great many, 23% (95% CI: 14%, 33%) of respondents were unable to decide, but 55.8% (95% CI: 47%, 70%) favored providing large benefits to fewer patients. Eliminating the 23% unable to decide, 47/62 or 76% (CI 63%, 86% expressed a distributional preference. With a smaller distributional discrepancy, indecision increased, with 35% of respondents having no preference and the remainder split almost evenly between the two programs. Other scenarios showed that health officials' pro-youth biases were only slightly larger than their distributional preferences and that distributional preferences were magnified when combined with minor differences in average ages of beneficiaries. CONCLUSIONS: A substantial minority of health care decision-makers had difficulty choosing between programs with similar overall gains and distributional differences--a result consistent with the utilitarian assumptions of cost-effectiveness analysis. However, when distributional differences were large, decision-makers clearly favored large gains for a few beneficiaries rather than small gains for many. Policy analysts should explicitly weigh distributional issues along with aggregate health gains when addressing resources allocation problems.