Background: Implementation science has been growing as discipline in the past decades, producing an increasing number of models in the area. On the other hand, most frameworks are intended to guide the implementation of programs, focusing on identifying elements and stages that increase their success. This article aims to structure this discussion, proposing a simplified tool that synthesizes common elements of other frameworks, and highlight the usefulness to use implementation science not only in identifying successful implementation strategies but as a tool to assess gaps in global health initiatives.

Methods: The study was carried out through a combined methodology that included an initial search of implementation science frameworks, experts’ opinions, and the use of references in frameworks to elaborate a list of articles to be reviewed. A total of 52 articles were analyzed, identifying their definitions of implementation science and the elements of different frameworks.

Results: The analysis of articles allowed identifying the main goals and definitions of implementation science. In a second stage, frameworks were classified into “time-based”, “component-based” and “mixed”, and common elements of each type of model were used to propose a synthetic framework with six elements: Diagnosis, Intervention provider/ system, Intervention, Recipient, Environment, and Evaluation. Finally, this simplified framework was used to identify gaps in global health was using The Lancet Global Health Series. Potential areas of intervention arise for five different global health issues: malaria, non-communicable diseases, maternal and child health, HIV/AIDS, and tuberculosis. Prioritization strategies differ for the different health issues, and the proposed framework can help identify and classify all these different proposals.

Conclusions: There is a huge variety of definitions and models in implementation science. The analysis showed the usefulness of applying an implementation science approach to identify and prioritize gaps in implementation strategies in global health.

Chile is facing a process of rapid aging which poses several challenges. Among these challenges is the increase of dependency in the population. Despite its rele- vance, the topic has not been prioritized in the agenda. One explanation for this low-priority is the lack of information on the concept of dependency. This article shows that, in fact, no consensus exists in Chile on how to define and measure dependency. Additionally, it provides an updated estimation of dependency in the country, aiming to foster further debate on the topic. 

Chile has a mixed health system with public and private actors engaged in provision and insurance.This dual system generates important differences in health expenditure between private and public insurances. Selection is a preeminent feature of the Chilean insurance system. In order to explain the role of the insurance in out-of-pocket expenditures between households for different insurance schemes,decomposition methods are applied to disentangle the effect of household ‘composition and insurance’degree of financial protection on health expenditures. Health expenditure patterns have not changed inthe last 10 years with drugs, outpatient care, and dental health representing 60% of the health expenditure. Health expenditure/income is similar for different income groups in the public insurance, but decreases with income in households with private coverage, reflecting regressivity in health expenditure. On the other hand, health expenditure as share of expenditure increases with income for both groups. Per capita health expenditure in households with private coverage is four times the expenditure of households with public insurance; this gap is mostly explained by differences in households’ expenditureand demographics. Roughly 80% of the difference in expenditure is explained by the model, showing the role of selection in understanding the expenditure gap between insurance schemes.

Objectives

Relationship between human resources for health and mortality remains inconclusive despite numerous studies published on the topic in the last decades. This paper investigates how and why methodological trade-offs implicitly made by researchers when using macro-data can in part explains this puzzling lack of agreement.

Methods

Using data from the Global Health Observatory, we build a model of the relationship between human resources and mortality, which we progressively alter by changing its scope, variables and analysis period. Then, we compare results among themselves to isolate the impact of methodological choices from other changes in the data.

Results

Results demonstrate how methodological choices linked to (1) the analysis period, (2) the definition of health inputs, health outcomes and control variables and (3) the choice of specific variables as proxy for human resources and health outcomes affects the relationship between human resources and health outputs.

Conclusions

Results presented highlights the need for complementing existing macro-analysis with other analytical strategies, for better documenting methodological choices in research studies, as well as for further supporting countries’ efforts to produce reliable and consistent data.

Chile has experienced tremendous changes over the past centuries. Notwithstanding the importance of many of these transformations, the demographic change has been crucial, given its influence on the whole Chilean society. This paper inquires into the effects of the Chilean demographic transition on the fiscal policies implemented by the government throughout a 150 years period. The results suggest a correlation between demographic variables and fiscal expenditure on different goods. Particularly, the estimations find a positive impact of a younger population on educational expenditure and negative effects of the share of adult population on fiscal expenditures.

Chile and Peru produce almost 45% of world’s mine copper output. This situation reflects their natural endowment and mining tradition, but is also the result of development processes undertaken over the last decades. As a result, both countries multiplied its mine copper production in more than 3 times in the last 20 years. Mining labor productivity played a central role achieving these amazing growth rates. Although there is a consensus about the relevance of this variable for the mining industry, the specific factors behind labor productivity changes are not completely understood.

In this paper we use a panel data approach to analyze labor productivity in the copper mining sector in Chile and Peru from 1992 to 2009. This technique is consistent with heterogeneity among mines and allows us to identify, describe and analyze all the different sources behind labor productivity changes.

The result of the analysis shows that better deposits and operational factors are important, but not enough to explain labor productivity improvements in the copper mining industry, and instead, company specific efforts and wide industry changes, such as technology and management innovations, are as important as the evolution of the reserve base or geological features of the operations.