Understanding Patients’ Needs and Healthcare Seeking Behavior in Rural Southern India: The Comparison of Providers through Patients’ Perceptions and Cost Issues

This study explores patients’ needs in rural Thanjavur, southern India through understanding how people with diabetes choose providers and perceive care-seeking experience. To measure perception, the study surveyed people regarding six common barriers to care-seeking behavior, selected from both literature and local expert interview. Ninety-one percent of the sampled population goes to public or private allopathic providers out of the six presented providers. The low socioeconomic group and people with more complications or comorbidities are more likely to go to private allopathic providers. What is more, there is no difference between public and private allopathic providers in patients’ perception of care except for perceived cost. Positive perceptions in both providers are very common except for perceptions in blood-sugar management, distance to facilities, and cost of care. Sixty-six percent of patients perceived their blood-sugar control to fluctuate or have no change versus improved control. Twenty-seven percent of patients perceived the distance to facilities as unreasonable, and sixty-two percent of patients perceived the cost as high for them. The results suggest that cost may affect low socioeconomic people’s choice of care significantly. However, for people in middle and higher socioeconomic groups, cost does not appear to be a major factor. For qualitative text analyses, physician’s behavior and reputation emerge as themes, which require further studies.

Mobile Clinics & Bundled Healthcare: An Exploration of Patient Perceptions of the SughaVazhvu Approach to Chronic Care Management

As the burden of non-communicable diseases increases worldwide, it is imperative that health systems adopt delivery approaches that will enable them to provide accessible, high-quality, and low-cost care to patients that need consistent management of their lifelong conditions. This is especially true in low- and middle-income country settings, such as India, where the disease burden is high and the health sector resources to address it are limited. The subscription-based, managed care model that SughaVazhvu Healthcare—a non-profit social enterprise operating in rural Thanjavur, Tamil Nadu—has deployed demonstrates potential for ensuring continuity of care among chronic care patients in resource-strained areas. However, its effectiveness and sustainability will depend on its ability to positively impact patient health status and patient satisfaction with the care management they are receiving. Therefore, this study is not only a program appraisal to aid operational quality improvement of the SughaVazhvu Healthcare model, but also an attempt to identify the factors that affect patient satisfaction among individuals with chronic conditions actively availing services.

Operationalizing the social-ecological systems framework to assess sustainability.

Environmental governance is more effective when the scales of ecological processes are well matched with the human institutions charged with managing human-environment interactions. The social-ecological systems (SESs) framework provides guidance on how to assess the social and ecological dimensions that contribute to sustainable resource use and management, but rarely if ever has been operationalized for multiple localities in a spatially explicit, quantitative manner. Here, we use the case of small-scale fisheries in Baja California Sur, Mexico, to identify distinct SES regions and test key aspects of coupled SESs theory. Regions that exhibit greater potential for social-ecological sustainability in one dimension do not necessarily exhibit it in others, highlighting the importance of integrative, coupled system analyses when implementing spatial planning and other ecosystem-based strategies.

Latent Space and Social Psychological Models of Diffusion

The problem of social diffusion has animated sociological thinking on topics ranging from the spread of an idea, an innovation or a disease, to the foundations of collective behavior and political polarization. While network diffusion has been a productive metaphor, the reality of diffusion processes is often muddier. Ideas and innovations diffuse differently from diseases, but, with a few exceptions, the diffusion of ideas and innovations has been modeled under the same assumptions as the diffusion of disease. In this dissertation, I develop two new diffusion models for "socially meaningful" contagions that address two of the most significant problems with current diffusion models: (1) that contagions can only spread along observed ties, and (2) that contagions do not change as they spread between people. I augment insights from these statistical and simulation models with an analysis of an empirical case of diffusion - the use of enterprise collaboration software in a large technology company. I focus the empirical study on when people abandon innovations, a crucial, and understudied aspect of the diffusion of innovations. Using timestamped posts, I analyze when people abandon software to a high degree of detail.

To address the first problem, I suggest a latent space diffusion model. Rather than treating ties as stable conduits for information, the latent space diffusion model treats ties as random draws from an underlying social space, and simulates diffusion over the social space. Theoretically, the social space model integrates both actor ties and attributes simultaneously in a single social plane, while incorporating schemas into diffusion processes gives an explicit form to the reciprocal influences that cognition and social environment have on each other. Practically, the latent space diffusion model produces statistically consistent diffusion estimates where using the network alone does not, and the diffusion with schemas model shows that introducing some cognitive processing into diffusion processes changes the rate and ultimate distribution of the spreading information. To address the second problem, I suggest a diffusion model with schemas. Rather than treating information as though it is spread without changes, the schema diffusion model allows people to modify information they receive to fit an underlying mental model of the information before they pass the information to others. Combining the latent space models with a schema notion for actors improves our models for social diffusion both theoretically and practically.

The empirical case study focuses on how the changing value of an innovation, introduced by the innovations' network externalities, influences when people abandon the innovation. In it, I find that people are least likely to abandon an innovation when other people in their neighborhood currently use the software as well. The effect is particularly pronounced for supervisors' current use and number of supervisory team members who currently use the software. This case study not only points to an important process in the diffusion of innovation, but also suggests a new approach -- computerized collaboration systems -- to collecting and analyzing data on organizational processes.