It seems safe to say that potential advances in clinical care are getting the most attention with the rapid rise of AI in healthcare, but some stakeholders are arguing that the new technologies could provide a critical shot in the arm to emerging specialty sectors in the healthcare world.
Writing recently at Medical Economics, for example, Tom Scott, CFO of HST Pathways, a software solutions company for the ambulatory surgery center (ASC) industry, notes that ASCs are one of the fastest growing segments of the healthcare system, and AI is poised to help them grow even faster.
Ironically, he notes, one of the primary reasons for the potential stems from the fact that ASCs were compelled to jump on the health information technology bandwagon quite as quickly as the rest of the healthcare sector, particularly when it came to efforts to implement EHRs across the system. “ASCs were exempted over the past roughly 10 years from interoperability requirements and standardization under the government’s Meaningful Use (MU) program,” he explains. “Thus, most ASC software systems operate independently without a ‘common language’ for data input and output; collectively, they also lack interoperability within the larger health information exchange (HIE) between provider, hospital, ASC, and patient.”
While that may have proved an impediment to their growing success not so long ago, now it means ASCs will be able to take faster advantage of new AI that may render obstacles like the lack of interoperability a thing of the past.
“Already, digital robots (a small piece of software programmed to do specific task on a computer) are helping move medical records to cloud-based storage with the goal of being accessible to clinical fingertips,” he says. “While current medical records are primarily kept in (EHRs), those records are usually stored on servers and incomplete, often because they are incompatible with other data sources, pre-date newer EHRs, or are paper chart-based. . . . Absent a way to translate medical histories into information that is easily accessible and actionable, some modern EHRs are simply an electronic version of a paper chart.
“To facilitate a clean transfer from a legacy system to a clinically actionable target system in ASCs (and after manual data extraction in the case of paper records), digital robots can supplant time-consuming administrative tasks normally delegated to staff. The robots, using machine learning, are programed to search and select relevant historical data such as allergies, medications, and previous medical procedures for capture and conversion, ensuring both data integrity and compliance with health record standards.”
In short, he says, “(w)ithin the near future, AI will be the key to facilitating data translation and exchange between conflicting software platforms. . . . Everything from ASC preauthorization and patient registration, to coding and clinician documentation, to un-adjudicated claims and resolution has the potential to be automated. This will, in turn, decrease the amount of staff labor time currently dedicated to tasks like scanning, data entry, and custom interfaces, and will help to minimize human error in the process.”
According to a report by the Advisory Board, notes Scott, by 2020, 60% of outpatient surgeries are expected to be performed in the ASC setting, and “looking ahead, the ASC market is expected to increase to a roughly $40 billion industry.”
And the rise of AI within and among ASCs could be one big reason why.