The mock EHR is the system of record. DeskGate never writes to it. It reads what the coordinator already has open, stages the payer-portal step, and stops before the irreversible click. Skip to the 30-day Specimen Ledger ↓
DeskGate does not create this. The clinical decision is already made and the case is already in their queue.
This decides whether the screen-read step may carry real PHI. The production route is DeskGate's Google Cloud project. Switch the provider below to see how the data flow ledger changes.
deskgate-production, so the screen-read step
may carry PHI on that route. Link 1 — DeskGate with each desk (the practice, or the billing agency
acting for it) — is signed per desk before that desk sends any live PHI. Until then, measurement
runs on synthetic or de-identified cases.The walkthrough above simulates how one single case is staged without leaving the browser session. In a live pilot, 30 days of that execution across a frozen cohort compiles into this exact ledger. Every metric and definition is agreed upon in writing before day one.
| Layer | Measured Dimension | Baseline derived · see working |
Illustrative 30-day cohort |
Delta / Impact |
|---|---|---|---|---|
| Desk outcome |
Completed cases / coordinator-day | 4.9 | 6.4 | +31%rate uplift · = 23% fewer coordinator-days at equal volume |
| Coordinator-days in period | 78.0 | 39.5 | — | |
| Runtime contribution |
Packets staged | 0nothing was staged — no stager existed | 253 | — |
| Accepted at gate, no material edit | no equivalentthe gate exists only because the runtime does | 71% | — | |
| Accepted after edit | no equivalentedit distance is unmeasurable without staged fields to edit | 22% | — | |
| Returned before gate | no equivalenta return is internal, before submission — distinct from a payer denial | 7% | — | |
| Explanation only |
Time-to-gate, median | ~80 mincumulative manual touch-time for a residual case — our figure, see working | 0:41 | the one clock the runtime owns |
| Time-at-gate, median | new taskreviewing staged output did not exist before — never counted as savings | 1:52 | — | |
| Integrity | Unauthorized submits | — | 0 | — |
| Cohort in / out / exceptions | — | 261 / 253 / 8 | — |
| 39 | prior-authorization requests per physician per week across all cases | AMA survey → [1] |
| 13 h | physician and staff time per physician per week on blended requests | AMA survey → [1] |
| 20 min | implied average staff time per routine request 13 × 60 ÷ 39 | derived |
| 80 min | cumulative touch-time for a residual case — manual portal entry, chart-note extraction, attachment assembly and phone follow-up, accumulated across days. This exceeds the published per-request range and is our figure, not the AMA's. | our assumption |
| 390 min | productive minutes per coordinator-day 6.5 h, not 8 — meetings, interruptions, other duties | assumption, stated |
| 4.9 | baseline completed cases per coordinator-day 390 ÷ 80 = 4.88 | derived |
| 6.4 | illustrative measured rate 253 staged ÷ 39.5 coordinator-days | modeled |
Change either assumption above and the baseline moves: at 60 minutes per residual case it is 6.5, at 90 minutes it is 4.3. That sensitivity is the point — a real measurement replaces this entire block with the desk's own prior-period count, which is why the baseline must be written down and agreed before staging begins. We publish the working so a desk can tell us it is wrong before we start, not after.
The illustrative column applies a 71% gate-accept rate to the staging share of that work (253 staged cases ÷ 39.5 coordinator-days = 6.4). It is arithmetic on an assumption, not a finding. No desk has produced this number.
Sources, so they can be checked:
AMA — practices complete 39 prior-authorization
requests per physician per week, consuming 13 staff hours [1] ·
AMA 2026 survey update — 40 requests weekly,
13 hours, 40% of practices employ staff working exclusively on prior authorization [2] ·
AMA Physician AI Sentiment Report — Prior authorization ranks as the #1 administrative burden physicians want automated (54%), with over 85% requiring human-in-the-loop confirmation [3].
Figures on requests per week and staff hours per week are the AMA's and are linked above [1, 2].
The per-residual-case time, the productive-day length and the resulting throughput are ours
and are labelled as assumptions in the table. AMA figures vary between survey years —
39 to 45 requests, 12 to 13 hours — so we use the lower published values rather than the
ones that would flatter the case [1, 2].
What this is worth, without us guessing your wage: at these specimen figures a desk
avoids 48 coordinator-days per 1,000 completed cases — 1,000 ÷ 4.9 = 204 days,
1,000 ÷ 6.4 = 156 days. Multiply by your own loaded daily cost. We publish no dollar figure
because we do not know what you pay, and a vendor quoting your payroll back at you is not evidence.
Note also that +31% is the rate uplift; the labor reduction is 23% — anyone quoting
31% as a cost saving has overstated it by roughly a third.
Why this matters: Only the middle block (Runtime contribution) requires DeskGate to exist.
Throughput can be pulled from any portal report; accept-rate and edit distance cannot.
That second block is the row that verifies whether the software actually did the work, or if the coordinator simply retyped it faster.
Each stage is bound to a task statement from the US Department of Labor's O*NET taxonomy. That is deliberate. A vendor ledger claiming "handling time fell 30%" is measuring itself against its own internal definition. A ledger reporting a change on 43-6013.00 · Complete insurance and other claim forms is measured against a public definition that predates us, applies to every desk in the country, and can be checked by anyone.
The headline number is cases completed per coordinator per day, not minutes saved per case. Minutes are the mechanism; throughput is what a desk actually budgets and hires for. A desk does not hire because a case takes four minutes longer — it hires because the queue does not clear. Measuring throughput is also the only way the result remains honest where labor costs vary: 30% of an inexpensive hour is negligible, but a queue that clears with fewer seats is valuable at any wage.
The full role, task by task, with the boundary of what we do and do not touch: see the complete task map →
Task statements are from O*NET, by the U.S. Department of Labor, Employment and Training Administration. O*NET® is a trademark of USDOL/ETA. Which stage maps to which task is our mapping, not part of the O*NET data — the Department of Labor publishes the tasks, not this product's interpretation of them.