Value Stream Mapping for Dialysis Centres: From Referral to Chair Time Without the Treatment Slot Gaps

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In the realm of outpatient haemodialysis, reliable treatment flow is both a clinical priority and an operational discipline. Patients need predictable access to treatment, clinicians need protected time for safe care, and leaders need sufficient chair capacity to meet demand without relying on continual overtime.

This is where value stream mapping becomes powerful. It creates a shared view of the complete flow of people, information, equipment and decisions, from referral through treatment and exit. The fundamental purpose is not simply to make staff work faster. It is to expose delays, rework, uneven demand and unclear hand-offs so the care pathway can be redesigned around patient value.

This deep guide uses a working example from an outpatient dialysis centre network with 19 chairs, three treatment shifts per day and 1,140 treatments per month.

Scope Selection: Define the Patient Family Before Mapping

A useful value stream map begins with a carefully selected product family. For this project, the product family is:

Standard in-centre haemodialysis treatment for stable chronic patients attending a Mon/Wed/Fri schedule.

The map starts at referral and eligibility confirmation and ends when the patient exits after treatment, documentation and discharge. The analysis also includes the chair-level flow from one patient disconnecting to the next patient being connected.

The working operating profile is:

  • 19 chairs
  • Three shifts per day
  • Approximately 13 treatments per chair per week
  • 1,140 treatments per month
  • Four hours of prescribed treatment time
  • Current average arrival-to-exit time of 6.8 hours
  • Current chair utilisation of 71%

For a practical takt calculation, assume the core Mon/Wed/Fri stream provides nine weekly shift opportunities. Demand per chair-shift is:

13 treatments ÷ 9 chair-shifts = 1.44 treatment starts per chair-shift

With 480 available minutes per chair-shift:

Takt time = 480 ÷ 1.44 = approximately 333 minutes

This means the planned rhythm is approximately one occupied chair slot every 5.55 hours per chair-shift, including treatment, hand-offs and turnover. Since prescribed treatment already consumes 240 minutes, the remaining time must accommodate preparation, discharge and chair turnover. This calculation makes a 15-minute turnover target operationally important.

Current-State Value Stream Map: Follow the Patient and the Chair

The current map should be built at the gemba with nurses, technicians, schedulers, reception staff, cleaners, nephrologists and managers. A value stream map should include both direct work and waiting, not only the steps described in standard operating procedures.

Referral-to-treatment information flow

Process step Direct work Typical delay or rework
Referral and eligibility 18 minutes 1.4 days awaiting complete referral information
Vascular access assessment 20 minutes 0.8 days awaiting assessment or clarification
Booking and slot allocation 12 minutes 0.6 days from slot negotiation and schedule confirmation
Pre-arrival bloods validation 8 minutes 11% arrive with incomplete blood results
Arrival and pre-treatment observations 13 minutes 33 minutes of queueing and hand-off delay
Machine setup and prime 8 minutes 20 minutes waiting for equipment or staff availability
Cannulation 15 minutes 22 minutes average delay; 4.4% access-related rework
Prescribed haemodialysis treatment 240 minutes Treatment duration is clinically prescribed
Post-treatment observations and haemostasis 8 minutes 13 minutes awaiting review or discharge readiness
Nephrologist review and documentation 4 minutes 16 minutes awaiting review, signature or record completion
Exit and discharge 2 minutes 14 minutes awaiting transport or final coordination

For the patient-day journey, direct work totals 50 minutes outside the prescribed treatment, while treatment contributes 240 minutes. The current average is:

  • Direct work and treatment: 290 minutes
  • Non-value-added waiting: 118 minutes
  • Arrival to exit: 408 minutes, or 6.8 hours

Therefore, the patient spends four hours receiving prescribed dialysis but remains in the centre for almost seven hours.

At chair level, the gap is equally clear:

Patient disconnect → haemostasis and exit → cleaning and disinfection → machine readiness → next patient arrival → cannulation

Current average turnover is 34 minutes, against a target of 15 minutes. This gap reduces effective capacity, creates uneven arrivals and contributes to late starts across all three shifts.

Current-state value stream mapping for dialysis patient flow

Where the Eight DOWNTIME Wastes Appear

The DOWNTIME framework helps the team classify waste without blaming individuals. It also connects naturally with the Voice of the Customer, Voice of the Business and Voice of the Process.

  1. Defects: Incomplete bloods, documentation errors and access-related cannulation rework.
  2. Overproduction: Preparing or scheduling capacity before confirmed demand, creating unused slots.
  3. Waiting: Patients wait for chairs, observations, equipment, cannulation support, physician review or transport.
  4. Non-utilised talent: Experienced nurses spend time searching for supplies, chasing results or correcting preventable scheduling issues.
  5. Transportation: Patients, equipment and paperwork move unnecessarily between reception, treatment bays and review points.
  6. Inventory: Excess work in process includes unconfirmed referrals, incomplete records and patients waiting for final clearance.
  7. Motion: Staff walk to distant supply locations, printers, medication areas or shared documentation stations.
  8. Extra-processing: Duplicate blood-result checks, repeated data entry and multiple verbal confirmations of the same appointment.

The current performance signals are consistent with these wastes:

  • 6.2% of sessions cancelled or rescheduled on the day
  • 11% of patients arriving with incomplete bloods
  • 4.4% access-related rework
  • 410 nurse overtime hours per month
  • Approximately 71 treatments per month affected by on-the-day cancellation or rescheduling, calculated as 1,140 × 6.2%

In DMAIC terms, these observations belong across the Define, Measure and Analyse phases. The Analyse phase should use Pareto charts, process stratification, a box plot of arrival-to-exit time, and cause-and-effect analysis to identify root causes rather than treating every delay as an isolated event.

Future-State Build: Create Flow Around the Chair

The future-state map should preserve clinical safeguards while removing avoidable friction. All changes require appropriate clinical governance and formal approval; however, approval checkpoints should be designed with clear decision rights so governance supports flow rather than creating another queue.

The future state includes:

  • Pre-arrival checklist: Validate bloods, transport, access information and medication requirements 24–48 hours before treatment.
  • SMS and bloods validation: Send a standard reminder and escalate incomplete results before the patient arrives.
  • Staggered shift start times: Smooth arrival waves instead of releasing large groups into the same reception and assessment queue.
  • Standard work for chair turnover: Define the sequence, roles and time targets for disconnect, cleaning, equipment check and chair release.
  • Setup kits and a prime station: Place standard supplies together and separate machine priming from chair turnover where clinically appropriate.
  • Dedicated cannulation coach: Provide rapid support for access-related variation and coach staff toward consistent technique.
  • Visual chair-status board: Display chairs as occupied, disconnecting, cleaning, ready, allocated or requiring review.
  • Shift-start huddle: Review demand, access risks, incomplete bloods, staffing, transport constraints and expected exceptions.
  • Parallel processing: Complete documentation, bloods verification and chair preparation in parallel where safe, rather than sequentially.

Future-state flow design for dialysis chair utilisation

Current versus future-state metrics

The following targets are an improvement model for the project and should be validated against local baseline data, staffing, acuity and clinical policy.

Metric Current state 90-day future-state target
Arrival-to-exit time 6.8 hours 5.2 hours
Chair utilisation 71% 84%
Chair turnover 34 minutes 15 minutes
On-the-day cancellation/reschedule rate 6.2% 2.0%
Incomplete-blood rate 11% 3.0%
Shortfall treatments per month 71 23
Nurse overtime 410 hours/month 140 hours/month
Patient satisfaction 78% 90%
Indicative cost per treatment $312 $294

The future state does not shorten the clinically prescribed four-hour treatment. Instead, it reduces the non-treatment burden around it. That distinction is essential: value is defined by the patient’s safe treatment and experience, while waste is removed from the supporting flow.

90-Day Kaizen Sequence

A disciplined sequence prevents the centre from launching too many changes simultaneously.

Period Kaizen focus Owner Weekly cadence
Weeks 1–2 Confirm baseline, map current state and validate delay definitions Project Black Belt and nurse manager Two gemba observations and one data review
Weeks 3–4 Standard work for chair turnover Charge nurse and technician lead Daily timing audit; Friday review
Weeks 5–6 Pre-arrival checklist, SMS and bloods validation Scheduler and clinical administrator Monday exception list; Wednesday audit
Weeks 7–8 Staggered shift start times and arrival smoothing Operations manager Daily arrival heatmap; weekly adjustment
Weeks 9–10 Setup kits, prime station and supply 5S Technician lead Two rapid improvement events
Weeks 11–12 Dedicated cannulation coach and visual chair-status board Nurse educator and charge nurse Shift-start huddle every operating day
Weeks 13 Sustainment review and control plan Sponsor and project lead Weekly dashboard and 30-day audit plan

The control plan should track turnover time, on-time starts, cancellation rate, incomplete bloods, access rework, overtime, chair utilisation and satisfaction. An X-bar chart can monitor average turnover by shift, while a companion R chart can reveal whether variation is stable. If three or more shift groups are compared, ANOVA can test whether their average arrival-to-exit times differ significantly. Bartlett’s Test may be used first to assess whether group variances are sufficiently equal for that analysis.

Build Capability Beyond One Dialysis Centre

Value stream mapping is not a one-time drawing exercise. It is a practical bridge between Lean thinking, Six Sigma analysis, Agile experimentation and daily management. Agile-style weekly iterations allow teams to test one change, review data and refine the standard without waiting for a large annual redesign.

A Yellow Belt can support observation, data collection and daily huddles. A Green Belt can lead the DMAIC project, analyse variation and manage the future-state implementation. A Black Belt can integrate the work across multiple centres, mentor Green Belts and establish governance for sustained performance.

For more structured development, explore Lean Six Sigma online training, Green Belt training and Black Belt training. For additional healthcare process-improvement context, review the AHRQ workflow assessment resources.

Ninety-day Kaizen sequence for dialysis centre flow improvement

Start your Lean Six Sigma certification journey and learn to convert complex healthcare processes into measurable, safer and more reliable value streams.

Kaizen. Kai-Care. Kai-Done. ( Lean Six Sigma)

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