More than half the fields on your UB-04 and CMS-1500 are completed before billing ever sees the account. Terri Meier's point is simple. If patient access staff are creating that much of the claim, they are not just scheduling patients. They are functioning as pre-billers. That makes registration one of the highest-leverage denial prevention investments in the hospital, yet many systems still staff it like an entry-level clerical role. The result shows up later as eligibility denials, rework, and avoidable cost to collect.
Meier is Assistant Chancellor of Revenue Cycle at the University of Arkansas and teaches revenue cycle courses through the University of San Diego extension program. On a recent episode of the RCM Reframe podcast, she walked through why she has treated patient access as a knowledge-worker function for most of her career, and what it took to build a pipeline of people who could actually do the job.
Start with the artifact. The UB-04 and the CMS-1500 are the output of your revenue cycle, and a majority of the fields on both are completed at registration. Meier is direct about this.
"I think, you know, I've always thought that, you know, patient access, they should be pre billers. I mean, because that's what they're doing. They're responsible for filling out over 50% of the form locators on both the 1500 and the UB04." â Terri Meier, Assistant Chancellor of Revenue Cycle, University of Arkansas
Her example of how that goes wrong is the kind of thing operators see every week. A registrar types a name that does not match what is on the insurance card, and an eligibility denial lands in the queue days later. That is a registration output showing up as a payer rejection. The denial exists because of a keystroke made at the front end.
Meier describes patient access as high-turnover work carrying a lot of responsibility without the compensation that would reflect that responsibility. That mismatch is not a soft HR observation. It is the input to everything downstream. The wage structure signals the expected skill level, which shapes the applicant pool, which influences the error rate, which drives the denial volume, which raises the cost to collect.
Her former boss at the University of San Diego saw this plainly enough to do something about it. She wanted knowledge workers at the front end and the labor market was not producing them at the volume or quality the operation needed. So she partnered with the University of San Diego extension program and co-designed a curriculum.
When that leader retired, Meier took over the teaching role. She now teaches revenue cycle 1, 2, and 3, plus an intensive that combines all three into one course. The program partnered with San Diego Workforce, an unemployment agency, which vetted students and used grant funding to help pay tuition. UC San Diego listed the certificate as a preferred qualification on patient access job postings because the hiring team knew the curriculum and knew what the graduates had learned.
That is the specific example. It is not a universal template. The point for operators is narrower. If patient access roles are structurally hard to fill in your market, the applicant funnel is a problem you can shape with intention, through a university partnership, a community college relationship, an internal academy, or a managed services arrangement. The form the pipeline takes is a local decision. Having one at all is the operator move.
Meier's point about transferable skills is worth pressure-testing against your own job descriptions. She tells her students to compare their prior experience against posted requirements and find the overlap. Retail customer service maps to patient-facing work in healthcare. Her own career started at 15 as a file clerk at Torrance Memorial Hospital, and she kept applying for roles where she did not meet the stated minimums.
"my approach to, you know, work and the opportunity without an education is that was my resume." â Terri Meier, Assistant Chancellor of Revenue Cycle, University of Arkansas
The operator lesson is not that every health system should drop degree requirements. It is that strict minimum qualifications in a labor-short market are a self-inflicted constraint, and that a credential tied to a known curriculum is often more useful than a generic degree when the role is specialized. Pull your current patient access job descriptions and ask whether a candidate with strong transferable skills from an adjacent industry would even make it past the first screen.
Reframing patient access as a pre-billing function changes four things in the operation.
First, QA. Billing teams have audit protocols, error rate thresholds, and feedback loops. Patient access rarely has the same discipline applied with the same rigor. If registrars are completing claim fields, their output deserves measurement that ties back to the downstream denials it produces. A workable starting set includes name-match rate against the insurance card, insurance card capture accuracy, registration QA score by site and by registrar, eligibility denial rate by point of origin, and time to proficiency for new hires.
Second, training. A new biller does not get hired and told to shadow for a day. They get trained, tested, and signed off. Meier points to teach-back as the Lean practice she uses. The learner demonstrates understanding by explaining the workflow back, which is a stronger signal than clicking through steps while someone watches.
Third, compensation. The wage band has to reflect what the role actually produces. The data to support a reclassification sits in denial reports. If you cannot categorize denials by root cause and trace them back to the point of origin, that is the first capability to build, because without it you cannot fund the change.
Fourth, career path. Meier's own hire of a dental hygienist, who moved into a billing environment and rose to the system director role Meier had previously held within five years, is a specific case. It is a reminder that leadership potential often appears in adjacent backgrounds when the organization chooses to develop it.
The predictable pushback is that reclassifying patient access raises labor cost in a function that is already a large headcount line. Fair. In our experience working with providers, the current model is paying for the error rate somewhere else, in denied claims, in appeal labor, in write-offs, and in back-end rework. Moving work and resources upstream to prevent the denial is, in most operations we see, cheaper than paying downstream to fight it. The way to prove that in your specific operation is to categorize your denial inventory by root cause and look at what percentage traces back to registration.
Meier frames the broader shift this way.
"It's going from burden to bandwidth," Meier said.
Her point is not to replace registrars with automation. It is to redesign the role so the repetitive, transactional work is handled by technology where appropriate, and the human time is spent on the data integrity, exception handling, and patient conversation that actually prevent denials.
Three things are actionable without a capital request.
Pull a recent initial denial report and categorize by root cause. Identify what percentage originated at registration. If you do not have the categorization capability, that is the first gap. You cannot fund what you cannot measure.
Pull your patient access job descriptions and compare the posted qualifications against the actual work. Ask whether a candidate with strong transferable skills from an adjacent industry would be screened out by the current filters. If yes, part of the pipeline problem is self-created.
Go to where the work is done. Meier calls this Gemba, and in her words, her job is to remove barriers so people can do their best work. Sit next to a registrar for a shift. Ask what frustrates them, what slows them down, and what they would change. The answers will tell you where the leaks are.
The larger shift is a budget and governance conversation. Our recommendation, based on what operators like Meier describe, is that patient access needs the same analytics access, the same QA infrastructure, and the same training investment that your billing operation already receives. Whether that is built internally, acquired through a vendor partnership, or assembled as a hybrid depends on scale and HR capacity. The capability itself is the point.
When a significant share of your claim fields are created at the front desk, the front desk becomes a decisive factor in your denial rate. Fund it accordingly, or keep paying for the denials on the back end. Pull the denial root-cause report, pull the job descriptions, and spend a shift on the registration floor this week. Those three steps cost nothing and will tell you whether you are running patient access as a scheduling function or as the pre-billing team it already is.