Radiology Leadership Research · Interactive Dashboard
Operational and Financial Metrics for the Radiology Manager
Busy is not productive. The statistics, formulas, starting thresholds, and calculators radiology leaders need for 2027, organized through Dr. Emrick’s IMAGING Performance Framework.
- Kelly Emrick, DHSc, PhD, MBA, BSRT(ARRT)R
- As of November 6, 2026
- Seven domains
- Nine calculators
- 2027 CMS final rules
Guiding principle
Busy is not productive.
Radiology departments rarely lack volume. They lack the right denominators. A department can post record exam counts in the same quarter its scanners run late, its reading worklist ages past clinical usefulness, its denials climb, and its contribution margin per scanner hour falls. Volume measures activity. Performance lives in ratios: completed exams per staffed scanner hour, final reports inside target at the 90th percentile, cash collected per exam performed, and margin per unit of the scarcest resource.
The centerpiece
Dr. Emrick’s IMAGING Performance Framework
Seven domains that follow the patient and the dollar from order to margin: Intake and Access, Machine Capacity, Assigned Workforce, Getting It Right, Interpretation, Net Revenue, and Gross Margin. Every metric has one home, and the domains are read in the order problems propagate.
Five findings leaders should act on
- 1
Access is a statistic, not a feeling.
No-show risk rises with scheduling lead time, from 2.71% at one week to 9.46% at six months in a 2.9 million visit study (Rosenbaum et al., 2018). Lead time is therefore both a revenue and an equity variable.
- 2
Utilization above roughly 85% buys volume with time.
Queueing mathematics shows that waiting grows nonlinearly as utilization approaches 100%. A scanner or reader run at 90% carries about nine times the relative queue of one run at 50%, which is why high utilization and long waits travel together.
- 3
The mean hides the patient who waited.
Report turnaround as a median and 90th percentile by priority class. Averages conceal the tail that emergency physicians and referring clinicians actually experience.
- 4
Revenue is a chain, and every link leaks.
Net revenue per exam depends on contracted yield, charge capture, authorization, denial, and collection. Independent review overturns advanced imaging prior authorization denials about five times as often as denials for other services (20.5% versus 4.1%), so a disciplined appeal program is a measurable revenue tactic (AuntMinnie, 2026b).
- 5
Margin must be measured per scanner hour, not per exam.
When time on the table is the scarce resource, the right question is which exam mix and slot design produce the most contribution per staffed hour. The worked example shows a single MRI scanner gaining about $362,000 in annual contribution from a five-minute slot reduction and a four-point drop in lost slots, with no new equipment.
Radiology operating indicators at a glance
As of November 6, 2026. Hover or focus any counter above for its source.
| Indicator | Latest figure | Source |
|---|---|---|
| 2027 Medicare PFS conversion factor (non-APM) | $32.6286, down 2.31% from $33.4009 | AHA, 2026a; ACC, 2026 |
| 2027 conversion factor (qualifying APM participants) | $32.9548, down 1.83% | ACC, 2026; AHA, 2026a |
| Site-neutral imaging without contrast, excepted off-campus PBDs | 40% of OPPS rate; about $260 million in 2027 | AHA, 2026b; ACR, 2026a |
| 2027 OPPS conversion factor (final) | $99.970; net OPPS update 2.3% | ACR, 2026a; AHA, 2026b |
| Interpretation turnaround, Medicare outpatient, 2014 to 2024 | Up 177% (2 h 11 min to 6 h 1 min) | HPI, 2026a; Radiology Business, 2026a |
| Technologist vacancy rate, 2025 | CT 19.4%; MRI 17.4%; radiography 15.6% | ASRT survey via Allegretto, 2025 |
| Outpatient imaging no-show rate | 3.25% overall; MRI 3.70%; mammography 6.99% | Rosenbaum et al., 2018 |
| Radiography reject rate target | 8%; investigate above 10% or below 5% | Little et al., 2023 (AAPM TG-305) |
| Median days in accounts receivable, radiology practices | Nearly 31 days; about 16% older than 120 days | RBMA 2023 survey via Radiology Business, 2023 |
| Advanced imaging prior authorization denials overturned | 20.5% versus 4.1% for all other services | AuntMinnie, 2026b |
Why radiology needs its own statistics
First
A chain of queues
An exam waits for authorization, a slot, the waiting room, the table, the reading worklist, and then the billing cycle. Each queue has its own arrival rate, service time, and variability, and delays at any link pass downstream. Statistics that describe queues are more useful than statistics that describe totals.
Second
Asset constrained
A 3T MRI scanner, a CT unit, and a reading radiologist are expensive, finite resources whose hours cannot be stored. An unused slot at 2 p.m. cannot be sold at 4 p.m. Time is the core denominator: exams per staffed hour of the constrained resource, and what each hour earned.
Third
Two businesses joined at the image
The technical component (equipment, technologists, space, supplies) and the professional component (radiologist interpretation) are paid for, staffed, and often owned differently. Leaders need statistics for both components and for the handoff between them.
How to use this dashboard
- 2027 Environment sets the payment and workforce context.
- Statistics Lab teaches the seven statistical rules with live demonstrations.
- The IMAGING Model is Dr. Emrick’s seven-domain framework, with every metric, formula, reference point, and tactic.
- Worked Example, Access & Queue Tools, and Payment & Revenue Tools hold nine calculators you can run on local data.
- IMAGING Scorecard grades your values against the starting thresholds; 90-Day Plan turns them into action.
Professional payment: a lower conversion factor on January 1
Medicare physician payment equals the sum of geographically adjusted work, practice expense, and malpractice RVUs multiplied by the conversion factor. For 2027, CMS finalized $32.9548 for qualifying APM participants and $32.6286 for everyone else (ACC, 2026). Most of the decline reflects the expiration of the one-year 2.5% increase Congress provided for 2026 (Medical Economics, 2026). CMS also continues the 2.5% work RVU efficiency adjustment introduced for 2026 (ACR, 2026b). The final rule was published November 4, 2026, with Federal Register publication scheduled for November 9, 2026 (CMS, 2026).
| Conversion factor | CY 2026 | CY 2027 final | Change | Per 1,000 total RVUs |
|---|---|---|---|---|
| Non-APM (most radiologists) | $33.4009 | $32.6286 | −2.31% | $33,400.90 to $32,628.60 (−$772.30) |
| Qualifying APM participant | $33.5675 | $32.9548 | −1.83% | $33,567.50 to $32,954.80 (−$612.70) |
Percent changes and per 1,000 RVU amounts computed for the report from the published conversion factors. Specialty-level impacts also depend on RVU revaluation; in July, CMS projected +2% for diagnostic radiology under the proposed rule (ACR, 2026c). Confirm final code-level impacts against the CMS and ACR final impact tables.
Conversion factor, 2026 versus 2027
Source: ACC, 2026; AHA, 2026a.
Technical payment: site-neutral imaging arrives
Beginning January 1, 2027, CMS pays the physician fee schedule equivalent rate (40% of the OPPS rate) for imaging services without contrast assigned to APCs 5521 through 5524 when furnished in excepted, grandfathered off-campus provider-based departments (ACR, 2026a; AHA, 2026b). Affected services include certain bone density, radiography, ultrasound, CT, and MRI codes; the proposal also named composite APCs 8004, 8005, and 8007 and exempted rural sole community hospitals (Phelps Dunbar, 2026).
The policy follows site-neutral payment for clinic visits in 2019 and drug administration in 2026, and KFF notes that savings would be far larger if site-neutral payment were extended to on-campus departments (KFF, 2026). For a hospital imaging leader this creates a new, site-specific statistic: site-neutral revenue at risk, equal to Medicare non-contrast exam volume in the affected APCs at excepted off-campus locations × the current OPPS payment × 60%.
Interpretation capacity: the decade-long climb in turnaround
The Neiman Institute analyzed 2.9 million Medicare fee-for-service office and hospital outpatient imaging studies and found that the interval between imaging and interpretation rose 177% from 2014 to 2024, with 92% of the increase occurring from 2022 to 2024 (HPI, 2026a). The observational design cannot identify causes and the measure is based on calendar days, but the pattern is consistent with a workforce operating near capacity.
Increase in mean interpretation turnaround by modality, 2014 to 2024
Figure 1 rebuild. Data: HPI (2026a) via AuntMinnie (2026a).
View the published figure
CT and MR saw the largest increases. Note the measure itself: a mean, which Section 3.2 warns can hide the tail. Recomputed from the printed minute-level endpoints, the increase is 175.6%; the published 177% reflects unrounded source data. See the verification ledger.
Workforce: vacancies remain near record highs
The ASRT 2025 survey found CT at an all-time high vacancy rate of 19.4%, MRI rising to 17.4%, and bone densitometry more than doubling to 16.3%, while radiography, sonography, and mammography improved modestly (Allegretto, 2025). The response rate was 2.6% of more than 18,000 managers, so read the figures as direction and magnitude rather than precise national estimates (Iversen, 2025a).
Technologist vacancy rates by discipline, 2023 and 2025
Figure 2 rebuild. Data: ASRT (2025) via Allegretto (2025).
View the published figure
Axis Imaging News, 2025; Iversen, 2025b.
Demand and value: more work for less real payment
AuntMinnie, 2026c; Jiang et al., 2022; Radiology Business, n.d. These spreads mean the payer and contract mix behind an exam can matter as much as the exam itself.
Statistical foundations for radiology leaders
Seven lessons form the statistical grammar of the report and of this dashboard. Each is stated as a rule, explained, and demonstrated live with a radiology example.
Every rate needs an honest denominator
A no-show rate computed against all scheduled appointments, including those canceled a week in advance, will look better than one computed against appointments still on the schedule 24 hours before the exam. Neither is wrong, but they answer different questions and cannot be compared. Display, beside every rate, the exact numerator, denominator, time window, and population.
Denominator demonstration
Same numerator, two denominators.
Report the median and the 90th percentile, not the mean
Operational times in radiology are right-skewed: most exams are read quickly, and a minority wait a very long time. The mean is pulled toward the tail and describes almost no actual patient. The median describes the typical exam; the 90th percentile (p90) describes the patient and clinician who waited longest among routine cases. An ED study reported a median radiology turnaround of 91 minutes before an intervention and 50 minutes after, with interquartile ranges of 45 to 256 and 30 to 106 minutes (van der Linden et al., 2019). A companion statistic is the tail ratio, p90 ÷ median: near 2 suggests a stable process; 4 or more signals a backlog forming at certain hours or worklists.
Skewed distribution demonstration
Move the sliders. Watch the mean drift away from the typical exam while the median holds.
Run with JavaScript enabled to simulate 600 studies.
Simulated lognormal sample of 600 studies with a fixed random seed; teaching demonstration only.
Weight volume by work
An MRI of the brain with and without contrast and a two-view chest radiograph are each one exam, but they consume very different scanner, technologist, and radiologist time. Raw exam counts misstate productivity whenever the case mix shifts. For the professional component use work RVUs per clinical FTE; for the technical component use total RVUs or a local weighted exam unit based on standard table minutes. Dividing weighted volume by worked hours gives a productivity ratio you can compare across months.
Weighted volume demonstration
Illustrative month-over-month mix shift. Edit any cell.
| Exam family | Standard minutes | Month A | Month B |
|---|---|---|---|
| Radiograph, chest two views | |||
| CT abdomen and pelvis | |||
| MRI brain with and without | |||
| Ultrasound abdomen | |||
| Technologist worked hours |
Raw volume says productivity rose 7.1%. Work-weighted volume says it fell 2.5%. The mix shifted toward short exams.
Read variation on a run chart before reacting
Every operational measure varies from week to week. Leaders who react to each movement create noise and erode trust. Plot the measure over time with its center line and control limits set at about three standard deviations. Treat a point outside the limits, or a sustained run of points on one side of the center line, as a signal worth investigating. Treat everything else as common cause variation that requires a process change, not a reprimand.
Control chart with signal rules
Weekly median ED CT turnaround (minutes), 26 weeks. Choose a scenario.
Common cause variation only. No signal: do not react to individual weeks.
Center line and limits from the first 13 weeks (baseline). Sigma estimated from the average moving range ÷ 1.128. Signal rules applied: any point beyond 3 sigma; a run of 8 consecutive points on one side of the center line. Illustrative data.
Queues follow two laws leaders should know
Little’s Law states that the average number of items in a system equals the arrival rate × the average time each item spends in the system (Little, 1961). If 40 studies per hour arrive and the average study waits 1.5 hours for a final report, the worklist holds about 60 unread studies; to bring the average to 45 minutes, hold it to about 30. Kingman’s approximation shows queue waiting time grows in proportion to u ÷ (1 − u), multiplied by terms for the variability of arrivals and service times (Kingman, 1961). Variability steepens the curve, so standardizing protocols and slot lengths shortens waits even when utilization does not change.
Little’s Law
Turn a turnaround target into a worklist limit.
Kingman’s utilization curve
Slide utilization; adjust variability.
Relative queue wait as a function of utilization
Figure 3 rebuild. At 70% the term equals 2.3; at 80%, 4.0; at 85%, 5.7; at 90%, 9.0; at 95%, 19.0.
View the published figure
Contribution margin and break-even
Contribution margin per exam is net revenue per exam minus the variable cost of performing it. Break-even volume equals fixed costs for the period ÷ contribution margin per exam. Because fixed costs dominate imaging, each exam above break-even contributes almost its entire margin to the bottom line, and each lost slot subtracts it. When scanner time is the constraint, the key metric becomes contribution margin per scanner hour.
Break-even in three numbers
Defaults from the Section 12 worked example.
Separate volume, rate, and mix
When revenue changes, decompose the change before explaining it. Volume variance equals the change in exam count × the prior average revenue per exam. Rate and mix variance equals the change in average revenue per exam × the current exam count. In the example below the department grew, but each exam earned less; the second number is what a 2027 conversion factor cut or a payer mix shift would produce. A further split separates pure price from mix by repricing current volume at prior rates.
| Component | Formula | Result |
|---|---|---|
| Prior period revenue | 10,000 exams × $480 | $4,800,000 |
| Current period revenue | 10,600 exams × $465 | $4,929,000 |
| Volume variance | (10,600 − 10,000) × $480 | +$288,000 |
| Rate and mix variance | ($465 − $480) × 10,600 | −$159,000 |
| Total change | Sum of variances | +$129,000 |
Designed by Kelly Emrick, DHSc, PhD, MBA, BSRT(ARRT)R
The IMAGING Performance Framework
A seven-domain model that follows the patient and the dollar from order to margin. Its purpose is practical: to give leaders a single, memorable map in which every metric has one home, every domain answers one question, and the domains are read in the same order that problems propagate. A delay in Intake becomes idle capacity in Machine; a staffing gap in Assigned Workforce becomes a late read in Interpretation; a missing authorization at Intake becomes a denial in Net Revenue; and every one of these reaches Gross Margin.
How problems propagate
Choose a failure to trace its path across the framework.
Select a scenario above. The path lights across the map.
View the published figure
| Domain | Leadership question | Core statistics |
|---|---|---|
| I: Intake and Access | Can patients get in, on time, with the paperwork done? | Days to third next available; order-to-exam days; no-show rate; backfill rate; authorization-on-file rate |
| M: Machine Capacity | Is the equipment available and working at its potential? | Exams per staffed scanner hour; slot and productive utilization; on-time starts; room turnover; uptime |
| A: Assigned Workforce | Is staffing matched to demand at a sustainable cost? | Vacancy rate; worked hours per weighted exam; premium labor share; turnover; radiologist wRVU per FTE |
| G: Getting It Right | Is the image right the first time, at the right dose? | Reject rate; technical recall rate; protocol compliance; dose outliers; safety events per 10,000 exams |
| I: Interpretation | Is the read timely, accurate, and acted upon? | Exam-complete-to-final median and p90; unread worklist; peer learning yield; follow-up completion |
| N: Net Revenue | Are we paid what we earned, and how fast? | Net revenue per exam; payer yield versus Medicare; denial rate; days in AR; net collection rate; site-neutral exposure |
| G: Gross Margin | Does each exam, and each scanner hour, cover its cost? | Cost per exam (TDABC); contribution margin per exam and per scanner hour; break-even volume |
Domain pages
Select a letter above or on the map. Each page holds the statistics table, the evidence, a figure or tool, and a tactic checklist you can tick as tactics go into place.
Section 5 · Operations
Intake and Access
Can patients get in, on time, with the paperwork done?
Access is where radiology first creates or destroys value. Every day an exam waits is a day of diagnostic delay for the patient, a day of exposure to no-show risk for the department, and, in competitive markets, a day the referral can leak to another provider.
Table 5. Intake and Access statistics
Days to third next available appointment
FormulaCalendar days from today to the third open slot, by modality and exam length
Reference pointStarting target of 7 days or less for routine outpatient MRI and CT
Local; informed by Daye et al., 2018
Order-to-exam wait days
FormulaExam date minus order date; report median and p90
Reference pointMean 7.95 days in an outpatient MRI cohort
Daye et al., 2018
Delayed-order rate
FormulaExams performed more than 10 days after the provider’s expected date ÷ exams ordered
Reference pointClose to 50% of outpatient MRI orders in a quaternary system
Lacson et al., 2024
No-show rate
FormulaNo-shows ÷ appointments still scheduled 24 hours before the exam
Reference point3.25% overall; MRI 3.70%; mammography 6.99%; radiography 1.24%
Rosenbaum et al., 2018
Late cancellation and backfill rate
FormulaSlots vacated within 48 hours that were refilled ÷ slots vacated within 48 hours
Reference pointLocal; track weekly
Local
Authorization-on-file rate
FormulaExams with verified authorization 48 hours before the exam ÷ exams requiring authorization
Reference pointLocal; payers must answer standard requests within 7 days and urgent within 72 hours
CMS-0057-F; Radiology Business, 2024
What the evidence says
The largest study of imaging no-shows, 2,893,626 outpatient visits at the University of Washington from 2000 to 2015, found an overall no-show rate of 3.25%, with wide variation by modality and by scheduling lead time (Rosenbaum et al., 2018). Exams booked six months ahead had a 9.46% no-show rate, compared with 5.26% at 30 days and 2.71% at one week (Figure 5).
In an outpatient MRI cohort at Massachusetts General Hospital, waits of 7 to 21 days raised the odds of a missed appointment by 39% and waits over 21 days by 77%; missed appointments were also more likely among Black and Hispanic patients and patients with lower socioeconomic status (Daye et al., 2018). Access is therefore both an equity and an efficiency measure.
Population matters. Another team reported a baseline outpatient MRI no-show rate of 19.3%, which a predictive model with targeted telephone reminders reduced to 15.9%; patients who could not be reached had a no-show rate of 40.3% (Chong et al., 2020). Benchmark against your own history and similar populations rather than a single national number.
No-show rates by modality and lead time
Figure 5 rebuild. Data: Rosenbaum et al. (2018).
View the published figure
Operating tactics 0 of 6 in place
Section 6 · Operations
Machine Capacity
Is the equipment available and working at its potential?
The scanner is the department’s most expensive fixed asset and its hours are perishable. Machine statistics answer two questions: how much of the available time is used, and how much output each used hour produces.
Table 6. Machine Capacity statistics
Staffed scanner hours
FormulaHours per week the scanner is open and staffed
Reference pointLocal; extend where demand exceeds supply before buying equipment
Local
Slot utilization
FormulaScheduled minutes ÷ staffed minutes
Reference pointStarting target 80% to 90% (see Figure 3 on queue risk)
Local; Kingman, 1961
Productive utilization
FormulaTable-time minutes of completed exams ÷ staffed minutes
Reference pointGap to slot utilization reveals no-shows, delays, and turnover
Local
Exams per staffed scanner hour (MRI)
FormulaCompleted exams ÷ staffed hours
Reference point1.25 per unit hour nationally in Canada, 2022 to 2023; site averages up to 2.32
CDA-AMC, 2024; 2025
On-time start rate
FormulaExams starting within 5 minutes of schedule ÷ exams
Reference point77% at an optimized MRI facility versus 50% and 63% at reference sites
RSNA News, 2025
Room turnover
FormulaTable-off of one patient to table-on of the next
Reference pointAbout 12 minutes reduced to about 2 minutes with two-table rooms
RSNA News, 2025
Uptime
Formula(Contracted base hours − unplanned downtime) ÷ base hours
Reference pointOEM guarantees of 98% and up to 99% on premium plans
Siemens Healthineers, n.d.; Philips, 2025
Downtime cost
FormulaLost exams × contribution margin + recovery costs
Reference pointCompute locally; do not import vendor estimates
This report
What the evidence says
Throughput benchmarks are scarce and setting-dependent. Canada’s national imaging inventory reported an average of 1.25 MRI exams per unit per hour in 2022 to 2023, with a range of 0.89 to 1.68 across jurisdictions, and earlier found that fixed units outperformed mobile units (1.88 versus 1.05 exams per hour at the site level) (CDA-AMC, 2024; 2025). These figures are orientation rather than targets, because exam mix, field strength, and protocol length differ widely.
The stronger evidence concerns design. At Mass General Brigham, an optimized outpatient MRI facility with three scanners, two dockable tables per scanner, and dedicated preparation bays achieved 77% on-time starts against 50% and 63% at two reference facilities, and shortened turnaround for common brain and spine protocols by roughly 2 to 6 minutes per exam (RSNA News, 2025).
At UW Health, a two-door, two-table smart suite reduced room turnover from about 12 minutes to about 2 and shortened the standard slot from 30 to 20 minutes (RSNA News, 2025).
MRI exams per unit hour: orientation, not targets
CDA-AMC (2024; 2025). Worked example values are illustrative assumptions from Section 12.
Operating tactics 0 of 6 in place
Section 7 · Operations
Assigned Workforce
Is staffing matched to demand at a sustainable cost?
Labor is imaging’s highest controllable cost and the binding constraint on both scanning and reading. Workforce statistics must show whether staffing matches demand hour by hour, whether it is sustainable, and what it costs per unit of work.
Table 7. Assigned Workforce statistics
Vacancy rate
FormulaOpen budgeted positions actively recruited ÷ budgeted positions
Reference pointCT 19.4%; MRI 17.4%; radiography 15.6%; sonography 12.4% (2025)
Allegretto, 2025
Worked hours per weighted exam
FormulaTechnologist worked hours ÷ weighted exam units
Reference pointLocal trend; compare like modalities only
Local
Staffing-to-demand match
FormulaTechnologists on duty by hour ÷ expected exams by hour
Reference pointLocal; plot both curves on one chart
Local
Premium labor share
Formula(Overtime + agency hours) ÷ total worked hours
Reference pointLocal target; rising share signals structural gap
Local
Labor cost per exam
Formula(Wages + benefits + premium pay) ÷ completed exams
Reference pointMedian wages: radiologic technologists $80,110; MRI technologists $95,480 (May 2025)
BLS, 2026
Radiologist wRVU per clinical FTE
FormulaAnnual wRVUs ÷ clinical FTE
Reference pointMedian about 12,500; 75th percentile about 43% above the 25th
Becker’s, 2025
Radiologist attrition
FormulaRadiologists leaving practice ÷ radiologists at start of year
Reference pointRose from 1.1% (2014) to 2.5% (2022)
AuntMinnie, 2026d
What the evidence says
The ASRT 2025 survey found CT at an all-time high vacancy rate of 19.4%, MRI rising to 17.4%, and bone densitometry more than doubling to 16.3%, while radiography, sonography, and mammography improved modestly (Allegretto, 2025). The response rate was 2.6% of more than 18,000 managers, so read the figures as direction and magnitude (Iversen, 2025a).
Vacancy rates understate the operational gap when positions are frozen rather than posted, so also track the coverage gap: staffed technologist hours short of the hours the template requires.
Radiologist productivity data vary by source and setting. One 2025 analysis placed median annual radiology wRVUs at 12,500, the highest of any specialty it reported, with a 43% spread between the 25th and 75th percentiles (Becker’s, 2025). Because a wRVU benchmark rewards volume without regard to complexity, subspecialty, call burden, or non-interpretive work, pair it with quality and turnaround measures.
2025 vacancy and change since 2023
ASRT (2025) via Allegretto (2025). Change in percentage points.
Operating tactics 0 of 5 in place
Section 8 · Operations
Getting It Right
Is the image right the first time, at the right dose?
Acquisition quality is an operational statistic because every repeated image, recalled patient, or incomplete exam consumes capacity twice. It is also a safety statistic because repeats add dose and delay.
Table 8. Getting It Right statistics
Radiography reject rate
FormulaRejected images ÷ total images acquired (vendor-neutral capture)
Reference pointTarget 8%; investigate above 10% or below 5%; pediatric target 5%, upper 7%
Little et al., 2023
Technical recall rate
FormulaPatients recalled for technically inadequate exams ÷ exams
Reference pointLocal; track by modality and technologist
Local
Incomplete exam rate
FormulaExams stopped early (claustrophobia, motion, IV failure) ÷ exams started
Reference pointLocal; pair with sedation and anxiety-support data
Local
Protocol compliance
FormulaExams performed on the approved protocol ÷ exams
Reference pointLocal; governed by protocol committee
Local
CT dose index outliers
FormulaExams above the local alert or diagnostic reference level ÷ CT exams
Reference pointCompare with registry benchmarks for the same exam type
Local; registry
Safety events per 10,000 exams
FormulaReportable MRI safety, contrast reaction, and extravasation events × 10,000 ÷ exams
Reference pointLocal; monitor on a control chart
Local
What the evidence says
AAPM Task Group 305 notes that published reject rate targets vary; the Conference of Radiation Control Program Directors suggests 5% to 7%, while AAPM Report 151 recommends a target of 8% with investigation thresholds of 10% and 5% (Little et al., 2023). A rate that is too low can signal that radiologists are receiving poor images rather than repeats.
TG-305 also notes that several sites reported higher reject rates after moving from computed radiography to flat panel digital radiography, making measurement more, not less, important in a digital department. A centralized reject database and standardized reject categories helped one academic center reduce its reject rate from 24.5% to 13% (AuntMinnie, 2017).
Measurement is also becoming part of payment policy. In the 2027 Quality Payment Program proposal, CMS proposed diagnostic radiology core measures, including exposure dose indices, patient exposure optimization, and appropriate follow-up imaging (AuntMinnie, 2026e). Confirm the final measure list in the final rule.
Where your reject rate sits
9.0%: amber. Above the 8% target; investigate before it reaches 10%.
Zones: AAPM Report 151 via TG-305 (Little et al., 2023). Academic center example: AuntMinnie, 2017.
Operating tactics 0 of 4 in place
Section 9 · Operations
Interpretation
Is the read timely, accurate, and acted upon?
The report is what the referring clinician and the patient actually receive. Interpretation statistics must measure timeliness from the clinician’s point of view, accuracy in a way that encourages learning rather than concealment, and whether recommendations are carried out.
Table 9. Interpretation statistics
Exam complete to final report
FormulaFinal signature time minus exam completion time; median and p90 by priority and patient class
Reference pointED CT median 58 minutes with on-site radiologist versus 81 minutes without
Radiology Business, 2026b
Next-day read share (outpatient)
FormulaStudies finalized one or more calendar days after acquisition ÷ studies
Reference pointRose from 1.97% (2014) to 7.39% (2024) in Medicare outpatient data
Radiology Business, 2026a
Unread worklist (work in process)
FormulaCount of unread studies at a moment; target = arrival rate × target turnaround
Reference pointLittle’s Law; set by priority
Little, 1961
Report-before-view rate
FormulaStudies finalized before the ordering clinician first opened the images ÷ studies
Reference pointMore than half of ED CT studies in one PACS audit
AuntMinnie, 2015
Peer learning yield
FormulaCases submitted with learning value ÷ radiologist per month
Reference pointRandom review reports far fewer discrepancies than external or blinded review
Merritt & Baram-Clothier, 2010; Yacoub et al., 2019
Actionable incidental finding follow-up completion
FormulaRecommended follow-ups completed by due date ÷ recommendations issued
Reference pointAbout one third lack documented completion; ED rates as low as 17%
Kadom et al., 2022
What the evidence says
Timeliness. In a study of 13,533 emergency CT exams from July 2025 through June 2026, median scan-to-final-report time was 58 minutes when a radiologist was on site and 81 minutes when reads were completed off site (Radiology Business, 2026b). A PACS audit at Staten Island University Hospital found that in more than half of ED CT cases the report was ready before the images were first viewed, or the images were never opened (AuntMinnie, 2015). That metric shifts the target from as fast as possible to ready when it is needed.
Accuracy. External expert review of randomly selected cases from 42 radiologists found significant error rates of about 3% to 4%, up to ten times the rates reported through internal RADPEER review (Merritt & Baram-Clothier, 2010). When one department embedded blinded, randomized peer review into PACS, the mean reported significant discrepancy rate per radiologist rose from 0.19% to 0.93% (Yacoub et al., 2019). Low reported discrepancy rates may be a measurement artifact; discrepancy data should support learning and system redesign, never ranking (Lee et al., 2020).
Follow-up. As many as a third of actionable incidental findings lack documented completion, with emergency department completion as low as 17% (Kadom et al., 2022). Tracking systems work: one program raised completion from 30.8% to 50.7% (Zaki-Metias et al., 2023), a dedicated tracking system raised it from 43% to 71% (Makeeva et al., 2021), and structured recommendation fields reached 87.4% loop closure (Reed Smith, 2022).
Follow-up completion before and after tracking
Figure 6 rebuild. Data: Zaki-Metias et al. (2023); Makeeva et al. (2021). Structured field result: Reed Smith (2022).
View the published figure
Operating tactics 0 of 5 in place
Section 10 · Financial results
Net Revenue
Are we paid what we earned, and how fast?
Net revenue is the product of a long chain: the contracted price, accurate charge capture, valid authorization, a clean claim, a timely payment, and the collection of patient balances. Each link leaks, and the leaks compound.
Table 10. Net Revenue statistics
Medicare PFS payment
Formula[(wRVU × GPCI work) + (PE RVU × GPCI PE) + (MP RVU × GPCI MP)] × conversion factor
Reference point2027 CF $32.6286 (non-APM)
ACC, 2026
Net revenue per exam
FormulaNet patient revenue ÷ completed exams, by modality and payer
Reference pointLocal; trend monthly
Local
Payer yield versus Medicare
FormulaPayer allowed amount ÷ Medicare allowed for the same CPT mix
Reference pointCommercial imaging about 2.4 times Medicare Advantage at the same hospital and insurer
Radiology Business, n.d.
Initial denial rate
FormulaClaims denied on first submission ÷ claims submitted
Reference pointIndustry guidance below 8% to 10%
ADSC, 2026
Days in accounts receivable
FormulaEnding AR ÷ average daily charges (or net revenue)
Reference pointRBMA median nearly 31 days
Radiology Business, 2023
AR older than 120 days
FormulaAR over 120 days ÷ total AR
Reference pointAbout 16% in the RBMA survey
Radiology Business, 2023
Net collection rate
FormulaPayments ÷ (charges − contractual adjustments)
Reference point95% or higher; best performers near 98%
Revecore, 2025
Cost to collect
FormulaBilling and collection cost ÷ procedures (or ÷ collections)
Reference pointAverage billing cost over $3 per procedure (RBMA)
Radiology Business, 2023
Prior authorization appeal yield
FormulaOverturned denials ÷ appealed denials
Reference point20.5% overturned for advanced imaging versus 4.1% for all services
AuntMinnie, 2026b
Site-neutral revenue at risk
FormulaMedicare non-contrast exams in APCs 5521 to 5524 at excepted off-campus PBDs × OPPS payment × 0.60
Reference pointPayment falls to 40% of OPPS on January 1, 2027
AHA, 2026b; ACR, 2026a
What the evidence says
Revenue cycle benchmarks for radiology often come from industry rather than peer-reviewed sources, so use them as starting points. The RBMA 2023 accounts receivable survey of 112 respondents found a median AR of nearly 31 days, about 16% of receivables older than 120 days, and an average billing cost above $3 per procedure (Radiology Business, 2023). Industry guidance places net collection at 95% or higher (Revecore, 2025) and the initial denial rate below 8% to 10% (ADSC, 2026).
One imaging network reported reducing its denial rate from 11.9% to 7.6% after revenue cycle process changes (Waystar, 2025). About 20.5% of advanced imaging prior authorization denials were overturned on independent review, roughly five times the rate for other services (AuntMinnie, 2026b). CMS’s interoperability and prior authorization rule requires impacted payers to give a specific reason for denials beginning in 2026, making denial reasons analyzable (Radiology Business, 2024).
Price is the other half of yield. Within the same hospital the maximum commercial negotiated price for shoppable radiology services averaged 3.8 times the minimum (Jiang et al., 2022). A payer yield table, which expresses each contract as a percentage of Medicare for the department’s actual CPT mix, is the clearest way to see where contracts are weak.
Revenue is a chain, and every link leaks
Enter the share of expected revenue each link retains. Leaks multiply, they do not add.
Illustrative teaching inputs, not benchmarks. Replace with local data.
Operating tactics 0 of 6 in place
Section 11 · Financial results
Gross Margin
Does each exam, and each scanner hour, cover its cost?
Gross margin closes the loop by asking whether the revenue earned by an exam, and by an hour of scanner time, covers what it costs to produce. Time-driven activity-based costing (TDABC) multiplies the minutes each resource spends on each exam step by that resource’s capacity cost rate.
Table 11. Gross Margin statistics
Capacity cost rate
FormulaTotal cost of a resource ÷ practical capacity minutes of that resource
Reference pointCompute for scanner, technologist, nurse, radiologist, and space
TDABC method
Cost per exam (TDABC)
FormulaΣ (minutes in step × capacity cost rate) + supplies and contrast
Reference pointPediatric brain MRI: $262 nonsedated, $842 sedated, $135 limited
Hayatghaibi et al., 2023
Contribution margin per exam
FormulaNet revenue per exam − variable cost per exam
Reference pointLocal; by exam family and payer
Local
Contribution margin per scanner hour
FormulaΣ contribution margin of exams in the hour ÷ staffed hours
Reference pointLocal; the decisive metric when table time is the constraint
This report
Break-even volume
FormulaFixed costs for the period ÷ contribution margin per exam
Reference pointSee worked example in Section 12
This report
Labor cost ratio
FormulaLabor cost ÷ net revenue
Reference pointLocal trend; pair with worked hours per weighted exam
Local
What the evidence says
TDABC studies in imaging consistently show that time drives the largest share of costs. A three-hospital TDABC analysis of pediatric outpatient noncontrast brain MRI found mean costs of $262 for nonsedated, $842 for sedated, and $135 for limited exams, with acquisition duration the largest influence on cost at each hospital (Hayatghaibi et al., 2023).
At Mayo Clinic, TDABC applied to MR enterography in more than 1,000 procedures reduced non-value-added cost by 13%, staff time from 198 to 165 minutes, and patient process time from 102 to 85 minutes (RSNA, 2016).
The lesson for leaders is that cost per exam is largely a function of minutes, so the same tactics that raise capacity (shorter protocols, parallel preparation, fewer incomplete exams) also lower unit cost.
Time drives cost
Hayatghaibi et al. (2023); RSNA (2016).
Operating tactics 0 of 4 in place
About the model. The IMAGING Performance Framework is an organizing and teaching model developed by Dr. Emrick for this report. It synthesizes published metrics but has not been empirically validated as a composite measure.
Worked example: one MRI scanner, one year
Statistics become persuasive when they are tied together. This model shows how intake, capacity, workforce, revenue, and margin statistics interact on a single outpatient MRI scanner. All inputs are illustrative assumptions chosen for teaching, not benchmarks. Replace them with local data; the defaults reproduce Tables 12 and 13 of the report exactly.
Scanner Capacity and Break-even calculator
Edit either scenario. Results update instantly.
Current state
Redesigned state
Shared assumptions
| Result | Current state | Redesigned state | Change |
|---|---|---|---|
| Available slots per week | 104.0 | 117.0 | +13.0 |
| Completed exams per week | 93.6 | 110.0 | +16.4 |
| Completed exams per year | 4,867 | 5,719 | +852 |
| Exams per staffed scanner hour | 1.20 | 1.41 | +0.21 |
| Productive utilization (table minutes ÷ staffed minutes) | 90.0% | 94.0% | +4.0 points |
| Technologist FTE and cost | 2.73 FTE; $338,859 | 2.73 FTE; $338,859 | None |
| Break-even exams per week (fixed ÷ margin) | 47.9 | 47.9 | None |
| Weekly contribution margin | $39,780 | $46,742 | +$6,962 |
| Annual contribution after fixed costs | $1,009,701 | $1,371,699 | +$361,998 |
| Annual margin lost to empty slots | $229,840 | $155,142 | −$74,698 |
Weekly slot flow: where the capacity goes
Figure 7 rebuild, live from the inputs.
View the published figure
Lesson 1
Break-even is low; the margin is in the last exams
The scanner breaks even at about 48 exams a week, roughly half its current volume. Each additional completed exam adds nearly its full $425 contribution, so the redesign is worth about $361,998 a year without new equipment or staff.
Lesson 2
An empty slot has a price
At current performance about 541 slots go unused each year, worth about $229,840 in contribution. That is the number to put beside the cost of a reminder program, a backfill coordinator, or transportation support.
Lesson 3
Higher utilization carries a warning
Productive utilization moves from 90.0% to 94.0%, where the queue term u ÷ (1 − u) rises from 9.0 to 15.7. The redesign works because shorter, standardized protocols also reduce service-time variability. Protect one flexible slot in every four-hour block for add-ons and overruns.
Policy shocks are rate variances
Price the 2027 conversion factor cut and site-neutral exposure on this scanner.
Both numbers arrive regardless of operating performance. Report them as rate variances so they are not mistaken for operating failure.
| Input | Current state | Redesigned state | Basis |
|---|---|---|---|
| Staffed hours per week | 78 (Mon to Fri 7 a.m. to 9 p.m.; Sat 8 a.m. to 4 p.m.) | 78 (unchanged) | Assumption |
| Standard slot length | 45 minutes | 40 minutes | Protocol and turnover redesign (Section 6) |
| Lost slots (no-shows plus unfilled late cancellations) | 10% | 6% | Lead-time cap, risk outreach, backfill (Section 5) |
| Net revenue per completed exam | $520 | $520 | Assumption: blended payer mix |
| Variable cost per exam | $95 | $95 | Supplies, contrast, linen, billing |
| Technologist cost | 2.73 FTE at $95,480 plus 30% benefits = $338,859 | Unchanged | 1.25 on duty × 78 h ÷ 40 h × 1.12 paid-to-worked; BLS median wage |
| Other fixed costs per year | $720,000 | $720,000 | Depreciation $260k; service $150k; front desk $90k; space $120k; overhead $100k |
Access and queue tools
Two calculators from the Intake and Interpretation domains: what lead time costs in empty slots, and what a turnaround target means for the reading worklist.
No-show and Lead-time calculator
Rosenbaum et al. (2018) rates by modality and by lead time. Combine them, or enter your own local rate.
Method, disclosed. The study reports modality and lead-time rates separately. This tool scales the modality rate by the lead-time rate relative to the 3.25% overall rate (for example, MRI at 30 days = 3.70% × 5.26 ÷ 3.25), interpolating lead time on a log scale between the published 7, 30, and 182 day points and holding the end values beyond them. It is an author-derived teaching approximation, not a published model. Populations differ widely: one MRI program reported a 19.3% baseline (Chong et al., 2020). Use the local override when you have your own rate.
Reading Queue calculator
Little’s Law turns a turnaround target into a worklist limit; Kingman shows how close the readers are to the steep part of the curve.
The worklist is 30 studies above the target-consistent level.
Little (1961); Kingman (1961). Assumes a stable arrival rate across the window; set separate targets and limits by priority class.
Payment and revenue tools
Four calculators from the Net Revenue domain and Section 2. Each shows its formula and source.
Medicare Payment calculator
Payment = [(wRVU × GPCI work) + (PE RVU × GPCI PE) + (MP RVU × GPCI MP)] × conversion factor
Defaults are illustrative RVUs summing to 1.00 with GPCIs of 1.000, so 1,000 services reproduce Table 2 exactly. Enter code-level values from the CMS PFS relative value file. Does not model RVU revaluation or the efficiency adjustment.
Site-neutral Exposure calculator
Revenue at risk = affected Medicare exams × OPPS payment × 0.60
Excepted off-campus, non-contrast imaging is paid at 40% of OPPS beginning January 1, 2027.
AHA, 2026b; ACR, 2026a; Phelps Dunbar, 2026. Confirm code-level APC assignment in the final rule addenda.
Revenue Variance calculator
Separate what volume did from what rate and mix did.
The department grew, but each exam earned less.
Revenue Cycle Health panel
Enter your values; each is scored against the IMAGING Scorecard starting thresholds (Table 14).
Compute days in AR and net collection rate from raw figures
RBMA 2023 survey via Radiology Business (2023); ADSC (2026); Revecore (2025). Industry reference points; use as starting thresholds.
The IMAGING Scorecard: starting thresholds
Enter local values to grade each statistic green, amber, or red. Where two bands share a boundary value, the boundary belongs to the better band. These are starting thresholds: each is anchored to a published reference point or a principle in the report, none has been validated as a performance standard, and every department should recalibrate after establishing its own baseline over at least three months.
| Domain | Statistic | Your value | Status | Green / Amber / Red | Anchor |
|---|---|---|---|---|---|
| I | Days to third next available, routine outpatient MRI | days | Not entered | 7 or fewer8 to 14More than 14 | Daye et al., 2018 |
| I | No-show rate, outpatient MRI | % | Not entered | 4% or less4% to 7%More than 7% | Rosenbaum et al., 2018 |
| I | Authorization on file 48 hours before exam | % | Not entered | 98% or more95% to 98%Below 95% | Local policy |
| M | Slot utilization | % | Not entered | 80% to 90%70% to 80% or 90% to 95%Below 70% or above 95% | Queueing (Section 3.5) |
| M | On-time start rate | % | Not entered | 75% or more60% to 75%Below 60% | RSNA News, 2025 |
| M | Uptime | % | Not entered | 98% or more96% to 98%Below 96% | OEM guarantees |
| A | Vacancy rate versus ASRT national rate for the modality | % | Not entered | At or belowUp to 2 points aboveMore than 2 points above | Allegretto, 2025 |
| G | Radiography reject rate | % | Not entered | 5% to 8%8% to 10%Above 10% or below 5% | Little et al., 2023 |
| I | ED CT exam-complete-to-final, median | min | Not entered | 45 minutes or less46 to 60 minutesMore than 60 minutes | Radiology Business, 2026b |
| I | Turnaround tail ratio (p90 ÷ median) | × | Not entered | 2 or less2 to 4More than 4 | Section 3.2 |
| I | Outpatient next-day read share | % | Not entered | 2% or less2% to 7%More than 7% | Radiology Business, 2026a |
| I | Incidental follow-up completion | % | Not entered | 85% or more70% to 85%Below 70% | Kadom et al., 2022; Reed Smith, 2022 |
| N | Initial denial rate | % | Not entered | 8% or less8% to 10%More than 10% | ADSC, 2026 |
| N | Days in accounts receivable | days | Not entered | 31 or fewer32 to 45More than 45 | Radiology Business, 2023 |
| N | AR older than 120 days | % | Not entered | 12% or less12% to 16%More than 16% | Radiology Business, 2023 |
| N | Net collection rate | % | Not entered | 97% or more95% to 97%Below 95% | Revecore, 2025 |
| G | Contribution margin per scanner hour versus plan | % of plan | Not entered | At or above planUp to 10% belowMore than 10% below | Local budget |
Status labels carry an icon and a word as well as a color. Values stay in this browser only; nothing is sent to a server.
A 90-day implementation plan
Statistics change behavior only when they are produced reliably, reviewed on a fixed rhythm, and connected to decisions. This plan moves a department from scattered reports to a governed scorecard in one quarter. Tick actions as they are completed; progress stays in this browser.
- 1
Define
Weeks 1 to 4
Deliverable: Signed data dictionary; three-month baseline
- 2
Diagnose
Weeks 5 to 8
Deliverable: Baseline scorecard; top five gaps ranked by dollars and patient impact
- 3
Act
Weeks 9 to 12
Deliverable: Tactic charters; first post-change run charts
- 4
Govern
Ongoing
Deliverable: Standing governance calendar
| Phase | Weeks | Actions | Deliverable |
|---|---|---|---|
| Define | Weeks 1 to 4 | Build the data dictionary: numerator, denominator, window, and population for every scorecard statistic. Validate RIS, PACS, EHR, and billing timestamps. Deduplicate CPT lines and handle modifier 26 consistently. | Signed data dictionary; three-month baseline |
| Diagnose | Weeks 5 to 8 | Plot run charts for each statistic. Report medians, p90s, and tail ratios. Compute contribution margin per scanner hour for each modality. Run TDABC on three high-volume exams. Analyze denials by reason code. Model site-neutral exposure by location. | Baseline scorecard; top five gaps ranked by dollars and patient impact |
| Act | Weeks 9 to 12 | Launch three tactics with owners (for example, lead-time cap with backfill list, protocol and slot redesign on one scanner, authorization work queue). Hold a weekly 15-minute operations huddle. Hold a monthly scorecard review. | Tactic charters; first post-change run charts |
| Govern | Ongoing | Review the scorecard monthly with physician and finance partners. Review payer yield quarterly. Recalibrate thresholds after six months. | Standing governance calendar |
Radiology Leadership Research · Kelly Emrick, DHSc, PhD, MBA, BSRT(ARRT)R
Busy is not productive.
Ten numbers every radiology manager should carry into 2027.
- 012.31%
Conversion factor cut
The 2027 non-APM Medicare physician fee schedule conversion factor falls from $33.4009 to $32.6286. A rate variance, not a volume variance.
AHA, 2026a; ACC, 2026 - 0240%
Site-neutral rate
Non-contrast imaging in excepted off-campus PBDs is paid at 40% of OPPS, removing about $260 million in 2027.
AHA, 2026b; ACR, 2026a - 03177%
Turnaround increase
Mean Medicare outpatient interpretation turnaround, 2014 to 2024; next-day reads rose from 1.97% to 7.39%.
HPI, 2026a - 0419.4%
CT vacancy rate
An all-time high; MRI reached 17.4% in the same ASRT 2025 survey.
Allegretto, 2025 - 059.46%
No-shows at six months of lead time
Versus 2.71% at one week across 2.9 million outpatient imaging visits.
Rosenbaum et al., 2018 - 069x
Queue at 90% utilization
Relative queue wait versus a resource run at 50%; 19x at 95%.
Kingman, 1961 - 078%
Reject rate target
Investigate above 10% or below 5%; too low can mean poor images reach the reader.
Little et al., 2023 - 0820.5%
PA denials overturned
Advanced imaging prior authorization denials overturned on independent review, versus 4.1% for other services.
AuntMinnie, 2026b - 0931
Days in AR, median
About 16% of radiology receivables are older than 120 days.
Radiology Business, 2023 - 10$362K
One scanner, one year
Annual contribution gained from a five-minute slot cut and a four-point drop in lost slots. No new equipment.
Section 12 worked example
Measure it with Dr. Emrick’s
IMAGING Performance Framework
Formula quick reference
Appendix A. Filter by name or formula.
| Statistic | Formula |
|---|---|
| Tail ratio | p90 turnaround ÷ median turnaround |
| Little’s Law | Items in queue = arrival rate × average time in system |
| Queue utilization term (Kingman) | u ÷ (1 − u), multiplied by arrival and service variability terms |
| Slot utilization | Scheduled minutes ÷ staffed minutes |
| Productive utilization | Completed table minutes ÷ staffed minutes |
| Exams per staffed scanner hour | Completed exams ÷ staffed hours |
| Uptime | (Base hours − unplanned downtime) ÷ base hours |
| No-show rate | No-shows ÷ appointments scheduled 24 hours before the exam |
| Vacancy rate | Open budgeted positions actively recruited ÷ budgeted positions |
| Reject rate | Rejected images ÷ total images acquired |
| Medicare PFS payment | [(wRVU × GPCI work) + (PE RVU × GPCI PE) + (MP RVU × GPCI MP)] × conversion factor |
| Payer yield | Payer allowed ÷ Medicare allowed for the same CPT mix |
| Days in AR | Ending AR ÷ average daily charges |
| Net collection rate | Payments ÷ (charges − contractual adjustments) |
| Site-neutral revenue at risk | Affected Medicare exams × OPPS payment × 0.60 |
| Capacity cost rate | Resource cost ÷ practical capacity minutes |
| TDABC cost per exam | Σ (step minutes × capacity cost rate) + supplies |
| Contribution margin per exam | Net revenue per exam − variable cost per exam |
| Break-even volume | Fixed costs ÷ contribution margin per exam |
| Volume variance | (Current exams − prior exams) × prior revenue per exam |
| Rate and mix variance | (Current revenue per exam − prior revenue per exam) × current exams |
Limitations
- Published benchmarks for radiology operations vary by setting, era, and definition. The largest no-show study covers one academic system from 2000 to 2015; national MRI throughput data come from Canada; and many revenue cycle reference points come from industry surveys and vendors rather than peer-reviewed research.
- The ASRT vacancy survey had a 2.6% response rate, and the Neiman turnaround analysis is observational, limited to Medicare fee-for-service outpatient claims, and measured in calendar days.
- The 2027 payment figures reflect final rules released November 4, 2026; code-level impacts depend on RVU revaluation, and Congress could alter the conversion factor before January 1.
- The IMAGING Performance Framework and scorecard thresholds are organizing and teaching tools synthesized for this report; they have not been empirically validated as composite measures, and local recalibration of the thresholds is recommended.
- The worked example is illustrative; it shows how statistics interact, not how to estimate any specific department’s results.
Verification ledger
Every worked number in the report was recomputed independently for this dashboard.
Table 13 worked example (all rows)
Reproduces exactly
Available slots 104.0 / 117.0 through annual contribution $1,009,701 / $1,371,699 and the $361,998 gain.
Table 2 conversion factors
Reproduces exactly
−2.31% and −$772.30 per 1,000 RVUs (non-APM); −1.83% and −$612.70 (APM).
Table 3 revenue variance
Reproduces exactly
+$288,000 volume, −$159,000 rate and mix, +$129,000 total.
Little’s Law and Kingman terms
Reproduces exactly
60 and 30 studies; 2.3, 4.0, 5.7, 9.0, 19.0.
Conversion factor impact on the worked scanner
Consistent
Recomputes to $17,556 using the exact 2.3122% change; the report rounds to about $17,600.
Turnaround increase, 2014 to 2024
Rounding difference, disclosed
From the printed endpoints (2 h 11 min to 6 h 1 min) the increase is 175.6%; the published 177% comes from unrounded source data.
Chong et al. relative improvement
Rounding difference, disclosed
From the printed rates (19.3% to 15.9%) the relative reduction is 17.6%; the report cites 17.2%, likely computed from unrounded rates.
Figure 7 lost slots, redesigned state
Display rounding
The model gives 7.02 lost slots per week; the published figure prints 7.
References
Linked citations from the report. Filter by source type.
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- Allegretto, A. (2025, July 28). ASRT survey shows vacancy rates still high among imaging departments. AuntMinnie. www.auntminnie.com/practice-management/article/15751626/asrt-survey-sh…
- American College of Cardiology. (2026, November 5). CMS releases final 2027 Medicare Physician Fee Schedule and Hospital OPPS rules. www.acc.org/Latest-in-Cardiology/Articles/2026/11/05/14/15/CMS-Release…
- American College of Radiology. (2026a, November 4). CMS finalizes site-neutral payments for non-contrast imaging services in OPPS. www.acr.org/News-and-Publications/2026/cms-neutral-payments-for-non-co…
- American College of Radiology. (2026b). Detailed summary of radiology provisions in the 2027 Medicare Physician Fee Schedule proposed rule. edge.sitecorecloud.io/americancoldf5f-acrorgf92a-productioncb02-3650/m…
- American College of Radiology. (2026c, July). Early summary of 2027 MPFS proposed rule released. www.acr.org/News-and-Publications/2026/early-summary-of-2027-mpfs-prop…
- American Hospital Association. (2026a, November 4). CMS issues CY 2027 physician fee schedule final rule. www.aha.org/news/headline/2026-11-04-cms-issues-cy-2027-physician-fee-…
- American Hospital Association. (2026b, November 4). CMS finalizes increases to Medicare hospital outpatient department payment rates, changes to site-neutral and 340B for 2027. www.aha.org/news/headline/2026-11-04-cms-finalizes-increases-medicare-…
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- AuntMinnie. (2026a, August). Imaging turnaround times continued to climb in 2024. www.auntminnie.com/practice-management/administration/article/15831662…
- AuntMinnie. (2026b). SIIM-CAIMI: 20% of advanced imaging prior auth denials get overturned. www.auntminnie.com/clinical-news/mri/article/15975517/siimcaimi-20-of-…
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- Becker’s Hospital Review. (2025). The wRVU volume gap across specialties. www.beckershospitalreview.com/compensation-issues/the-wrvu-gap-across-…
- Bureau of Labor Statistics. (2026). Occupational outlook handbook: Radiologic and MRI technologists. U.S. Department of Labor. www.bls.gov/ooh/healthcare/radiologic-technologists.htm
- Canada’s Drug Agency. (2024). Average volume of MRI exams conducted per hour across Canada (CMII Service Report CM0008). canjhealthtechnol.ca/index.php/cjht/article/download/CM0008/1752?inlin…
- Canada’s Drug Agency. (2025). MRI exam throughput per unit per hour in Canada (CMII Service Report CM0040). www.canjhealthtechnol.ca/index.php/cjht/article/download/CM0040/CM0040
- Centers for Medicare & Medicaid Services. (2026). CY 2027 payment policies under the Medicare Physician Fee Schedule (CMS-1848-F). www.cms.gov/medicare/payment/fee-schedules/physician/federal-regulatio…
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