Abstract
Heart attacks are one of the leading causes of death and often have a high chance of reoccurrence. A heart attack is caused by lack of blood flow and oxygen to the heart, which results in progressive death of cardiomyocytes without sufficient cellular renewal. Thus, I am conducting research to discover pathways and strategies that may enhance cardiomyocyte renewal, allowing the damaged cells to be healthy again. To do so, a computational model will be developed of the cardiomyocyte cell cycle and complexes to determine the key players in regulating cardiomyocyte regeneration. The model is focused on the intermediary step of developing a tool for further research. Therefore, while designing the model, the human and social dimensions would need to be considered since they encompass direct stakeholders, such as researchers and funders. The model is being funded through the National Heart, Blood, and Lung Institute, which has a number of objectives relating to promoting the prevention and treatment of the heart. One of the objectives that align with cardiomyocyte regeneration is to investigate newly discovered pathobiological mechanisms important to the onset and progression regarding to the heart. While my technical research concerns designing models for heart attacks, my STS research focuses on the impact of wearable devices on diagnosing and monitoring patients through the relationships in healthcare.
Wearable device technology has risen in popularity in the past decade, allowing both users and doctors to have access to their own or the patient’s personal health at all times of the day. With this convenience and the continual growth of a personal health monitor, the devices would change healthcare and the relationships in it. The devices are also predicted to influence aspects of prevention, diagnosis, and disease management, in addition to health status. To analyze how the relationship between patients and physicians may change, the Interactive Sociotechnical Analysis (ISTA) framework was utilized. This framework draws on previous studies of in order to analyze how social groups impacts each other. ISTA was applied to data gathered from interviewing qualified professionals that work closely with wearables in the healthcare system. Each interviewees’ response was parsed through to code certain words or phrases for quantification and analysis. Through the research, I seek to investigate how the rise of wearable devices would affect the healthcare system and the relationship between patients and healthcare providers. We are expecting that the responses would be a mixture of opinions because the devices are not accurate enough compared to the clinical medical equipment.
Both the computational model and the wearable device technology would change the way healthcare is perceived. With the model focusing on healing after a heart attack, and the devices as a preventative diagnostic tool.
