Welcome to Digital Health Briefing, a new email providing the latest news, data, and insight on how digital technology is disrupting the healthcare ecosystem, produced by BI Intelligence.
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RESEARCHERS TAP DEEP LEARNING TO PREDICT IN-HOSPITAL PATIENT MORTALITY AND READMISSION RATES: Newly published collaborative research from Google, Stanford, the University of Chicago, and the University of California, suggests that artificial intelligence (AI) can be used in combination with electronic health record data to predict mortality, readmission, and other events that have an adverse impact on healthcare in the US.
The study adds considerable weight to the growing body of research in the field of big data and health analytics. Researchers fed almost 47 billion data points, including clinical notes, into deep learning models. These models analyzed the data, which had been de-identified for anonymity, and predicted with significant accuracy things like in-hospital mortality rates, 30-day unplanned hospital re-admissions, prolonged length of stay, and patients’ final diagnosis. Moreover, these deep learning models outperformed traditional state-of-the-art predictive models in all instances.
Big data presents a significant cost-saving opportunity for healthcare systems, and researchers are working hard to unlock its potential. Predictive analytics, precision medicine, and population health could help alleviate mortality rates, improve medication adherence, and monitor chronic illnesses such as heart arrhythmias, which are a heavy burden on the healthcare system. Each year in the US, healthcare-related infections lead to more than 99,000 deaths, problems with medication result in more than 770,000 injuries and deaths, and unexpected hospital readmissions cost up to $17 billion, according to Google head of product and research Katherine Chou.
There are a growing number of healthcare systems hoping to leverage the early potential of big data to improve patient quality of care. Several challenges stand in the way of predictive analytics being used en masse. However, small-scale operations are already being explored. Last week, for example, Yale New Haven Hospital announced a partnership with Epic Systems with the aim of using real-time big data to enhance the quality of healthcare. And researchers in Cleveland are looking into using its population and health data to better understand and address people outside of hospitals.
- BI Intelligence
AI CHATBOT FOR DEPRESSION LAUNCHES IN APP STORE: An AI chatbot designed to help people with feelings of depression and anxiety launched a stand-alone app in the iOS App Store last Thursday, according to Business Insider. The chatbot, dubbed “Woebot,” is programmed to provide scripted responses in line with Cognitive Behavioral Therapy model. Once signed up, Woebot engages with users daily, recording things like mood and energy levels – two symptoms associated with depression and anxiety. Digital tools like Woebot are growing in number as mental health professionals seek new ways to bypass the barriers in the way of providing sufficient patient care. These include things like a lack of resources, not enough trained professionals, and the social stigma around mental illness. Apps and chatbots offer around-the-clock self-monitoring, which may help improve patient outcomes and illness management. They can also help people who are either embarrassed about going to see a professional, or don’t think they have time for regular check-ins get a small-degree of help. In the US, around two-thirds of people with a mental illness are estimated to have gone at least a year without treatment, according to NAMI.
ISRAEL’S PM ANNOUNCES UPCOMING NATIONAL DIGITAL HEALTH PROJECT: During the World Economic Forum in Davos, Switzerland last week, Israeli Prime Minister Benjamin Netanyahu outlined plans to launch a NIS 1 billion ($295 million) digital health project in collaboration with software giant SAP, The Jerusalem Post reports. The initiative, which will be carried out over five years, aims to stimulate and support research into personalized and preventative medicine, with a focus on the implementation of artificial intelligence (AI) systems to facilitate analysis of Israel’s population. It will be submitted to the Israeli government in the coming weeks for approval. Israel is a fast-growing digital health innovation hub in large part because of the government’s efforts to drive and incentivize investments in the emerging field, according to a study published in The Lancet. The vast troves of patient data that result from nationwide digital health systems will be the key to developing population health. The data is necessary for AI platforms to be able to reveal useful insights for things like predicting illness outbreaks.
MEDICAL DEVICE MAKER HOPES TO INCREASE PATIENT ADHERENCE VIA RPM: Biotricity, a medical-grade wearable provider, is developing a range of remote patient monitoring solutions aimed at increasing patient adherence and improving patient outcomes, according to mHealthWatch. The company’s flagship product, Bioflux, is a mobile cardiac telemetry device that provides physicians with real-time monitoring and ECG information. Biotricity believes that RPM devices can improve patient adherence rates by demonstrating how certain choices directly impact on their health. This can include sticking to treatment plans and engaging in healthy lifestyle choices. Non-adherence is a massive strain on healthcare systems, leading to increased hospital readmissions and additional clinical visits to physicians.
In other news …
- Allscripts was hit with a class-action lawsuit accusing the company of not sufficiently protecting its clients’ health data, according to FierceHealthcare. The lawsuit comes just one week after two Allscripts data centers were attacked by ransomware.
- New York governor Andrew Cuomo will devote $664 million to building a new unified health system in Brooklyn, according to an announcement last week. $70 million of the planned funding will go towards creating an enterprise-wide health IT platform, providing a single medical records system across three partnering hospitals.