Mount Sinai Hospital Announces Digital Health Partnerships

Oct. 18, 2016
New York City-based Mount Sinai Hospital announced last week two partnership with digital health and health IT companies aimed at improving care management for chronic disease patients and improving the patient experience.

New York City-based Mount Sinai Hospital announced last week two partnership with digital health and health IT companies aimed at improving care management for chronic disease patients and improving the patient experience.

Mount Sinai Hospital (MSH) will collaborate with Palo Alto, Calif.-based CloudMedx to use advanced analytics to improve clinical outcomes for patients with congestive heart failure (CHF). According to a press release, this collaboration is meant to leverage intelligent predictive insights from CloudMedx in order to identify patients who are at higher risk of CHF and use evidence based care interventions to improve their outcomes such as reduced readmissions and overall wellbeing.

The hospital system wanted to combine evidence-based digital medicine technology with a team of remote monitoring, therefore MSH is partnering with CloudMedx who will provide an advanced analytics solution that works within MSH's workflows. “We are passionate about bringing advanced analytics to the forefront of managing our chronic patients and improving our patient wellbeing,” Ashish Atreja, chief technology innovation and engagement officer in medicine at Icahn School of Medicine at Mount Sinai, said in a statement. “As an industry, we do not have a sufficiently sophisticated tool to predict certain things such as disease progression and resulting readmissions in hospitals.

Atreja continued, “We are working with CloudMedx to use new guidelines and algorithms, using clinical data to determine these risks and predictors. CloudMedx has a fast, scalable platform that can allows us to do just that. We found CloudMedx to be very intuitive and useful. CloudMedx has a robust clinical AI platform that has the ability to 1) ingest and process large amounts of data; 2) do big-data analytics fast; and 3) perform natural language processing on unstructured notes to surface patient risk profiles in real time. All of this reduces time, effort, and expense drastically.”

Some 20 percent of Medicare patients being discharged all across the country get readmitted within 30 days of discharge with an estimated cost of unplanned re-hospitalizations being more than $17.4 billion, according to an article in the New England Journal of Medicine.. These adverse events occur because of a variety of reasons ranging from discharge plans not being followed to complications as a result of comorbidities or medications. MSH is designing its program towards identifying patients who are at-risk for certain adverse events using a combination of clinical and socio-economic data. Once the parameters are analyzed and the relevant patients are determined, the cohort is enrolled in specialized connected health program like HealthPromise to help them better manage their condition and symptoms, according to MSH. This initiative is in line with large scale reform programs like the Delivery System Reform Incentive Payment Program (DSRIP), a state-wide, $8 billion effort that aims to reduce avoidable hospital use by 25 percent. Therefore, one of the main objectives for organizations like MSH is to reduce these costly events across multiple disease areas such as CHF and other chronic diseases.

Specifically, CloudMedx predicts patient clinical risks during their visits, including any gaps in their care that need to be addressed immediately. It also determines which of these patients are at high risk and therefore would be likely to get readmitted within a certain amount of time. These risks can then be countered by custom tailoring treatment guidelines to ensure that patients do not fall sick again.

CloudMedx is leveraging its large scale predictive algorithms to deliver cross sectional analytics on patient profiles including clinical risks, gaps in care, and certain outcomes. CloudMedx predictive analytics are currently helping health systems stratify, track and improve value based initiatives leveraging machine learning and natural language processing. “Through our clinical models, we can predict who are the high risk patients, would need more follow ups, more hand holding, and more care interventions. Based on these insights, we can equip case managers with insights to follow up with the necessary interventions that ensure a smooth transition for these patients back into their own homes where they would feel more comfortable and safe, yet still be able to communicate with their doctors as they feel necessary. Our tools will keep monitoring their health remotely and trigger alerts as and when the need arises therefore automating this entire workflow for the health system,”Tashfeen Suleman, CEO of CloudMedx, said in a prepared statement.  

App-Based Health Coaching

Last week, Mount Sinai Health System also announced a partnership with digital health startup Kaigo Health to provide its patients with an app that combines personal health coaching, chronic disease management and telehealth. Mount Sinai will roll out the technology for patients in its OB-GYN, maternal health, cancer and urology departments to begin with.

Kaigo Health’s platform simplifies the healthcare experience by formulating a detailed health action plan, and linking patients seamlessly with personal care assistants and partnered doctors and specialists. For physicians, the startup helps them connect seamlessly with other physicians across Kaigo’s platform.

The service is free to patients at the moment, with organizations paying on a per member per month basis.

"Right after we joined Kaigo I was able to meet with other physicians on the Kaigo platform, which gave me the opportunity to network with my peers that had synergies with my practice on the Kaigo system,” Garfield Clunie, M.D., of Mount Sinai’s Maternal-Fetal Medicine Group, said. “Kaigo is filling a much needed void in the healthcare system - personal interaction. Patient care is vastly improved when physicians have the opportunity to know about and communicate effortlessly with other physicians.”

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