In today’s evolving healthcare environment, the release of information (ROI) process is not a simple function. It involves at least 45 specific steps, each presenting its own complexities and compliance risks. Additionally, interoperability remains a challenge. A lack of true standards makes the movement of data between systems a labor-intensive and expensive process. It’s no longer enough to simply push paper back and forth. The process is too unwieldy, and inefficiencies add to cost burdens and have the potential to endanger patients.
But we’re finally seeing the light with tech-forward shifts that will influence the entire industry through artificial intelligence and automation. The benefits could reduce the waste inherent to the U.S. healthcare system and create much greater value for patients and the government in better allocating each dollar spent toward qualitative, long-term positive outcomes.
Resources are not being deployed properly, however. Roughly $5 billion is invested annually in new initiatives in scheduling, medication tracking, chronic disease monitoring, and other fields. Far less, however, is spent on a central solution to the waste problem: Access to data.
Take for example the complexity today in serving medical records: There are approximately 250,000 hospitals using some form of electronic medical records (EMRs). While the 10 largest EMRs own somewhere between 60-80% market share, the remaining 20-40% of all EMRs can be divided among the hundreds of smaller EMR vendors. Some hospitals have more than one EMR in place, and even for those hospitals and providers using the same EMRs, there are no assurances that the same versions are in use. The net outcome is that there are dozens of standards to deal with—HL7v2/3, DICOM, FHIR, LOINC, proprietary, and the like. Most EMRs, of course, only offer download of records as a printout, and there’s variability whether they offer a summary or details of these records.
When we consider all of these compounding issues, retrieving, digitizing, and delivering medical records becomes a very complex, manually intensive, lengthy process. To help the workforce serve patients faster and at the right cost, companies like Ciox are deploying technology to help put a significant dent in that $1 trillion waste figure, with help from a combination of technologies like robotic process automation (RPA), blockchain, and artificial intelligence (AI).
Using these kinds of technologies in concert, Ciox built an augmented workforce to solve the last mile of medical record interoperability. The systems are not perfect, and they still need to be taught, managed and overseen by real people but, with these technologies, we are heading into a far more efficient era.
Leveraging these technologies makes it possible to improve the quality of records and the ease with which they are freely exchanged. This can improve claims, arm doctors with better information about every patient they see, and impact the health sciences industry with more complete data sets. It can also help in catching correlations more quickly and delivering information that helps providers make better choices, including pharmacists on drug interactions. These technologies can also help pharmaceutical companies gather better trial groups and help life sciences companies use historical data that once would have been too hard to gather.
So much of that estimated $1 trillion of waste in the healthcare system can be directly addressed by one issue: the automation of medical records extraction and the digitization of the information in those records. It’s how we broker the U.S. healthcare system into the world of advanced data practices, and how we can drive actionable insight across the entirety of healthcare with far less waste, improved patient care, and better medical outcomes as a byproduct.
