Is hospital discharge administrative data an appropriate source of information for cancer registries purposes? Some insights from four Spanish registries

Background. The use of hospital discharge administrative data (HDAD) has been recommended for automating, improving, even substituting, population-based cancer registries. The frequency of false positive and false negative cases recommends local validation. Methods. The aim of this study was to detect newly diagnosed, false positive and false negative cases of cancer from hospital discharge claims, using four Spanish population-based cancer registries as the gold standard. Prostate cancer was used as a case study. Results. A total of 2286 incident cases of prostate cancer registered in 2000 were used for validation. In the most sensitive algorithm (that using five diagnostic codes), estimates for Sensitivity ranged from 14.5% (CI95% 10.3-19.6) to 45.7% (CI95% 41.4-50.1). In the most predictive algorithm (that using five diagnostic and five surgical codes) Positive Predictive Value estimates ranged from 55.9% (CI95% 42.4-68.8) to 74.3% (CI95% 67.0-80.6). The most frequent reason for false positive cases was the number of prevalent cases inadequately considered as newly diagnosed cancers, ranging from 61.1% to 82.3% of false positive cases. The most frequent reason for false negative cases was related to the number of cases not attended in hospital settings. In this case, figures ranged from 34.4% to 69.7% of false negative cases, in the most predictive algorithm. Conclusions. HDAD might be a helpful tool for cancer registries to reach their goals. The findings suggest that, for automating cancer registries, algorithms combining diagnoses and procedures are the best option. However, for cancer surveillance purposes, in those cancers like prostate cancer in which care is not only hospital-based, combining inpatient and outpatient information will be required.

The Role of Information in Contemporary Migration. More Sources but Less Informed

La migració internacional contemporània és integrada en un procés d'interconnexió global definit per les revolucions del transport i de les tecnologies de la informació i la comunicació. Una de les conseqüències d'aquesta interconnexió global és que les persones migrants tenen més capacitat per a processar informació tant abans com després de marxar. Aquests canvis podrien tenir implicacions inesperades per a la migració contemporània pel que fa a la capacitat de les persones migrants per a prendre decisions més informades, la reducció de la incertesa en contextos migratoris, el desdibuixament del concepte de distància o la decisió d'emigrar cap a llocs més llunyans. Aquesta recerca és important, ja que la manca de coneixement sobre aquesta qüestió podria contribuir a fer augmentar la distància entre els objectius de les polítiques de migració i els seus resultats. El paper que tenen els agents de la informació en els contextos migratoris també podria canviar. En aquest escenari, perquè les polítiques de migració siguin més efectives, s'haurà de tenir en compte la major capacitat de la població migrant de processar la informació i les fonts d'informació en què es confia. Aquest article demostra que l'equació més informació equival a més ben informat no es compleix sempre. Fins i tot en l'era de la informació, les fonts no fiables, les expectatives falses, la sobreinformació i els rumors encara són presents en els contextos migratoris. Tanmateix, defensem l'argument que aquests efectes no volguts es podrien reduir complint quatre requisits de la informació fiable: que sigui exhaustiva, que sigui rellevant, que s'hi confiï i que sigui actualitzada.

Two-sided learning in new keynesian models: dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified

The evolution of information suppression in communicating robots with conflicting interests.

Reliable information is a crucial factor influencing decision-making and, thus, fitness in all animals. A common source of information comes from inadvertent cues produced by the behavior of conspecifics. Here we use a system of experimental evolution with robots foraging in an arena containing a food source to study how communication strategies can evolve to regulate information provided by such cues. The robots could produce information by emitting blue light, which the other robots could perceive with their cameras. Over the first few generations, the robots quickly evolved to successfully locate the food, while emitting light randomly. This behavior resulted in a high intensity of light near food, which provided social information allowing other robots to more rapidly find the food. Because robots were competing for food, they were quickly selected to conceal this information. However, they never completely ceased to produce information. Detailed analyses revealed that this somewhat surprising result was due to the strength of selection on suppressing information declining concomitantly with the reduction in information content. Accordingly, a stable equilibrium with low information and considerable variation in communicative behaviors was attained by mutation selection. Because a similar coevolutionary process should be common in natural systems, this may explain why communicative strategies are so variable in many animal species.

A Review of the State's Leased Space and the Leasing Process, General Services Enterprise of the Department of Administrative Services, July 1, 1998 through June 30, 2003

Other Audit Reports - State Leasing

A semantic model of selective dissemination of information for digital libraries

In this paper we present the theoretical and methodologicalfoundations for the development of a multi-agentSelective Dissemination of Information (SDI) servicemodel that applies Semantic Web technologies for specializeddigital libraries. These technologies make possibleachieving more efficient information management,improving agent–user communication processes, andfacilitating accurate access to relevant resources. Othertools used are fuzzy linguistic modelling techniques(which make possible easing the interaction betweenusers and system) and natural language processing(NLP) techniques for semiautomatic thesaurus generation.Also, RSS feeds are used as “current awareness bulletins”to generate personalized bibliographic alerts.

Open source business strategies in the domain of embedded systems

El tema de este estudio es el aumento de la comprensión teórica y empírica de la estrategia de negocio de código abierto en el dominio de sistemas embebidos por investigar modelos de negocios de código abierto, retos, recursos y capacidades operativas y dinámicas.

Let's (not) talk about sex: The effect of information provision on gender differences in performance under competition

We study how gender differences in performance under competition areaffected by the provision of information regarding rival s gender and/ordifferences in relative ability. In a laboratory experiment, we use two tasks thatdiffer regarding perceptions about which gender outperforms the other. Weobserve women s underperformance only under two conditions: 1) tasks areperceived as favoring men and 2) rivals gender is explicitly mentioned. Thisresult can be explained by stereotype-threat being reinforced when explicitlymentioning gender in tasks in which women already consider they are inferior.Omitting information about gender is a safe alternative to avoid women sunderperformance in competition.

Two-sided learning in New Keynesian models: Dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank(two-sided learning) in a New Keynesian framework in which both sides of the economyhave asymmetric and imperfect knowledge about the true data generating process. Weassume that all agents employ the data that they observe (which may be distinct fordifferent sets of agents) to form beliefs about unknown aspects of the true model ofthe economy, use their beliefs to decide on actions, and revise these beliefs througha statistical learning algorithm as new information becomes available. We study theshort-run dynamics of our model and derive its policy recommendations, particularlywith respect to central bank communications. We demonstrate that two-sided learningcan generate substantial increases in volatility and persistence, and alter the behaviorof the variables in the model in a significant way. Our simulations do not convergeto a symmetric rational expectations equilibrium and we highlight one source thatinvalidates the convergence results of Marcet and Sargent (1989). Finally, we identifya novel aspect of central bank communication in models of learning: communicationcan be harmful if the central bank's model is substantially mis-specified.