An Evaluation of Partnership for Productive Development in Brazil's Healthcare: Measuring the Knowledge Translation from Implementation to the Impact

An Evaluation of Partnership for Productive Development in Brazil's Healthcare: Measuring the Knowledge Translation from Implementation to the Impact

Jorge Lima Magalhães (Oswaldo Cruz Foundation (FIOCRUZ), Brazil), Zulmira Hartz (Universidade Nova de Lisboa (UNL), Portugal) and Adelaide M. S. Antunes (National Institute for Industrial Property (INPI), Brazil & University of Rio de Janeiro (UFRJ), Brazil)
DOI: 10.4018/978-1-5225-1674-3.ch031
OnDemand PDF Download:
$30.00
List Price: $37.50

Abstract

21st Century brings great challenges in the information and knowledge areas. The public health is intensified in Developing and Less Developed Countries on account of parasitic diseases as well as developed countries because emerging and reemerging diseases. This diseases associated with chronic or acute diseases can intensify causing a serious health problem as drugs resistance, neglected disease and to afford perpetuate poverty. Thus, it is urgent new ways for information management. The management of the Partnership for Productive Development (PDP) have been shown a promising tool to help internalize new technologies and foster R,D&I. This chapter gives an evaluation for Healthcare using the example of the Brazilian PDP whose last way may be considered as a Knowledge Translation. In five years were conducted 103 PDP involving public and private pharmaceutical companies and international producer, promoting the development of local economy and reducing government spending from medicines derived from PDP.
Chapter Preview
Top

1. Introduction

The information can be seen as a condition for survival, given that it extends the communication context and rescuing and preserving social memory. Its value is intangible and resists all the mechanisms of destruction and oblivion since the collection of information. This is due, on the grounds that allows reconstructing the cognitive and knowledge assessment of a given situation in question (Lawrence & Giles, 2000).

However, in the 21 century the capacity to generate speed information is modern and unprecedented in the world because of the Internet. Data created are practically instantaneous. Technological per-capita capacity of the world to store information nearly doubled every 40 months since the 1980s. From 2012, every day 2.5 quintillion (2.5 × 1018) bytes of data are created (Lynch, 2008). This phenomenon growing is called Big Data (Lawrence & Giles, 2000; McKinsey Global Institute, 2011)

Quantity of daily data posted on the Web has led to a constant training of new professionals in all science areas. New activities have appeared such as the Data Scientist - one who constantly seeks the best way to deal with the phenomenon of Big Data. The Big Data term has been consolidated within the scientific community due to the set of technological solutions capable of dealing with the ongoing accumulation of data that are unstructured and are captured from several sources. They are presented in order of petabytes, i.e.; quadrillion bytes of stored data. It's challenging the way to deal with these issues both for conducting scientific projects and any type of business organizations (Lynch, 2008).

At the institutional level decisions made without the right information lead to inaccurate decisions and sometimes disastrous. Decisions based on facts and reliable information are more likely to generate good results thereby enabling decision maker’s subsidies to meet the everyday challenges. Proper and timely information can develop effective strategies and acts proactively. This action can be called a competitive strategy when it involves business approach, which maximizes the value of the capacity of the organization to distinguish the company from its competitors (Porter, 2008).

Any scientific research area or an organization to lead to the advancement in technology, i.e., to improve to the management of large volumes of data, must apply the concept to extract data in order to have a more consistent view for decision making of managers. An example about online (and in time) information on a particular topic can be seen in Figure 1, in this case it was used the term “technology transfer”.

Figure 1.

Overview about technology in the world in general news.

Source: Newsmap (http://newsmap.jp/. (Access: October 6, 2014).

It should be emphasized that the data shown by Newsmap are interactive and they gather all the information commented on a certain day and time period on the topic researched. Thus, it is possible to have an overview of the particular subject and immediately report to the most relevant topic for the decision maker. Thereby, from this point to extracting the core information into other scientific bases. Figure 1 shows also that the greater the size of the rectangle, greatest the consistency of the research topic, i.e. it reflects that topic got a bigger number of reviews and publications in relation to the others shown in the search. In this sense, clicking the selected rectangle, you can redeem the respective articles.

It is globally recognized that the Science is data intensive and information but the scale with which it presents itself in recent times is exponential in any science area. Even considering their correlations in a globalized context. Therefore, requires new tools for extracting, analyzing and informational treatment. One approach that has enabled this activity is that the information science which have focused on information enables multidisciplinary interface with several areas (Magalhães, Quoniam, & Boechat, 2013; Quoniam, L, 2011; Trigo, Gouveia, Quoniam, & Riccio, 2007).

Complete Chapter List

Search this Book:
Reset