Thyroid disease awareness is associated with high rates of identifying subjects with previously undiagnosed thyroid dysfunction.

BACKGROUND: Conventional screening for hypothyroidism is controversial. Although hypothyroidism is underdiagnosed, many organizations do not recommend screening, citing low disease prevalence in unselected populations. We studied attendees at a thyroid health fair, hypothesizing that certain patient characteristics would enhance the yield of testing. METHODS: We carried out an observational study of participants at a Michigan health fair that focused on thyroid disease. We collected patient-reported symptoms and demographics by questionnaire, and correlated these with the TSH values obtained through the health fair. RESULTS: 794 of 858 health fair attendees participated. Most were women, and over 40% reported a family history of thyroid disease. We identified 97 (12.2%) participants with previously unknown thyroid dysfunction. No symptom or combination of symptoms discriminated between hypothyroid and euthyroid individuals. Hypothyroid and euthyroid participants in the health fair reported each symptom with a similar prevalence (p > 0.01), a prevalence which was very high. In fact, when compared with a previously published case-control study that reported symptoms, the euthyroid health fair participants reported a higher symptom prevalence (range 3.9% to 66.3%, mean 31.5%), than the euthyroid individuals from the case-control study (range 2% to 54%, mean 17.4%). CONCLUSIONS: A high proportion of previously undiagnosed thyroid disease was identified at this health fair. We initially hypothesized symptoms would distinguish between thyroid function states. However, this was not the case in this health fair screening population. The prevalence of reported symptoms was similar and high in both euthyroid and hypothyroid participants. Because attendees were self-selected, it is possible that this health fair that focused on thyroid disease attracted participants specifically concerned about thyroid health. Despite the lack of symptom discrimination, the much higher prevalence of hypothyroidism in this study (12%) compared with the general population (<2%) suggests that screening may be appropriate and effective in certain circumstances such as thyroid health fairs.

Procedures performed by hospitalist and non-hospitalist general internists.

BACKGROUND: In caring exclusively for inpatients, hospitalists are expected to perform hospital procedures. The type and frequency of procedures they perform are not well characterized. OBJECTIVES: To determine which procedures hospitalists perform; to compare procedures performed by hospitalists and non-hospitalists; and to describe factors associated with hospitalists performing inpatient procedures. DESIGN: Cross-sectional survey. PARTICIPANTS: National sample of general internist members of the American College of Physicians. METHODS: We characterized respondents to a national survey of general internists as hospitalists and non-hospitalists based on time-activity criteria. We compared hospitalists and non-hospitalists in relation to how many SHM core procedures they performed. Analyses explored whether hospitalists' demographic characteristics, practice setting, and income structure influenced the performance of procedures. RESULTS: Of 1,059 respondents, 175 were classified as "hospitalists". Eleven percent of hospitalists performed all 9 core procedures compared with 3% of non-hospitalists. Hospitalists also reported higher procedural volumes in the previous year for 7 of the 9 procedures, including lumbar puncture (median of 5 by hospitalists vs. 2 for non-hospitalists), abdominal paracentesis (5 vs. 2), thoracenteses (5 vs. 2) and central line placement (5.5 vs. 3). Performing a greater variety of core procedures was associated with total time in patient care, but not time in hospital care, year of medical school graduation, practice location, or income structure. Multivariate analysis found no independent association between demographic factors and performing all 9 core procedures. CONCLUSIONS: Hospitalists perform inpatient procedures more often and at higher volumes than non-hospitalists. Yet many do not perform procedures that are designated as hospitalist "core competencies."

How do community practitioners decide whether to prescribe antibiotics for acute respiratory tract infections?

BACKGROUND: Overuse of antibiotics in the treatment of acute respiratory tract infection (ARI) contributes to the growing problem of antibiotic-resistant infections. OBJECTIVE: To identify factors that influence community practitioners to prescribe antibiotics and examine how they differ from the recommendations of the Centers for Disease Control and Prevention (CDC) guideline for treatment of ARI. DESIGN: Paper case vignette study using a fractional factorial design. PARTICIPANTS: One hundred one community practitioners and eight faculty members. MAIN MEASUREMENTS: We asked community practitioners to estimate how likely they would be to prescribe antibiotics in each of 20 cases of ARI and then used multiple regression to infer the importance weights of each of nine clinical findings. We then compared practitioners' weights with those of a panel of eight faculty physicians who evaluated the cases following the CDC guidelines rather than their own judgments. MAIN RESULTS: Practitioners prescribed antibiotics in 44.5% of cases, over twice the percentage treated by the panel using the CDC guidelines (20%). In deciding to prescribe antibiotic treatment, practitioners gave little or no weight to patient factors such as whether the patients wanted antibiotics. Although weighting patterns differed among practitioners, the majority (72%) gave the greatest weight to duration of illness. When illness duration was short, the rate of prescribing (20.1%) was the same as the rate of the faculty panel (20%). CONCLUSIONS: Based on hypothetical cases of ARI, community practitioners prescribed antibiotics at twice the rate of faculty following CDC practice guidelines. Practitioners were most strongly influenced by duration of illness. The effect of duration was strongest when accompanied by fever or productive cough, suggesting that these situations would be important areas for practitioner education and further clinical studies.

"Get smart Colorado": impact of a mass media campaign to improve community antibiotic use.

CONTEXT: Large-scale strategies are needed to reduce overuse of antibiotics in US communities. OBJECTIVES: To evaluate the impact of a mass media campaign-"Get Smart Colorado"-on public exposure to campaign, antibiotic use, and office visit rates. DESIGN: Nonrandomized controlled trial. SETTING: Two metropolitan communities in Colorado, United States. SUBJECTS: The general public, managed care enrollees, and physicians residing in the mass media (2.2 million persons) and comparison (0.53 million persons) communities. INTERVENTION: : The campaign consisting of paid outdoor advertising, earned media and physician advocacy ran between November 2002 and February 2003. PRINCIPAL MEASURES: Antibiotics dispensed per 1000 persons or managed care enrollees, and the proportion of office visits receiving antibiotics measured during 10 to 12 months before and after the campaign. RESULTS: After the mass media campaign, there was a 3.8% net decrease in retail pharmacy antibiotic dispenses per 1000 persons (P = 0.30) and an 8.8% net decrease in managed care-associated antibiotic dispenses per 1000 members (P = 0.03) in the mass media community. Most of the decline occurred among pediatric members, and corresponded with a decline in pediatric office visit rates. There was no change in the office visit prescription rates among pediatric or adult managed care members, nor in visit rates for complications of acute respiratory tract infections. CONCLUSIONS: A low-cost mass media campaign was associated with a reduction in antibiotic use in the community, and seems to be mediated through decreases in office visits rates among children. The campaign seems to be cost-saving.

Gender differences in patient-provider symptom agreement in reporting respiratory complaints on a questionnaire.

BACKGROUND: Men and women communicate differently, but it is unclear whether this influences health care outcomes. OBJECTIVE: Because women patients frequently choose women health care providers, we examined whether this preference was affected by communication styles. We focused on communication of disease-specific symptoms, hypothesizing that symptom agreement between women patients and women health care providers would be greater than between other patient-provider gender combinations. METHODS: Patients attending outpatient clinics were recruited as part of a study of respiratory illness at 7 university-affiliated sites during 3 consecutive influenza seasons (2000-2003). Individuals aged > or = 19 years were offered enrollment if they sought care for cold or flu symptoms at a participating study site. Patients were eligible to participate in the study if they reported any 1 of 6 symptoms: cough, runny nose, fever (subjective), muscle aches, sore throat, and/or exhaustion. Using separate questionnaires, patients and their health care providers recorded the patients' respiratory symptoms (as present or absent). Patients recorded their symptoms before visiting their health care provider, and providers recorded patient symptoms after the visit. Symptom agreement was compared using general estimating equations across all gender combinations. RESULTS: A total of 327 patients (220 women, 107 men) and 84 health care providers (37 women, 47 men) participated in the study. Overall symptom agreement for all patient-provider gender combinations was 81.9% (95% CI, 79.6%-84.2%). For each symptom, the observed agreement significantly exceeded the agreement expected by chance alone (P < 0.001 for all symptoms except "no energy," which was P = 0.023). The male-male pairing of patient and provider was more likely to agree on a symptom than were the other gender combinations, although not statistically significantly more so than the female-female pairing. CONCLUSIONS: In this survey of patients with respiratory illness, there was no significant difference in symptom agreement for most symptoms between the male-male and female-female patient-provider combinations. Based on these findings, symptom agreement alone does not explain why women patients select women health care providers.

What do the theories of Egon Brunswik have to say to medical education?

Every day physicians make judgments about patient management and diagnosis based on less than perfect information from many different sources. Judgment and decision-making research has taught us a great deal about such decisions, but these insights rarely find their way into the medical curriculum. One productive line of investigation in the study of judgment and decision making has followed the insights and theories developed by the psychologist, Egon Brunswik. His theories are becoming increasingly relevant to modern judgment problems. In this paper, I outline Brunswik's theories, trace their development over the last 50 years and speculate on what role they should play in medical education.

The declining number and variety of procedures done by general internists: a resurvey of members of the American College of Physicians.

BACKGROUND: A survey of general internist members of the American College of Physicians (ACP) in 1986 found that they did a large number and variety of procedures in their practices. Since then, changes in the practice of medicine, regulatory requirements, and availability of subspecialists may have affected the number and type of procedures done by internists. OBJECTIVE: To determine the number and types of procedures currently done by general internist members of the ACP compared with 1986. DESIGN: Mailed questionnaire. SETTING: National probability sample of general internists. PARTICIPANTS: Respondents to a national survey of 2500 general internist members of the ACP who were similar in characteristics to those who participated in the 1986 survey. Of the 1389 questionnaires that were returned, 990 were from general internists who had completed the survey. MEASUREMENTS: Responses to questions about procedures done and practice characteristics. RESULTS: The number and variety of procedures done by general internists has decreased dramatically. On average, the percentage of general internists doing each procedure now is less than half of that in 1986. The average number of different procedures done in practice decreased from 16 in 1986 to 7 in 2004. As in the 1986 survey, the number of procedures related strongly to personal and practice characteristics. Internists who practice in smaller towns and smaller hospitals do twice as many procedures on average as those in larger cities and larger hospitals. The number and variety of procedures done by internists also increased with greater time spent in total patient care. LIMITATIONS: The number and type of procedures were determined by self-reporting, not direct observation. CONCLUSIONS: Both the number and variety of procedures done by general internists have decreased considerably since 1986. As in the 1986 survey, general internists who practice in smaller cities and smaller hospitals and those who spend more hours in patient care perform more procedures. Recommendations and practices for internal medicine residency training in procedures should be reexamined in light of these changes.

Predictors of urinary tract infection based on artificial neural networks and genetic algorithms.

BACKGROUND: Among women who present with urinary complaints, only 50% are found to have urinary tract infection. Individual urinary symptoms and urinalysis are not sufficiently accurate to discriminate those with and without the diagnosis. METHODS: We used artificial neural networks (ANN) coupled with genetic algorithms to evolve combinations of clinical variables optimized for predicting urinary tract infection. The ANN were applied to 212 women ages 19-84 who presented to an ambulatory clinic with urinary complaints. Urinary tract infection was defined in separate models as uropathogen counts of > or =10(5) colony-forming units (CFU) per milliliter, and counts of > or =10(2) CFU per milliliter. RESULTS: Five-variable sets were evolved that classified cases of urinary tract infection and non-infection with receiver-operating characteristic (ROC) curve areas that ranged from 0.853 (for uropathogen counts of > or =10(5) CFU per milliliter) to 0.792 (for uropathogen counts of > or =10(2) CFU per milliliter). Predictor variables (which included urinary frequency, dysuria, foul urine odor, symptom duration, history of diabetes, leukocyte esterase on urine dipstick, and red blood cells, epithelial cells, and bacteria on urinalysis) differed depending on the pathogen count that defined urinary tract infection. Network influence analyses showed that some variables predicted urine infection in unexpected ways, and interacted with other variables in making predictions. CONCLUSIONS: ANN and genetic algorithms can reveal parsimonious variable sets accurate for predicting urinary tract infection, and novel relationships between symptoms, urinalysis findings, and infection.

Variability in emergency physician decision making about prescribing opioid analgesics.

STUDY OBJECTIVE: The purpose of this study is to determine what factors influence emergency physicians' decisions to prescribe an opioid analgesic for 3 common, painful conditions. METHODS: We developed items thought to influence the decision to prescribe an opioid analgesic through a review of the literature, expert consultation, and interviews with practicing emergency physicians. We developed a baseline vignette and items expected to influence the decision for each of the 3 conditions: migraine, back pain, and ankle fracture. We surveyed 650 physicians randomly selected from the American College of Emergency Physicians. The influence of individual items was explored through a univariate analysis of the response distribution. Patterns were assessed by analytically creating scales. RESULTS: We received responses from 398 (63%) of the 634 eligible physicians. Physicians' likelihoods of prescribing an opioid showed marked variability, with at least 10% of physicians saying they were unlikely and 10% of physicians saying they were likely to prescribe for each condition. Physician responses to individual pieces of clinical information, such as the patient requesting "something strong" for the pain, were also highly variable, with at least 10% of physicians saying they would be negatively influenced by this request and at least 10% saying they would be positively influenced by it. CONCLUSION: Even when faced with identical case scenarios, physicians' decisions to prescribe opioid analgesics are highly variable. Moreover, the same clinical information, such as a patient requesting a strong analgesic, changes the likelihood of prescribing opioids in opposite directions for different physicians.

Use of genetic algorithms for neural networks to predict community-acquired pneumonia.

BACKGROUND: Genetic algorithms have been used to solve optimization problems for artificial neural networks (ANN) in several domains. We used genetic algorithms to search for optimal hidden-layer architectures, connectivity, and training parameters for ANN for predicting community-acquired pneumonia among patients with respiratory complaints. METHODS: Feed-forward back-propagation ANN were trained on sociodemographic, symptom, sign, comorbidity, and radiographic outcome data among 1044 patients from the University of Illinois (the training cohort), and were applied to 116 patients from the University of Nebraska (the testing cohort). Binary chromosomes with genes representing network attributes, including the number of nodes in the hidden layers, learning rate and momentum parameters, and the presence or absence of implicit within-layer connectivity using a competition algorithm, were operated on by various combinations of crossover, mutation, and probabilistic selection based on network mean-square error (MSE), and separately on average cross entropy (ENT). Predictive accuracy was measured as the area under a receiver-operating characteristic (ROC) curve. RESULTS: Over 50 generations, the baseline genetic algorithm evolved an optimized ANN with nine nodes in the first hidden layer, zero nodes in the second hidden layer, learning rate and momentum parameters of 0.5, and no within-layer competition connectivity. This ANN had an ROC area in the training cohort of 0.872 and in the testing cohort of 0.934 (P-value for difference, 0.181). Algorithms based on cross-generational selection, Gray coding of genes prior to mutation, and crossover recombination at different genetic levels, evolved optimized ANN identical to the baseline genetic strategy. Algorithms based on other strategies, including elite selection within generations (training ROC area 0.819), and inversions of genetic material during recombination (training ROC area 0.812), evolved less accurate ANN. CONCLUSION: ANN optimized by genetic algorithms accurately discriminated pneumonia within a training cohort, and within a testing cohort consisting of cases on which the networks had not been trained. Genetic algorithms can be used to implement efficient search strategies for optimal ANN to predict pneumonia.

The effect of race/ethnicity and desirable social characteristics on physicians' decisions to prescribe opioid analgesics.

OBJECTIVE: Racial/ethnic disparities in physician treatment have been documented in multiple areas, including emergency department (ED) analgesia. The purpose of this study was to determine if physicians were predisposed to different treatment decisions based on patient race/ethnicity and if physicians' treatment predispositions changed when socially desirable information about the patient (occupation, socioeconomic status, and relationship with a primary care physician) was made explicit. METHODS: The authors developed three clinical vignettes designed to engage physicians' decision-making processes. The patient's race/ethnicity was included. Each vignette randomly included or omitted explicit socially desirable information. The authors mailed 5,750 practicing emergency physicians three clinical vignettes and a one-page questionnaire about demographic and practice characteristics. Chi-square tests of significance for bivariate analyses and multiple logistic regression were used for multivariate analyses. RESULTS: A total of 2,872 (53%) of the 5,398 potential physician subjects participated. Patient race/ethnicity had no effect on physician prescription of opioids at discharge for African Americans, Hispanics, and whites: absolute differences in rates of prescribing opioids at discharge were less than 2% for all three conditions presented. Making socially desirable information explicit increased the prescribing rates by 4% (95% CI = 0.1% to 8%) for the migraine vignette and 6% (95% CI = 3% to 8%) for the back pain vignette. CONCLUSIONS: Patient race/ethnicity did not influence physicians' predispositions to treatment plans in clinical vignettes. Even knowing that the patient had a high-prestige occupation and a primary care provider only minimally increased prescribing of opioid analgesics for conditions with few objective findings.

Can internal medicine residents master microscopic urinalysis? Results of an evaluation and teaching intervention.

PURPOSE: Although microscopic urinalysis (micro UA) is commonly used in clinical practice, and residents are trained in micro UA, proficiency in this procedure has not been studied. METHOD: In 1996-97, 38 residents in the University of Nebraska Medical Center's internal medicine (IM) residency program were evaluated on their technical ability to perform micro UA, and on their cognitive skills in recognizing common micro UA findings. After identifying deficits in the residents' cognitive competency, two educational interventions were applied and residents were tested after each intervention. RESULTS: A total of 24 residents (63%) correctly prepared the specimen for analysis (the technical portion). On the cognitive portion, only one of the 38 residents correctly identified 80% of all micro UA findings in the urinary sediment, although 11 (29%) residents identified UA findings specific to urinary tract infection (UTI). The first educational intervention did little to improve residents' performance. A second more intensive intervention resulted in 10 (45%) residents identifying 80% of all micro UA findings, and 19 (86%) residents correctly identifying UTI findings. CONCLUSIONS: Many residents were not proficient in performing micro UA, even after intensive educational interventions. Although micro UA is a simple procedure, residents' mastery cannot be assumed. Residency programs should assess competency in this procedure.

Prediction of community-acquired pneumonia using artificial neural networks.

BACKGROUND: Artificial neural networks (ANN) have been used in the prediction of several medical conditions but have not been previously used to predict pneumonia. The authors used ANN to predict the presence or absence of pneumonia among patients presenting to the emergency department with acute respiratory complaints and compared the results with those obtained using logistic regression modeling. METHODS: Feed-forward back-propagation ANN were trained on sociodemographic, symptom, sign, comorbidity, and radiographic outcome data among 1,044 patients from the University of Illinois (the training cohort) and were applied to 116 patients from the University of Nebraska (the testing cohort). ANN trained using different strategies were compared to each other and to main-effects logistic regression. Calibration accuracy was measured as mean square error and discrimination accuracy as the area under a receiver operating characteristic (ROC) curve. RESULTS: A 1 hidden-layer ANN trained using oversampling of pneumonia cases had an ROC area in the training cohort of 0.895, which was greater than the area of 0.840 for logistic regression (P = 0.026). This ANN had an ROC area in the testing cohort of 0.872, not significantly different from its area in the training cohort (P = 0.597). Operating at a threshold of 0.25, the ANN would have detected 94% to 95% of patients with pneumonia in the 2 cohorts while correctly excluding 39% to 50% of patients with other conditions. ANN trained using other strategies discriminated equally in the 2 cohorts but no better than did logistic regression. CONCLUSIONS: Among adults presenting with acute respiratory illness, ANN accurately discriminated patients with and without pneumonia and, under some circumstances, improved on the accuracy of logistic regression.

The relationship between treatment objectives and practice patterns in the management of urinary tract infections.

OBJECTIVE: To describe physicians' goals when treating uncomplicated urinary tract infections (UTIs) and the relationship between goals and practice patterns. STUDY DESIGN: Analysis of survey results. POPULATION: Primary care physicians. OUTCOMES MEASURED: Self-reported treatment objectives and practice patterns. RESULTS: Most physicians reported their UTI management was convenient for the patient (81.3%). Fewer stated they minimized patients' costs (53.4%), made an accurate diagnosis (56.7%), or avoided unnecessary antibiotics (40.9%). Physicians who stressed convenience or minimizing patient expenses were less likely to use many resources (urine culture, microscopic urinalysis, followup visits and tests, and prolonged antibiotic treatment) and more likely to use telephone treatment. Physicians who stressed accurate diagnoses or avoiding unnecessary antibiotics were more likely to use the same resources and less likely to use telephone treatment. CONCLUSION: UTI management goals vary across physicians and are associated with different clinical approaches. Differences in treatment objectives may help explain variations in practice patterns.

The effects of proficiency and bias on residents' interpretation of the microscopic urinalysis.

OBJECTIVE: This study aims to determine whether residents are influenced by clinical information when interpreting microscopic urinalysis (UA) and estimating the probability of a urinary tract infection (UTI), and to determine the accuracy and reliability of UA readings. DESIGN: Residents estimated the UA white blood cell count and the probability of a UTI in vignettes using a fractional factorial design, varying symptoms, gender, and the white blood cell count on preprepared urine slides. RESULTS: Individual-level results indicated a clinical information bias and poor accuracy. Seventeen of 38 residents increased the white blood cell count in response to female gender; 14 increased the white blood cell count in response to UTI symptoms. Forty-nine percent of the readings were inaccurate; agreement ranged from 50% to 67% for white and red blood cells and bacteria. CONCLUSION: Many residents gave inaccurate UA readings, and many readings varied with clinical information. A significant portion of residents needs assistance in objectively and accurately interpreting the UA.