Healthcare 4.0: trends,challenges and research directions

Abstract

This paper aims at examining the trends, challenges and theoretical gaps in the implementation of Healthcare 4.0 (H4.0) based on a scoping review of the literature. For that, we searched journal articles in four widely known databases and screened the retrieved articles to obtain a publications’ portfolio. Our findings indicate that, despite the recency of the subject, research in H4.0 has been conducted in an interdisciplinary way with a diversified set of applications and functionalities. In terms of its implementation, H4.0 has been more commonly found in hospitals’ information flows, especially the ones related to healthcare treatments. The identified implementation trends, however, neglect a more holistic approach for H4.0, which originated three main research directions for this topic. Although identified as a trending topic in the area of healthcare operations management, literature on H4.0 may be viewed as randomly conceived, lacking academic alignment and practical orientation based on a grounded theory, which we aim at providing with the present study.     

The role of non-governmental organizations for the welfare of the elderly: the case of HelpAge India

Since there has been a gradual increase in the population aged 60 and older, a developing country like India is unable to cope with the needs and problems of its aged populations. While the government continues its efforts to introduce programs for the elderly, the non-governmental organizations (NGOs) have played a key role in bringing to the forefront the socioeconomic and health problems of older people in the society at large. This paper looks at the role of the NGOs through their various welfare activities and beneficial programs in carving out a place for the elderly in India. The work of HelpAge India is highlighted to examine how voluntary organizations have worked in the field of aging in India and made an impact on the lives of the senior citizens, especially those below the poverty line who are economically and socially deprived.     

Employee turnover forecasting for human resource management based on time series analysis

In some organizations, the hiring lead time is often long due to responding to human resource requirements associated with technical and security constrains. Thus, the human resource departments in these organizations are pretty interested in forecasting employee turnover since a good prediction of employee turnover could help the organizations to minimize the costs and impacts from the turnover on the operational capabilities and the budget. This study aims to enhance the ability to forecast employee turnover with or without considering the impact of economic indicators. Various time series modelling techniques were used to identify optimal models for effective employee turnover prediction. More than 11-years of monthly turnover data were used to build and validate the proposed models. Compared with other models, a dynamic regression model with additive trend, seasonality, interventions, and a very important economic indicator effectively predicted the turnover with training R²?=?0.77 and holdout R²?=?0.59. The forecasting performance of optimal models confirms that time series modelling approach has the ability to predict employee turnover for the specific scenario observed in our analysis.