In health information management, the patient’s clinical journey does not end when the discharge order is signed. A second value stream begins: documentation must become a complete, accurate, coded and billable episode.
Value stream mapping makes that journey visible. It connects the movement of the chart and coded episode with the movement of information between clinicians, health information management (HIM), clinical documentation integrity (CDI), coders and revenue cycle teams. As AHRQ explains, VSM visualises both process and information flow so teams can identify waste, bottlenecks and improvement opportunities.
For clinical coding, the fundamental purpose is not simply to make people work faster. It is to create reliable flow: complete documentation reaches the right specialist at the right time, queries receive structured responses, coding quality remains strong and claims are released with fewer delays.
The following worked example uses dummy data from a hypothetical hospital’s inpatient surgical service.
Select a Focused Episode and Define the Value Boundary
A useful VSM begins with one clearly defined value object. Mapping every HIM activity at once creates complexity without creating control.
Scope selected
- Episode type: Inpatient surgical separations
- Volume: 112 discharged episodes per weekday
- Start point: Discharge order entered in the electronic health record
- End point: Coded episode validated, released from discharged-not-final-billed (DNFB), and sent to billing
- Customer outcomes: Timely claim release, accurate coding, compliant documentation and reliable financial information
The map includes:
- Discharge notification
- Chart assembly and deficiency review
- Documentation completion
- Coding queue entry
- Clinical coding
- Query creation and provider response
- Final coding and validation
- Billing edit resolution
- DNFB release
A cross-functional team should include the HIM manager, inpatient coding lead, two coders, a CDI specialist, a chart completion representative, a physician champion, revenue cycle staff and an EHR analyst. A short Gemba review, observing the work where it occurs, helps distinguish the written procedure from the real workflow.
Build the Current-State Map with Measured Data
The current-state map should show process steps, information signals, work-in-process (WIP), waiting time and quality measures. The figures below are a realistic simulation, not an industry benchmark.
Demand and takt time
The department has:
- 20 inpatient coders
- 7 productive coding hours per coder per day
- 112 surgical episodes demanded per day
[
\text{Available time} = 20 \times 7 \times 60 = 8{,}400 \text{ minutes/day}
]
[
\text{Takt time} = \frac{8{,}400}{112} = 75 \text{ minutes per episode}
]
The average end-to-end coding touch time is below takt, but the process still accumulates WIP because episodes wait between activities and queries remain open.
Current-state process data
| Process step | Average touch time | Average waiting time | First-pass accuracy or completion |
|---|---|---|---|
| Discharge notification and queue creation | 3 min | 0.3 days | 98% |
| Chart assembly and deficiency review | 12 min | 0.9 days | 88% complete |
| Provider documentation completion | 8 min | 1.1 days | 91% on first review |
| Clinical coding | 62 min | 0.7 days | 86% first-pass accuracy |
| Query preparation | 8 min | 0.2 days | 94% correctly routed |
| Provider query response | 4 min | 2.4 days | 79% within target |
| Final coding and validation | 10 min | 0.1 days | 96% |
| Billing edits and DNFB release | 4 min | 0.1 days | 97% |
Total measured touch time is:
[
3+12+8+62+8+4+10+4 = 111 \text{ minutes}
]
However, not every minute is value-added. Query preparation and validation are necessary compliance activities, while some repeated review is rework. For this simulation, the practical value-adding touch time is 96 minutes.
The average discharge-to-billable lead time is 5.8 days:
[
5.8 \times 1{,}440 = 8{,}352 \text{ minutes}
]
[
\text{Process Cycle Efficiency} = \frac{96}{8{,}352}\times100 = 1.15%
]
This result does not mean the coding team is productive for only 1.15% of the day. It means each episode spends most of its journey waiting, often in queues or awaiting information.
WIP ageing profile
| Episode age since discharge | Episodes in WIP | Primary location |
|---|---|---|
| 0–1 day | 96 | Coding queue and chart completion |
| 2–3 days | 88 | Coding queue and documentation review |
| 4–5 days | 60 | Query pending |
| More than 5 days | 74 | Provider response, rework or billing edit |
| Total | 318 |
The key signal is the 74 episodes aged beyond five days. These cases require rapid review because they create financial delay, increase follow-up effort and amplify the likelihood of duplicated handling.
Convert the Eight DOWNTIME Wastes into Improvement Opportunities
The eight DOWNTIME wastes provide a structured lens for analysing clinical coding flow.
- Defects: Incorrect code selection, missing present-on-admission indicators, incomplete provider documentation and rejected billing edits create rework. The 86% first-pass coding accuracy indicates a measurable improvement opportunity.
- Overproduction: Coding preliminary details that will later be replaced because the operative note or discharge summary is incomplete creates unnecessary effort. Work should be performed at the right time with the best available information.
- Waiting: Episodes wait for chart assembly, unsigned documentation, coder capacity and provider query responses. The simulated query turnaround of 2.4 days is the largest delay.
- Non-utilisation of talent: Experienced coders spend time chasing unsigned notes, manually sorting queues and sending repeat reminders instead of applying clinical judgement and mentoring newer team members.
- Transportation: Electronic records may be moved between separate work queues, inboxes, spreadsheets and messaging platforms. Each transfer increases the possibility of missed information.
- Inventory: The 318 open episodes represent WIP inventory. Ageing inventory hides the real condition of the process and makes prioritisation more difficult.
- Motion: Coders search across multiple screens for operative notes, discharge summaries, query history and payer edits. A standard chart-review layout can reduce unnecessary navigation.
- Extra-processing: Repeated chart checks, duplicate query follow-up, manual status reporting and multiple validation passes consume capacity without improving the episode proportionately.
Design a Faster Future State with Controlled Flow
The future-state map should not depend on individual heroics. It should establish predictable signals, clear ownership and a manageable WIP level.
1. Introduce targeted concurrent coding
Apply concurrent coding to high-complexity surgical episodes using defined criteria such as:
- Expected length of stay above five days
- Major operating room procedures
- High-value or high-risk DRGs
- Cases with known documentation gaps
- Episodes approaching discharge
The coder or CDI specialist reviews documentation during the stay, identifies clarification opportunities earlier and records preliminary coding decisions in a controlled work queue.
2. Create query standard work
Use an electronic query template with:
- Approved clinical indicators
- Neutral wording
- Required supporting documentation
- Named provider owner
- Automatic reminders at 24 and 48 hours
- Escalation to the service-line physician champion after 48 hours
Separate “query drafted,” “query viewed,” “response received” and “coding finalised” statuses. This prevents the team from treating every open query as one undifferentiated category.
3. Improve documentation at the front end
CDI and physician champions can create short documentation prompts for recurring surgical issues, including:
- Acute blood loss anaemia
- Acute kidney injury
- Respiratory failure
- Postoperative complications
- Principal diagnosis clarification
- Procedure detail and laterality
Prompts should support clinical reasoning rather than encourage unsupported documentation.
4. Level the coding workload
Use a daily capacity board that shows:
- New discharges
- Episodes ready for coding
- Query-pending episodes
- Cases approaching DNFB thresholds
- Available coder capacity
A simple pull rule can prioritise episodes that are complete and ready for coding, while preventing query-pending cases from repeatedly re-entering the main queue.
Compare the Current and Future Performance
The future-state targets below are based on a 90-day pilot covering the inpatient surgical service.
| Measure | Current state | Future-state target | Improvement |
|---|---|---|---|
| Discharge-to-billable lead time | 5.8 days | 2.1 days | 64% reduction |
| Practical touch time | 96 min | 82 min | 15% reduction |
| Process Cycle Efficiency | 1.15% | 2.7% | 135% relative increase |
| Coder productivity | 5.6 episodes/day | 6.4 episodes/day | 14% increase |
| First-pass coding accuracy | 86% | 94% | +8 percentage points |
| Query turnaround time | 2.4 days | 0.8 days | 67% reduction |
| Average DNFB days | 4.6 days | 2.0 days | 57% reduction |
| WIP aged over five days | 74 episodes | 18 episodes | 76% reduction |
The future state does not eliminate necessary compliance activity. Instead, it moves clarification earlier, reduces queue switching and creates a visible flow from discharge to billable episode.
Sequence the First 90 Days of Kaizen
Days 1–30: Establish the baseline and stabilise the flow
Owners: HIM manager, coding lead and EHR analyst
Actions:
- Validate the current-state map with staff who perform the work.
- Confirm definitions for lead time, touch time, DNFB days and first-pass accuracy.
- Create separate queues for ready-to-code, documentation pending and query pending.
- Begin daily WIP ageing review.
- Select a 30-episode pilot sample.
Metrics: Baseline accuracy, query turnaround, WIP ageing and discharge-to-first-coding-touch time.
Days 31–60: Pilot concurrent coding and query standard work
Owners: CDI lead, physician champion and inpatient coding supervisor
Actions:
- Apply concurrent coding criteria to the pilot service.
- Launch the standard electronic query template.
- Add 24-hour and 48-hour reminders.
- Train providers on response expectations and documentation clarity.
- Review a weekly Pareto chart of delay causes.
Metrics: Query response within 48 hours, first-pass accuracy, query rate per episode and coder productivity.
Days 61–90: Level capacity and lock in control
Owners: Revenue cycle director, HIM manager and Lean Six Sigma project lead
Actions:
- Introduce the daily capacity and demand board.
- Set a WIP limit for each queue.
- Create a weekly DNFB review by root cause.
- Audit 20 coded episodes per week for accuracy and rework.
- Publish a control plan with metric owners and escalation rules.
Metrics: Lead time, PCE, DNFB days, episodes aged over five days, accuracy and productivity.
For additional process-improvement practice, use the Lean Six Sigma process cycle efficiency calculator to test your own assumptions and convert observed waiting time into a measurable baseline.
Build the Capability to Improve Healthcare Processes
Value stream mapping is most effective when the team can connect observation, data analysis, root-cause investigation and controlled implementation. Lean Six Sigma training develops that capability across the organisation.
Lean 6 Sigma Hub provides CSSC-accredited, self-paced online training from White Belt through Master Black Belt, with practical examples, simulations, templates, charts and end-to-end DMAIC applications.
- White Belt training introduces foundational principles and DMAIC awareness.
- Yellow Belt training prepares team members to support improvement projects.
- Green Belt training develops the skills to lead data-driven projects.
- Black Belt training prepares advanced practitioners to lead complex transformation.
- Master Black Belt training builds enterprise governance, mentoring and deployment capability.
Start with your discharge-to-billable episode map, measure the real flow, and pursue CSSC-accredited Lean Six Sigma certification to lead sustainable improvement.
Kaizen. Kai-Care. Kai-Done. Lean Six Sigma
