Long-Term Variability in Bioassessments: A Twenty-Year Study from Two Northern California Streams

Long-term variability of bioassessments has not been well evaluated. We analyzed a 20-year data set (1984–2003) from four sites in two northern California streams to examine the variability of bioassessment indices (two multivariate RIVPACS-type O/E scores and one multimetric index of biotic integrity, IBI), as well as eight metrics. All sites were sampled in spring; one site was also sampled in summer. Variability among years was high for most metrics (coefficients of variation, CVs ranging from 16% to 246% in spring) but lower for indices (CVs of 22–26% for the IBI and 21–32% for O/E scores in spring), which resulted in inconsistent assessments of biological condition. Variance components analysis showed that the time component explained variability in all metrics and indices, ranging from 5% to 35% of total variance explained. The site component was large (i.e., >40%) for some metrics (e.g., EPT richness), but nearly absent from others (e.g., Diptera richness). Seasonal analysis at one site showed that variability among seasons was small for some metrics or indices (e.g., Coleoptera richness), but large for others (e.g., EPT richness, O/E scores). Climatic variables did not show consistent trends across all metrics, although several were related to the El Niño Southern Oscillation Index at some sites. Bioassessments should incorporate temporal variability during index calibration or include climatic variability as predictive variables to improve accuracy and precision. In addition, these approaches may help managers anticipate alterations in reference streams caused by global climate change and high climatic variability

Using Home Visits to Understand Medication Errors in Children

Summary: Current research methods are not well designed to detect medication errors that occur at home. We developed home visit methods to investigate home medication errors in children with chronic conditions. These methods include observation of parent administration of medication to the child by a trained nurse observer who takes detailed ethnographic notes; review of all prescription and over-the-counter medications for dispensing errors, pill counts, and medication reconciliation; and parent interviews to identify barriers to effective home use of medications, prior home medication errors that parents are aware of, and suggestions for systemic improvements. Details about each possible error detected are recorded using a structured data collection form (allergies, medication list, dispensing errors, administration errors). We conducted several pilot home visits and found that this approach has the potential to help understand home medication errors in order to develop interventions to improve the safety of medication self-management

Validation of a new measure of concept of a good death

BACKGROUND: The concept of a good death is central to end-of-life care research. Despite its importance and the high interest in the topic, there are few measures currently available for use in clinical research. PURPOSE: The present work describes the development and testing of a set of items intended to measure the importance of several components posited to be critical to the concept of a good death. It is intended for use with health care providers and lay people in the context of end-of-life care research and education. POPULATION: Four cohorts (n = 596) were recruited to participate, representing two helping profession disciplines, nonhelping professionals, and a range of ages, specifically: (1) undergraduate medical students; (2) master\u27s degree students in nursing; (3) graduate students from the life sciences; and (4) practicing hospice nurses. METHODS: Participants completed self-report questionnaires at baseline and retest. Psychometric analyses included item frequency distributions, factor analysis, alpha reliability, intraclass correlation, and measures of association. RESULTS: The new Concept of a Good Death measure demonstrated good item frequency distributions, acceptable internal consistency reliability, and test-retest stability. Its factor structure revealed that three distinct domains are measured, reflecting the psychosocial/spiritual, physical, and clinical aspects of a good death. An examination of patterns of correlations showed differential associations with death anxiety, spiritual beliefs and practices, anxious mood, and sociodemographic characteristics. CONCLUSIONS: The new Concept of a Good Death instrument appears to measure three distinct factors which people consider important to a Good Death. Ratings of the importance of these factors are reliable and valid. The instrument has the advantage of being a brief, self-report index for use in end-of-life care research

Longitudinal chirality, enhanced non-reciprocity, and nano-scale planar one-way guiding

When a linear chain of plasmonic nano-particles is exposed to a transverse DC magnetic field, the chain modes are elliptically polarized, in a single plane parallel to the chain axis; hence, a novel longitudinal plasmon-rotation is created. If, in addition, the chain geometry possesses longitudinal rotation, e.g. by using ellipsoidal particles that rotate in the same plane as the plasmon rotation, strong non-reciprocity is created. The structure possesses a new kind of chirality--the longitudinal chirality--and supports one-way guiding. Since all particles rotate in the same plane, the geometry is planar and can be fabricated by printing leaf-like patches on a single plane. Furthermore, the magnetic field is significantly weaker than in previously reported one-way guiding structures. These properties are examined for ideal (lossless) and for lossy chains.Comment: to appear in PR

Patient Adherence to Laboratory Tests to Monitor Medication Therapy: A Mixed-Methods Study

Background Little is known about the contribution of patient behavior to incomplete laboratory monitoring and the reasons for patient non-completion of ordered laboratory tests remain unclear. Objective To describe factors, including patient-reported reasons, associated with non-completion of ordered laboratory tests. Design Mixed-methods study including a quantitative assessment of the frequency of patient adherence to ordered monitoring tests combined with qualitative, semi-structured, patient interviews. Participants Quantitative assessment included patients 18 years or older from a large multispecialty group practice prescribed a medication requiring monitoring. Qualitative interviews included a subset of adherent and non-adherent patients prescribed a cardiovascular, anti-convulsant, or thyroid replacement medication. Main Measures Proportion of recommended monitoring tests for each medication not completed, factors associated with patient non-adherence, and patient-reported reasons for non-adherence. Results Of 27,802 patients who were prescribed one of 34 medications, patient non-completion of ordered tests varied (range: 0% to 29%, by drug-test pair). Factors associated with higher odds of test non-completion included younger patient age (\u3c 40 years vs. ≥80 years, adjusted odds ratio [AOR] 1.52, 95% confidence interval [95% CI] 1.27-1.83), lower medication burden (1 medication vs. more than 1 drug, AOR for non-completion 1.26, 95% CI 1.15-1.37), and lower visit frequency (0-5 visits/year vs. ≥19 visits/year, AOR 1.41, 95% CI 1.25 to 1.59). Drug-test pairs with black box warning status were associated with greater odds of non-completion compared to drugs included only in the PDR (AOR 1.91, 95% CI 1.66-2.19). Qualitative interviews, with 16 non-adherent and 7 adherent patients, identified forgetting as the main cause of non-adherence. Conclusions Patient non-adherence contributed to missed opportunities to monitor medications and was associated with younger patient age and lower medication burden and black box warning status. Interventions to improve laboratory monitoring should target patients as well as physicians

Dissemination of Evidence-based Atypical Antipsychotic Information to Nursing Homes

Background: Accumulating evidence demonstrates minimal benefit and increased risk of off-label use of atypical antipsychotic medications for dementia-related behaviors. Optimal strategy for disseminating evidence-based guides to nursing home (NH) stakeholders is unclear. Our objective is to describe the impact of differing dissemination efforts in Connecticut NHs. Methods: Forty-three Connecticut NHs were randomized to one of 3 arms receiving incrementally intensive dissemination strategies of the Agency for Healthcare Research and Quality Comparative Effectiveness Review Summary Guide on the off-label use of atypical antipsychotic drugs, which was included in a toolkit informed by a needs assessment of NHs. All NHs received the paper-based toolkit and notifications regarding the online toolkit. Additionally, Arm 2 received individualized quarterly audit and feedback reports with atypical antipsychotic prescribing rates; Arm 3 received in-person educational visits and audit and feedback reports. Toolkit reach was assessed using interviews with NH leadership and staff. Online toolkit use was assessed using Google analytics. Results: Eighty leaders and 222 direct care staff were interviewed. Leadership and direct care staff in Arm 3 NHs were more likely to be familiar with the toolkit that those in Arm 1 (p=0.008) and Arm 2 (p Conclusions: Intensive dissemination, using multi-pronged approach including academic detailing and direct care staff trainings, appeared to be associated with higher familiarity with paper-based toolkit, but not Internet-based use of the toolkit in the NH setting

Understanding Antipsychotic Drug Use in the Nursing Home Setting

Introduction: The increasing prevalence of antipsychotic medication use in residents of nursing homes (NH) in the absence of psychiatric diagnoses is concerning. To address these concerns, it is essential to explore how these medications are being prescribed and managed in the NH setting. Our objectives were to understand the decision-making process that influences prescribing and factors that trigger administration of antipsychotic medications to residents with dementia in NHs and to explore why residents remain on antipsychotic medications over an extended period of time. Methods: Interviews with prescribers, caregivers, and family members, on-site observations in study facilities, and review of NH resident medical records. Facilities were selected to obtain a diverse sample of NHs. Results: 204 NH residents with dementia in 26 facilities distributed across five selected Centers for Medicaid and Medicare Services regions were included. Problematic behaviors were the dominant reasons offered as influencing prescribing of antipsychotic medications. Providers indicated that they chose an antipsychotic, rather than another drug class, because they believed that antipsychotic medications were more likely to be effective. There was no standard approach to taper attempts. Family members identified a lack of communication as a barrier to their involvement in decision-making. Conclusions: There is widespread perception that antipsychotic medications are effective and beneficial in managing problematic behaviors in NH residents with dementia. Little attention is given to planning for antipsychotic tapering or discontinuation. There may be opportunities to involve family members more fully in decision-making around the use of antipsychotic medications

Use of Electronic Health Record Access and Audit Logs to Identify Physician Actions Following Noninterruptive Alert Opening: Descriptive Study

BACKGROUND: Electronic health record (EHR) access and audit logs record behaviors of providers as they navigate the EHR. These data can be used to better understand provider responses to EHR-based clinical decision support (CDS), shedding light on whether and why CDS is effective. OBJECTIVE: This study aimed to determine the feasibility of using EHR access and audit logs to track primary care physicians\u27 (PCPs\u27) opening of and response to noninterruptive alerts delivered to EHR InBaskets. METHODS: We conducted a descriptive study to assess the use of EHR log data to track provider behavior. We analyzed data recorded following opening of 799 noninterruptive alerts sent to 75 PCPs\u27 InBaskets through a prior randomized controlled trial. Three types of alerts highlighted new medication concerns for older patients\u27 posthospital discharge: information only (n=593), medication recommendations (n=37), and test recommendations (n=169). We sought log data to identify the person opening the alert and the timing and type of PCPs\u27 follow-up EHR actions (immediate vs by the end of the following day). We performed multivariate analyses examining associations between alert type, patient characteristics, provider characteristics, and contextual factors and likelihood of immediate or subsequent PCP action (general, medication-specific, or laboratory-specific actions). We describe challenges and strategies for log data use. RESULTS: We successfully identified the required data in EHR access and audit logs. More than three-quarters of alerts (78.5%, 627/799) were opened by the PCP to whom they were directed, allowing us to assess immediate PCP action; of these, 208 alerts were followed by immediate action. Expanding on our analyses to include alerts opened by staff or covering physicians, we found that an additional 330 of the 799 alerts demonstrated PCP action by the end of the following day. The remaining 261 alerts showed no PCP action. Compared to information-only alerts, the odds ratio (OR) of immediate action was 4.03 (95% CI 1.67-9.72) for medication-recommendation and 2.14 (95% CI 1.38-3.32) for test-recommendation alerts. Compared to information-only alerts, ORs of medication-specific action by end of the following day were significantly greater for medication recommendations (5.59; 95% CI 2.42-12.94) and test recommendations (1.71; 95% CI 1.09-2.68). We found a similar pattern for OR of laboratory-specific action. We encountered 2 main challenges: (1) Capturing a historical snapshot of EHR status (number of InBasket messages at time of alert delivery) required incorporation of data generated many months prior with longitudinal follow-up. (2) Accurately interpreting data elements required iterative work by a physician/data manager team taking action within the EHR and then examining audit logs to identify corresponding documentation. CONCLUSIONS: EHR log data could inform future efforts and provide valuable information during development and refinement of CDS interventions. To address challenges, use of these data should be planned before implementing an EHR-based study.