Effect of a Clinical Evidence Technology on Patient Skin Disease Outcomes in Primary Care: A Cluster-Randomized Controlled Trial

Objective: Providers’ use of clinical evidence technologies (CETs) improves their diagnosis and treatment decisions. Despite these benefits, few studies have evaluated the impact of CETs on patient outcomes. Investigators evaluated the effect of one CET, VisualDx, on skin problem outcomes in primary care. Methods: The cluster-randomized controlled pragmatic trial was set in outpatient clinics at an academic medical center in the Northeast. Participants were Primary Care Providers (PCPs) and adult patients seen for skin problems. The intervention was VisualDx as used by PCPs. Outcomes were patient-reported time from index clinic visit to problem resolution, and the number of follow-up visits to any provider for the same problem. PCPs assigned to intervention agreed to use VisualDx as their primary evidence source for skin problems. Control group PCPs agreed not to use VisualDx. Investigators collected outcome data from patients by phone at 30 day intervals. Cox proportional hazards models assessed time to resolution. Wilcoxon-rank sum tests and logistic regression compared return appointments. Results: Thirty-two PCPs and 433 patients participated. In proportional hazards modelling adjusted for provider clusters, the days from index visit to skin problem resolution were similar in both groups (HR 0.92; CI 0.70, 1.21 P= 0.54). Patient follow-up appointments did not differ significantly between groups (OR 1.26 95% CI 0.94, 1.70 P =0.29). Conclusion: This pragmatic trial tested the effectiveness of VisualDx on patient reported skin disease outcomes in a generalizable clinical setting. There was no difference in skin problem resolution or number of follow-up visits when PCPs used VisualDx

Automated Identification of Unhealthy Drinking Using Routinely Collected Data: A Machine Learning Approach

Background: Unhealthy drinking is prevalent in the United States and can lead to serious health and social consequences, yet it is under-diagnosed and under-treated. Identifying unhealthy drinkers can be time-consuming for primary care providers. An automated tool for identification would allow attention to be focused on patients most likely to need care and therefore increase efficiency and effectiveness. Objectives: To build a clinical prediction tool for unhealthy drinking based solely on routinely collected demographic and laboratory data. Methods: We obtained demographic and laboratory data on 89,325 adults seen at the University of Vermont Medical Center from 2011-2017. Logistic regression, support vector machines (SVM), k-nearest neighbor, and random forests were each used to build clinical prediction models. The model with the largest area under the receiver operator curve (AUC) was selected. Results: SVM with polynomials of degree 3 produced the largest AUC. The most influential predictors were alkaline phosphatase, gender, glucose, and serum bicarbonate. The optimum operating point had sensitivity 31.1%, specificity 91.2%, positive predictive value 50.4%, and negative predictive value 82.1%. Application of the tool increased the prevalence of unhealthy drinking from 18.3% to 32.4%, while reducing the target population by 22%. Limitations: Universal screening was not used during the time data was collected. The prevalence of unhealthy drinking among those screened was 60% suggesting the AUDIT-C was administered to confirm rather than screen for unhealthy drinking. Conclusion: An automated tool, using commonly available data, can identify a subset of patients who appear to warrant clinical attention for unhealthy drinking

Barriers and Facilitators to Use of a Clinical Evidence Technology for Management of Skin Problems in Primary Care: Insights from Mixed Methods

Background: A previous cluster-randomized controlled trial tested the effectiveness of a clinical evidence technology (CET), VisualDx, for skin problems seen by Primary Care Providers (PCPs). Based on patient report, there was no effect on time to problem resolution or return appointments. Objective: To explain, from the provider perspective, why the CET did not make a difference in the clinical trial and to identify barriers and facilitators to use. Methods: Mixed methods study design. Providers from both arms completed a survey about their use of VisualDx and information-seeking during and after the trial. Active arm providers participated in interviews to explore their opinions and experiences using VisualDx. Behavioral steps of the evidence-based medicine (EBM) paradigm informed the 6 step model. Results: PCPs found VisualDx easy to use (median 3 on a 1-4 scale), but found it only somewhat useful (median 2 on a 1-4 scale). PCPs with fewer years in practice used it more often and found it easier to use. Interviews identified facilitators and barriers to using VisualDx. Facilitators included diagnostic uncertainty, positive attitude, easy access, utility for diagnosis and therapy decisions, and utility for patient communication. Barriers included confidence in dermatology, preference for other sources, interface difficulty, and retrieval of irrelevant diagnoses and images. Some PCPs reported positive impacts on patient treatment and fewer referrals; others saw no difference. PCPs found VisualDx easy to access, but some found the interface difficult to use. They found it useful and relevant at times, but also frustrating and time-consuming. They used other sources in addition to, or instead of, VisualDx. Conclusion: PCPs did not perceive VisualDx as “useful” often enough for them to use it frequently or exclusively, thereby reducing the likelihood of its making a difference in patient-level outcomes such as problem resolution and return appointments

Barriers and Facilitators to Use of a Clinical Evidence Technology in the Management of Skin Problems in Primary Care: Insights from Mixed Methods

Objective: Few studies have examined the impact of a single clinical evidence technology (CET) on provider practice or patient outcomes from the provider’s perspective. A previous cluster-randomized controlled trial with patient-reported data tested the effectiveness of a CET (i.e., VisualDx) in improving skin problem outcomes but found no significant effect. The objectives of this follow-up study were to identify barriers and facilitators to the use of the CET from the perspective of primary care providers (PCPs) and to identify reasons why the CET did not affect outcomes in the trial. Methods: Using a convergent mixed methods design, PCPs completed a post-trial survey and participated in interviews about using the CET for the management of patients’ skin problems. Data from both methods were integrated. Results: PCPs found the CET somewhat easy to use but only occasionally useful. Less experienced PCPs used the CET more frequently. Data from interviews revealed barriers and facilitators at four steps of evidence-based practice: clinical question recognition, information acquisition, appraisal of relevance, and application with patients. Facilitators included uncertainty in dermatology, intention for use, convenience of access, diagnosis and treatment support, and patient communication. Barriers included confidence in dermatology, preference for other sources, interface difficulties, presence of irrelevant information, and lack of decision impact. Conclusion: PCPs found the CET useful for diagnosis, treatment support, and patient communication. However, the barriers of interface difficulties, irrelevant search results, and preferred use of other sources limited its positive impact on patient skin problem management

Basic Parameter Estimation of Binary Neutron Star Systems by the Advanced LIGO/Virgo Network

Within the next five years, it is expected that the Advanced LIGO/Virgo network will have reached a sensitivity sufficient to enable the routine detection of gravitational waves. Beyond the initial detection, the scientific promise of these instruments relies on the effectiveness of our physical parameter estimation capabilities. The majority of this effort has been towards the detection and characterization of gravitational waves from compact binary coalescence, e.g. the coalescence of binary neutron stars. While several previous studies have investigated the accuracy of parameter estimation with advanced detectors, the majority have relied on approximation techniques such as the Fisher Matrix. Here we report the statistical uncertainties that will be achievable for optimal detection candidates (SNR = 20) using the full parameter estimation machinery developed by the LIGO/Virgo Collaboration via Markov-Chain Monte Carlo methods. We find the recovery of the individual masses to be fractionally within 9% (15%) at the 68% (95%) credible intervals for equal-mass systems, and within 1.9% (3.7%) for unequal-mass systems. We also find that the Advanced LIGO/Virgo network will constrain the locations of binary neutron star mergers to a median uncertainty of 5.1 deg^2 (13.5 deg^2) on the sky. This region is improved to 2.3 deg^2 (6 deg^2) with the addition of the proposed LIGO India detector to the network. We also report the average uncertainties on the luminosity distances and orbital inclinations of ideal detection candidates that can be achieved by different network configurations.Comment: Second version: 15 pages, 9 figures, accepted in Ap

Prevalence of antiplatelet therapy in patients with diabetes

OBJECTIVE: To determine the prevalence of, and patient characteristics associated with, antiplatelet therapy in a cohort of primary care patients with Type 1 or Type2 diabetes. METHODS: Subjects participating in a randomized trial of a decision support system were interviewed at home and medication usage verified by a research assistant. Eligibility for antiplatelet therapy was determined by American Diabetes Association criteria and clinical contraindications. The association between antiplatelet use and patient characteristics was examined using bivariate and multivariate logistic regression. RESULTS: The mean age of subjects was 64 years (range 31–93). The prevalence of antiplatelet use was 54% overall; 45% for subjects without known CVD vs. 78% for those with CVD; 46% for women vs. 63% for men; and 45% for younger subjects (age< 65) vs. 62% for senior citizens. After controlling for race/ethnicity, income, education, marital status, insurance status and prescription coverage, the following were associated with the use of antiplatelet therapy: presence of known CVD (OR 3.4 [2.2, 5.1]), male sex (OR 2.0 [1.4, 2.8]), and age > = 65 (OR 1.9 [1.3, 2.7]). The prevalence of antiplatelet therapy for younger women without CVD was 32.8% compared to a prevalence of 90.3% for older men with CVD. CONCLUSION: Despite clinical practice guidelines recommending antiplatelet therapy for patients with diabetes, there are still many eligible patients not receiving this beneficial therapy, particularly patients under 65, women, and patients without known CVD. Effective methods to increase antiplatelet use should be considered at the national, community, practice and provider level

Literacy and health outcomes: a cross-sectional study in 1002 adults with diabetes

BACKGROUND: Inconsistent findings reported in the literature contribute to the lack of complete understanding of the association of literacy with health outcomes. We evaluated the association between literacy, physiologic control and diabetes complications among adults with diabetes. METHODS: A cross-sectional study of 1,002 English speaking adults with diabetes, randomly selected from the Vermont Diabetes Information System, a cluster-randomized trial of a diabetes decision support system in a region-wide sample of primary care practices was conducted between July 2003 and March 2005. Literacy was assessed by the Short-Test of Functional Health Literacy in Adults. Outcome measures included glycated hemoglobin, low density lipoprotein, blood pressure and self-reported complications. RESULTS: After adjusting for sociodemographic characteristics, duration of diabetes, diabetes education, depression, alcohol use, and medication use we did not find a significant association between literacy and glycemic control (beta coefficent,+ 0.001; 95% confidence interval [CI], -0.01 to +0.01; P = .88), systolic blood pressure (beta coefficent, +0.08; 95% CI, -0.10 to +0.26; P = .39), diastolic blood pressure (beta coefficent, -0.03; 95% CI, -0.12 to +0.07, P = .59), or low density lipoprotein (beta coefficent, +0.04; 95% CI, -0.27 to +0.36, P = .77. We found no association between literacy and report of diabetes complications. CONCLUSION: These findings suggest that literacy, as measured by the S-TOFHLA, is not associated with glycated hemoglobin, blood pressure, lipid levels or self-reported diabetes complications in a cross-sectional study of older adults with diabetes under relatively good glycemic control. Additional studies to examine the optimal measurement of health literacy and its relationship to health outcomes over time are needed

Limitations of diabetes pharmacotherapy: results from the Vermont Diabetes Information System study

BACKGROUND: There are a wide variety of medications available for the treatment of hyperglycemia in diabetes, including some categories developed in recent years. The goals of this study were to describe the glycemic medication profiles in a cohort of adult patients enrolled in primary care, to compare the regimens with measures of glycemic control, and to describe potential contraindicated regimens. METHODS: One thousand and six subjects with diabetes cared for in community practices in the Northeast were interviewed at home at the time of enrollment in a trial of a diabetes decision support system. Laboratory data were obtained directly from the clinical laboratory. Current medications were obtained by direct observation of medication containers by a research assistant. RESULTS: The median age of subjects was 63 years; 54% were female. The mean A1C was 7.1%, with 60% of subjects in excellent glycemic control (A1C < 7%). Ninety percent of patients were taking 2 or fewer medications for glycemic control, with a range of 0 to 4 medications. Insulin was used by 18%. As the number of diabetes medications increased from 0 to 4, the A1C increased from 6.5% to 9.2% (p < 0.001). The association between glycemic control and number of glycemic medications was confirmed using logistic regression, controlling for potential confounders. Almost 20% of subjects on metformin or thiazolidenediones had potential contraindications to these medications. CONCLUSION: Patients with diabetes cared for in primary care are on a wide variety of medication combinations for glycemic control, though most are on two or fewer medications. A greater number of diabetes medications is associated with poorer glycemic control, reflecting the limitations of current pharmacotherapy. One quarter of patients are on glycemic medications with potential contraindications

Availability, Strengths and Limitations of US State Driver&apos;s License Data for Obesity Research

Abstract Objectives: Driver&apos;s license records in the United States typically contain age, sex, height, weight, and home address. By combining the body mass index (calculated from the reported height and weight) and address information, researchers can explore and quantify the relationships between obesity and specific environmental features surrounding the place of residence. We report here our experience obtaining those data and the current state of driver&apos;s license data as an epidemiological resource. Methods: The specific state agency responsible for maintaining driver&apos;s license databases was contacted by email, phone, or both methods for each of the 50 states and the District of Columbia. Results: Fourteen states with a combined population of 89.8 million people indicated they could provide a total of 73.3 million unique driver&apos;s license (and non-driver identification) data records with address, height, weight, gender, and age, representing 82% of the population in these states. Four additional states will provide data with a zip code but not the street address. A total of 52.6 million unique analyzable records from seven states has been acquired and analyzed. Obesity is more prevalent among males and those living in less urbanized areas. Conclusion: Driver&apos;s licenses represent an underused resource for studying the geographic correlates of obesity and other public health issues