In this blog, Dr Mani Hussain, Director of Primary and Community Care, talks about CQC's involvement in the multi-agency advice service on artificial intelligence. Artificial intelligence (AI) and Data-driven technologies have exciting potential to improve the quality of care for people using services. For example, hospitals are now using AI to support radiologists with their decision making. In diagnostics, AI can help analyse x-rays leading to the quick identification of abnormalities. In research, AI is used to analyse large swathes of data which helps to discover and validate new drugs.
Rich countries pour heart-stopping amounts of money into health care. Advanced economies typically spend about 10% of gdp on keeping their citizens in good nick, a share that is rising as populations age. The American system's heft and inertia, perpetuated by the drugmakers, pharmacies, insurers, hospitals and others that benefit from it, have long protected it from disruption. Its size and stodginess also explain why it is being covetously eyed by big tech. Few other industries offer a potential market large enough to move the needle for the trillion-dollar technology titans.
The West Midlands Academic Health Science Network (WMAHSN) is supporting a new digital healthcare innovation which helps patients who are recovering from lung surgery or experiencing a collapsed lung. Thopaz is a portable digital chest drainage and monitoring system, which enables patients to be monitored via digital readings. This supports patients' recovery and helps to reduce the length of their stay in hospital. By showing this data digitally, it helps support effective clinical decision making, improves patient safety and provides a cost-effective solution. In addition, when compared to conventional chest drains, patients are able to get up out of bed much earlier, as Thopaz is portable, which aids recovery.
Artificial Intelligence is proving its prominence in every industry out there and the healthcare industry is no different. From patient care to Administrative processes AI has huge potential in the healthcare industry. There are many research studies suggesting that AI can perform as well as or better than humans at key healthcare tasks. We have seen robots performing surgeries or assisting doctors with more precision and flexibility. Algorithms are outperforming radiologists in detecting dangerous tumors and advising researchers on how to build cohorts for expensive clinical trials.
Find all episodes of our series Smarter health here. Stacy Hurt is a cancer survivor and patient advocate. She says AI could transform health care for the better, as long as it doesn't transform the sacred patient-doctor relationship for the worse. "Any technology that occurs should only enhance that. It should not put any distance between that," she says.
This week Aidoc announced that they have raised $110 million in their Series D expansion round. This round of funding was co-led by TCV and Alpha Intelligence Capital with participation from CDIB Capital. Funding raised in this round will go toward expansion of Aidoc's first of its kind AI Care Platform. The platform offers health systems a singular platform solution designed to help doctors manage the entire patient lifecycle--from diagnostic aid, to consultation, to suggested treatment paths, to patient follow-up tools. In clinical studies, this platform has proven to reduce turnaround time, shorten patient length of stay and improve patient outcomes.
Artificial intelligence poses a lot of ethical risks to businesses: It may promote bias, lead to invasions of privacy, and in the case of self-driving cars, even cause deadly accidents. Because AI is built to operate at scale, when a problem occurs, the impact is huge. Consider the AI that many health systems were using to spot high-risk patients in need of follow-up care. Researchers found that only 18% of the patients identified by the AI were Black—even though Black people accounted for 46% of the sickest patients. And the discriminatory AI was applied to at least 100 million patients. The sources of problems in AI are many. For starters, the data used to train it may reflect historical bias. The health systems’ AI was trained with data showing that Black people received fewer health care resources, leading the algorithm to infer that they needed less help. The data may undersample certain subpopulations. Or the wrong goal may be set for the AI. Such issues aren’t easy to address, and they can’t be remedied with a technical fix. You need a committee—comprising ethicists, lawyers, technologists, business strategists, and bias scouts—to review any AI your firm develops or buys to identify the ethical risks it presents and address how to mitigate them. This article describes how to set up such a committee effectively.
Our latest roundup of contracts and go lives features news from Kent and Medway Medical Imaging Consortium and The Royal Marsden, who both selected new PACS, and more. We start with news last month from Barnsley Hospital NHS Foundation Trust, who went live with its new e-prescribing system, in a bid to increase efficiency and improve patient safety. The implementation of System C's CareFlow Medicines Management system means staff at Barnsley can use the new digital tool to chart drugs, complete rounds and administer medications. It removes the issue of the potential illegibility of paper prescriptions, which is freeing up staff time and minimising the risk of errors. The roll out was supported by local university students who are on clinical placement with the trust.
Cedars-Sinai researchers have received a federal grant to study how AI can be used to help predict heart attacks and other cardiac concerns. A team from the Los Angeles health system's Smidt Heart Institute and Division of Artificial Intelligence in Medicine is using a $7 million grant from the National Institutes of Health's National Heart, Lung and Blood Institute to set up the new program, which will use data from positron emission tomography and CT scans to analyze a patient's risk of cardiac issues. "Advanced imaging data could help predict patients' risk of serious cardiac events, but is so complex that clinicians aren't always able to use it," Piotr Slomka, PhD, director of Innovation in Imaging and professor of Cardiology and Medicine in the Division of Artificial Intelligence in Medicine at Cedars-Sinai and the lead researcher in the project, said in a press release. "This grant will allow us to create artificial intelligence tools that help physicians everywhere identify high-risk patients who would benefit from targeted therapy." According to the American Heart Association, more than 18 million people died of cardiovascular disease in 2019.
The healthcare sector has grown by leaps and bounds in the past few years and Artificial Intelligence (AI) has dramatically transformed the healthcare sector leading to many promising discoveries and outcomes. AI has enabled practitioners to deploy precise, timely and impactful interventions, synonymous with an engine that drives constant improvements across the care continuum. The pandemic has accelerated AI adoption which directly correlates with researchers conducting millions of experiments by simulating chemistry with computers, identifying more compounds that could pass the regulatory process and speeding up the drug discovery process. According to Nasscom's report, data analytics and AI in the healthcare sector can boost India's GDP by $25-$30 billion by 2025. AI and Machine Learning (ML) technologies are assisting businesses in making healthcare accessible to all sections of the country, including the most distant ones.