Larger Healthcare Organizations Use More AI Solutions Than Smaller Ones
A new report details the implementation of AI tools within organizations, noting that facilities with over 1,000 beds used more AI solutions on average than their peers.
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By - A report from the Center for Connected Medicine and KLAS provided data surrounding the growth of the artificial intelligence (AI) market along with the high frequency associated with using this technology for disease management and how the size of an organization affects the application of solutions.
As a result of rapid technological development in the last several years, AI use in healthcare continues to grow. According to the Center for Connected Medicine’s 2018 Top of Mind report, 63 percent of healthcare organizations indicated low urgency surrounding AI implementation. However, the most recent two editions of this survey did not show similar results.
The Center for Connected Medicine report defines AI as software that provides machine learning (ML) or natural language processing (NLP) capabilities for healthcare–related clinical, operational, or financial areas.
Data from this edition of the report indicated that two-thirds of survey respondents are using AI within their organizations. Due to having access to necessary resources, larger organizations (facilities with 1,001-plus beds) are the most common users of AI. On average, facilities of this size are using 3.6 AI solutions. Following them are organizations with 501-1,000 beds and one-500 beds, which use an average of 3.3 and 2.7 AI solutions, respectively.
Regarding the types of AI most used, prebuilt machine-learning models had the highest number of users. Within organizations with 1,001-plus beds or 501-1,000 beds, 61 percent to 80 percent used data-science ML prebuilt models. However, 81 percent to 100 percent of those with one-500 beds used this type of solution. Meanwhile, the use of robotic process automation (RPA) and conversational AI is also growing.
Although the use of AI varies, the most popular application and second most popular area of investment is health/disease management and prediction. This is largely due to the efficiency of AI in identifying at-risk patients, along with its ability to detect certain diseases early. The report also described that this type of information often serves as a foundation of population health management (PHM) and value-based care (VBC) within an organization.
Among 34 organizations, the survey indicated that 11 facilities with 1,001-plus beds, seven facilities with 501-1,000 beds, and six facilities with one-500 beds are currently using AI for health/disease management and prediction. Among ambulatory clinics, post-acute care facilities, and health plans, three are doing the same.
Regarding AI investment plans in the coming two years, investment in operational optimization is top-of-mind for survey respondents, followed by health/disease management and prediction.
Similar research has indicated the growing use of AI in healthcare.
In March, Outbound AI and the Health Management Academy released survey results that indicated the common use of AI for curbing workforce issues.
Staffing and labor insufficiencies are a frequent challenge in the healthcare industry, made worse during the COVID-19 pandemic. Survey results indicated that 47.5 percent of executives used AI to address this challenge. Meanwhile, the remaining 52.5 percent considered its use.
