Patient Intake Improvement Modelss

Front Door Reliability Model

Patient Intake Improvement Model

An interactive maturity and performance simulator for the five linked stages of the front door — scheduling, check-in, registration, encounter, and payment. Set a baseline, exercise five operational levers, and surface the trade-offs beneath digital transformation.

Overview & Front Door Reliability Score

The FDRS is a composite of three weighted dimensions — Experience (30%), Accuracy (40%), and Throughput (30%) — with a friction penalty when digital adoption outpaces assisted-support coverage. The score maps to a five-stage maturity ladder, providing a shared language for project plans and weekly huddles.

Composite FDRS

8.4/10
Optimized

Stable systems, predictable variation, continuous improvement embedded.

Sub-score breakdown

Experience
8.6
Accuracy
8.7
Throughput
7.9
ReactiveHeroics & rework
DefinedDocumented basics
StandardizedConsistent execution
OptimizedPredictable variation
AdaptiveSelf-correcting

Headline KPIs

Live recalculation against the active scenario. Adjust inputs in Baseline Config and Five Levers to see movement.

Projected Wait Time
9min
Door-to-imaging table-time interval
Registration Defect Rate
3.2%
% encounters with downstream-correctable error
Initial Denial Rate
4.1%
First-pass payer rejection
No-Show Rate
6.8%
% scheduled exams not completed
Rework / Encounter
4.6min
Staff time spent correcting upstream defects
Patient Experience
8.5/10
Composite of access, communication, dignity

How to use this model

Run three passes — the value is in comparing them, not in any single number.

Pass 1

Map the current state

Use Baseline Config to enter today’s actuals from your weekly ops scorecard. Save as Baseline.

Pass 2

Model a realistic plan

Modest portal uptake plus a readability uplift plus staffed assistance. Save as Near-Term Plan.

Pass 3

Stress-test an aggressive strategy

High kiosk adoption with reduced staffing. Save as Aggressive Plan and watch for equity friction and error rebound.

Baseline Configuration

Enter your current-state actuals. These six inputs anchor every downstream calculation. Pull values directly from your weekly intake huddle scorecard or RCM reporting.

Door-to-imaging-table interval, captured at the modality.
0 min 22 min 90 min
% encounters with at least one downstream-correctable defect (insurance, demographic, authorization).
0% 9.0% 30%
First-pass payer rejection (HFMA MAP Keys: target < 5%).
0% 8.0% 25%
% scheduled exams not completed (cancel < 24h or no-arrival).
0% 11.0% 30%
Minutes of registrar/tech time correcting upstream defects per encounter.
0 min 8.0 min 30 min
Composite (0–10) from access, communication, dignity domains.
0 7.4 10
Three-pass methodology: save your current state as Baseline first, then return to Five Levers to model the Near-Term and Aggressive plans. Each saved scenario persists in your browser and is available in Scenario Compare.

The Five Levers

These are the operational design choices that move the front door. Move a slider and the model recalculates Headline KPIs, the Stage Heatmap, and the FDRS in real time. Watch what happens when portal adoption climbs faster than assisted-support coverage.

% patients completing pre-arrival registration via patient portal.
0% 40% 100%
Front-desk + scheduling FTE relative to demand benchmark (1.0 = matched).
0.50 1.00 1.50
% on-site check-ins routed through self-service kiosk vs. registrar.
0% 25% 100%
1–10 score for plain-language clarity, multilingual coverage, screen-reader support.
1 6.0 10
% patients who can access live-assist (call, in-person, video) when digital channels fail.
0% 55% 100%

Lever → KPI Impact

Marginal effect of moving each lever ±10 points (or one std unit for Staffing) on the projected KPIs.

Stage Analysis

Defects don’t always surface where they are caused. The attribution model traces downstream denials and delays back to their upstream root cause — published RCM literature consistently finds that ~70% of denials are seeded at registration, even when the rejection lands at the back end.

Defect rate by stage

Severity color: LowModerateHigh

Stage 1
Scheduling
2.1%
Defect rate
Stage 2
Check-in
3.4%
Defect rate
Stage 3
Registration
5.8%
Defect rate
Stage 4
Encounter
1.6%
Defect rate
Stage 5
Payment
3.0%
Defect rate

Denial attribution (root cause)

Where each $1 of denied revenue is actually born — not where it surfaces.

Stage-level performance

Quality score per stage (10 = defect-free).

Diagnostic prompt: the highest-defect stage is rarely the right intervention point. Read the attribution chart first — if registration is upstream of most denials, fixing the payment stage is treating the symptom.

Scenario Compare

Side-by-side view of saved scenarios with delta indicators. The radar shows shape difference; the table shows magnitude. If a row is empty, save that scenario in Baseline Config first.

Scenario shape comparison

Six normalized KPIs — further from center is better in all directions.

FDRS movement

Composite score by scenario; the gap between Near-Term and Aggressive is the risk premium.

KPI delta table

Metric Baseline Near-Term Δ Aggressive Δ

Equity & Risk

Two patterns degrade the front door silently. Equity friction appears when digital adoption outpaces assisted-support coverage — the system gets faster for the digitally fluent and slower for everyone else. Error rebound appears when staffing cuts and self-service automation arrive together — rework climbs as the safety net thins.

Equity Friction Index

0.18
Within tolerance

Portal adoption is supported by adequate assisted-support coverage. Continue monitoring as portal grows.

Error Rebound Risk

Low
Stable

Staffing index and kiosk mix are in balance. No automation rebound signal.

Vulnerable-Population Coverage

82%
Adequate

Estimated share of LEP, low-digital-literacy, and elderly patients with viable assisted-support pathway.

What the model is watching

Trigger 1

Portal − Assist gap > 20 points

Apply a friction penalty to the FDRS. Patients without portal access experience longer waits and higher defect rates because the registrar workflow is no longer the primary path.

Trigger 2

Staffing < 0.85 AND Kiosk > 60%

Flag error rebound. Self-service captures volume but produces input errors that reappear as denials and rework downstream — with too few staff to absorb the rework.

Trigger 3

Readability < 5

Amplify defect rebound on kiosk and portal channels. Plain-language and multilingual coverage are the prerequisite for any self-service strategy.

Trigger 4

Friction penalty active for > 1 quarter

Sustained equity gaps require structural mitigation: financial counseling, language-line investment, scheduled assist, or paper-track preservation — not just slider movement.

Toolkit

Operational artifacts to translate the model output into a project plan. All fields persist in your browser and can be printed.

PDSA Worksheet — Front Door Improvement Cycle

Plan

Do

Study

Act

Weekly Intake Huddle Template (15 minutes)

A3 Project Canvas (one-page)

Background

Current condition

Target condition

Root cause analysis

Countermeasures

Plan / measure / sustain

Intervention Library

Each card maps to one or more levers. Use it as a starting menu, not an exhaustive list.

PortalStage 1–2Pre-arrival registration link via SMS + emailSent 5 days, 24 hours, and morning-of with one-tap access. Captures insurance, demographics, consent.
StaffingStage 2–4Floating registrar / patient navigatorRoving assist for kiosk users, LEP patients, and complex authorizations. Backstops automation.
KioskStage 2Bilingual self-service kiosk with assist call-buttonOne-tap escalation to registrar; auto-flags incomplete fields before submission.
ReadabilityStage 1–3Plain-language form rewrite (8th-grade target)Rewritten consent, prep instructions, and authorization questions. Multilingual at point of use.
AssistAll stagesScheduled assist appointment15-minute pre-appointment call for patients flagged as high-friction; replaces day-of confusion.
PortalStage 5Pre-service price transparency & estimatePatient sees expected cost before arrival; reduces surprise-billing complaints and time-of-service rework.

Reliability Specification

The spec defines what each KPI means, how it’s measured, who owns it, and the threshold for each maturity stage. Without this, the model produces numbers that can’t be defended in a budget conversation.

KPI definitions

KPI Definition Numerator / Denominator Source Cadence Owner
Wait Time Door-to-modality-table interval. Σ (table_time − arrival_time) / N encounters RIS arrival/start timestamps Daily Imaging Ops Manager
Registration Defect Rate Encounters with at least one downstream-correctable error. defective_encounters / total_encounters RCM workqueue + audit sample Weekly PFS / Patient Access Director
Initial Denial Rate First-pass payer rejections. denied_837 / total_837 (first 60 days) 835 remits Monthly Revenue Cycle Director
No-Show Rate Scheduled exams not completed (cancel < 24h or no-arrival). noshow + late_cancel / scheduled Scheduling system Weekly Scheduling Manager
Rework / Encounter Staff time correcting upstream defects per encounter. corrective_min / total_encounters Time study + workqueue resolution log Quarterly Patient Access Director
Patient Experience Composite of access, communication, dignity domains. weighted mean of domain top-box % Press Ganey / NRC / internal short-form Monthly PX Officer
FDRS Composite reliability score. 0.30·Exp + 0.40·Acc + 0.30·Thr − friction_penalty Computed from above Monthly Imaging VP / Service Line Lead
Equity Friction Index Gap between digital adoption and assisted-support coverage. max(0, (portal − assist − 20) / 100) Computed Monthly Health Equity Officer

Maturity-stage thresholds

Stage FDRS Defect Rate Initial Denial Rate PX Hallmark
Reactive < 5.5 > 12% > 10% < 6.5 Heroics. Variation absorbed by staff overtime.
Defined 5.5 – 7.0 8 – 12% 7 – 10% 6.5 – 7.5 Documented basics. Process exists; adherence inconsistent.
Standardized 7.0 – 8.0 5 – 8% 5 – 7% 7.5 – 8.2 Consistent execution. Defects detected, not yet prevented.
Optimized 8.0 – 9.0 3 – 5% 3 – 5% 8.2 – 9.0 Predictable variation. Continuous improvement embedded.
Adaptive ≥ 9.0 < 3% < 3% ≥ 9.0 Self-correcting. System learns from each defect; equity gaps actively closed.

Governance & cadence

Daily

Wait time, no-show. Modality-level huddle.

Weekly

Defect rate, rework, equity friction. Service-line huddle.

Monthly

FDRS, denial rate, PX. Operating committee with maturity-stage review.

Patient Intake Improvement Model — Front Door Reliability Score · Designed by Kelly Emrick, DHSc, PhD, MBA · PHB Design System

Executive Command Center

System performance against the Intake Quality Index (IQI), an illustrative composite of experience, accuracy, and throughput.

Live System Data

Composite IQI Score

8.9/10

Weighted blend of patient experience, registration accuracy, and front-door throughput.

Experience

9.4

Accuracy

9.8

Throughput

7.5

Trend

↑ 14%

Time to Ready: Digital Intake vs Manual Front Desk

Grounded in a digital check-in deployment (25% faster check-in, 20% higher satisfaction) and an AI assisted outpatient study that cut median wait from 1.97 hours to 0.38 hours.

Clean Claim Rate

98.2% 3.1%

Above the HFMA best practice target of 98% (95% minimum)

Intake Attributable Denials

26% Target

Registration and eligibility account for roughly one quarter of all denied claims, the share the front door can directly prevent.

Financial Impact Engine

Quantifying the shift from clerical cost to protected revenue, grounded in 2024 to 2026 revenue cycle data.

5002,500 exams10,000
10%26%50%
10%50%90%

Projected Annual Value

$0
Revenue at risk protected$0
Rework cost avoided$0
Front desk labor efficiency$0
Front-end denials prevented0 claims

Model Logic

Prevented front-end denials = annual exams × denial rate × intake share × capture rate. Value sums protected reimbursement, avoided rework (about $44 per claim), and front desk labor saved ($12 per registration). Adjust every assumption above.

The Zero-Touch Experience

This simulation walks the patient journey from a mobile pre-arrival link. Automating identity and insurance at the front door shrinks the waiting room and stops registration errors before they become denials.

  • 1

    Image based capture of ID and insurance card, reducing typed entry errors

  • 2

    Real time eligibility and coverage verification

  • 3

    Transparent arrival pass and wait status

S

Hello, Sarah.

Your CT Brain scan is scheduled for 2:30 PM today.

Preparation Step

Fast-Track Check-in

Skip the desk. Verify your insurance now and walk straight to imaging.

University Radiology Health System

Insurance Verification

Position your card inside the frame.

Tap to Scan Card

Analyzing payer data…

You are verified

Coverage confirmed with Blue Shield. No co-pay is due today.

Arrival Pass

Show this at the arrival kiosk

Fast-Track: ON

Intake 2.0 Engineering Framework © 2026 · Streamline Health Partners

Executive Command Center

System performance against the Intake Quality Index (IQI), an illustrative composite of experience, accuracy, and throughput.

Live System Data

Composite IQI Score

8.9/10

Weighted blend of patient experience, registration accuracy, and front-door throughput.

Experience

9.4

Accuracy

9.8

Throughput

7.5

Trend

↑ 14%

Time to Ready: Digital Intake vs Manual Front Desk

Grounded in a digital check-in deployment (25% faster check-in, 20% higher satisfaction) and an AI assisted outpatient study that cut median wait from 1.97 hours to 0.38 hours.

Clean Claim Rate

98.2% 3.1%

Above the HFMA best practice target of 98% (95% minimum)

Intake Attributable Denials

26% Target

Registration and eligibility account for roughly one quarter of all denied claims, the share the front door can directly prevent.

Financial Impact Engine

Quantifying the shift from clerical cost to protected revenue, grounded in 2024 to 2026 revenue cycle data.

5002,500 exams10,000
10%26%50%
10%50%90%

Projected Annual Value

$0
Revenue at risk protected$0
Rework cost avoided$0
Front desk labor efficiency$0
Front-end denials prevented0 claims

Model Logic

Prevented front-end denials = annual exams × denial rate × intake share × capture rate. Value sums protected reimbursement, avoided rework (about $44 per claim), and front desk labor saved ($12 per registration). Adjust every assumption above.

The Zero-Touch Experience

This simulation walks the patient journey from a mobile pre-arrival link. Automating identity and insurance at the front door shrinks the waiting room and stops registration errors before they become denials.

  • 1

    Image based capture of ID and insurance card, reducing typed entry errors

  • 2

    Real time eligibility and coverage verification

  • 3

    Transparent arrival pass and wait status

S

Hello, Sarah.

Your CT Brain scan is scheduled for 2:30 PM today.

Preparation Step

Fast-Track Check-in

Skip the desk. Verify your insurance now and walk straight to imaging.

University Radiology Health System

Insurance Verification

Position your card inside the frame.

Tap to Scan Card

Analyzing payer data…

You are verified

Coverage confirmed with Blue Shield. No co-pay is due today.

Arrival Pass

Show this at the arrival kiosk

Fast-Track: ON

Intake 2.0 Engineering Framework © 2026 · Streamline Health Partners