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Spatial shift-share analysis as a health policy tool

100%

Jewczak M. , Żółtaszek A.

Issues related to the functioning of the healthcare sector always result in turbulent and endless discussions. Most of those voices concern: the reduction of costs, spending on healthcare, walk outs, multi-occupation of medical staff, operating and health sector entities’ debts. The criteria of economic analysis in the health sector require to look at the activities of medical units, from the perspective of the society and its char- acteristics that determine them, and taking into account the effects connected with the geographic diversification of the management, financing and organization of the health- care system. The aim of this paper is to apply the spatial shift-share methods that are based on information about of the structural changes of economic and social phenomena, developed in geographic space, within a specified period of time, to analyze the state of the health sector. The attempt to identify regional trends in the health care sector, depending on the sector's major characteristics, will be made. The analysis also aims to identify areas and determinants of health care sector that may play a key role in specialization and the development of the regions.

An integrated review on machine learning approaches for heart disease prediction: Direction towards future research gaps

75%

Vellameeran F. A. , Brindha T.

2022

tom Vol. 18, no. 1

69--83

Objectives: To make a clear literature review on state-ofthe-art heart disease prediction models. Methods: It reviews 61 research papers and states the significant analysis. Initially, the analysis addresses the contributions of each literature works and observes the simulation environment. Here, different types of machine learning algorithms deployed in each contribution. In addition, the utilized dataset for existing heart disease prediction models was observed. Results: The performance measures computed in entire papers like prediction accuracy, prediction error, specificity, sensitivity, f-measure, etc., are learned. Further, the best performance is also checked to confirm the effectiveness of entire contributions. Conclusions: The comprehensive research challenges and the gap are portrayed based on the development of intelligent methods concerning the unresolved challenges in heart disease prediction using data mining techniques.

Employee satisfaction with tangible and intangible rewards in health care sector

63%

Beck-Krala E. , Tarczoń E. , Masłyk T.

tom Vol. 16, No. 2

17--27

Satisfaction with the reward systems produces desired employee behaviors that, in turn, may produce high quality of service as well as financial benefits to the organization. This is especially important in sectors that play a major role in society as the public health care, which despite increased demand for staff, is experiencing an outflow of workers. The aim of this paper is to evaluate employees’ satisfaction with rewards among employees in a hospital selected from the public health care service in Poland. Results of this study showed what aspects of the rewards system need to be modified and also confirmed that satisfaction with reward is conditioned by demographic characteristics of employees.

Satysfakcja z systemów wynagradzania powoduje pożądane zachowania pracowników, które z kolei mogą zapewnić wysokiej jakości usługi, a także korzyści finansowe dla organizacji. Jest to szczególnie ważne w sektorach, które odgrywają ważną rolę w społeczeństwie, jak publiczna służba zdrowia, która pomimo zwiększonego zapotrzebowania na pracowników doświadcza odpływu pracowników. Celem niniejszego artykułu jest ocena satysfakcji pracowników z nagród wśród pracowników szpitala wybranego z publicznej służby zdrowia w Polsce. Wyniki tego badania pokazały, jakie aspekty systemu nagród wymagają modyfikacji, a także potwierdziły, że satysfakcja z nagrody zależy od cech demograficznych pracowników.