Narrow Results

Motivated by recent empirical studies of the length distribution of hospital waiting lists, we introduce and solve a set of models that imitate the formation of waiting lists. Patients arriving in the system must choose a waiting list to join, based on its length. At the same time patients leave the lists as they get served. The model illustrates how the power-law distributions found in the empirical studies might arise, but indicates that the mechanism causing the power-laws is unlikely to be the preferential behavior of patients or their physicians.

The healthcare industry in India provides an essential service to everyone in society yet the costs involved have deterred access to the public. This is driven by the incompetent use of healthcare technology, an incomplete system of payments, additional medical services, and limited involvement by patients in the decision-making process of the healthcare system. The spread of COVID-19 vividly demonstrated these weaknesses associated with India’s healthcare system. Given this situation, this chapter identifies the causes of unsustainable healthcare expenditure in India and discusses how to curtail healthcare costs while contributing toward improving the environmental and social impacts of this sector. We conducted research by exploring how the healthcare companies can curtail costs by implementing new practices such as improving the efficiency of utilizing technology. In doing so, this study reveals that only limited efforts in research and development are taking place. The findings of this chapter signify that India’s healthcare is in a weak shape and requires massive transformation. Other developing countries should take India as an example of how to progress and improve their own healthcare sector.

This paper analyzes data on approximately 30,000 women from a survey in Uttar Pradesh in 1995 together with the data from surveys of public and private providers of healthcare and family planning services. A framework was developed for analyzing the effects of quality of services on utilization, and for understanding the gradual evolution of the healthcare infrastructure. The empirical results from logistic regressions for use of female sterilization and IUD showed significant effects of quality of services in government and private hospitals, and of socioeconomic variables such as education, caste, and an index of household possessions. Secondly, models for infant mortality of children born in the preceding 3-year period showed significant effects of socioeconomic variables, quality of healthcare services and birth spacing. Lastly, analysis of data at a more aggregated (Primary Sampling Unit) level indicated differential effects of economic development on the quality of services available in the public and private facilities.

Healthcare is usually the first that comes to our minds when dealing with the consequence of major hazards to deal with the large numbers of casualties; however, this was not available due to the ineffective preparedness. Literature illustrates a significant number of publications covering the resilience of healthcare to major hazards; however these tend to be fragmented due to the complexity of this service which often gives an incomplete picture of the health service and thus leads to inadequate level of preparedness. This chapter addresses some of this fragmentation by shedding light on disaster-resilience in the healthcare sector with the view to enhance the understanding of this service and thus builds its capacity and ultimately mitigates disaster risks. The chapter covers the performance of healthcare post disasters; hospitals’ structural, non-structural and functional integrity; regulations and safety codes; and the integration of resilience and the sustainability agendas through an illustration of international case studies. This chapter also presents new dimensions for enhancing disaster-resilience in a healthcare setting. These dimensions are based on a new concept known as sustainable healthcare.