Tinea infections (often called ringworm) are caused by dermatophyte fungi and classified by the body site involved. Tinea corporis and tinea capitis are most common in prepubertal children, and tinea cruris, tinea pedis, and tinea unguium (most common type of onychomycosis) are more likely in adolescents and adults. Clinical diagnosis without testing may be unreliable because other conditions can resemble tinea infections (eg, tinea corporis can be confused with eczema, and onychomycosis with dystrophic toenails from repeated low-level trauma or psoriasis). Tinea corporis, tinea cruris, and tinea pedis generally respond to inexpensive topical antifungal agents, but oral antifungal agents may be indicated for patients with extensive disease, lack of response to topical treatment, immunocompromise, or hair follicle involvement (eg, tinea capitis). Oral terbinafine is considered first-line therapy for tinea capitis and onychomycosis because it is well tolerated, effective, and inexpensive. Emerging tinea infections may be more severe than classic tinea infections and generally do not improve with first-line topical or oral antifungals. These infections may require prolonged oral antifungal therapy and specialized diagnostic testing. Antifungal stewardship, including avoiding the use of combination antifungal-corticosteroids, should be emphasized to optimize outcomes and help prevent resistance.

Introduction: Little is known about trends in the incidence of dependent adult abuse (DAA). Objectives: To determine the annual incidence of DAA in Iowa from 1984 to 2023. Trends in abuse rates were evaluated for their associations with calendar year, number of caseworkers and abuse laws, political party, and unemployment. Methods: Iowa Department of Health and Human Services DAA reports, investigations, and substantiations were analyzed. Report data were available for 10 years. Investigation and substantiation data were available for 40 years. Long-term trends over time were described and associations between abuse rates and number of caseworkers and abuse laws, political party, and unemployment were explored. Results: Both investigations and substantiations increased from 50 to 182 per 100 000 adults and 17 to 38 per 100 000 adults between 1984 and 2023, respectively. Increasing calendar year and Democratic party majority in the Iowa legislature were positively and independently associated with investigated and substantiated abuse rates. An inverse correlation between the proportion of reports that were investigated and the proportion of investigations that were substantiated (Spearman’s rho = −.81; P < .01) was found. Conclusions: During the 40-year study period, investigated and substantiated cases of DAA in Iowa have been steadily increasing.

Simply having safe staffing levels is not enough for therapeutic settings, the congress audience was told.

Although many authors have addressed the ethics of placebo-controlled trials, few have addressed the ethics of noninferiority trials.[1][1]–[3][2] The purpose of this commentary is to explore some of the ethical issues associated with noninferiority trials. We posit that there are several ethical

BioethicsVolume 32, Issue 7 p. 402-404 GUEST EDITORIAL Empathy is a poor foundation on which to base legislative medical policy Mark A. Graber, Corresponding Author Mark A. Graber markagraber@gmail.com orcid.org/0000-0001-7632-9572 Correspondence Mark A. Graber, Department of Emergency Medicine, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, 1008 RCP, Iowa City, Iowa 52333, USA. Email: markagraber@gmail.comSearch for more papers by this authorJohn W. Ely, John W. ElySearch for more papers by this author Mark A. Graber, Corresponding Author Mark A. Graber markagraber@gmail.com orcid.org/0000-0001-7632-9572 Correspondence Mark A. Graber, Department of Emergency Medicine, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, 1008 RCP, Iowa City, Iowa 52333, USA. Email: markagraber@gmail.comSearch for more papers by this authorJohn W. Ely, John W. ElySearch for more papers by this author First published: 23 August 2018 https://doi.org/10.1111/bioe.12508Citations: 1Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article.Citing Literature Volume32, Issue7September 2018Pages 402-404 RelatedInformation

BACKGROUND AND OBJECTIVESPhysicians often accuse their peers of being "black clouds" if they repeatedly have more than the average number of hospital admissions while on call. Our purpose was to determine whether the black-cloud phenomenon is real or explainable by random variation.METHODSWe analyzed hospital admissions to the University of Iowa family medicine service from July 1, 2010 to June 30, 2015. Analyses were stratified by peer group (eg, night shift attending physicians, day shift senior residents). We analyzed admission numbers to find evidence of black-cloud physicians (those with significantly more admissions than their peers) and white-cloud physicians (those with significantly fewer admissions). The statistical significance of whether there were actual differences across physicians was tested with mixed-effects negative binomial regression.RESULTSThe 5-year study included 96 physicians and 6,194 admissions. The number of daytime admissions ranged from 0 to 10 (mean 2.17, SD 1.63). Night admissions ranged from 0 to 11 (mean 1.23, SD 1.22). Admissions increased from 1,016 in the first year to 1,523 in the fifth year. We found 18 white-cloud and 16 black-cloud physicians in simple regression models that did not control for this upward trend. After including study year and other potential confounding variables in the regression models, there were no significant associations between physicians and admission numbers and therefore no true black or white clouds.CONCLUSIONSIn this study, apparent black-cloud and white-cloud physicians could be explained by random variation in hospital admissions. However, this randomness incorporated a wide range in workload among physicians, with potential impact on resident education at the low end and patient safety at the high end.

Taking specific steps to make diagnosis more reliable is something we should all consider. We will never be perfect, but we owe it to our patients and our profession to improve. A diagnostic checklist is included.

In this article we review current evidence on strategies to evaluate diagnostic error solutions, discuss the methodological challenges that exist in investigating the value of these strategies in patient care, and provide recommendations for methods that can be applied in investigating potential solutions to diagnostic errors. These recommendations were developed iteratively by the authors based upon initial discussions held during the Research Summit of the 7th Annual Diagnostic Error in Medicine Conference in September 2014. The recommendations include the following elements for designing studies of diagnostic research solutions: (1) Select direct and indirect outcomes measures of importance to patients, while also practical for the particular solution; (2) Develop a clearly-stated logic model for the solution to be tested; (3) Use rapid, iterative prototyping in the early phases of solution testing; (4) Use cluster-randomized clinical trials where feasible; (5) Avoid simple pre-post designs, in favor of stepped wedge and interrupted time series; (6) Leverage best practices for patient safety research and engage experts from relevant domains; and (7) Consider sources of bias and design studies and their analyses to minimize selection and information bias and control for confounding. Areas of diagnostic error mitigation research identified for further attention include: role of competing diagnoses, understanding the impacts of organizational culture, timing of diagnosis, and sequencing of research studies. Future research will likely require novel clinical, health services, and qualitative research methods to address the age-old problem of arriving at an accurate diagnosis.

Only about half of eligible individuals undergo colon cancer screening. We have limited knowledge about the patient beliefs that adversely affect screening decisions and about which beliefs might be amenable to change through education. As part of a clinical trial, 641 rural Iowans, aged 52 to 79 years, reported their beliefs about colon cancer screening in response to a mailed questionnaire. Consenting subjects were randomized into four groups, which were distinguished by four levels of increasingly intensive efforts to promote screening. Two of the groups received mailed educational materials and completed a follow-up questionnaire, which allowed us to determine whether their beliefs about screening changed following the education. We also completed a factor analysis to identify underlying (latent) factors that might explain the responses to 33 questions about readiness, attitudes, and perceived barriers related to colon cancer screening. The strongest predictors of a patient's stated readiness to be screened were a physician's recommendation to be screened (1 point difference on 10-point Likert scale, 95 % confidence interval [CI], 0.5 to 1.6 point difference), a family history of colon cancer (0.85-point Likert scale difference, 95 % CI, 0.1 to 1.6), and a belief that health-care decisions should be mostly left to physicians rather than patients (Spearman correlation coefficient 0.21, P < .001). Of the 33 questionnaire items about screening beliefs, 11 (33 %) changed favorably following the educational intervention. In the factor analysis, the 33 items were reduced to 8 underlying factors, such as being too busy to undergo screening and worries about screening procedures. We found a limited number of underlying factors that may help explain patient resistance to colon cancer screening.

Background: Many diagnostic errors are caused by premature closure of the diagnostic process. To help prevent premature closure, we developed checklists that prompt physicians to consider all reasonable diagnoses for symptoms that commonly present in primary care.Methods: We enrolled 14 primary care physicians and 100 patients in a randomized clinical trial. The study took place in an emergency department (5 physicians) and a same-day access clinic (9 physicians). The physicians were randomized to usual care vs. diagnostic checklist. After completing the history and physical exam, checklist physicians read aloud a differential diagnosis checklist for the chief complaint. The primary outcome was diagnostic error, which was defined as a discrepancy between the diagnosis documented at the acute visit and the diagnosis based on a 1-month follow-up phone call and record review.Results: There were 17 diagnostic errors. The mean error rate among the seven checklist physicians was not significantly different from the rate among the seven usual-care physicians (11.2% vs. 17.8%; p=0.46). In a post-hoc subgroup analysis, emergency physicians in the checklist group had a lower mean error rate than emergency physicians in the usual-care group (19.1% vs. 45.0%; p=0.04). Checklist physicians considered more diagnoses than usual-care physicians during the patient encounters (6.5 diagnoses [SD 4.2] vs. 3.4 diagnoses [SD 2.0], p < 0.001).Conclusions: Checklists did not improve the diagnostic error rate in this study. However further development and testing of checklists in larger studies may be warranted.

Tinea infections are caused by dermatophytes and are classified by the involved site. The most common infections in prepubertal children are tinea corporis and tinea capitis, whereas adolescents and adults are more likely to develop tinea cruris, tinea pedis, and tinea unguium (onychomycosis). The clinical diagnosis can be unreliable because tinea infections have many mimics, which can manifest identical lesions. For example, tinea corporis can be confused with eczema, tinea capitis can be confused with alopecia areata, and onychomycosis can be confused with dystrophic toenails from repeated low-level trauma. Physicians should confirm suspected onychomycosis and tinea capitis with a potassium hydroxide preparation or culture. Tinea corporis, tinea cruris, and tinea pedis generally respond to inexpensive topical agents such as terbinafine cream or butenafine cream, but oral antifungal agents may be indicated for extensive disease, failed topical treatment, immunocompromised patients, or severe moccasin-type tinea pedis. Oral terbinafine is first-line therapy for tinea capitis and onychomycosis because of its tolerability, high cure rate, and low cost. However, kerion should be treated with griseofulvin unless Trichophyton has been documented as the pathogen. Failure to treat kerion promptly can lead to scarring and permanent hair loss.

As physicians, we take pride in our ability to generate, from memory, a complete differential diagnosis for our patients' presenting symptoms. We expect this of ourselves and our trainees, but we do not do it reliably. Studies have found that the most common cause of diagnostic error is the physician's failure to consider the correct diagnosis as a possibility. Other professionals, like airline pilots and nuclear plant operators, have accepted the fallibility of their memories and have learned how to ensure reliable completion of critical tasks by using checklists. But our culture in medicine glorifies physicians who complete the critical task of diagnosis using their memories and disparages those who cheat by referring to a list. Recent studies have supported the use of checklists in the operating room and intensive care unit, but so far they have not been used to make diagnosis more reliable. This essay explores a possible use for differential-diagnosis checklists by describing the author's experience with them in a primary care clinic.

Background: Many adults have not been screened for colon cancer, a potentially preventable cause of death.Methods: This was a randomized controlled trial conducted between December 2008 and April 2011 to improve CRC screening in 16 rural family physician offices. Subjects due for CRC screening were randomized within each practice to 1 of 4 groups: (1) usual care; (2) physician chart reminder; (3) physician chart reminder, mailed education, CRC reminder magnet, and fecal immunochemical test (FIT) (mailed education/FIT); or (4) all the preceding plus a structured telephone call to the patient from project staff to provide education, assess interest in screening, explain the screening tests, and address barriers (mailed education/FIT plus phone call). The main outcome was completion of any CRC screening.Results: This study enrolled 743 patients. CRC screening was completed by 17.8% in the usual care group, 20.5% in the chart reminder group, 56.5% in the mailed education/FIT group, and 57.2% in the mailed education/FIT plus phone call group. We found no effect from the chart reminder compared with usual care (odds ratio [OR], 1.2; 95% confidence interval [CI], 0.7-2.0); and a beneficial effect from the mailed education/FIT (OR, 6.0; 95% CI, 3.7-9.6) and the mailed education/FIT plus phone call (OR, 6.2; 95% CI, 3.8-9.9). Both FIT and colonoscopy rates increased significantly in both mailed education groups.Conclusion: CRC screening rates increased significantly among patients who were overdue for screening after they received mailed educational materials and a FIT. The addition of a phone call did not further increase screening rates.

Background: Diagnostic errors occur more commonly than other kinds of errors, they are more likely to harm patients, and they are more likely to be preventable. Little is known about the presenting complaints, initial (incorrect) diagnoses, and physicians' personal lessons learned related to diagnostic errors. Methods: In 2009 and 2010, we invited a random sample of 200 family physicians, 200 general internists, and 200 general pediatricians practicing in Iowa to describe an important diagnostic error using a 1-page, mailed questionnaire. The data were analyzed using quantitative and qualitative methods. Results: The response rate was 34% (202 of 600 physicians). Common presenting complaints included abdominal pain (n = 27 of 202 patients, 13%); fever (n = 19; 9%); and fatigue (n = 15, 7%). Common initial (incorrect) diagnoses included benign viral infections (n = 35, 17%); musculoskeletal pain (n = 21, 10%); and chronic obstructive pulmonary disease/asthma (n = 13, 6%). The 202 responding physicians described 254 personal lessons learned, which we used to develop a taxonomy of 24 generic lessons. Three common lessons were: (1) consider diagnosis X in patients presenting with symptom Y (n = 37 lessons, 15%; eg, “Any discomfort above the umbilicus may be coronary artery disease.”); (2) look beyond the initial, most obvious diagnosis (n = 26 lessons, 10%); and (3) be alert to atypical presentations of disease (n = 24 lessons, 9%). Conclusions: In this study, diagnostic errors often were preceded by common symptoms and common, relatively benign initial diagnoses. The lessons learned often involved various aspects of broadening the differential diagnosis.

Introduction: Only about half of all eligible Americans have been screened for colorectal cancer (CRC). The objective of this study was to test whether mailed educational materials and a fecal immunochemical test (FIT), with or without a scripted telephone reminder, led to FIT testing. In addition, we compared changes in attitudes toward, readiness for, and barriers to screening from baseline to follow-up after education about screening. Methods: Subjects due for CRC screening were recruited from 16 Iowa Research Network family physician offices. Half of the subjects were randomized to receive mailed written and DVD educational materials, along with a FIT, either with or without a telephone call designed to encourage screening and address barriers. Subjects completed surveys regarding their attitudes and readiness for CRC screening at baseline and after education about screening. The main outcome was whether the subject completed FIT testing. Results: A total of 373 individuals received educational materials (including a FIT) and 231 (62%) returned a posteducation survey. The mean age was 61.2 years; 52% were women, 99% were white, 39% had a high school education or less, 39% had a total family income of less than $40,000, and 7% had no insurance. The written materials were read by 82%, understood by 91% (of those who read them), and 82% felt their knowledge was increased. The DVD was viewed by 67%, understood by 94% of those who viewed it, and 86% felt the DVD increased their knowledge. Compared with baseline, individuals reported being significantly more likely to bring up CRC screening at their next doctor's visit (P < .0001) and being more likely to be tested for CRC in the next 6 months (P < .0001). Comparing baseline with follow-up, summary attitude scores improved (P < .0001), readiness scores improved (P < .0001), and there were fewer barriers (P = .034, Wilcoxon signed rank). The FIT return rate increased from 0% to 45.2% in the education alone group and from 0% to 48.7% for the group receiving education plus the telephone call (P < .0001 for each group individually and overall when compared with Medicare beneficiaries in Iowa). Conclusions: Mailing FIT kits with easy-to-understand educational materials improved attitudes toward screening and dramatically increased CRC screening rates among patients who were due for screening in a practice-based research network. A telephone call addressing barriers to screening did not result in increased FIT testing compared with mailed education alone.

Background: Only about half of eligible Americans are adherent with colorectal cancer (CRC) screening. Because patients generally access CRC screening via their primary care physicians, interventions to improve screening should be tested in the primary care setting. This article describes the recruitment and baseline characteristics of patients from 16 practice-based research network practices for a study to improve CRC screening. Methods: A total of 8327 invitations were mailed to patients of these practices, and 1685 returned consent forms and baseline surveys. Results: Of those who consented, 942 were up to date with screening, which indicates that office databases were unable to provide information about those who were already screened. The 743 due for screening were younger (mean age, 61 vs. 63 years), less likely to have an immediate family member with CRC (11% vs. 19%), less likely to have Medicare (29% vs. 40%), more likely to have no insurance (5% vs. 1%), and less likely to report a physician/nurse recommendation for CRC screening (63% vs. 92%) for all comparisons. Conclusions: Our experiences for this practice-based research network randomized clinical intervention trial may be useful to others. Practice and patient recruitment processes were onerous with institutional review board issues, poorly prepared patient databases, and discarding of mail by the US Postal Service.

CONTEXT:Community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) is a major pathogen among skin and soft tissue infections (SSTIs). Most CA-MRSA infections are managed initially on an outpatient basis. It is critical that primary care clinicians recognize and appropriately treat patients suspected of having such infections.OBJECTIVE:To identify and evaluate best methods and procedures for primary care clinicians to manage skin and soft tissue infections.DESIGN, SETTING, AND PATIENTS:Preintervention/postintervention study in eight Iowa Research Network offices conducted between October 2007 and August 2010. We reviewed medical records of 216 patients with SSTI before a set of interventions (preintervention) and 118 patients after the intervention (postintervention).INTERVENTIONS:Included a focus group meeting at each office, distribution of a modified Centers for Disease Control and Prevention (CDC) algorithm, "Outpatient Management of MRSA Skin and Soft Tissue Infections," education handouts, and an office policy for patients with skin infections.MAIN OUTCOME MEASURES:Proportion of subjects who were prescribed an antibiotic that would cover MRSA at the initial visit and proportion who were prescribed an antibiotic that would cover MRSA at any time.RESULTS:Three hundred sixty-eight forms (244 preintervention and 124 postintervention) were returned; 216 (89%) preintervention forms and 118 (95%) postintervention forms were usable. Multivariable logistic regression models found statistically significant and independent factors associated with MRSA coverage at the initial visit included being in the postintervention rather than the preintervention group, having an abscess component compared with cellulitis alone, having a culture sent, being prescribed two or fewer antibiotics, and not being hospitalized.CONCLUSIONS:The CDC algorithm was feasible for offices to use. Following a discussion of SSTI management in the outpatient setting, use of MRSA coverage increased both initially and overall. Thus, involving clinicians in a discussion about guidelines rather than simply providing guidelines or a didactic session may be a useful way to change physician practices.

Diagnostic errors are common and can often be traced to physicians' cognitive biases and failed heuristics (mental shortcuts). A great deal is known about how these faulty thinking processes lead to error, but little is known about how to prevent them. Faulty thinking plagues other high-risk, high-reliability professions, such as airline pilots and nuclear plant operators, but these professions have reduced errors by using checklists. Recently, checklists have gained acceptance in medical settings, such as operating rooms and intensive care units. This article extends the checklist concept to diagnosis and describes three types of checklists: (1) a general checklist that prompts physicians to optimize their cognitive approach, (2) a differential diagnosis checklist to help physicians avoid the most common cause of diagnostic error--failure to consider the correct diagnosis as a possibility, and (3) a checklist of common pitfalls and cognitive forcing functions to improve evaluation of selected diseases. These checklists were developed informally and have not been subjected to rigorous evaluation. The purpose of this article is to argue for the further investigation and revision of these initial attempts to apply checklists to the diagnostic process. The basic idea behind checklists is to provide an alternative to reliance on intuition and memory in clinical problem solving. This kind of solution is demanded by the complexity of diagnostic reasoning, which often involves sense-making under conditions of great uncertainty and limited time.

OBJECTIVE:Clinical questions are often long and complex and take many forms. We have built a clinical question answering system named AskHERMES to perform robust semantic analysis on complex clinical questions and output question-focused extractive summaries as answers. DESIGN:This paper describes the system architecture and a preliminary evaluation of AskHERMES, which implements innovative approaches in question analysis, summarization, and answer presentation. Five types of resources were indexed in this system: MEDLINE abstracts, PubMed Central full-text articles, eMedicine documents, clinical guidelines and Wikipedia articles. MEASUREMENT:We compared the AskHERMES system with Google (Google and Google Scholar) and UpToDate and asked physicians to score the three systems by ease of use, quality of answer, time spent, and overall performance. RESULTS:AskHERMES allows physicians to enter a question in a natural way with minimal query formulation and allows physicians to efficiently navigate among all the answer sentences to quickly meet their information needs. In contrast, physicians need to formulate queries to search for information in Google and UpToDate. The development of the AskHERMES system is still at an early stage, and the knowledge resource is limited compared with Google or UpToDate. Nevertheless, the evaluation results show that AskHERMES' performance is comparable to the other systems. In particular, when answering complex clinical questions, it demonstrates the potential to outperform both Google and UpToDate systems. CONCLUSIONS:AskHERMES, available at http://www.AskHERMES.org, has the potential to help physicians practice evidence-based medicine and improve the quality of patient care.

Although it is important to begin the evaluation of generalized rash with an inclusive differential diagnosis, the possibilities must be narrowed down by taking a focused history and looking for key clinical features of the rash. Part I of this two-part article lists the common, uncommon, and rare causes of generalized rashes. In part II, the clinical features that help distinguish these rashes are described. These features include key elements of the history (e.g., travel, environmental exposures, personal or family history of atopy); characteristics of individual lesions, such as color, size, shape, and scale; areas of involvement and sparing, with particular attention to palms, soles, face, nails, sun-exposed areas, and extensor and flexor surfaces of extremities; pruritic or painful lesions; systemic symptoms, especially fever; and dermatologic signs, such as blanching, and the Koebner phenomenon.