Burden and trajectory of social needs after breast cancer diagnosis at a safety-net hospital.

PURPOSE: Unmet social needs pose barriers to cancer care, contributing to adverse outcomes and health inequities. A better understanding of how social needs change after cancer diagnosis can inform more effective, equity-focused interventions. METHODS: In this study, we examined self-reported social needs at 0, 3, and 6 months after a breast cancer diagnosis in a racially diverse, multilingual sample (n = 222) enrolled in patient navigation intervention at an urban safety-net hospital. At each timepoint, respondents completed surveys about social needs related to employment, disability benefits, housing and utilities, and personal and family stability. RESULTS: Over three-quarters (78%, n = 175) reported ≥ 1 social need, and 46% (n = 102) reported ≥ 3 social needs. The most frequently reported need was housing and utilities (64%, n = 142), followed by employment (40%, n = 90). Individuals from minoritized groups more frequently reported an increased number of social needs over time, compared with their White counterparts (p = 0.02). CONCLUSION: Our findings suggest that despite navigation, many cancer patients from historically underrepresented populations continue to experience social concerns over the first 6 months of treatment. Further research, conducted with historically underrepresented populations in research, is needed to better understand the social needs of breast cancer patients to inform effective and equitable interventions.

Performance of three screening tools to predict COVID-19 positivity in emergency department patients.

BACKGROUND: COVID-19 symptoms vary widely. This retrospective study assessed which of three clinical screening tools-a nursing triage screen (NTS), an ED review of systems (ROS) performed by physicians and physician assistants and a standardised ED attending (ie, consultant) physician COVID-19 probability assessment (PA)-best identified patients with COVID-19 on a subsequent reverse transcription PCR (RT-PCR) confirmation. METHODS: All patients admitted to Boston Medical Center from the ED between 27 April 2020 and 17 May 2020 were included. Sensitivity, specificity and positive predictive value (PPV) and negative predictive value (NPV) were calculated for each method. Logistic regression assessed each tool's performance. RESULTS: The attending physician PA had higher sensitivity (0.62, 95% CI 0.53 to 0.71) than the NTS (0.46, 95% CI 0.37 to 0.56) and higher specificity (0.76, 95% CI 0.72 to 0.80) than the NTS (0.71, 95% CI 0.66 to 0.75) and ED ROS (0.62, 95% CI 0.58 to 0.67). Categorisation as moderate or high probability on the ED physician PA was associated with the highest odds of having COVID-19 in regression analyses (adjusted OR=4.61, 95% CI 3.01 to 7.06). All methods had a low PPV (ranging from 0.26 for the ED ROS to 0.40 for the attending physician PA) and a similar NPV (0.84 for both the NTS and the ED ROS, and 0.89 for the attending physician PA). CONCLUSION: The ED attending PA had higher sensitivity and specificity than the other two methods, but none was accurate enough to replace a COVID-19 RT-PCR test in a clinical setting where transmission control is crucial. Therefore, we recommend universal COVID-19 testing prior to all admissions.

Patient navigation to address sociolegal barriers for patients with cancer: A comparative-effectiveness study.

BACKGROUND: Sociolegal barriers to cancer care are defined as health-related social needs like affordable healthy housing, stable utility service, and food security that may be remedied by public policy, law, regulation, or programming. Legal support has not been studied in cancer care. METHODS: The authors conducted a randomized controlled trial of patients who had newly diagnosed cancer at a safety-net medical center in Boston from 2014 through 2017, comparing standard patient navigation versus enhanced navigation partnered with legal advocates to identify and address sociolegal barriers. English-speaking, Spanish-speaking, or Haitian Creole-speaking patients with breast and lung cancer were eligible within 30 days of diagnosis. The primary outcome was timely treatment within 90 days of diagnosis. Secondary outcomes included patient-reported outcomes (distress, cancer-related needs, and satisfaction with navigation) at baseline and at 6 months. RESULTS: In total, 201 patients with breast cancer and 19 with lung cancer enrolled (response rate, 78%). The mean patient age was 55 years, 51% of patients were Black and 22% were Hispanic, 20% spoke Spanish and 8% spoke Haitian Creole, 73% had public health insurance, 77% reported 1 or more perceived sociolegal barrier, and the most common were barriers to housing and employment. Ninety-six percent of participants with breast cancer and 73% of those with lung cancer initiated treatment within 90 days. No significant effect of enhanced navigation was observed on the receipt of timely treatment among participants with breast cancer (odds ratio, 0.88; 95% CI, 0.17-4.52) or among those with lung cancer (odds ratio, 4.00; 95% CI, 0.35-45.4). No differences in patient-reported outcomes were observed between treatment groups. CONCLUSIONS: Navigation enhanced by access to legal consultation and support had no impact on timely treatment, patient distress, or patient needs. Although most patients reported sociolegal barriers, few required intensive legal services that could not be addressed by navigators. LAY SUMMARY: In patients with cancer, the experience of sociolegal barriers to care, such as unstable housing, utility services, or food insecurity, is discussed. Addressing these barriers through legal information and assistance may improve care. This study compares standard patient navigation versus enhanced navigation partnered with legal advocates for patients with breast and lung cancers. Almost all patients in both navigation groups received timely care and also reported the same levels of distress, needs, and satisfaction with navigation. Although 75% of patients in the study had at least 1 sociolegal barrier identified, few required legal advocacy beyond what a navigator who received legal information and coaching could provide.

Calculating power for the Finkelstein and Schoenfeld test statistic for a composite endpoint with two components.

The Finkelstein and Schoenfeld (FS) test is a popular generalized pairwise comparison approach to analyze prioritized composite endpoints (eg, components are assessed in order of clinical importance). Power and sample size estimation for the FS test, however, are generally done via simulation studies. This simulation approach can be extremely computationally burdensome, compounded by increasing number of composite endpoints and with increasing sample size. Here we propose an analytical solution to calculate power and sample size for commonly encountered two-component hierarchical composite endpoints. The power formulas are derived assuming underlying distributions in each of the component outcomes on the population level, which provide a computationally efficient and practical alternative to the standard simulation approach. Monte Carlo simulation results demonstrate that performance of the proposed power formulas are consistent with that of the simulation approach, and have generally desirable objective properties including robustness to mis-specified distributional assumptions. We demonstrate the application of the proposed formulas by calculating power and sample size for the Transthyretin Amyloidosis Cardiomyopathy Clinical Trial.

Racial equity in linkage to inpatient opioid use disorder treatment in patients that received emergency care.

OBJECTIVES: Opioid use disorder (OUD) is a national epidemic, and Black and Hispanic patients are less likely to receive treatment when compared to white patients. In this study, race was used as a proxy to assess potential effects of racism on the referral process for OUD treatment. Our primary aim was to examine whether Black or Hispanic patients experienced increased barriers to inpatient OUD detoxification (detox) placement at a community-integrated, substance use disorder support program based in an emergency department (ED). Our secondary aim was to determine if Black and Hispanic patients were more likely to have >3 referrals. METHODS: This retrospective cohort study was conducted at a large urban safety-net hospital and included patients seen in the ED from July 2018 to September 2019 with ICD-10 codes for an opioid-related visit and who sought placement to inpatient detox. A generalized linear mixed model controlling for multiple visits, age, sex, insurance, time, day of week, and time of year was used to assess the association between race/ethnicity and hypothesized barriers to placement. The proportion of patients with >3 visits for referral to inpatient detox was compared between Black and Hispanic patients and white patients using a chi-squared test. RESULTS: We identified 1733 encounters from 782 unique patients seeking connection to inpatient detox for OUD. Of the 1733 encounters, 45% were among Black and Hispanic patients. Hispanic and Black men had significantly lower odds of having a barrier to inpatient OUD detox than white men (OR = 0.734, 95% CI 0.542-0.995). No significant difference was found for Hispanic and Black women (OR = 1.212, 95% CI 0.705-2.082). More Black and Hispanic patients experienced >3 referrals to inpatient detox compared to white patients (19.2% vs 12.9%, p = 0.016). CONCLUSIONS: This study suggests in the context of near-universal health insurance coverage, an ED-based OUD support program staffed by diverse community members can mitigate inequities in access to inpatient detox. However, the increased number of ED visits for OUD detox placement by Black and Hispanic patients suggests racial inequities in OUD treatment exist after linkage to care. Additional research should explore the causes, specifically structural and interpersonal racism, and determine solutions to address racial inequities in detox placement as well as maintenance in treatment programs.

Measuring rater bias in diagnostic tests with ordinal ratings.

Diagnostic tests are frequently reliant upon the interpretation of images by skilled raters. In many clinical settings, however, the variability observed between experts' ratings plays a detrimental role in the degree of confidence in these interpretations, leading to uncertainty in the diagnostic process. For example, in breast cancer testing, radiologists interpret mammographic images, while breast biopsy results are examined by pathologists. Each of these procedures involves elements of subjectivity. We propose here a flexible two-stage Bayesian latent variable model to investigate how the skills of individual raters impact the diagnostic accuracy of image-related testing in large-scale medical testing studies. A strength of the proposed model is that the true disease status of a patient within a reasonable time frame may or may not be known. In these studies, many raters each contribute classifications on a large sample of patients using a defined ordinal grading scale, leading to a complex correlation structure between ratings. Our modeling approach considers the different sources of variability contributed by experts and patients while accounting for correlations present between ratings and patients, in contrast to currently available methods. We propose a novel measure of a rater's ability (magnifier) that, in contrast to conventional measures of sensitivity and specificity, is robust to the underlying prevalence of disease in the population, providing an alternative measure of diagnostic accuracy across patient populations. Extensive simulation studies demonstrate lower bias in estimation of parameters and measures of accuracy, and illustrate outperformance of the proposed model when compared with existing models. Receiver operator characteristic curves are derived to assess the diagnostic accuracy of individual experts and their overall performance. Our proposed modeling approach is applied to a large breast imaging study for known disease status and a uterine cancer dataset for unknown disease status.

A Comparison of Etomidate, Ketamine, and Methohexital in Emergency Department Rapid Sequence Intubation.

BACKGROUND: Rapid sequence intubation (RSI) is routinely used for emergent airway management in the emergency department (ED). It involves the use of induction, and paralytic agents help facilitate endotracheal tube placement. OBJECTIVE: In response to a previous national drug shortage resulting in the use of alternative induction agents for RSI, we describe the effectiveness and safety of ED RSI with ketamine or methohexital compared with etomidate. METHODS: We conducted a retrospective, single-center observational study from March 1-August 31, 2012 describing RSI with etomidate, ketamine, and methohexital. All adult patients undergoing RSI in the ED who received etomidate prior to its shortage and methohexital or ketamine during the shortage were included. RESULTS: The study included 47, 9, and 26 patients in the etomidate, ketamine, and methohexital groups, respectively. Successful intubation on the first attempt occurred in 74.5%, 55.6%, and 73.1% of the etomidate, ketamine, and methohexital groups, respectively. The mean number of intubation attempts and time to intubation seemed to be similar in all groups. At least three intubation attempts were required in 22.2% and 7.7% of the ketamine and methohexital groups, respectively, compared with none in the etomidate group. Two aspirations were observed in the etomidate group. CONCLUSION: Methohexital and etomidate had similar rates of successful intubation on the first attempt and seem to be more effective than ketamine. Etomidate may reduce the need for three or more intubation attempts. Larger, prospective studies are needed to determine if ketamine or methohexital are more effective than etomidate for RSI.

Measuring intrarater association between correlated ordinal ratings.

Variability between raters' ordinal scores is commonly observed in imaging tests, leading to uncertainty in the diagnostic process. In breast cancer screening, a radiologist visually interprets mammograms and MRIs, while skin diseases, Alzheimer's disease, and psychiatric conditions are graded based on clinical judgment. Consequently, studies are often conducted in clinical settings to investigate whether a new training tool can improve the interpretive performance of raters. In such studies, a large group of experts each classify a set of patients' test results on two separate occasions, before and after some form of training with the goal of assessing the impact of training on experts' paired ratings. However, due to the correlated nature of the ordinal ratings, few statistical approaches are available to measure association between raters' paired scores. Existing measures are restricted to assessing association at just one time point for a single screening test. We propose here a novel paired kappa to provide a summary measure of association between many raters' paired ordinal assessments of patients' test results before versus after rater training. Intrarater association also provides valuable insight into the consistency of ratings when raters view a patient's test results on two occasions with no intervention undertaken between viewings. In contrast to existing correlated measures, the proposed kappa is a measure that provides an overall evaluation of the association among multiple raters' scores from two time points and is robust to the underlying disease prevalence. We implement our proposed approach in two recent breast-imaging studies and conduct extensive simulation studies to evaluate properties and performance of our summary measure of association.

Marginal analysis of ordinal clustered longitudinal data with informative cluster size.

The issue of informative cluster size (ICS) often arises in the analysis of dental data. ICS describes a situation where the outcome of interest is related to cluster size. Much of the work on modeling marginal inference in longitudinal studies with potential ICS has focused on continuous outcomes. However, periodontal disease outcomes, including clinical attachment loss, are often assessed using ordinal scoring systems. In addition, participants may lose teeth over the course of the study due to advancing disease status. Here we develop longitudinal cluster-weighted generalized estimating equations (CWGEE) to model the association of ordinal clustered longitudinal outcomes with participant-level health-related covariates, including metabolic syndrome and smoking status, and potentially decreasing cluster size due to tooth-loss, by fitting a proportional odds logistic regression model. The within-teeth correlation coefficient over time is estimated using the two-stage quasi-least squares method. The motivation for our work stems from the Department of Veterans Affairs Dental Longitudinal Study in which participants regularly received general and oral health examinations. In an extensive simulation study, we compare results obtained from CWGEE with various working correlation structures to those obtained from conventional GEE which does not account for ICS. Our proposed method yields results with very low bias and excellent coverage probability in contrast to a conventional generalized estimating equations approach.

A paired kappa to compare binary ratings across two medical tests.

Agreement between experts' ratings is an important prerequisite for an effective screening procedure. In clinical settings, large-scale studies are often conducted to compare the agreement of experts' ratings between new and existing medical tests, for example, digital versus film mammography. Challenges arise in these studies where many experts rate the same sample of patients undergoing two medical tests, leading to a complex correlation structure between experts' ratings. Here, we propose a novel paired kappa measure to compare the agreement between the binary ratings of many experts across two medical tests. Existing approaches can accommodate only a small number of experts, rely heavily on Cohen's kappa and Scott's pi measures of agreement, and thus are prone to their drawbacks. The proposed kappa appropriately accounts for correlations between ratings due to patient characteristics, corrects for agreement due to chance, and is robust to disease prevalence and other flaws inherent in the use of Cohen's kappa. It can be easily calculated in the software package R. In contrast to existing approaches, the proposed measure can flexibly incorporate large numbers of experts and patients by utilizing the generalized linear mixed models framework. It is intended to be used in population-based studies, increasing efficiency without increasing modeling complexity. Extensive simulation studies demonstrate low bias and excellent coverage probability of the proposed kappa under a broad range of conditions. Methods are applied to a recent nationwide breast cancer screening study comparing film mammography to digital mammography.

Central venous catheter placement after ultrasound guided peripheral IV placement for difficult vascular access patients.

OBJECTIVES: Ultrasound guided peripheral intravenous catheters (USPIV) are frequently utilized in the Emergency Department (ED) and lead to reduced central venous catheter (CVC) placements. USPIVs, however, are reported to have high failure rates. Our primary objective was to determine the proportion of patients that required CVC after USPIV. Our secondary objective was to determine if classic risk factors for difficult vascular access were predictive of future CVC placement. METHODS: We performed a retrospective review for patients treated at a large academic hospital. Patients were identified by electronic health record and were restricted to age older than 21 years, had received USPIV, and admittance. Exclusion criteria included an existing CVC. Descriptive statistics, t-tests, chi-square proportions, and logistic regression were performed to test associations. RESULTS: Of 363 eligible patients, 20 were excluded allowing for 343 for analysis. Of 343, 45 (13.1% 95% CI 9.9-17.1%) required CVC after USPIV. For secondary outcomes, no expected characteristics (diabetes, end-stage renal disease, IV drug abuse, peripheral vascular disease, or sickle cell disease) were predictive of CVC placement. The only predictive variables were admission to ICU/stepdown and length of stay. Each additional day of hospitalization had an OR 1.11 (95% CI 1.06-1.16%) of having a CVC placed. CONCLUSION: Of those admitted after USPIV placement, approximately 7 out of every 8 patients did not require a subsequent CVC. Of the nearly 1 in 8 patients that required a CVC, factors associated with CVC placement were admission to a higher level of care and length of stay.

Point-of-care influenza testing does not significantly shorten time to disposition among patients with an influenza-like illness.

INTRODUCTION: Availability of anti-viral agents and need to isolate infected patients increases the need to confirm the diagnosis of influenza before determining patient disposition. OBJECTIVES: We sought to determine if time-to-disposition (TTD) was shorter among patients tested for influenza using an Emergency Department (ED) Point-of-care (POC) test compared to core laboratory (lab) test and to determine difference in antibiotic use between groups. METHODS: We prospectively enrolled a convenience sample of ED patients for whom influenza testing was ordered during influenza season 2017. Participants were randomized to POC or lab. Data collected included demographics, chief complaint, influenza test results, turnaround time (TAT), whether antibiotics were given, and TTD. Descriptive statistics were calculated and group comparisons conducted using chi squared and Wilcoxon Rank Sum tests. RESULTS: Study population included 100 in the POC group and 97 in the lab group. Demographics were similar between POC and lab participants. More flu positive results were reported in the POC group compared to the lab group (51.0% vs. 33.0% p = 0.01). The median TTD was 146.5 min (IQR 98.5) for POC group and 165.5 min (IQR 127) for lab group (p = 0.26). The median TAT was 30.5 min (IQR 7.5) for POC group and 106.0 min (IQR 55) for core lab group (p = 0.001). Antibiotics were given to 14.0% of POC participants and 14.4% of lab participants (p = 0.93). CONCLUSIONS: Although use of a POC influenza test provided more rapid TAT than use of a core lab test, there was no significant difference in TTD or antibiotic use between groups.

The association among diet, dietary fiber, and bowel preparation at colonoscopy.

BACKGROUND AND AIMS: Pre-colonoscopy dietary restrictions vary widely and lack evidence-based guidance. We investigated whether fiber and various other foods/macronutrients consumed during the 3 days before colonoscopy are associated with bowel preparation quality. METHODS: This was a prospective observational study among patients scheduled for outpatient colonoscopy. Patients received instructions including split-dose polyethylene glycol, avoidance of vegetables/beans 2 days before colonoscopy, and a clear liquid diet the day before colonoscopy. Two 24-hour dietary recall interviews and 1 patient-recorded food log measured dietary intake on the 3 days before colonoscopy. The Nutrition Data System for Research was used to estimate dietary exposures. Our primary outcome was the quality of bowel preparation measured by the Boston Bowel Preparation Scale (BBPS). RESULTS: We enrolled 201 patients from November 2015 to September 2016 with complete data for 168. The mean age was 59 years (standard deviation, 7 years), and 90% of colonoscopies were conducted for screening/surveillance. Only 17% and 77% of patients complied with diet restrictions 2 and 1 day(s) before colonoscopy, respectively. We found no association between foods consumed 2 and 3 days before colonoscopy and BBPS scores. However, BPPS was positively associated with intake of gelatin, and inversely associated with intake of red meat, poultry, and vegetables on the day before colonoscopy. CONCLUSIONS: Our findings support recent guidelines encouraging unrestricted diets >1 day before colonoscopy if using a split-dose bowel regimen. Furthermore, we found no evidence to restrict dietary fiber 1 day before colonoscopy. We also found evidence to promote consumption of gelatin and avoidance of red meat, poultry, and vegetables 1 day before colonoscopy.

Modeling rater diagnostic skills in binary classification processes.

Many disease diagnoses involve subjective judgments by qualified raters. For example, through the inspection of a mammogram, MRI, or ultrasound image, the clinician himself becomes part of the measuring instrument. To reduce diagnostic errors and improve the quality of diagnoses, it is necessary to assess raters' diagnostic skills and to improve their skills over time. This paper focuses on a subjective binary classification process, proposing a hierarchical model linking data on rater opinions with patient true disease-development outcomes. The model allows for the quantification of the effects of rater diagnostic skills (bias and magnifier) and patient latent disease severity on the rating results. A Bayesian Markov chain Monte Carlo (MCMC) algorithm is developed to estimate these parameters. Linking to patient true disease outcomes, the rater-specific sensitivity and specificity can be estimated using MCMC samples. Cost theory is used to identify poor- and strong-performing raters and to guide adjustment of rater bias and diagnostic magnifier to improve the rating performance. Furthermore, diagnostic magnifier is shown as a key parameter to present a rater's diagnostic ability because a rater with a larger diagnostic magnifier has a uniformly better receiver operating characteristic (ROC) curve when varying the value of diagnostic bias. A simulation study is conducted to evaluate the proposed methods, and the methods are illustrated with a mammography example.

Is hallway care dangerous? An observational study.

OBJECTIVES: In response to crowding the use of hallway beds has become an increasingly prevalent practice in Emergency Departments (EDs). There is limited research on whether caring for patients in hallways (HP) is associated with adverse outcomes. The goal of this study was to examine the effects of HP triage on 30 day outcomes for ED return, readmission, and mortality. METHODS: We performed a retrospective cohort study at an urban, academic ED comparing HPs (defined as HP for ≥30 min) to matched controls triaged to standard ED beds from 9/30/14 to 10/1/15. We analyzed data from the hospital's clinical data warehouse. Matched controls were selected by gender, age, ethnicity, and language. We used McNemar's test to assess the association between triage location and 30 day study outcomes. We also examined adverse outcomes by triage severity using McNemar's test. RESULTS: A total of 10,608 HPs were matched to control patients. Compared to controls, HPs had 2.0 times the odds of returning to the ED in 30 days (95% CI: 1.8-2.1), 1.6 times the odds of inpatient readmission (95% CI: 1.4-1.9), and 1.7 times the odds of readmission to observation (95% CI: 1.4-2.0). The odds ratio for mortality in HPs versus controls was 0.80, (95% CI: 0.50-1.3). CONCLUSIONS: Patients initially triaged to the hallway have an increased odds of 30 day return to the ED, observation and inpatient admission. After adjusting for ESI, the increased odds for return remained similar. The small sample size precluded testing effects of HP status on mortality.

Are Geriatric Patients Placed in an Emergency Department Observation Unit on a Chest Pain Pathway More Likely Than Non-Geriatric Patients to Re-Present to the Hospital within 30 Days?

BACKGROUND: Emergency department observation units (EDOUs) are used frequently for low-risk chest pain evaluations. OBJECTIVE: The purpose of this study was to determine whether geriatric compared to non-geriatric patients evaluated in an EDOU for chest pain have differences in unscheduled 30-day re-presentation, length of stay (LOS), and use of stress testing. METHODS: We conducted an exploratory, retrospective, cohort study at a single academic, urban ED of all adult patients placed in an EDOU chest pain protocol from June 1, 2014 to May 31, 2015. Our primary outcome was any unscheduled return visits within 30 days of discharge from the EDOU. Secondary outcomes included EDOU LOS and stress testing. We used Wilcoxon non-parametric and χ2 tests to compare geriatric to non-geriatric patients. RESULTS: There were 959 unique EDOU placements of geriatric (n = 219) and non-geriatric (n = 740) patients. Geriatric compared to non-geriatric patients had: no significant difference in unscheduled 30-day return visits after discharge from the EDOU (15.5% vs. 18.5%; p = 0.31); significantly longer median EDOU LOS (22.1 vs. 20.6 h; p < 0.01) with a greater percentage staying longer than 24 h (42% vs. 29.1%; p < 0.01). Geriatric patients had significantly fewer stress tests (39.7% vs. 51.4%; p < 0.01), more of which were nuclear stress tests (78.2% vs. 39.5%; p < 0.01). CONCLUSIONS: In this exploratory retrospective study, geriatric EDOU chest pain patients did not have an increased rate of re-presentation to the hospital within 30 days compared to non-geriatric patients. Geriatric patients had a longer EDOU LOS than non-geriatric patients. Geriatric patients in the EDOU had fewer stress tests, but more of those were nuclear stress tests.

Evaluating the effects of rater and subject factors on measures of association.

Large-scale agreement studies are becoming increasingly common in medical settings to gain better insight into discrepancies often observed between experts' classifications. Ordered categorical scales are routinely used to classify subjects' disease and health conditions. Summary measures such as Cohen's weighted kappa are popular approaches for reporting levels of association for pairs of raters' ordinal classifications. However, in large-scale studies with many raters, assessing levels of association can be challenging due to dependencies between many raters each grading the same sample of subjects' results and the ordinal nature of the ratings. Further complexities arise when the focus of a study is to examine the impact of rater and subject characteristics on levels of association. In this paper, we describe a flexible approach based upon the class of generalized linear mixed models to assess the influence of rater and subject factors on association between many raters' ordinal classifications. We propose novel model-based measures for large-scale studies to provide simple summaries of association similar to Cohen's weighted kappa while avoiding prevalence and marginal distribution issues that Cohen's weighted kappa is susceptible to. The proposed summary measures can be used to compare association between subgroups of subjects or raters. We demonstrate the use of hypothesis tests to formally determine if rater and subject factors have a significant influence on association, and describe approaches for evaluating the goodness-of-fit of the proposed model. The performance of the proposed approach is explored through extensive simulation studies and is applied to a recent large-scale cancer breast cancer screening study.

Social Network Structures of Breast Cancer Patients and the Contributing Role of Patient Navigators.

BACKGROUND: Minority women in the U.S. continue to experience inferior breast cancer outcomes compared with white women, in part due to delays in care delivery. Emerging cancer care delivery models like patient navigation focus on social barriers, but evidence demonstrating how these models increase social capital is lacking. This pilot study describes the social networks of newly diagnosed breast cancer patients and explores the contributing role of patient navigators. MATERIALS AND METHODS: Twenty-five women completed a one hour interview about their social networks related to cancer care support. Network metrics identified important structural attributes and influential individuals. Bivariate associations between network metrics, type of network, and whether the network included a navigator were measured. Secondary analyses explored associations between network structures and clinical outcomes. RESULTS: We identified three types of networks: kin-based, role and/or affect-based, or heterogeneous. Network metrics did not vary significantly by network type. There was a low prevalence of navigators included in the support networks (25%). Network density scores were significantly higher in those networks without a navigator. Network metrics were not predictive of clinical outcomes in multivariate models. CONCLUSION: Patient navigators were not frequently included in support networks, but provided distinctive types of support. If navigators can identify patients with poorly integrated (less dense) social networks, or who have unmet tangible support needs, the intensity of navigation services could be tailored. Services and systems that address gaps and variations in patient social networks should be explored for their potential to reduce cancer health disparities. IMPLICATIONS FOR PRACTICE: This study used a new method to identify the breadth and strength of social support following a diagnosis of breast cancer, especially examining the role of patient navigators in providing support. While navigators were only included in one quarter of patient support networks, they did provide essential supports to some individuals. Health care providers and systems need to better understand the contributions of social supports both within and outside of health care to design and tailor interventions that seek to reduce health care disparities and improve cancer outcomes.

Assessing the influence of rater and subject characteristics on measures of agreement for ordinal ratings.

Widespread inconsistencies are commonly observed between physicians' ordinal classifications in screening tests results such as mammography. These discrepancies have motivated large-scale agreement studies where many raters contribute ratings. The primary goal of these studies is to identify factors related to physicians and patients' test results, which may lead to stronger consistency between raters' classifications. While ordered categorical scales are frequently used to classify screening test results, very few statistical approaches exist to model agreement between multiple raters. Here we develop a flexible and comprehensive approach to assess the influence of rater and subject characteristics on agreement between multiple raters' ordinal classifications in large-scale agreement studies. Our approach is based upon the class of generalized linear mixed models. Novel summary model-based measures are proposed to assess agreement between all, or a subgroup of raters, such as experienced physicians. Hypothesis tests are described to formally identify factors such as physicians' level of experience that play an important role in improving consistency of ratings between raters. We demonstrate how unique characteristics of individual raters can be assessed via conditional modes generated during the modeling process. Simulation studies are presented to demonstrate the performance of the proposed methods and summary measure of agreement. The methods are applied to a large-scale mammography agreement study to investigate the effects of rater and patient characteristics on the strength of agreement between radiologists. Copyright © 2017 John Wiley & Sons, Ltd.

Is the Pelvic Examination Still Crucial in Patients Presenting to the Emergency Department With Vaginal Bleeding or Abdominal Pain When an Intrauterine Pregnancy Is Identified on Ultrasonography? A Randomized Controlled Trial.

STUDY OBJECTIVE: We determine whether omitting the pelvic examination in emergency department (ED) evaluation of vaginal bleeding or lower abdominal pain in ultrasonographically confirmed early intrauterine pregnancy is equivalent to performing the examination. METHODS: We conducted a prospective, open-label, randomized, equivalence trial in pregnant patients presenting to the ED from February 2011 to November 2015. Patients were randomized to no pelvic examination versus pelvic examination. Inclusion criteria were aged 18 years or older, English speaking, vaginal bleeding or lower abdominal pain, positive ß-human chorionic gonadotropin result, and less than 16-week intrauterine pregnancy by ultrasonography. Thirty-day record review and follow-up call assessed for composite morbidity endpoints (unscheduled return, subsequent admission, emergency procedure, transfusion, infection, and alternate source of symptoms). Wilcoxon rank sum tests were used to assess patient satisfaction and throughput times. RESULTS: Only 202 (of a planned 720) patients were enrolled, despite extension of the study enrollment period. The composite morbidity outcome was experienced at similar rates in the intervention (no pelvic examination) and control (pelvic examination) groups (19.6% versus 22.0%; difference -2.4%; 90% confidence interval [CI] -11.8% to 7.1%). Patients in the intervention group were less likely to report feeling uncomfortable or very uncomfortable during the visit (11.2% versus 23.7%; difference -12.5; 95% CI -23.0% to -2.0%). CONCLUSION: Although there was only a small difference between the percentage of patients experiencing the composite morbidity endpoint in the 2 study groups (2.4%), the resulting 90% CI was too wide to conclude equivalence. This may have been due to insufficient power. Patients assigned to the pelvic examination group reported feeling uncomfortable more frequently.