Privatization of social services: quality differences in Swedish elderly care.

One of the major policy trends in recent decades has been the privatization of social services. This trend has also reached Sweden, a welfare state with health care and social service sectors that previously had almost no private providers. One of the most affected areas is elderly care, i.e. home-help services and residential care provided to citizens older than 65 years, where the proportion of private providers increased from 1% in 1990 to 16% in 2010. The ongoing privatization in Sweden and many other countries has raised important questions regarding the consequences of this policy transformation. In this paper, we present a cross-sectional study comparing the quality of services in private and public elderly care. Using statistics from 2007 displaying a variety of quality dimensions covering over 99% of all elderly care residents in Sweden, we were able to show that privatization is indeed associated with significant quality differences. Structural quality factors such as the number of employees per resident was significantly smaller (-9%) in private elderly care. On the other hand, the proportion of residents participating in the formulation of their care plan (+7%), the proportion of elderly with a reasonable duration between evening meal and breakfast (+15%), and the proportion of elderly offered different food alternatives (+26%) were significantly in favour of private contractors. Our conclusion is that private care providers seem to emphasize service aspects rather than structural prerequisites for good care.

Mechanisms behind privatization: a case study of private growth in Swedish elderly care.

For many years the Swedish Welfare State has been associated with a welfare model in which the public sector dominates both the provision and financing of the elderly care system. However, influenced by the ongoing trend of New Public Management, the past 15 years have been characterized by governmental regimes encouraging competition and as a result there has been a substantial increase in private providers. This case study on elderly care in Sweden provides new insights into the mechanisms behind the spread and growth of privatization. Our results show that in 1990 only 1% of the labour force in the elderly care sector was employed by private organizations, in comparison to 2003 when the private share had increased to 13%. The accompanying organizational changes have been controversial and are often criticized. In general, left-wing politicians have frequently defended the traditional welfare model dominated by public providers, whereas right-wing politicians have urged for a larger share of alternative providers. In this study, statistics between the years 1990 and 2003 were used to model the relationship between privatization and a number of economic, political and social/demographic variables. The results from regression and diffusion analysis imply that privately managed elderly care has established itself mainly in metropolitan areas dominated by right-wing regimes. Surprisingly, neighbouring municipalities tend to follow these pioneers irrespective of their political colour or economic situation. In fact, after shifting political power many of those neighbouring municipalities dominated by left-wing regimes not only maintain an abundance of private contractors but also encourage a continued process of contracting out publicly managed elderly care units. As a result, clusters of municipalities with an increasing degree of privatization arise despite political and economic differences. In conclusion, geographical proximity seems to be an important variable in addition to population density, ideology and financial situation when privatization reforms are implemented in the Swedish elderly care system.

Second-order peak detection for multicomponent high-resolution LC/MS data.

The first step when analyzing multicomponent LC/MS data from complex samples such as biofluid metabolic profiles is to separate the data into information and noise via, for example, peak detection. Due to the complex nature of this type of data, with problems such as alternating backgrounds and differing peak shapes, this can be a very complex task. This paper presents and evaluates a two-dimensional peak detection algorithm based on raw vector-represented LC/MS data. The algorithm exploits the fact that in high-resolution centroid data chromatographic peaks emerge flanked with data voids in the corresponding mass axis. According to the proposed method, only 4 per thousand of the total amount of data from a urine sample is defined as chromatographic peaks; however, 94% of the raw data variance is captured within these peaks. Compared to bucketed data, results show that essentially the same features that an experienced analyst would define as peaks can automatically be extracted with a minimum of noise and background. The method is simple and requires a priori knowledge of only the minimum chromatographic peak width-a system-dependent parameter that is easily assessed. Additional meta parameters are estimated from the data themselves. The result is well-defined chromatographic peaks that are consistently arranged in a matrix at their corresponding m/z values. In the context of automated analysis, the method thus provides an alternative to the traditional approach of bucketing the data followed by denoising and/or one-dimensional peak detection. The software implementation of the proposed algorithm is available at http://www.anchem.su.se/peakd as compiled code for Matlab.