A new joint report from KLAS and CHIME polled some early adopters of artificial intelligence and machine learning tools, and asked how the technology is impacting their clinical, financial and operational goals. WHY IT MATTERS The study is based on interviews with IT leaders at 57 organizations – CIOs, CMIOs, data scientists and more – that are using AI across a variety of cases, from clinical decision support to patient engagement to revenue cycle management. It asked them about some tangible gains the technology has helped them achieve. It also gleaned some insights about a handful of leading vendors, and found some common best practices for AI adoption. KLAS focused on purpose-built AI vendors – those focused primarily on analytics and AI, with dedicated, standalone product – and analytics platforms with AI infrastructure.
A survey of IT leaders by KLAS Research and the College of Healthcare Information Management Executives (CHIME) found artificial intelligence (AI) is assisting health care organizations in clinical areas such as predicting readmissions and avoidable emergency department visits. KLAS and CHIME polled leaders at 57 organizations that were early adopters of artificial intelligence (AI) software, specifically machine learning and natural language processing. Respondents cited early success with using AI software to reduce readmissions and detect sepsis risk. The survey also examined the use of AI in financial and operational areas and compared the performance of software vendors. ""Artificial intelligence is driving outcomes, saving patient lives, and driving operational and financial efficiencies for providers and payers," said study co-author Ryan Pretnik of KLAS Research.
AI in healthcare has a bias problem. Last year, it came to light that six algorithms used on an estimated 60-100 million patients nationwide were prioritizing care coordination for white patients over black patients for the same level of illness. The algorithm was trained on costs in insurance claims data, predicting which patients would be expensive in the future based on who was expensive in the past. Historically, less is spent on black patients than white patients, so the algorithm ended up perpetuating existing bias in healthcare. Therein lies the danger of using narrow datasets in Artificial Intelligence: If the data is biased, the AI will be biased.
Artificial intelligence and machine learning are quickly becoming an integral part of healthcare delivery. Both on the clinical care and operational side of healthcare organizations, AI has is powering technology that keeps patients safe and improves efficiency for the revenue cycle, supply chain and more. Here are 100-plus companies in the healthcare space using artificial intelligence. To add a company to this list, contact Laura Dyrda at email@example.com. AiCure is an AI and advanced data analytics company that uses video, audio and behavioral data to better understand the connection between patients, disease and treatment. It allows physicians to have access to clinical and patient insights.
Artificial intelligence (AI) is a generic phrase used to describe computer systems that can analyze their environment. These systems can learn and act in reaction to what they are recognizing. It is predicted that 20% of healthcare organizations will experience 15-20% productivity gains by 2021 through the use of AI technologies. Machine intelligence has a beneficial effect on the healthcare workforce, not by replacing jobs, but by acting as a co-pilot in treatment and routine processes. AI is an indispensable assistant to verify patient insurance or improve clinical documentation.