Faced by enormous health care costs and an unsustainable system, more efficient medical practices are needed. This motivates the shift toward preventative and individualized medicine, both of which require a better understanding of disease interactions and the underlying genetic and biological influences.
Using disease ontologies and genetic information, we construct disease networks that capture the co-morbities among diseases, at the phenotype as well as the genetic level, enabling a better understanding as well as predictability.
As prevention is better than cure, a patient-centric preventive healthcare is being adopted to detect diseases in their nascent stage, thus reducing healthcare costs. The health care reforms have led to digitalization of health care.
According to the Federal Interagency Forum on Aging-Related Statistics, the aging population (people aged 65 years and above) in the United States is expected to be twice as large in 2030, compared to 2000 as the “Baby boomers” start turning 65 years from 2011. Though, the life expectancy has also increased, there is a greater prevalence of chronic diseases like hypertension. Thus, technology and relationship building can play an important role to reduce re-admission risks and improve the quality of life for seniors. The driving questions are: how digitization of health care can lead transformation in wellness sustainability in the senior population? How to empower the physician or the community health care worker to ensure the continuity of care?
As a part of Memorial Hospital Community Health Enhancement Aging in Place Programming, “Heritage House”, in South Bend, Indiana, is built to provide home to 72 senior families.We build a smart phone based healthcare application for the senior patients. The application has following components: Medication Scheduling and Management, Medication Adherence, and Observations of Daily Living. Observations of Daily Living are indicative of risks or trends in a patient’s health and include questions about exercise, diet, mood, sleep patterns. To combat with chronic diseases, alerts for their daily medications, medical appointments will be provided. The patients are required to scan the QR codes on the medication bottles, to confirm their medicine intake. For continuity of care, the application would be used as a medium to provide the community health worker with discharge summaries.
We evaluate the efficiency of the application by performing a survey among the users. The efficacy of the application can be evaluated by a comparative study of dosage misses before and after the use of the application; and a comparative study between the number of re-admissions between before and after the use of the application.
Childhood Obesity Project
The driving principle behind this work is the reality that today there are many isolated interventions dealing with childhood obesity. Those that focus on educating children, those that focus on getting kids active. However, this work aims to utilize a collective impact intervention between all of these different areas. Currently the United Way is initiating this type of collective impact programming, aiming to utilize many different community programs, some previously validated such as CATCH and others new and upcoming such as prescription to play. Our part of this work is to create a social wellness platform that will allow children to set and track wellness goals, as well as provide them feedback for progress and information pertaining to their specific interests. The ability to monitor progress is central, aiming to show improvement not just success or failures. They can also utilize controlled social groups within classes and friends to challenge each other for improved performance and reinforce positive behaviors.
Chronic diseases such as diabetes take a great deal of personal commitment and awareness to manage effectively. We understand that every individual is unique, and there may be many causes for these difficulties. However the current practice of retroactively treating this issues is both expensive and less effective than early action treatment. However we understand that in the challenging healthcare environment today creating wide spread interventions for all diabetic patients is not a practical solution. We believe that through the integration of technology and data mining into patient care we can augment the move away from this reactive paradigm to a preventative care model.
The aim of this project is to directly address these concerns. Through a combination of personalized features we aim to identify those individuals at high risk for management issues. We then intend to determine a personalized course of action based on the resources available to that individual.