EP7w, Infusion Center Project.pdf
Infusion Center Throughput – Phase 1
Green Belt: Ranjeeta Kumar, MBA, Luanne Sims, RN, FNP &
Dawn Shelton
Champion: Alice Issai
Date March 21, 2012
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EP7w, Infusion Center Project.pdf
DEFINE PHASE
What is the problem?
LSS: Infusion Center Throughput
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DEFINE
Problem Statement
Wait time is a significant problem impacting Infusion
Centers (IC) nationwide
What is our problem?
Patients arrived for scheduled infusion treatment incur an
average of 24 minute wait before being roomed
(from the time patient arrives to the time patient is roomed)
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DEFINE
Problem Statement
How do we know it is a problem?
Survey conducted from 11 April to 15 April with a sample size of 326 patient
visits. Data demonstrated 10 minutes to 3 hours wait time before patient is
roomed
27% of sample data indicated that the wait resulted from absence or lack of
necessary documents that enable treatment to begin
•
‘Lack of Patient Readiness’
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DEFINE
Problem Statement
What “pain” does it cause? (impact to patient and/or bottom line)
Waiting creates:
• - Lack of unit control and patient flow
– - Patients arrive at unscheduled times
 - Patients and staff alike experience an increase level of anxiety and stress
• - Loss of confidence in UCI’s ability to offer good patient care
• - Loss of future patient referral when patient satisfaction diminishes
–
- UCI commitment to patient satisfaction - DSRIP is a significant component of Healthcare reform
• - Loss of revenue
– - Lack of throughput, increase in overhead (staff over-time, lack of utilization of unit, etc)
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DEFINE
Project Charter
EP7w, Infusion Center Project.pdf
Project Name: Infusion Center Patient Flow
Optimization – Phase 1
Champion: Alice Issai, COO
Belt: Ranjeeta Kumar, MBA & Luanne Sims, RN
Master Black Belt: Henry Alvarez & Laura Winner
Problem Statement:
Project Goal:
Infusion Center pts incur an average of 24 minute wait from the time
patient arrives to the time patient is roomed, resulting in poor
patient/staff satisfaction, negative impact on patient referral process
(loss in revenue)
Reduce number of defects that are causing the ~24 min delay by
25%. Total soft savings - $105K
(Xs = absence of chart, orders, labs, and consents)
Project Y / Path-Y:
Scope:
Project Y= Total Time of Arrival for Infusion Center Appointment to
Discharged
Reduce wait time for chemotherapy patients in the infusion center.
Path Y1 = Patient arrival time to time patient is roomed
Exclusions: 1st time chemo, IM, IV, SQ injections, hydrations,
symptom management/acuity, same day appointment, walk-ins
(unscheduled) and non-oncology patients
Path Y2 = Pharmacy Time required to prepare medications
Path Y3 = Wait time from end of preparation to start infusion
Path Y4 = How long Patient is in chair receiving infusion
Team Members:
Claudette Bettis, RN
Gema De La Cruz
Nancy Eagan, RN
Daniel Hoang, Pharm.D.
Ranjeeta Kumar, MBA
Marie Polito, RN
Benefits:
Tara Seery, MD
Luanne Sims, RN
Dawn Shelton
Julie Smith, RN
Raja Zeitany, Pharm D
Ensure patient safety
Increase patient, staff and physician satisfaction
Increase volume, capacity and revenue
Increase likelihood to recommend by patients
Timeline:
Define/Measure
Analyze
Improve/Control
March – April 2011
May – Dec 2011
Dec – March 2012
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DEFINE
Why is this important?
• Health Care is dedicated to quality and perfection of
outcomes
– We have been entrusted with Oncology patients lives
• Understanding what is important to a patient is
critical to achieving quality
• Stable processes minimizes variations in outcomes
• Design is optimal when we listen to our customers
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DEFINE
Why is this important? - VOC
Voice of the Customer (VOC)
5 questions over 5 days
44 total responses
Assumptions
-
Patients were dissatisfied with IC experience
Patients preferred to see Oncologist same day
Patients preferred to get labs drawn same day
IC staff did not see the value of informing patients of delay
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EP7w, Infusion Center Project.pdf
DEFINE
Why is this important?
VOC Results - used to defined Critical to Quality
Would you recommend this infusion center to your friends and family?
- 89% of patients would refer UCI IC to Friends and Family
Do you prefer to see your oncologist on the same day as your infusion appt. even if it
can cause delays in getting your treatment?
- 50% of patient would not see their Oncologist on the same day
of their IC appointment if it reduces wait time
How valuable would it be for you if you could have your blood work and other tests
taken one or two days before your appointment in order to prevent any delays during
your treatment?
- 65% of patients would get labs drawn 48 hrs prior to IC
appointment to reduce waiting time
VOC graphs are in appendices
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EP7w, Infusion Center Project.pdf
DEFINE
Why is this important?
VOC Results - used to defined Critical to Quality
Would you have your blood work and other tests done several days before your
appointment in order to shorten the length of time you spend in the infusion center on
the day of treatment?
- 64% of patients would get labs drawn 48 hrs prior to IC
appointment to reduce waiting time
If you encounter a delay while waiting for your treatment, how important is it to your
to be given a reason for the delay?
- 64% of patients would get labs drawn 48 hrs prior to IC
appointment to reduce waiting time
VOC graphs are in appendices
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EP7w, Infusion Center Project.pdf
DEFINE
Waiting is an Epidemic
Problem!!
Perception of ineffective care are
directly proportional to a patients
wait time
Survey of 200 patients suggested
wait time affects perception of
quality, satisfaction and likeability,
as well as likelihood of
recommendation and repeat visits
* HealthMarkQ, 2005: 23(2);69-87
Visited multiple IC – UCSD, UCLA,
UCSF and City of Hope
All are experiencing wait issues
(no labs, change in pts acuity, etc)
Article in appendices
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EP7w, Infusion Center Project.pdf
DEFINE
Why is this important?
Why this, why now? (“Burning Platform”)
•
The pain of continuing with the “status quo” process of unchecked charts, missing
orders and consents was creating a burden for Infusion Center staff and increasing
delay in patient start times.
•
Domino effect from late morning starts created afternoon bottleneck effect for the
remainder of the day which increased the patient’s expected wait time.
•
Average wait time was 24 minutes after patient registration to room assignment
due to incomplete required medical record data.
•
A new patient flow was needed for the unit to function efficiently because the
current process became more inefficient as patient volume increased.
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DEFINE
Why is this important?
What will happen if we don’t fix this?
•
Inconsistent wait times creates anxiety for patients and the health care team.
•
Prolonged delays for medical records, physician orders, labs or consents impacts
customer service ratings and recommendation for future referrals.
•
Patient acuity becomes the driver of the process instead of the patients having
proper scheduling and avoiding delays of treatment.
•
Maximum patient capacity can not be fully achieved in the Infusion Center due to
our current process/design.
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EP7w, Infusion Center Project.pdf
DEFINE
SIPOC
S
I
P
O
C
Suppliers
Inputs
Processes
Outputs
Customers
1st Step
•
Physicians
•
Orders
•
Registration Info
•
Patients
•
Patient Family/
Friends
•
Physicians
•
Pharmacy
•
Staff
•
Clinic
•
EVS
•
Nutrition
•
Revenue Audit
Patient arrives
•
Pharmacy
•
Medical Records
•
Drug Information
•
RN
•
Drugs
•
Chemical Data
•
Medical Records
•
Consent
•
Billing - Encounters
•
Authorization Unit
•
Labs
•
Scheduler
•
Chair/Room
•
Patient Information
•
Staffing
•
Medical Supplies
•
EVS
•
Nutrition
Patient is roomed
Infusion prepared
by pharmacy
Infusion treatment
Patient is
discharged
Last Step
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DEFINE
Value Stream Map
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DEFINE
Swim Lanes
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DEFINE
Stakeholder Analysis
Understand the influences that may ultimately
determine project success
Purpose:
Step 1
Step 2
Stakeholder(s)
Identify all stakeholders (refer to SIPOC diagram)
Seek to understand their perspective/interests
Step 3
Determine the risk or benefit to the project
Step 4
Leverage the learning to develop a strategy for
project success
Level of Influence
Interest in project 2
Current Level of Support
Likert 1 - 5
Strategy
High = 3 Medium = 2 Low = 1
Gain = 3 Neutral = 2 Loss = 1
Very supportive = 5 Slightly Supportive =4 Neutral =
3 Slightly Resistant =2 Very Resistant = 1
Name and Title
Dr. Sender, Clinical Director
could they determine project success?
High
do they perceive a gain or loss?
Gain
how supportive are they currently?
Very supportive
how can we engage their support?
Dr. Seery, Medical Director
Alice Issai, COO
High
High
Gain
Gain
Very supportive
Very supportive
schedule weekly meeting to discuss barriers
Cancer Center, Medicine
High
Loss, believe process belongs to infusion center
Slightly Resistant
Schedule meetings with managers and staff
Pharmacy
Medium
Loss, believe all problems are operational
Neutral
Meet with managers
Cancer Center, Neuro
High
Loss, believe process belongs to infusion center
Slightly Resistant
Schedule meetings with managers and staff
Cancer Center, GynOnc
High
Loss, believe process belongs to infusion center
Slightly Resistant
Schedule meetings with managers and staff
Infusion Center RNs
Medium
Gain, eliminating muda (waste) will enable happier staff
with less room for error
Very supportive
Engage staff by providing status and results of
project
Medical Records
Low
Neutral, want to see improvement in charts being
returned
Neutral
Meet with MR manager
Scheduler
Authorization Unit
Low
Low
Neutral
Gain
Very supportive
Very supportive
Meet with scheduler to understand barriers. Meet
with Quest
Meet with unit
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EP7w, Infusion Center Project.pdf
DEFINE
Early Waste Identification DOMOWIT
Defects
• Incomplete medical records
• Chemotherapy order missing
• Consents and laboratory result not in chart
Overprocessing
• Re-writing lost chemotherapy orders
• Repeating labs and obtaining consents
• Providing customer service recovery efforts
• Double/triple chart check review
• Double check of schedule
Motion
• Poor design – excessive walking
• Poor flow
• Charts moving from clinic to infusion center
• Movement between RN and pharmacy
• Movement between registration and patient room
• Supplies removed from unit
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EP7w, Infusion Center Project.pdf
DEFINE
Early Waste Identification DOMOWIT
Over
production
Waiting
• Re-adjusting and evaluating patient schedule and nurse assignments
• Re-assignment of patients
• Contact clinic for missing items
• Calling MD/Fellows for signature
• Chart arrival from clinic (bldg 23) to Infusion Center (Douglas Hospital)
• Arrival for chemo orders, labs, & consents
• Receipt of chemotherapy drugs
• Pharmacy drug production flow for same day/research patients
• Waiting for patients to be discharged
• Waiting for lab results
• Waiting for MD/Fellow to answer questions
• Wait for Nurse practitioner for symptom management
• Wait for MA to take patient to be roomed and vital
• Wait for RN to evaluate patient
• Clinic waiting for IC scheduler to schedule patient
• Clinic waiting for IC Nurse manager to return call
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DEFINE
Early Waste Identification DOMOWIT
• Patients in lobby
• Excess chemotherapy drug (patient evaluated and sent home)
Inventory
Transportation
• Paper movement – charts, labs, orders, etc
• Moving patients from hallway to bed/chair
• Transporting medical records
• Transporting patients from clinic (bldg 23) to Infusion Center (Douglas Hospital)
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MEASURE PHASE
What are the causes?
LSS: Infusion Center Throughput
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EP7w, Infusion Center Project.pdf
MEASURE
Baseline Data for Y
Data was collected on individual
oncological patients. Data is
comprised of a sample size of
326 patient visits from 11 April
to 15 April
In order to reduce the time
measurement variation the data
was collected using server time
tide to all computers
Data was collected via a time
study. Time study form was
created to capture time for each
step of an infusion visit process
Time study collection tool in appendices
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MEASURE
Baseline Data for Y
• Project Y is the ‘Total time from Arrival time for infusion center appointment to discharge’
– Multiple Path Ys indentified within the process
– Phase 1 focus on Path Y1 = Patient arrival time to time patient is roomed
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MEASURE
Normality
• Graphical summary of
patients actual arrival time
to their scheduled appt
Early
Late
• Understand arrival
patterns of IC patients
• On average our patients
arrived ~14 min late
paste
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MEASURE
Normality
Interpretation of Graphical Summary
Patient arrived vs. Patient scheduled appointment
Graph to look at patients arrival pattern
P-value is < .005.
Data set is not behaving normally, therefore data is non-normal
Non-normal data is expected when using ‘time’ as your data set approaches 0
(Time data in this case usually forms a weibull distribution)
With 95% confidence we can state that on avg. patients arrive 8.5 -20 mins
late to an appointment
Used data outcome to assess how to educate patients
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MEASURE
Normality
• Data distribution of actual
patient arrival time to
actual roomed time
• Showed significant outliers
• On average the process
took 24 mins to get patient
roomed
paste
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EP7w, Infusion Center Project.pdf
Normality
Interpretation of Graphical Summary
Patient Arrived vs. Patient roomed
P-value is < .005
Data set is not behaving normally, therefore data is non-normal
Non-normal data is expected when using ‘time’ as data set approaches 0
(Time data in this case usually forms a weibull distribution)
With 95% confidence we can state that on avg. it took 20-26.5 mins for a patient to
get roomed
Outliers helped identify ‘Patient Readiness’ issues
paste
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EP7w, Infusion Center Project.pdf
MEASURE
Capability
• Capability goal is to room a
patient in 15 mins or less
(Reflects UCI MC goal of
rooming patient within 15 mins)
• DPMO expected overall
performance is 625,191
• Plenty of opportunity for
improvement
paste
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EP7w, Infusion Center Project.pdf
MEASURE
Stability
• Process is beyond control
limits
• Upper limits = 15 mins
• Lower limits = 0 mins
• Process is extremely
unstable
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EP7w, Infusion Center Project.pdf
MEASURE
Baseline Process Map
NVA wait time is created by defects
before patients are in the chair
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MEASURE
Process Flow
• Majority of Non Value Added wait is found
between the time patient arrive to the time
patient is roomed
• A separate process flow was developed to
understand the steps the IC goes through
when necessary documents are missing
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MEASURE
Process Flow
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MEASURE
Measure – Ishikawa Diagram
ALL potential X’s …
Infusion Center Throughput Project- Phase 1: Fishbone Diagram
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MEASURE
Filter X’s
C & E Matrix in appendices
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MEASURE
Sequence of Events
Total annual cost for daily chart check review for six missing;
- Charts
- Labs
- Consents
- Orders
$105,853.11
Sequence of Events in appendices
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EP7w, Infusion Center Project.pdf
MEASURE
Measure
Data highlighted significant defects (Xs) via time study
- Missing medical records
- Missing or outdated lab results
- Missing or incomplete MD orders
- Missing patient consent
Additional data was collected to validate assumed Xs
Data is comprised of a sample size of 85 (excluding chart checks) 513
defects from 13 June to 21 June
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MEASURE
Measure
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MEASURE
Measure – Pareto Charts
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MEASURE
Measure – Pareto Charts
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EP7w, Infusion Center Project.pdf
MEASURE
Measure – Pareto Charts
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EP7w, Infusion Center Project.pdf
MEASURE
Measure
Spaghetti Diagram – data comprised of
1 day (2 shifts)
- 1st shift = 1 RN (Fast-track), 2 RN, 1 MA
- 2nd Shift = 1 RN, 1 MA
Spaghetti illustrated following in the GEMBA
OVER PROCESSING
MOTION
TRANSPORTATION
OVER-PRODUCTION
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MEASURE
Spaghetti Diagram
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MEASURE
Spaghetti Diagram
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MEASURE
Spaghetti Diagram
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ANALYZE PHASE
What is the root cause?
LSS: Infusion Center Throughput
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ANALYZE
Analyze
• Analyzed data using following tools:
– 5-Why’s
• To determine root cause
• To rule out non-value added steps
– Fault-Tree
• Identify potential causes of a problem
– 5S
• Streamline the process
– Benefit and Effort Matrix
• Prioritized the DOMOWIT
– Pareto chart check
• Impact of missing documents on infusion center
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EP7w, Infusion Center Project.pdf
ANALYZE
Analyze 5-Why’s
Why?
Medical records and required documents are missing on the day of
the Infusion treatment
Why?
No one is reviewing Infusion center roster the day before tx to
prepare charts (required documents)
Why?
Clinic RN is not held accountable to ensue charts are reviewed day
before their patients tx
Project Y
Infusion Center appointments
are delayed due to incomplete
medical records
Why?
There is no standardize process for chart check review on the
day before tx
Why?
Issue has not been identified by Infusion Center as a
cause for delay
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EP7w, Infusion Center Project.pdf
ANALYZE
Analyze Fault - Tree
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ANALYZE
Benefit & Effort Matrix
Benefit & Effort Matrix in appendices
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ANALYZE
Analyze – 5S
Sort
Create 3 colored labeled bins to separate the medical records to
easily identify what is missing
Straightened
Re-organize layout of bed/chairs to organize flow
Organize medical records by terminal digit when preparing
charts for next day tx
Scrub
Clean up medical records and infusion center to make room for
new colored bins
Standardize
Create standardized clinical teams assigned to new pods within
new layout
Create procedure to notify clinic manager if chart check process
is not being followed
Sustain
Daily page reminders to nursing staff that charts are ready to be
reviewed in medical record room in clinic
Daily report to track missing items by MD/RN to monitor
compliance
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Analyze – Chart check by Clinic
• Based on the collected chart check data:
– HemOnc represented the highest volume of
defects (missing charts, no labs, no consents, no
orders)
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Analyze – Chart check by Clinic
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ANALYZE
Analyze
HemOnc couldn’t find the charts. We identify missing chart locations
Data collected 14 June to 21 June.
Sample size of 85 defects
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EP7w, Infusion Center Project.pdf
ANALYZE
Analyze
Impact on Infusion Center if these Xs are missing
No Charts
No Labs
No Orders
No Consents
No reference
documentation
Unauthorized lab
draws – loss of rev.
Patient safety
Lack of confidence
in continuity of care
Patient cancelled –
loss of revenue
Delay in care
Rx delay
Patient trust is
compromised
Loss of confidence
Patient safety
Impact to patient
flow/delay
Failure to follow
COPE
Negative customer
service
Lack of confidence
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EP7w, Infusion Center Project.pdf
IMPROVE PHASE
Trial Interventions
LSS: Infusion Center Throughput
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IMPROVE
Improve Plan
Improve plan in appendices
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IMPROVE
Improve
Created clinic RN chart check review process
– Kanban (3 colored bins)
• Green
– Compliant = Current orders/labs/consents in chart
• Yellow
– Non-compliant = missing labs ONLY
• Red
– Non-compliant = missing orders/labs/consents
– Red bin will contain missing chart list
Improvement doc in appendices
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IMPROVE
Improve
•Developed educational
handout for clinic
• Helpful hints for IC
patients
•Highlight key services at
the IC
Educational Handout in appendices
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IMPROVE
Improve
• Reorganized IC layout
• Created 3 teams
– Teams consist of 3 RNs and
1 MA
• Increases ability to cross
cover
Revised layout in appendices
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IMPROVE
Improve
Spaghetti Diagram – data comprised of
1 day (2 shifts)
- 1st shift = 1 RN, 1 MA
- 2nd Shift = 1 RN, 1 MA
Minimized distance and movement
• Eliminated wasted steps
• Facilitate one-piece flow to pharmacy and front desk
• Improve communication
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IMPROVE
Improve - Spaghetti
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IMPROVE
Improve - Spaghetti
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IMPROVE
Improve
Staff comments ….
Revised layout in appendices
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IMPROVE
Results/Benefits
Quality
 Increased Patient Safety by allowing double checks (layout)
 Reduction in rework/defects by having clinic RN review chart to ensure
proper documentation is in the IC before patient’s scheduled
appointment
Efficiency
 Reduced wait time by creating a process to ensure all documents are
in place before patient’s schedule
 Increase capacity by starting patients as scheduled in Quest
 Increased throughput by starting infusions on time
Financial
 Increased revenue by maximizing utilization
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CONTROL PHASE
Establish and follow up
LSS: Infusion Center Throughput
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CONTROL
Final Capability
Initial capability: 10.54% defects
Final capability: ONLY 0.81% defects
Attribute Capability Plan in appendices
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CONTROL
Control Plan
Control Plan in appendices
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Control- Poka-Yoke
BEST
• Elimination: Eliminate possibility of error
– All chemo consents are now scanned into EMR
• Facilitation: Make distinctions more obvious
– Created colored kanbans to identify items needing
attention
• Detection: Identified defects before further
processing occurs
– Implemented chart check process 24 hrs before
appointment to identify defects in advance to decrease
delay of infusion start time
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Appendices
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
Voice of the Customer Results
The Oncology Report article
Time Study Tool
Graphical Summary – Pt arrival to pt schedule
Graphical Summary – Pt arrival to pt roomed
Process Capability – Pt arrival to pt roomed
Stability – Pt arrival to pt roomed
Cause & Effect Matrix
Sequence of Events
Benefit & Effort Matrix
Improvement Plan
Improvement Documentation - Kanban
Education Handout
Revised Layout
Capability by Attribute Data
Control Plan
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