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This brief chapter explores my experiences with music and death throughout my cancer treatment. Though I constantly confronted my mortality throughout my cancer treatment, music also helped to distract me from unpleasant, lengthy or boring treatments, as well as helping me to process my feelings about my own mortality. It thus served two distinct purposes, both focusing my mind on death and pain and distancing me from it.

This is the third in a series of papers aimed at providing models effective in predicting the degree of pain and discomfort in canines. The first two papers provided benchmarking and examination of dogs suffering from osteoarthritis (OA). In this chapter, we extend the study to include dogs suffering from OA, sarcoma, and oral mucositis (a side effect of chemotherapy and radiation treatments). The R programming language and SAS JMP are used to clean data, generate ANOVA, LSR regression, decision tree, and nominal logistic regression models to predict changes in activity levels associated with the progression of arthritis. The predictive models provide a diagnostic basis for determining the degree of disease in a dog (based on demographics and activity levels) and provide forecasts that assist in establishing appropriate medication dosages for suffering dogs.

The Abdur Razzaque Ansari Memorial Weavers Hospital (ARAM) came into effect on 7 April 1996, and is dedicated to the people of Jharkhand and weavers. To deal with the issues of inequity in healthcare services, ARAM was founded for the extension of affordable healthcare services to the needy in and around the area of Jharkhand. Visualised by a great social worker and legend Abdur Razzaque Ansari, it has been successfully run by his eldest son Mr Sayeed Ahmad Ansari for 28 years. This research uses mainly a case-study approach through secondary data from the hospital website and other websites citing ARAM and its functions. Consent to use data for the study was obtained from Mr. Sayeed Ahmad Ansari. Primary information was collected through the patients who availed facilities from the hospital. They were interviewed through a semi-structured questionnaire each taking 30-40 minutes. Taken over by Medanta Group on 8 July 2015 (earlier being managed by Apollo Hospitals Group for 20 years), it is the first super speciality community hospital in Eastern India. Treating over 50,000 patients yearly with state-of-the-art medical equipment and providing discounts to lower-income groups, people from the weaver’s community, freedom fighters and members of ICSI have intrigued people from these sections for affordable treatment and facilities in and near Jharkhand. With a 200 bed-capacity, nine different disciplines and 12 departments spread across the city of Ranchi, the hospital caters to a massive population at a much-subsidised rate. Reaching out to rural villages through free medical camps and awareness campaigns, the hospital showcases how a successful model of healthcare cooperative can be replicated accordingly in similar developing and underdeveloped regions.

Barriers to adequate healthcare in rural areas remain a grand challenge for local healthcare systems. In addition to patients' travel burdens, lack of health insurance, and lower health literacy, rural healthcare systems also experience significant resource shortages, as well as issues with recruitment and retention of healthcare providers, particularly specialists. These factors combined result in complex change management-focused challenges for rural healthcare systems. Change management initiatives are often resource intensive, and in rural health organizations already strapped for resources, it may be particularly risky to embark on change initiatives. One way to address these change management concerns is by leveraging socio-technical simulation models to estimate techno-economic feasibility (e.g., is it technologically feasible, and is it economical?) as well as socio-utility feasibility (e.g., how will the changes be utilized?). We present a framework for how healthcare systems can integrate modeling and simulation techniques from systems engineering into a change management process. Modeling and simulation are particularly useful for investigating the amount of uncertainty about potential outcomes, guiding decision-making that considers different scenarios, and validating theories to determine if they accurately reflect real-life processes. The results of these simulations can be integrated into critical change management recommendations related to developing readiness for change and addressing resistance to change. As part of our integration, we present a case study showcasing how simulation modeling has been used to determine feasibility and potential resistance to change considerations for implementing a mobile radiation oncology unit. Recommendations and implications are discussed.

Purpose – Objective measures of a new treatment's expected ability to improve patients’ health are presumed to be significant factors influencing physicians’ treatment decisions. Physicians’ behavior may also be influenced by their patients’ disease severity and insurance reimbursement policies, firm promotional activities and public media reports. This chapter examines how objective evidence of the incremental effectiveness of novel drugs to treat cancer (“chemotherapies”) impacts the rate at which physicians’ adopt these treatments into practice, holding constant other factors.

Design/methodology – The novelty of the analysis resides in the dataset and estimation strategy employed. Data is derived from a United States population-based chemotherapy order entry system, IntrinsiQ Intellidose. Quality/price endogeneity is overcome by employing sample selection methods and an estimation strategy that exploits quality variation at the molecule-indication level. Pooled diffusion rates across molecule-indication pairs are estimated using nonparametric hazard models.

Findings – Results suggest incremental effectiveness is negatively and nonsignificantly associated with the diffusion of new chemotherapies; faster rates of diffusion are positively and significantly related to low five-year survival probabilities and measures of perceived clinical significance. Results are robust to numerous specification checks, including a measure of alternative therapeutic availability. We discuss the magnitude and potential direction of bias introduced by several threats to internal validity. Evidence of incremental effectiveness does not appear to motivate the rate of specialty physician diffusion of new medical treatment; in all models high risk of disease mortality and perceptions of therapeutic quality are significant drivers of physician use of novel chemotherapies.

Value/originality – Understanding the rate of technological advance across different clinical settings, as well as the product-, provider-, and patient-level determinants of this rate, is an important subject for future research.

Researchers continue to seek understanding of industrialization as a state managed process. How to create and implement new industries based on advanced knowledge is on the policy agenda of many advanced nations. Measures that promote these developments include national capacity building in science and technology, the formation of technology transfer systems, and the establishment of industrial clusters. What these templates often overlook is an analysis of use. This chapter aims to increase the understanding of the processes that embed new solutions in structures from an industrial network perspective. The chapter describes an empirical study of high-technology industrialization in Taiwan that the researcher conducts to this end. The study shows that the Taiwanese industrial model is oversimplified and omits several important factors in the development of new industries. This study bases its findings on the notions that resource combination occurs in different time and space, the new always builds on existing resource structures, and the users are important as active participants in development processes.

In this chapter, we identify three distinct transformational performance improvement (TPI) approaches commonly used to redesign work processes in health care organizations. We describe the unique components or tools that each approach uses to improve the delivery of health services. We also summarize what is empirically known about the effectiveness of each TPI approach according to systematic reviews and recent studies published in the peer-reviewed literature. Based on examination of this research, we discuss what knowledge is still needed to strengthen the evidence for whole system transformation. This involves the use of conceptual frameworks to assess and guide implementation efforts, and facilitators and barriers to change as revealed in a recent evaluation of one major initiative, the Lean Enterprise Transformation (LET) at the Veterans Health Administration. The analysis suggests ways in which TPI facilitators can be developed and barriers reduced to improve the effectiveness and sustainability of quality initiatives. Finally, we discuss appropriate study designs to evaluate TPI interventions that may strengthen the evidence for their effectiveness in real world practice settings.