MEDICAL STUDENT IN THE FAMILY HEALTH STRATEGY ON THE FIRST YEARS OF COLLEGE: PERCEPTION OF GRADUATES

There is a lack of knowledge about the effective value of the experience gained by medical students who participate in the Family Health Strategy (Estratégia Saúde da Família (ESF)) during the early stages of their medical training. This teaching strategy is based on learning by experiencing the problems that exist in real life. This study proposed to understand the value of this teaching strategy from the viewpoint of the students who had participated, after their graduation. The method adopted was a qualitative study conducted through interviews with students who graduated in the years 2009, 2010 and 2011. The data analysis used the hermeneutic dialectic technique as its model. The graduates considered that this experience enabled them to understand the organization and functioning of the health service and the context of the daily life of the users. This experience facilitated the doctor patient relationship, the development of clinical reasoning and the bond with the user. However the students emphasized that a lack of maturity prevented them gaining a higher level of benefit from the experience. Therefore, although the structure of the course is permeated by advances and challenges, it was concluded that this experience contributed to the student's learning of certain essential elements of medical training.

Iowa’s Drug Control Strategy, November 1, 2006

The attached annual report is submitted in satisfaction of Chapter 80E.1 of the Code of Iowa which directs the Drug Policy Coordinator to monitor and coordinate all drug prevention, enforcement and treatment activities in the state. Further, it requires the Coordinator to submit an annual report to the Governor and Legislature concerning the activities and programs of the Coordinator, the Governor’s Office of Drug Control Policy and all other state departments with drug enforcement, substance abuse treatment, and prevention programs. Chapter 80E.2 establishes the Drug Policy Advisory Council (DPAC), chaired by the Coordinator, and consisting of a prosecuting attorney, substance abuse treatment specialists, law enforcement officers, a prevention specialist, a judge and representatives from the departments of corrections, education, public health, human services, public safety and human rights. This report and strategy were in developed in consultation with the DPAC.

Reconciling global mammal prioritization schemes into a strategy.

The huge conservation interest that mammals attract and the large datasets that have been collected on them have propelled a diversity of global mammal prioritization schemes, but no comprehensive global mammal conservation strategy. We highlight some of the potential discrepancies between the schemes presented in this theme issue, including: conservation of species or areas, reactive and proactive conservation approaches, conservation knowledge and action, levels of aggregation of indicators of trend and scale issues. We propose that recently collected global mammal data and many of the mammal prioritization schemes now available could be incorporated into a comprehensive global strategy for the conservation of mammals. The task of developing such a strategy should be coordinated by a super-partes, authoritative institution (e.g. the International Union for Conservation of Nature, IUCN). The strategy would facilitate funding agencies, conservation organizations and national institutions to rapidly identify a number of short-term and long-term global conservation priorities, and act complementarily to achieve them.

Family Health Strategy professionals' view on the effects of Hansen's disease training

OBJECTIVEEvaluating how professionals of family health teams from three municipalities of Pernambuco perceive and interpret the effects of Hansen's disease training.METHODSA qualitative study using the perspective of Habermas. Six focus groups, totaling 33 nurses and 22 doctors were formed. The guide consisted of: reactions to training, learning, transfer of knowledge and organizational results.RESULTSThere were recurrent positive opinions on instructor performance, course materials, and an alert attitude to the occurrence of cases; the negative points were about lack of practical teaching, a lot of information in a short period of time and little emphasis on basic content. Low perceived self-efficacy and low locus of control, ambiguity, conflict of skills and the lack of support for the learning application. Nurses showed greater dissatisfaction with the organizational support.CONCLUSIONThe low effectiveness of training reveals the need to negotiate structured training from work problematization, considering performance conditions.

Managerial nursing competencies in the expansion of the Family Health Strategy

Abstract OBJECTIVE To relate the managerial competencies required of nurses with the process of change experienced in the expansion of the Family Health Strategy (FHS). METHOD A qualitative research conducted in primary health care in a southern Brazilian city, through interviews with 32 managerial and clinical nurses. The interviews were processed by IRAMUTEQ software. The resulting classes were examined under five managerial competencies to promote change. RESULTS The four classes obtained from data were: the Family Health Strategy expansion process; confrontations and potentialities; mobilization for the change; innovations in medical and nursing consultations. The classes were related to one or more competencies. CONCLUSION The expansion of the Family Health Strategy requires managerial competencies of implementing and sustaining change, negotiating agreements and commitments, using power and influence ethically and effectively, sponsoring and selling new ideas, and encouraging and promoting innovation.

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing froman offer set, have recently become popular in assortment optimization and revenue management.The dynamic program for these models is intractable and approximated by a deterministiclinear program called the CDLP which has an exponential number of columns. However, whenthe segment consideration sets overlap, the CDLP is difficult to solve. Column generationhas been proposed but finding an entering column has been shown to be NP-hard. In thispaper we propose a new approach called SDCP to solving CDLP based on segments and theirconsideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound onthe dynamic program but coincides with CDLP for the case of non-overlapping segments. Ifthe number of elements in a consideration set for a segment is not very large (SDCP) can beapplied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by(i) simulations, called the randomized concave programming (RCP) method, and (ii) by addingcuts to a recent compact formulation of the problem for a latent multinomial-choice model ofdemand (SBLP+). This latter approach turns out to be very effective, essentially obtainingCDLP value, and excellent revenue performance in simulations, even for overlapping segments.By formulating the problem as a separation problem, we give insight into why CDLP is easyfor the MNL with non-overlapping considerations sets and why generalizations of MNL posedifficulties. We perform numerical simulations to determine the revenue performance of all themethods on reference data sets in the literature.

Approximate knowledge of rationality and correlated equilibria

We extend Aumann's theorem [Aumann 1987], deriving correlated equilibria as a consequence of common priors and common knowledge of rationality, by explicitly allowing for non-rational behavior. Wereplace the assumption of common knowledge of rationality with a substantially weaker one, joint p-belief of rationality, where agents believe the other agents are rational with probability p or more. We show that behavior in this case constitutes a kind of correlated equilibrium satisfying certain p-belief constraints, and that it varies continuously in the parameters p and, for p sufficiently close to one,with high probability is supported on strategies that survive the iterated elimination of strictly dominated strategies. Finally, we extend the analysis to characterizing rational expectations of interimtypes, to games of incomplete information, as well as to the case of non-common priors.

Equivalence of piecewise-linear approximation and Lagrangian relaxation for network revenue management

The network revenue management (RM) problem arises in airline, hotel, media,and other industries where the sale products use multiple resources. It can be formulatedas a stochastic dynamic program but the dynamic program is computationallyintractable because of an exponentially large state space, and a number of heuristicshave been proposed to approximate it. Notable amongst these -both for their revenueperformance, as well as their theoretically sound basis- are approximate dynamic programmingmethods that approximate the value function by basis functions (both affinefunctions as well as piecewise-linear functions have been proposed for network RM)and decomposition methods that relax the constraints of the dynamic program to solvesimpler dynamic programs (such as the Lagrangian relaxation methods). In this paperwe show that these two seemingly distinct approaches coincide for the network RMdynamic program, i.e., the piecewise-linear approximation method and the Lagrangianrelaxation method are one and the same.

A new compact linear programming formulation for choice network revenue management

The choice network revenue management model incorporates customer purchase behavioras a function of the offered products, and is the appropriate model for airline and hotel networkrevenue management, dynamic sales of bundles, and dynamic assortment optimization.The optimization problem is a stochastic dynamic program and is intractable. A certainty-equivalencerelaxation of the dynamic program, called the choice deterministic linear program(CDLP) is usually used to generate dyamic controls. Recently, a compact linear programmingformulation of this linear program was given for the multi-segment multinomial-logit (MNL)model of customer choice with non-overlapping consideration sets. Our objective is to obtaina tighter bound than this formulation while retaining the appealing properties of a compactlinear programming representation. To this end, it is natural to consider the affine relaxationof the dynamic program. We first show that the affine relaxation is NP-complete even for asingle-segment MNL model. Nevertheless, by analyzing the affine relaxation we derive a newcompact linear program that approximates the dynamic programming value function betterthan CDLP, provably between the CDLP value and the affine relaxation, and often comingclose to the latter in our numerical experiments. When the segment consideration sets overlap,we show that some strong equalities called product cuts developed for the CDLP remain validfor our new formulation. Finally we perform extensive numerical comparisons on the variousbounds to evaluate their performance.

On equilibria in duopolies with finite strategy spaces

We will call a game a reachable (pure strategy) equilibria game if startingfrom any strategy by any player, by a sequence of best-response moves weare able to reach a (pure strategy) equilibrium. We give a characterizationof all finite strategy space duopolies with reachable equilibria. Wedescribe some applications of the sufficient conditions of the characterization.

Exact and approximate stepdown methods for multiple hypothesis testing

Consider the problem of testing k hypotheses simultaneously. In this paper,we discuss finite and large sample theory of stepdown methods that providecontrol of the familywise error rate (FWE). In order to improve upon theBonferroni method or Holm's (1979) stepdown method, Westfall and Young(1993) make eective use of resampling to construct stepdown methods thatimplicitly estimate the dependence structure of the test statistics. However,their methods depend on an assumption called subset pivotality. The goalof this paper is to construct general stepdown methods that do not requiresuch an assumption. In order to accomplish this, we take a close look atwhat makes stepdown procedures work, and a key component is a monotonicityrequirement of critical values. By imposing such monotonicity on estimatedcritical values (which is not an assumption on the model but an assumptionon the method), it is demonstrated that the problem of constructing a validmultiple test procedure which controls the FWE can be reduced to the problemof contructing a single test which controls the usual probability of a Type 1error. This reduction allows us to draw upon an enormous resamplingliterature as a general means of test contruction.

On the throughput-WIP trade-off in queueing systems, diminishing returns and the threshold property: A linear programming approach

We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.

Strategy communication and measurement systems

Organizations often face the challenge of communicating their strategiesto local decision makers. The difficulty presents itself in finding away to measure performance wich meaningfully conveys how to implement theorganization's strategy at local levels. I show that organizations solvethis communication problem by combining performance measures in such away that performance gains come closest to mimicking value-added asdefined by the organization's strategy. I further show how organizationsrebalance performance measures in response to changes in their strategies.Applications to the design of performance metrics, gaming, and divisionalperformance evaluation are considered. The paper also suggests severalempirical ways to evaluate the practical importance of the communicationrole of measurement systems.