Team Effectiveness in Patient Health Management: An Overview of Reviews

Background: The desire to improve the quality of health care for an aging population with multiple chronic diseases is fostering a rapid growth in inter-professional team care, supported by health professionals, governments, businesses and public institutions. However, the weight of evidence measuring the impact of team care on patient and health system outcomes has not, heretofore, been clear. To address this deficiency, we evaluated published evidence for the clinical effectiveness of team care within a chronic disease management context in a systematic overview. Methods: A search strategy was built for Medline using medical subject headings and other relevant keywords. After testing for perform- ance, the search strategy was adapted to other databases (Cinhal, Cochrane, Embase, PsychInfo) using their specific descriptors. The searches were limited to reviews published between 1996 and 2011, in English and French languages. The results were analyzed by the number of studies favouring team intervention, based on the direction of effect and statistical significance for all reported outcomes. Results: Sixteen systematic and 7 narrative reviews were included. Diseases most frequently targeted were depression, followed by heart failure, diabetes and mental disorders. Effective- ness outcome measures most commonly used were clinical endpoints, resource utilization (e.g., emergency room visits, hospital admissions), costs, quality of life and medication adherence. Briefly, while improved clinical and resource utilization endpoints were commonly reported as positive outcomes, mixed directional results were often found among costs, medication adherence, mortality and patient satisfaction outcomes. Conclusions: We conclude that, although suggestive of some specific benefits, the overall weight of evidence for team care efficacy remains equivocal. Further studies that examine the causal interactions between multidisciplinary team care and clinical and economic outcomes of disease management are needed to more accurately assess its net program efficacy and population effectiveness.

Value / personality - attitude - behavior hierarchy and its impact on individual performance in the context of market orientation

The purpose of this dissertation is to better understand how individual employees? values and personality traits influence their attitudes toward market orientation; how such attitudes impact their market-oriented behaviors; and how in turn, these behaviors lead to their superior individual performance. To investigate these relationships, an empirical study was conducted in the French speaking part of Switzerland and data were collected from a sample of service firms? employees from diverse departments and hierarchical levels. To a large extent, the results support the hypothesis of a hierarchical chain moving from value / personality to attitude to behavior to individual performance in relation to market orientation. Le sujet de cette thèse de doctorat est de mieux comprendre comment les valeurs et les traits de personnalité des employés influencent leurs attitudes envers l'orientation vers le marché ; comment ces attitudes ont un effet sur les comportements orientés vers le marché de ces employés et enfin, comment ces comportements conduisent à une meilleure performance individuelle. Afin d'étudier ces relations, une enquête a été conduite en Suisse romande et des données ont été collectées auprès d'un échantillon d'employés d'entreprises de service de différents départements et niveaux hiérarchiques. Les résultats sont concordants avec l'hypothèse d'une chaîne causale allant des valeurs / traits de personnalité aux attitudes, aux comportements et finalement à la performance individuelle dans le contexte de l'orientation vers le marché.

How to identify and recruit nurses to a survey 14 and 24 years after graduation in a context of scarce data : lessons learnt from the 2012 nurses at work pilot study on nurses' career paths

Nursing workforce data are scarce in Switzerland, with no active national registry of nurses. The worldwide nursing shortage is also affecting Switzerland, so that evidence-based results of the nurses at work project on career paths and retention are needed as part of the health care system stewardship; nurses at work is a retrospective cohort study of nurses who graduated in Swiss nursing schools in the last 30 years. Results of the pilot study are presented here (process and feasibility). The objectives are (1) to determine the size and structure of the potential target population by approaching two test-cohorts of nursing graduates (1988 and 1998); (2) to test methods of identifying and reaching them 14 and 24 years after graduation; (3) to compute participation rates, and identify recruitment and participation biases.

L'assistance au suicide en Suisse dans le contexte de polypathologie invalidante irréversible [Assisted suicide in Switzerland in the context of irreversible illness].

La prise en charge des personnes en fin de vie s'est beaucoup développée en Suisse au cours des dernières décennies, et assure, grâce aux soins gériatriques et palliatifs, dans une grande majorité des cas, une fin de vie digne aux patients. Il arrive toutefois que des malades, motivés notamment par une grande lassitude, aient recours à une association telle qu'EXIT pour les accompagner dans leur désir de mettre fin à leurs jours, même s'ils ne sont pas atteints d'une maladie mettant leur vie en danger. Nous avons étudié ce phénomène chez les 21 personnes, qui ont mis fin à leurs jours avec l'aide de l'association EXIT, sur une période de cinq ans (2001-2005) ; les souffrances physiques de ces malades étaient représentées essentiellement par des douleurs importantes, une asthénie, des troubles respiratoires, neurologiques ou digestifs. A cela, s'ajoutaient les difficultés psychologiques liées à la perte d'autonomie, la solitude, l'angoisse et le sentiment de perte de dignité. Malgré l'absence de maladie mortelle en soi, nous avons pu observer que les critères exigés par l'association EXIT pour envisager un accompagnement étaient respectés dans tous les cas.

Persistence of Transmitted HIV-1 Drug Resistance Mutations Associated with Fitness Costs and Viral Genetic Backgrounds.

Transmission of drug-resistant pathogens presents an almost-universal challenge for fighting infectious diseases. Transmitted drug resistance mutations (TDRM) can persist in the absence of drugs for considerable time. It is generally believed that differential TDRM-persistence is caused, at least partially, by variations in TDRM-fitness-costs. However, in vivo epidemiological evidence for the impact of fitness costs on TDRM-persistence is rare. Here, we studied the persistence of TDRM in HIV-1 using longitudinally-sampled nucleotide sequences from the Swiss-HIV-Cohort-Study (SHCS). All treatment-naïve individuals with TDRM at baseline were included. Persistence of TDRM was quantified via reversion rates (RR) determined with interval-censored survival models. Fitness costs of TDRM were estimated in the genetic background in which they occurred using a previously published and validated machine-learning algorithm (based on in vitro replicative capacities) and were included in the survival models as explanatory variables. In 857 sequential samples from 168 treatment-naïve patients, 17 TDRM were analyzed. RR varied substantially and ranged from 174.0/100-person-years;CI=[51.4, 588.8] (for 184V) to 2.7/100-person-years;[0.7, 10.9] (for 215D). RR increased significantly with fitness cost (increase by 1.6[1.3,2.0] per standard deviation of fitness costs). When subdividing fitness costs into the average fitness cost of a given mutation and the deviation from the average fitness cost of a mutation in a given genetic background, we found that both components were significantly associated with reversion-rates. Our results show that the substantial variations of TDRM persistence in the absence of drugs are associated with fitness-cost differences both among mutations and among different genetic backgrounds for the same mutation.

Data triangulation in the context of opioids monitoring via wastewater analyses.

BACKGROUND: The need to contextualise wastewater-based figures about illicit drug consumption by comparing them with other indicators has been stressed by numerous studies. The objective of the present study was to further investigate the possibility of combining wastewater data to conventional statistics to assess the reliability of the former method and obtain a more balanced picture of illicit drug consumption in the investigated area. METHODS: Wastewater samples were collected between October 2013 and July 2014 in the metropolitan area of Lausanne (226,000 inhabitants), Switzerland. Methadone, its metabolite 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP), the exclusive metabolite of heroin, 6-monoacetylmorphine (6-MAM), and morphine loads were used to estimate the amounts of methadone and heroin consumed. RESULTS: Methadone consumption estimated from EDDP was in agreement with the expectations. Heroin estimates based on 6-MAM loads were inconsistent. Estimates obtained from morphine loads, combined to prescription/sales data, were in agreement with figures derived from syringe distribution data and general population surveys. CONCLUSIONS: The results obtained for methadone allowed assessing the reliability of the selected sampling strategy, supporting its ability to capture the consumption of a small cohort (i.e., 743 patients). Using morphine as marker, in combination with prescription/sales data, estimates in accordance with other indicators about heroin use were obtained. Combining different sources of data allowed strengthening the results and suggested that the different indicators (i.e., administration route, average dosage and number of consumers) contribute to depict a realistic representation of the phenomenon in the investigated area. Heroin consumption was estimated to approximately 13gday(-1) (118gday(-1) at street level).

Functional error modeling for uncertainty quantification in hydrogeology

Approximate models (proxies) can be employed to reduce the computational costs of estimating uncertainty. The price to pay is that the approximations introduced by the proxy model can lead to a biased estimation. To avoid this problem and ensure a reliable uncertainty quantification, we propose to combine functional data analysis and machine learning to build error models that allow us to obtain an accurate prediction of the exact response without solving the exact model for all realizations. We build the relationship between proxy and exact model on a learning set of geostatistical realizations for which both exact and approximate solvers are run. Functional principal components analysis (FPCA) is used to investigate the variability in the two sets of curves and reduce the dimensionality of the problem while maximizing the retained information. Once obtained, the error model can be used to predict the exact response of any realization on the basis of the sole proxy response. This methodology is purpose-oriented as the error model is constructed directly for the quantity of interest, rather than for the state of the system. Also, the dimensionality reduction performed by FPCA allows a diagnostic of the quality of the error model to assess the informativeness of the learning set and the fidelity of the proxy to the exact model. The possibility of obtaining a prediction of the exact response for any newly generated realization suggests that the methodology can be effectively used beyond the context of uncertainty quantification, in particular for Bayesian inference and optimization.

A model for the evolution of reinforcement learning in fluctuating games

Many species are able to learn to associate behaviours with rewards as this gives fitness advantages in changing environments. Social interactions between population members may, however, require more cognitive abilities than simple trial-and-error learning, in particular the capacity to make accurate hypotheses about the material payoff consequences of alternative action combinations. It is unclear in this context whether natural selection necessarily favours individuals to use information about payoffs associated with nontried actions (hypothetical payoffs), as opposed to simple reinforcement of realized payoff. Here, we develop an evolutionary model in which individuals are genetically determined to use either trial-and-error learning or learning based on hypothetical reinforcements, and ask what is the evolutionarily stable learning rule under pairwise symmetric two-action stochastic repeated games played over the individual's lifetime. We analyse through stochastic approximation theory and simulations the learning dynamics on the behavioural timescale, and derive conditions where trial-and-error learning outcompetes hypothetical reinforcement learning on the evolutionary timescale. This occurs in particular under repeated cooperative interactions with the same partner. By contrast, we find that hypothetical reinforcement learners tend to be favoured under random interactions, but stable polymorphisms can also obtain where trial-and-error learners are maintained at a low frequency. We conclude that specific game structures can select for trial-and-error learning even in the absence of costs of cognition, which illustrates that cost-free increased cognition can be counterselected under social interactions.

Privacy as a Tradeoff: Introducing the Notion of Privacy Calculus for Context-Aware Mobile Applications

Evidences collected from smartphones users show a growing desire of personalization offered by services for mobile devices. However, the need to accurately identify users' contexts has important implications for user's privacy and it increases the amount of trust, which users are requested to have in the service providers. In this paper, we introduce a model that describes the role of personalization and control in users' assessment of cost and benefits associated to the disclosure of private information. We present an instantiation of such model, a context-aware application for smartphones based on the Android operating system, in which users' private information are protected. Focus group interviews were conducted to examine users' privacy concerns before and after having used our application. Obtained results confirm the utility of our artifact and provide support to our theoretical model, which extends previous literature on privacy calculus and user's acceptance of context-aware technology.