SeVA: Seniors Virtual Assistant
In the United States, approximately 6 million patients suffer from Alzheimer’s dementia. This number is only going to grow in the future. Alzheimer’s is the leading cause of death in the United States, and out of the top causes of death, is the only one that cannot be prevented. Complicating the course of Alzheimer’s dementia in hospitalized patients is superimposed delirium, which is frequently missed by the care teams. Inouye et al. (2014), in their landmark LANCET study, were able to add a financial cost to this diagnosis and reported an estimated loss of $160 billion per year. A significant fraction of that lost revenue comes from patient’s prolonged stay in the hospital due to delirium and its complications. Each additional hospital day beyond the expected length of stay (defined by Medicare and commercial payers using the Diagnosis Related Group bundled payment methodology), adds to the hospital financial losses.
50 million people suffered from Alzheimer’s dementia worldwide in 2017. A new person develops dementia every 3 seconds. In general, the population that can benefit from SeVA platform is huge, is growing, and threatens to drain the financial resources for both developed and developing countries. Beyond Alzheimer’s dementia, SeVA can also be utilized for delirium prevention in all hospitalized patients. In 2016, according to Center for Disease Control (CDC), an estimated 35 Million patients were hospitalized. Based on studies, one in every five patients in the hospital develops delirium, leading to an increased length of stay anywhere between 2-5 days. With these numbers in mind, SeVA has a cumulative potential of impacting and improving care for 7 million hospitalized patients each year in the United States, decrease cumulative hospital length of stay by 14 million – 35 million patient days and therefore, have an enormous financial impact for both Healthcare systems and payers like Medicare. Average cost per hospital day in the United States is $2,346. As such cumulative cost-saving potential for SeVA is anywhere between $ 32 Billion to $ 80 Billion.
SeVA brings value by optimizing nursing workload. Nurses in acute care facilities (Hospitals, SNFs, IRFs, etc.) perform many cyclical tasks at regular intervals for continuous patient monitoring. These tasks include activities like checking on the patient frequently for toileting questions, delirium detection, etc. In addition, the nurses also provide a personal touch to patients by talking to them about their day, concerns, etc. However, even with this intense schedule, the patient still has windows of “unsupervised care”, with no direct observation. These windows of unsupervised care lead to adverse events like falls. For delirious/Alzheimer’s dementia patients, with an inability to use the nursing call light, basic needs like water, bathroom trips go unaddressed. SeVA has the capability to provide a meaningful bi-directional and medically oriented conversation with the patient. This can decrease the cyclical checks the nurses perform. For example, instead of the nurse checking on the patient every hour for bathroom needs, SeVA can auto-activate to ask this question every hour. The AEI technology in SeVA analyzes the answer and directs the patient’s needs to the nursing staff and improving the workflow related to cyclical checks. With further developments and upgrades, SeVa will be able to document this encounter in the EHR, thus eliminating both nursing charting time and also recording accurate patient events.
HELP has been shown to improve cost related to delirium in hospitalized patients. Study done involving 7000 patients per year on 6 hospital units resulted in annual savings of $6.9 million. For patients above the age of 65,
For Health Systems, nursing time optimization has been a challenge. Each nurse on an average cares for 4-5 patients per shift. An hourly check protocol can take up to 5 minutes which can translate to 20-25 minutes every hour of nursing time. SeVA can decrease nursing workload by performing these monotonous tasks accurately and consistently every hour, therefore providing precious minutes to the nurse for more actionable care, thereby increasing both patient and nurse employee satisfaction.
Impact: The SeVA platform and technology will have the following profound impact on healthcare
The SeVA platform will increase the rate of delirium detection, and as such, alert the care teams to intervene earlier and prevent complications.
SeVA will continuously interact with patients to promote social interaction, engage them to reduce loneliness, and as such, prevent subsequent delirium episodes with this cognitive encouragement. In fact, all available competitor medical devices, either in development phase or already in the market, are instruments for diagnosis (with varying level of accuracy). SeVA is both diagnostic, and therapeutic, i.e., post diagnosis of delirium, it will also employ non-pharmacological methods to prevent future episodes. This aspect and functionality of SeVA technology will result in a significant reduction in resource utilization for hospitals and other care entities.
The SeVA platform will free up nursing time to perform timely checks on the patient, and therefore will provide time to nurses for more hands-on actionable care, rather than spend time in assessments. Nursing teams can optimize their time towards patient care with SeVA’s technology.
SeVA platform will result in significant reduction in extra-hospital days and consequently this results in a cumulative cost-saving potential anywhere between $ 32 Billion to $ 80 Billion a year.
SeVA platform will provide continuous monitoring of patient conditions and can immediately report medical emergency events to the care team (doctors) for intervention. This will significantly improve the quality of healthcare and save life due to immediate alert notification capability of SeVA technology.
ViNA: Virtual Nursing Assistant
Nurses in acute care facilities (Hospitals, Skilled nursing facilities, Rehab, etc.) perform many cyclical tasks at regular intervals for continuous patient monitoring. These tasks include activities like checking on the patient frequently for toileting questions, delirium detection, etc. In addition, the nurses also provide a personal touch to patients by talking to them about their day, concerns, etc. However, even with this intense schedule, the patient still has windows of “unsupervised care”, with no direct observation. Studies have shown that at least 35% of nursing time1 is spent on charting, translating to 8 hours of “unsupervised care’. These windows of unsupervised care lead to adverse events like falls. For delirious/Alzheimer’s dementia patients, with inability to use the nursing call light, basic needs like water, bathroom trips go unaddressed.
The Product: ViNA has the capability for a meaningful bi-directional and medically oriented conversation with the patient. This can decrease the cyclical checks the nurses perform. For example, instead of the nurse checking on the patient every 2 hours for bathroom needs, the ViNA can auto-activate to vocally ask this question every 2 hours. The AI technology in the ViNA analyzes the answer, asks patient to stay in bed until the nurse comes. Correspondingly, ViNA is sends a signal to the nurse. This helps the nurse provide immediate assistance, while also eliminating the two hourly cyclical monitoring. With further development and upgrades, the ViNA will document this encounter in the EHR, thus eliminating both nursing charting time and also recording accurate patient events.
The ViNA is being made intelligent using case based scenarios created by Dr. Agarwal, Medical Director of Geriatrics division at BUMCP and UA-COMP. With every passing day, new scenarios are sent to the tech team, which develops mock situations for feeding in the ViNA.