Your Point-of-Service (POS), Your Electronic Medical Record (EMR), Your Billing System: Three Islands
Written By: Brian Choate, Co-Founder & Managing Partner, SGS
Ask any billing leader where the day actually goes and you'll hear the same answer: chasing information between systems that were never built to talk to each other. POS knows the patient encounter. The EMR knows the clinical picture. Billing needs both, plus a dozen other data points, before a claim can even be built. Reconciliation is a nightmare. Or, worse, the billing team doesn’t have a deep insight into the information that may be available in POS or the EMR to help with pre-billing functions.
Most of that connective work is still manual. Someone re-keys a field. Someone cross-references a run number. Someone catches the mismatch that would have kicked the claim back three weeks later. It's not glamorous work, but it's the work that determines how fast you get paid and how clean your data is when a payer, an auditor, or your own board asks a question.
Here's the number worth sitting with: agencies that map out where POS, ePCR, and billing actually connect find that somewhere around 60-70% of those manual touches follow a pattern. Same field, same cross-check, same fix, over and over. That's not a staffing problem. That's an automation opportunity hiding in plain sight.
If you want to see where your own percentage lives, start here:
Pull your last 20 claim corrections and look for the common thread: is it a field, a timing gap, a handoff?
Ask your billing team which single piece of information they chase down most often, and trace it back to where it originates.
Map the actual path a patient encounter takes from point of service to paid claim. Count the number of times a human has to move data by hand: verifying primary insurance, searching for secondary Medicare/Medicaid coverage, enriching demographics, routing exceptions to the right workflow.
Most agencies are surprised by what that exercise turns up. The fix isn't always technology. Sometimes it's a process change or a form redesign. But when the pattern really is systemic, three systems that don't natively share data, a checklist only gets you so far. Most claim scrubbers stop at flagging the problem for someone to work by hand. The harder, more valuable step is resolving it automatically, before it ever reaches a person.
If you go through this exercise and want a second set of eyes on what you find, that's exactly the conversation IntelliScrub 2.0 was built to have. Happy to walk through it.
