Medical Laboratory Managers Success with Preanalytical Errors

Clinicians rely heavily on accurate laboratory results to diagnose and treat their patients. Laboratory errors can occur in any area of total testing phases, but more than half of the errors occur in the preanalytical phase. Framed by the total quality management theory, the purpose of this multiple case study was to explore medical laboratory managers\u27 strategies to reduce preanalytical errors. A purposive sample of 2 organizations with laboratories in southern California participated in semistructured face-to-face interviews. Company A had 2 participants and 3 participants participated in the study from Company B. Each participant had at least 5 years of laboratory experience, with a minimum of 2 years of management experience in preanalytical testing, and had completed one project to minimize laboratory errors. Thematic analysis exposed 5 main themes: quality improvement, recognition, reward, and empowerment, education and training, communication, and patient satisfaction. The participants highlighted the need for organizations to concentrate on quality management to achieve patient satisfaction. To achieve quality services, medical laboratory managers noted the importance of employee engagement, education and training, and communication as successful strategies to mitigate preanalytical errors. The recommendation for action is for laboratory leaders to review and apply effective strategies exposed by the data in this study to reduce preanalytical errors in their medical laboratory. Positive implications of this study include reduction of preanalytical errors, increased operational cost, and improved patient experience

Supplying Improved Seed to Farmers in Rural Kenya: The Case of Freshco Kenya Ltd.

Freshco, a small producer and distributor of hybrid maize seed and macadamia seedlings, was one of the first private companies to enter the Kenya seed market after its liberalization. Currently, the company produces and markets six high yielding maize varieties that are suited for diverse agro-ecological conditions. Despite the company’s encouraging growth in the local maize seed market, Freshco’s executives recognize the need to scale up operations to stay competitive. The company’s challenge is to recognize business opportunities and customer needs in an environment susceptible to ecological, political, and socioeconomic change.Kenya, seed industry, smallholder farmers, scenario planning, Crop Production/Industries, Farm Management, Research Methods/ Statistical Methods, Q10, Q12,

Dengue epidemic in southern Vietnam, 1998.

A widespread epidemic of dengue hemorrhagic fever (DHF) occurred in southern Vietnam in 1998, with 438.98 cases/100,000 population and 342 deaths. The number of DHF cases and deaths per 100,000 population increased 152.4% and 151.8%, respectively, over a 1997 epidemic. Dengue viruses were isolated from 143 patient blood samples; DEN-3 virus was identified as the predominant serotype, although a resurgence of DEN-4 was noted

Unconventional anomalous Hall effect in 3d/5d multilayers mediated by the nonlocal spin-conductivity

We evidenced unconventionnal Anomalous Hall Effects (AHE) in 3d/5d (Co0.2nm/Ni0.6nm)N multilayers grown on a thin Pt layer or thin Au:W alloy. The inversion observed on AHE originates from the opposite sign of the spin-orbit coupling of Pt compared to Ni. Via advanced simulations methods for the description of the spin-current profiles based on the spin-dependent Boltzmann formalism, we extracted the spin Hall angle (SHA) of Pt and (Co/Ni) as well as the relevant transport parameters. The extracted SHA for Pt, +20%, is opposite to the one of (Co/Ni), giving rise to an effective AHE inversion for thin (Co/Ni) multilayers (N < 17). The spin Hall angle in Pt is found to be larger than the one previously measured in combined spin-pumping inverse spin-Hall effect experiments in a geometry of current perpendicular to plane. Whereas magnetic proximity effects cannot explain the effect, spin-current leakage and anisotropic electron scattering at Pt/(Co,Ni) interfaces fit the experiments.Comment: 7 pages, 2 figure

Association between Post-Hospital Clinic and Telephone Follow-up Provider Visits with 30-Day Readmission Risk in an Integrated Health System

BACKGROUND: Follow-up visits with clinic providers after hospital discharge may not be feasible for some patients due to functional limitations, transportation challenges, need for physical distancing, or fear of exposure especially during the current COVID-19 pandemic. METHODS: The aim of the study was to determine the effects of post-hospital clinic (POSH) and telephone (TPOSH) follow-up provider visits versus no visit on 30-day readmission. We used a retrospective cohort design based on data from 1/1/2017 to 12/31/2019 on adult patients (n = 213,513) discharged home from 15 Kaiser Permanente Southern California hospitals. Completion of POSH or TPOSH provider visits within 7 days of discharge was the exposure and all-cause 30-day inpatient and observation stay readmission was the primary outcome. We used matching weights to balance the groups and Fine-Gray subdistribution hazard model to assess for readmission risk. RESULTS: Unweighted all-cause 30-day readmission rate was highest for patients who completed a TPOSH (17.3%) followed by no visit (14.2%), non-POSH (evaluation and management visits that were not focused on the hospitalization: 13.6%) and POSH (12.6%) visits. The matching weighted models showed that the effects of POSH and TPOSH visits varied across patient subgroups. For high risk (LACE 11+) medicine patients, both POSH (HR: 0.77, 95% CI: 0.71, 0.85, P \u3c .001) and TPOSH (HR: 0.91, 95% CI: 0.83, 0.99, P = .03) were associated with 23 and 9% lower risk of 30-day readmission, respectively, compared to no visit. For medium to low risk medicine patients (LACE\u3c 11) and all surgical patients regardless of LACE score or age, there were no significant associations for either visit type with risk of 30-day readmission. CONCLUSIONS: Post-hospital telephone follow-up provider visits had only modest effects on 30-day readmission in high-risk medicine patients compared to clinic visits. It remains to be determined if greater use and comfort with virtual visits by providers and patients as a result of the pandemic might improve the effectiveness of these encounters

Understanding the groups of care transition strategies used by U.S. hospitals: An application of factor analytic and latent class methods

BACKGROUND: After activation of the Hospital Readmission Reduction Program (HRRP) in 2012, hospitals nationwide experimented broadly with the implementation of Transitional Care (TC) strategies to reduce hospital readmissions. Although numerous evidence-based TC models exist, they are often adapted to local contexts, rendering large-scale evaluation difficult. Little systematic evidence exists about prevailing implementation patterns of TC strategies among hospitals, nor which strategies in which combinations are most effective at improving patient outcomes. We aimed to identify and define combinations of TC strategies, or groups of transitional care activities, implemented among a large and diverse cohort of U.S. hospitals, with the ultimate goal of evaluating their comparative effectiveness. METHODS: We collected implementation data for 13 TC strategies through a nationwide, web-based survey of representatives from short-term acute-care and critical access hospitals (N = 370) and obtained Medicare claims data for patients discharged from participating hospitals. TC strategies were grouped separately through factor analysis and latent class analysis. RESULTS: We observed 348 variations in how hospitals implemented 13 TC strategies, highlighting the diversity of hospitals\u27 TC strategy implementation. Factor analysis resulted in five overlapping groups of TC strategies, including those characterized by 1) medication reconciliation, 2) shared decision making, 3) identifying high risk patients, 4) care plan, and 5) cross-setting information exchange. We determined that the groups suggested by factor analysis results provided a more logical grouping. Further, groups of TC strategies based on factor analysis performed better than the ones based on latent class analysis in detecting differences in 30-day readmission trends. CONCLUSIONS: U.S. hospitals uniquely combine TC strategies in ways that require further evaluation. Factor analysis provides a logical method for grouping such strategies for comparative effectiveness analysis when the groups are dependent. Our findings provide hospitals and health systems 1) information about what groups of TC strategies are commonly being implemented by hospitals, 2) strengths associated with the factor analysis approach for classifying these groups, and ultimately, 3) information upon which comparative effectiveness trials can be designed. Our results further reveal promising targets for comparative effectiveness analyses, including groups incorporating cross-setting information exchange