Healthcare is a technological paradox. On the clinical side, the bleeding edge of science and engineering present physicians with increasingly greater imaging tools, robotic surgical devices, gene-targeted therapy: the limits of what is technologically possible in healthcare are in lockstep with the limits of human understanding. At the same time, despite two decades of explosive development, the technologification of running a healthcare organization, of documenting care delivery and putting that data to work, lags behind.
The overriding philosophy of the early days of Meaningful Use involved giving healthcare provider organizations an ROI through automation, with the unmentioned consequence of revenue coming from the dismissal of coding, billing, and documentation experts. In leveraging technology to simplify complex processes, the overriding approach was to then push the remainder of that simplified work onto the clinicians themselves. This has resulted in a new pressure point on an already overworked healthcare system tied directly to physician burnout: outside of their clinical duties, doctors are spending more than 50% of an 11 hour workday in EHR activities. Technology holds incredible potential benefits to any organization, but productivity benefits in particular need to be centered around reducing, not increasing workload for those outcomes.
The goal has to be genuine technological enablement. Coders code, doctors see patients. And for good reason. Coders are experts unto themselves, and asking doctors to do their work, no matter how simplified through an application, results in more non-clinical strain on doctors and a prohibitively negative impact on the quality of the data gathered, inhibiting that data from reliable use down the line.
Any technology integrated into a hospital workflow needs to account for current clinical best practices, leverage and equitably empower all care team expertise, and provide a genuine lift beyond automation.
With Lumanent, we’ve employed our technology from end-to-end across the patient continuum to accomplish exactly that. Risk activities can be addressed before, during, and after the patient encounter through existing workflows to deliver actionable insights and support physicians.
The Pre-Encounter Prep module processes all available clinical data and surfaces risk gap suggestions and reminders to the broader care team. Only in cases where our AI has high confidence (95%) on any conditions in a patient relevant to risk, the physician is engaged. Otherwise, the entire workflow is parsed to relevant support staff, especially in lower (still greater than 60%) confidence results. Through this supportive workflow, the critical but previously easier-to-miss conditions relevant to a patient’s well-being and a hospital or practice’s overall risk adjustment strategy are vetted and, when necessary, addressed during the encounter. This not only means doctors have greater opportunities to comprehensively treat their patients, the relationship between physician and patient is impacted by that proactive approach. The patient feels seen and heard by their doctor, creating an additional boost to health outcomes.
After the encounter, Lumanent is engaged by the coding team via our Post-Encounter Review module. The full volume of clinical data on a given patient is engaged, as well as documentation on the most recent encounter. Through our NLP analyzing, processing, and prioritizing that data, the coding team receives suggestions based on anything the doctor may have missed, up to and including modifying coding opportunities based on case complexity increased through chronic conditions that are present but undocumented in the most recent visit.
In doing so, a more robust and accurate reimbursement is available to the provider organization. At the same time, because coders are experts in their own right, the fidelity of new data coming out of the most recent encounter is more reliable. This not only impacts the RAF for that patient and, through enough volume, the relevant population at the hospital or practice, it also ensures that when those patients come back, the data going forward has a new level of accuracy and therefore actionability.
Operationally, healthcare IT solutions aren’t about checking a technology box for CMS, nor are they about a single visit, especially when patient data is in the mix. It’s about using what’s there, improving it each time, and therefore raising the bar on both quality of care and organizational revenue. Most of all though, it’s about using technology to empower rather than replace human experts, to relieve clinical staff of non-clinical work, and live up to the promise of the terminology: a solution must actually be a solution.