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PubMed2002

Referral letters in oral medicine: standard versus non-standard letters.

Usually referral letters are the only means of communication between general practitioners and specialists in the health area. However, they are inadequate if important basic data are omitted. The aim of this study was to compare the content of standard and non-standard letters. A total of 1956 files from the Oral Medicine Service were consecutively evaluated (March 1996 to September 2000). Key items were considered for analysis and the results were stored in a database using the Epinfo 6.04 program. The chi2 test (alpha=0.05) was applied to the results. Of the 1956 files examined, 34% (662) had a referral letter, 31% of them being standard letters and 69% non-standard letters. Most standard letters (87%) were from professionals of public health institutions. Most percent discrepancies between standard and non-standard letters were observed for patient address (14.90 vs 1.32%), patient age (54.81 vs 9.47%), chief complaint (32.21 vs 8.37%), fundamental lesion (29.33 vs 13.66%), and symptoms (27.81 vs 15.42%). Statistically significant differences were observed for patient age, professional referring the patient, chief complaint, and site of the lesion. The quality and quantity of the information differed significantly between the two types of letters. The standard letters were more complete and contained information commonly absent in the non-standard letters. We suggest the use of standard letters for improving the quality of communication among professionals.

Chi-Square Distribution↗
PubMed1998

Fielding standardized patients in primary care settings: lessons from a study using unannounced standardized patients to assess preventive care practices.

OBJECTIVES: To document detection and suspicion rates of unannounced standardized patients visiting community-based practices. DESIGN: Primary care physicians were recruited to participate in a study using standardized patients. Four standardized patient scenarios were used. SETTING: Community-based primary care physicians' practices in southern Ontario between September 1994 and August 1995. STUDY PARTICIPANTS: Sixty-two primary care physicians. MAIN OUTCOME MEASURES: A 'believability' questionnaire completed after all four standardized patients had visited the practices. RESULTS: Of the primary care physicians approached, 50% (62) agreed to participate. Twenty-one per cent of all visits were suspected as standardized patient encounters. Forty-six per cent suspected one or more standardized patients. Only five physicians (8%) suspected all four standardized patients. Reasons for suspecting standardized patients were associated with the characteristics of the physician's practices, the physician's practice profile and the standardized patient cover story. CONCLUSION: The portrayal of asymptomatic patients seeking a new primary care physician presents unique challenges. Carefully constructed cover stories, and detailed knowledge of the local area and of the practices of the participating physicians is required to allow standardized patients cases to be tailored to fit into primary care settings without arousing suspicion.

Adult↗
PubMed2002

[Roaming through methodology. XXXVIII. Common misconceptions involving standard deviation and standard error].

Standard deviation and standard error have a clear mutual relationship, but at the same time they differ strongly in the type of information they supply. This can lead to confusion and misunderstandings. Standard deviation describes the variability in a sample of measures of a variable, for instance the variability in ages of the members of a group. It represents the degree to which the values are scattered around their mean: the higher the standard deviation the wider the spread. The value of the standard deviation is not influenced by the number of observations in the sample. The standard error is always used for extrapolation: to estimate the intervals between which the true value of a statistic will occur, based on a sample of observations and with a certain degree of certainty. When interpreting a standard error, it is important to know which statistic (mean, percentage, relative risk, odds ratio) is to be estimated. The value of the standard error is strongly influenced by the number of observations in the sample: the bigger the sample, the smaller the standard error and the more accurate the estimation. To avoid confusion it is recommended to report no longer the standard error of the mean but instead the confidence intervals of the mean to estimate the true value of the mean.

Confidence Intervals↗
PubMed2002

U.S. military weight standards: what percentage of U.S. young adults meet the current standards?

PURPOSE: Each branch of the U.S. military enforces maximum allowable weight standards that must be met to join the military. We wanted to determine what percentage of U.S. civilians between the ages of 17 and 20 years met these standards. METHODS: The height and weight of adults between the ages of 17 and 20 years, as measured in the nationally representative sample of the Third National Health and Nutritional Examination Survey, were matched against the height/weight charts of the military services. The percentage of men and women in each population subgroup who weighed more than the maximum allowable weight was calculated. RESULTS: The percentage of young adults whose weight exceeded the military weight standard ranged from 13% to 18% for men and 17% to 43% for women. When stratified by race, 15% to 20% of non-Hispanic white men and 12% to 36% of non-Hispanic white women were over the weight standards, 11% to 19% of non-Hispanic black men and 35% to 56% of non-Hispanic black women were over the standards, and 13% to 24% of Mexican American men and 26% to 55% of Mexican American women exceeded the military weight standards. CONCLUSION: A large percentage of the young adult population from which the U.S. volunteer military is drawn is over the military weight standards, particularly among minorities, who comprise a disproportionately large proportion of the military. There is a marked discrepancy between the weight standards for men and women, and the appropriateness of these standards needs to be assessed.

Adolescent↗
PubMed2003

Standard reference material for Her2 testing: report of a National Institute of Standards and Technology-sponsored Consensus Workshop.

A workshop was sponsored by the National Institute of Standards and Technology, the Cancer Diagnosis Program of the National Cancer Institute, the Food and Drug Administration, and the College of American Pathologists to address the need for a reference material for Her2 gene protein testing. It was agreed that such a standard was desirable and necessary to ensure the reliability of Her2 testing to qualify patients for trastuzumab therapy. Two standards consisting of well characterized cell lines will be produced, 1 that will be a National Institute of Standards and Technology-certifiable standard, and 1 that will be a commercially developed standard for use in all Her2 testing. It was also agreed that all Her2 testing must be performed on samples fixed only in 10% buffered formalin, as specified in the Food and Drug Administration-approved testing methods. Participants agreed to plan strategies to educate pathologists, clinicians, and laboratories about the need and use of such a standard. A National Committee for Clinical Laboratory Standards guideline for the use of the standard reference material will be created to facilitate this process.

Cell Line, Tumor↗
PubMed2005

['Gold standard', not 'golden standard'].

In medical literature, both 'gold standard' and 'golden standard' are employed to describe a reference test used for comparison with a novel method. The term 'gold standard' in its current sense in medical research was coined by Rudd in 1979, in reference to the monetary gold standard. In the same way that the monetary gold standard allowed for the comparison of different currencies, the medical gold standard allowed for the comparison of different diagnostic tests. Whereas the gold standard was never regarded as infallible, the incorrect term 'golden standard' implies a level of perfection that is unattainable in medical science. Consequently, the correct term should be 'gold standard'.

Diagnostic Tests, Routine↗
PubMed1998

Standardizing flow cytometry: a classification system of fluorescence standards used for flow cytometry.

The growing number of standards commercially available in the field of flow cytometry makes it difficult to know which standards to use to obtain a desired level of quality assurance. A classification system of fluorescence standards has been developed on the basis of their physical characteristics. In turn, these physical characteristics determine the ability of the specific standards to perform selected functions, such as alignment, target referencing, compensation, and calibration. Knowing the properties and limitations of specific standards will help flow cytometer users to select the appropriate standard for the application that they will be performing, especially in regard to intra- and interlaboratory quality assurance. Common protocols used in conjunction with specific classifications of reference standards can provide unified analysis regions or window of analysis across different instruments and/or laboratories. In addition, specific classifications of calibration standards can help select those standards that will provide independent and direct comparison of instrument performance parameters, especially in studies involving multiple laboratories. Knowledge and understanding of the classification system can guide flow cytometer users in more efficient and accurate instrument setup and quality control when conducting research, as well as clinical applications.

Calibration↗