1,120 research outputs found
Transitions in Care: Medication Reconciliation in the Community Pharmacy Setting After Discharge
Objective: To assess the feasibility of a workflow process in which pharmacists in an independent community pharmacy group conduct medication reconciliation for patients undergoing transitions in care.Methods: Three workflow changes were made to improve the medication reconciliation process in a group of three independent community pharmacies. Analysis of the process included workflow steps performed by pharmacy staff, pharmacist barriers encountered during the medication reconciliation process, number of medication discrepancies identified, and pharmacist comfort level while performing each medication reconciliation service.Key Findings: Sixty patient medication reconciliation services met the inclusion criteria for the study. Pharmacists were involved in all steps associated with the medication reconciliation workflow, and were the sole performer in four of the steps: verifying discharge medications with the pharmacy medication profile, resolving discrepancies, contacting the prescriber, and providing patient counseling. Pharmacists were least involved in entering medications into the pharmacy management system, performing that workflow step 13% of the time. The most common barriers were the absence of a discharge medication list (24%) and patient not present during consultation (11%). A total of 231 medication discrepancies were identified, with an average of 3.85 medication discrepancies per discharge. Pharmacistsâ comfort level performing medication reconciliation improved through the 13 weeks of the study.Conclusions: These findings suggest that medication reconciliation for patients discharged from hospitals and long term care facilities can be successfully performed in an independent community pharmacy setting. Because many medication discrepancies were identified during this transition of care, it is highly valuable for community pharmacists to perform medication reconciliation services
A boosting method for maximizing the partial area under the ROC curve
<p>Abstract</p> <p>Background</p> <p>The receiver operating characteristic (ROC) curve is a fundamental tool to assess the discriminant performance for not only a single marker but also a score function combining multiple markers. The area under the ROC curve (AUC) for a score function measures the intrinsic ability for the score function to discriminate between the controls and cases. Recently, the partial AUC (pAUC) has been paid more attention than the AUC, because a suitable range of the false positive rate can be focused according to various clinical situations. However, existing pAUC-based methods only handle a few markers and do not take nonlinear combination of markers into consideration.</p> <p>Results</p> <p>We have developed a new statistical method that focuses on the pAUC based on a boosting technique. The markers are combined componentially for maximizing the pAUC in the boosting algorithm using natural cubic splines or decision stumps (single-level decision trees), according to the values of markers (continuous or discrete). We show that the resulting score plots are useful for understanding how each marker is associated with the outcome variable. We compare the performance of the proposed boosting method with those of other existing methods, and demonstrate the utility using real data sets. As a result, we have much better discrimination performances in the sense of the pAUC in both simulation studies and real data analysis.</p> <p>Conclusions</p> <p>The proposed method addresses how to combine the markers after a pAUC-based filtering procedure in high dimensional setting. Hence, it provides a consistent way of analyzing data based on the pAUC from maker selection to marker combination for discrimination problems. The method can capture not only linear but also nonlinear association between the outcome variable and the markers, about which the nonlinearity is known to be necessary in general for the maximization of the pAUC. The method also puts importance on the accuracy of classification performance as well as interpretability of the association, by offering simple and smooth resultant score plots for each marker.</p
Self-assembly of Microcapsules via Colloidal Bond Hybridization and Anisotropy
Particles with directional interactions are promising building blocks for new
functional materials and may serve as models for biological structures.
Mutually attractive nanoparticles that are deformable due to flexible surface
groups, for example, may spontaneously order themselves into strings, sheets
and large vesicles. Furthermore, anisotropic colloids with attractive patches
can self-assemble into open lattices and colloidal equivalents of molecules and
micelles. However, model systems that combine mutual attraction, anisotropy,
and deformability have---to the best of our knowledge---not been realized.
Here, we synthesize colloidal particles that combine these three
characteristics and obtain self-assembled microcapsules. We propose that mutual
attraction and deformability induce directional interactions via colloidal bond
hybridization. Our particles contain both mutually attractive and repulsive
surface groups that are flexible. Analogous to the simplest chemical bond,
where two isotropic orbitals hybridize into the molecular orbital of H2, these
flexible groups redistribute upon binding. Via colloidal bond hybridization,
isotropic spheres self-assemble into planar monolayers, while anisotropic
snowman-like particles self-assemble into hollow monolayer microcapsules. A
modest change of the building blocks thus results in a significant leap in the
complexity of the self-assembled structures. In other words, these relatively
simple building blocks self-assemble into dramatically more complex structures
than similar particles that are isotropic or non-deformable
A qualitative investigation of breast cancer survivorsâ experiences with breastfeeding
This is an exploratory, qualitative investigation of breast cancer survivorsâ experiences with breastfeeding. Previous studies have focused on the physiology of lactation after surgery and treatment, but have not explored factors influencing breastfeeding decisions and behavior.
We used purposeful sampling to identify 11 breast cancer survivors who had a child after their diagnosis and treatment. Participants were recruited from among those in the Womenâs Healthy Eating and Living (WHEL) study and a Young Survival Coalition (YSC) affiliate. We conducted semi-structured, open-ended telephone interviews lasting 45â75Â min. We used social cognitive theory (SCT) to structure questions regarding influences on breastfeeding behavior. We transcribed interviews and used cross-case, inductive analysis to identify themes.
Ten of 11 participants initiated breastfeeding. The following main themes emerged: 1) Cautiously hopeful, 2) Exhausting to rely on one breast, 3) Motivated despite challenges, 4) Support and lack of support, and 5) Encouraging to others.
Study participants were highly motivated to breastfeed but faced considerable challenges. Participants described problems that are not unique to women with breast cancer, but experienced these to a much greater degree because they relied mostly or entirely on one lactating breast. This study revealed a need for improved access to information and support and greater sensitivity to the obstacles faced by breast cancer survivors.
Results of this qualitative analysis indicate that interventions to support the efforts of breast cancer survivors who are interested in breastfeeding are warranted. Additional research would aid in the development of such interventions
Photovoltaic power plants: a multicriteria approach to investment decisions and a case study in western Spain
his paper proposes a compromise programming (CP) model to help investors decide whether to construct photovoltaic power plants with government financial support. For this purpose, we simulate an agreement between the government, who pursues political prices (guaranteed prices) as low as possible, and the project sponsor who wants returns (stochastic cash flows) as high as possible. The sponsor s decision depends on the positive or negative result of this simulation, the resulting simulated price being compared to the effective guaranteed price established by the country legislation for photovoltaic energy. To undertake the simulation, the CP model articulates variables such as ranges of guaranteed prices, tech- nical characteristics of the plant, expected energy to be generated over the investment life, investment cost, cash flow probabilities, and others. To determine the CP metric, risk aver- sion is assumed. As an actual application, a case study on photovoltaic power investment in Extremadura, western Spain, is developed in detail.Garcia-Bernabeu, A.; Benito Benito, A.; Bravo Selles, M.; Pla SantamarĂa, D. (2015). Photovoltaic power plants: a multicriteria approach to investment decisions and a case study in western Spain. Annals of Operations Research. 1-12. doi:10.1007/s10479-015-1836-2S112Andrews, R. W., Pollard, A., & Pearce, J. M. (2012). Improved parametric empirical determination of module short circuit current for modelling and optimization of solar photovoltaic systems. Solar Energy, 86(9), 2240â2254.Anwar, Y., & Mulyadi, M. S. (2011). Income tax incentives on renewable energy industry: Case of geothermal industry in USA and Indonesia. African Journal of Business Management, 5(31), 12264â12270.Aouni, B., & Kettani, O. (2001). Goal programming model: A glorious history and a promising future. European Journal of Operational Research, 133(2), 225â231.Ballestero, E. (1997). 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Quantum adiabatic machine learning
We develop an approach to machine learning and anomaly detection via quantum
adiabatic evolution. In the training phase we identify an optimal set of weak
classifiers, to form a single strong classifier. In the testing phase we
adiabatically evolve one or more strong classifiers on a superposition of
inputs in order to find certain anomalous elements in the classification space.
Both the training and testing phases are executed via quantum adiabatic
evolution. We apply and illustrate this approach in detail to the problem of
software verification and validation.Comment: 21 pages, 9 figure
Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at â s = 8 TeV with the ATLAS detector
Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fbâ1 of â s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente
Differential surface density and modulatory effects of presynaptic GABAB receptors in hippocampal cholecystokinin and parvalbumin basket cells
Challenges in supporting lay carers of patients at the end of life: results from focus group discussions with primary healthcare providers
Background: Family caregivers (FCGs) of patients at the end of life (EoL) cared for at home receive support from professional and non-professional care providers. Healthcare providers in general practice play an important role as they coordinate care and establish contacts between the parties concerned. To identify potential intervention targets, this study deals with the challenges healthcare providers in general practice face in EoL care situations including patients, caregivers and networks.
Methods: Focus group discussions with general practice teams in Germany were conducted to identify barriers to and enablers of an optimal support for family caregivers. Focus group discussions were analysed using content analysis.
Results: Nineteen providers from 11 general practices took part in 4 focus group discussions. Participants identified challenges in communication with patients, caregivers and within the professional network. Communication with patients and caregivers focused on non-verbal messages, communicating at an appropriate time and perceiving patient and caregiver as a unit of care. Practice teams perceive themselves as an important part of the healthcare network, but also report difficulties in communication and cooperation with other healthcare providers.
Conclusion: Healthcare providers in general practice identified relational challenges in daily primary palliative care with potential implications for EoL care. Communication and collaboration with patients, caregivers and among healthcare providers give opportunities for improving palliative care with a focus on the patient-caregiver dyad. It is insufficient to demand a (professional) support network; existing structures need to be recognized and included into the care
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