Clinic Patient Flow Study Final Report Presentation Rebekah Andrews Kaywee lian Kristen Ydoate Team 6 December 13 th 2016 Introduction Client Clinic At Livonia Center for Specialty Care ID: 572810
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Slide1
Urology at Livonia Center for Specialty Care
Clinic Patient Flow StudyFinal Report Presentation
Rebekah Andrews |
Kaywee
lian
| Kristen
Ydoate
Team 6
December 13
th
,
2016Slide2
Introduction
Client: Clinic At Livonia Center for Specialty CareDirector: John Wei, MD Manager: Karen Moore Professor of Urology Ambulatory Care Manager Intermediate
Coordinators: Process and Operations Analysis Office
Mary Duck Kyle Worley
Industrial Engineer Expert
Lean
Coach Industrial EngineerSlide3
Urology Clinic at Livonia Provides General Urologic Care
841-5
Medical Assistants
Registered Nurses
Providers, depending on the scheduleSlide4
General Process Flow for Consultation Appointment/Nurse VisitSlide5
General Patient FlowSlide6
Patient Stratification by Patient/Visit Type, and Patient Diagnosis
Urology Clinic Patient
Patient/Visit Type
Patient Diagnosis
New Patient
Return Visit
Consultation
Procedural
Kidney Stones
Benign Prostatic
Hyperplasia
Urinary Tract Infection
Incontinence
Erectile Dysfunction
Elevated Prostate-Specific Antigen
Hematuria
Others
Nurse VisitSlide7
Decision Tree for Patient Scheduling Time
Clinic utilizes a pre-arrival scheduling approachSlide8
Current Process
Flow Has Several IssuesLack of quantifiable data
Unknown areas of waste
Disparity between scheduled and actual timeSlide9
Goals and Objectives
Background: Clinic wants to understand the patient flow process better through collecting information on timing of each step, and where waste resides in the current process.Goals:
Identify Wastes and Opportunities for Improvement
Quantify Current Patient FlowSlide10
Methods
Combined Time Study FormObservations
Interviews
Surveys
MiChart
Data
Literature ReviewSlide11
Observations
Preliminary Observations with Clinic Staff September 13th and September 20th 1:00 PM - 4:00 PMUnsupervised Clinic Observations September 22nd – October 20th Total of 18 man hours Shadowing of Providers
October 27
th
Three different providers were shadowed Slide12
Observations
Facility Observations
Understanding of
Clinic Operations and Flow
Witnessed
Known Bottlenecks
Observed Clinic CultureSlide13
Literature Search
Methods Time Study Process
Sub-steps
Data Collection Form design
Current State Visualization
Value Stream Map
Swim Lane Diagram
Recommendations
Process Standardization
Team HuddlesSlide14
MiChart Data
Data Pulled – November 2nd 2015 – October 31st 2016 7500 entries detailing patient check-in and check-out timeCategorized into 7 Diagnosis Types
1. Stones
2. Benign Prostatic Hyperplasia
3. Urinary Tract Infections and Cysts
4. Incontinence
5. Erectile Dysfunction
6. Elevated PSA
7. HematuriaSlide15
MiChart Data
Data inputted into Minitab *Results discussed in data analysis
All patient identifiers were removed
Total time spent in clinic was analyzed by
patient diagnosisSlide16
Time Study and Process Diagnostic Form
PilotPatients (time study form)
Staff (process diagnostics form)
Patients opposition to cooperate
Staff cannot locate process form
Feedback
Reiterate
Combined all data collection into one form
Only require staff participationSlide17
Time Study and Process Diagnostic Form
Pilot Phase: October 21st - October 25th
Date
Count
% Time Study Complete
% Process Form Complete
% Complete
October 21st
13
46%
38%
8%
October 24th
26
50%
46%
27%
October 25th
17
24%
12%
6%
Data Collection
: October
21st
- October
25th
14 work days
The
team collected a total of 594 samples.
Slide18
Time Study and Process Diagnostic Form
Collects the following fields:Patient stratification
Provider last Name
Gender
Time of each staff interaction
Planned and unplanned activity performed for each staff interaction
Waste observed
Time Study FormSlide19
Time Study and Process Diagnostic Form
Inputted into Microsoft Excel and Minitab *Results discussed in data analysis
Stratified
by:
Visit Type
Patient Type
Analyzed to identify:
Specific encounter times
Types of waste occurringSlide20
Interviews
Initial Interviews – September 13th and September 20th Ambulatory Care Manager and Administration Associate Supervisor Understand the patient flow process Determine what metrics to collect Determine how to design the data collection
Secondary Interviews–
September 22
nd
– October 20
th
MA’s, RN’s, PA’s, and Doctors
Explain trends revealed from data analysis Help to shape recommendations Slide21
Interviews
Administrative ManagerAdministration Associate Supervisor
MA’s, RN’s, PA’s, and Doctors
Provided big
picture of clinic
processes and common
areas of
waste
Introduced key staff members
Shaped recommendations and offered explanation of data trendsSlide22
Staff Surveys
Google Forms Survey sent on November 8th – 4 Responses
Estimate Indirect Patient Care Time
Detail Consequences from patient build-upSlide23
Data Analysis
Value Stream MappingPareto Chart of Wastes
MiChart
AnalysisSlide24
Value Stream Mapping
Value Stream Maps
4
New Patients
Return Visit Consultations
Return Visit Procedural
Nurse VisitsSlide25
Value Stream Mapping
Return Procedural Patient Flow Most Inefficient
Value
Stream Map Summary Table Stratified by Patient and Visit Type
Source: Time Studies Data from 11/2/15 - 10/31/16, N = 594Slide26
Value Stream Mapping
Monday, Tuesday, and Wednesdays Experience Longer MA and Provider (Mondays and Tuesday) Wait TimesValue stream map totals across day of the week
Source: Time study data 10/21/16 - 11/15/16, N = 513
Slide27
Value Stream Mapping
Excess Wait Time for MA, Nurse, and ProviderValue Stream Map Summary Table for Steps in the Patient Flow Process in MinutesSource: Time Studies Data from 11/2/15 - 10/31/16, N = 548Slide28
MiChart Analysis
Patients with elevated PSA spend the longest time in the clinicInterviews reveal a possible explanation is elevated PSA patients are often sensitive conversations and involve teaching
MiChart
data shows that 6 is significantly higher than 5, 3 and 1
Source:
Michart
Data from 11/2/15 - 10/31/16, N = 7500; 1 = Stones, 2 = Benign Prostatic Hyperplasia, 3 = Urinary Tract Infection and Cysts. 4 = Incontinence, 5 = Erectile Dysfunction, 6 = Elevated PSA, 7 = HematuriaSlide29
Pareto Chart
Forms of waste identified from analyzing time study and process diagnostic form data are:
Wait times exceeding 5 minutes
Actual times exceeding allotted times
>2 provider interactions
Added-
on proceduresSlide30
Pareto Chart
Figure 6: Pareto chart of the frequency of waste within the clinic.
Source: Time study data 10/21/16 - 11/15/16; N = 594
Patients spend
>60
minutes in the clinic
>5 minute wait
for MA
> 5
minute
wait for provider
Top
3
Forms of WasteSlide31
Waste #1: Patients Spend >60 Minutes in the Clinic
54%of patients spend > 60 minutes at the clinic
patients who spend > 60 minutes,
spend
up to 90 minutes at the clinic
Median
=
61
minutes
Mean
= 67.04 minutes
Data Summary
60
%Slide32
Waste #1: Patients Spend >60 Minutes in the Clinic
Stratified by Provider – Large variation between providers
Average
time in clinic by provider
Source: Time study data 10/21/16 - 11/15/16; N = 240
Percent
of patient visits greater than 60 minutes by provider
Source: Time study data 10/21/16 - 11/15/16; N = 240Slide33
Waste #2: >5 Minute Wait for MA
49%of wait times are
over 10 minutes
Median
= 8 minutes
Mean
= 11.2 minutes
Data Summary
o
f patients experience
> 5 minute waits for
MA
41
%Slide34
Waste #2: >5 Minute Wait for MA
Stratified by Time of DayPercent
of MA wait times greater than 5 minutes across time of day
Source: Time study data 10/21/16 - 11/15/16; N = 296
Excess Wait Times for MA at start of day and during lunch breaksSlide35
Waste #3: >5 Minute Wait for Provider
Median = 3 minutesMean = 8.1 minutesData Summary
69%
w
aited over 15 minutes*
waited over 10 minutes*
*of patients who had to wait over 5 minutes
45
%Slide36
Waste #3: >5 Minute Wait for Provider
Stratified by Provider - Large variation between providersAverage
wait time by provider
Source: Time study data 10/21/16 - 11/15/16; N = 79
Percentage
of time providers are late to appointment
(Source: Time study data 10/21/16 - 11/15/16; N = 79)Slide37
Waste #3: >5 Minute Wait for Provider
Scheduled 15 Minutes Appointment Insufficient for All Patient Care Tasks for a Single PatientProvider indirect and direct care time by provider, 15 minute appointmentSource: Time study data 10/21/16 - 11/15/16; N = 79
Provider
indirect and direct care time by provider, 30 minute appointment
Source: Time study data 10/21/16 - 11/15/16; N = 79Slide38
Waste #3: >5 Minute Wait for Provider
Non-standardized Handling of Indirect Patient Care and Add-on Procedures another Source of Variability
P
roviders complete required tasks:
Before seeing a patient
While seeing a patient
During breaks in their schedule
P
roviders accept add-on procedures:
Perform immediately after consult
Reschedule different appointment
Slide39
Waste #4: Prep time exceeds scheduled prep time by > 5 minutes
Patients are scheduled for either a 15 minute or 30 minute prep time
15 Minute
30 Minute
Median
= 32 minutes
Mean
= 37.6 minutes
Median
= 22 minutes
Mean
= 29.8 minutes
Data SummarySlide40
Waste #4: Prep time exceeds scheduled prep time by > 5 minutes
Half of Prep Time for Both 15 Minutes and 30 Minutes is Spent WaitingPercentage of Time Patient Spends Waiting versus with a Staff Member
Source: Time Study Data 10/21/16 - 11/15/16; N = 350Slide41
Waste #4: Prep time exceeds scheduled prep time by > 5 minutes
Wait Time Longer for RV for 15 Minute Prep Time but Longer for NP for 30 Minute Prep Time
NP takes staff 1.5 – 2 minutes more to prep in terms of actual staff interaction time
Time
Spent With Staff for 15 Minute Prep, Broken Down into RV and NP
Source: Time Study Data 10/21/16 - 11/15/16; N = 244Slide42
Waste #4: Prep time exceeds scheduled prep time by > 5 minutes
Wait Time Longer for RV for 15 Minute Prep Time but Longer for NP for 30 Minute Prep Time
Opposite trend is apparent
New patients have a 38 minute prep time on average while return visits are under 20 minutes
Time
Spent With Staff for 30 Minute Prep, Broken Down into RV and NP
Source: Time Study Data 10/21/16 - 11/15/16; N = 106Slide43
Waste #4: Prep time exceeds scheduled prep time by > 5 minutes
Patients Arriving for Procedure Usually Scheduled for 15 Minutes Prep Time but Prep Time Varies by Procedure TypeActual Prep Time by Procedure Performed Source: Time Study Data 10/21/16 -
11/15/16
; N = 106Slide44
Waste #4: Prep time exceeds scheduled prep time by > 5 minutes
Stratified by Time of Day
–
Total prep time varies throughout the day while time spent with staff is consistent
Actual
15 Min Prep Time by Time of Day
Source: Time Study Data 10/21/16 - 11/15/16; N = 244
Actual
30 Min Prep Time by Time of Day
Source: Time Study Data 10/21/16 - 11/15/16; N = 106Slide45
Waste #5: Patients arrive to clinic > 5 minutes late
of patients were lateof those were over 10 minutes late
Data Summary
28
%
70
%
Median
=
12
minutes
Mean
=
15.9
minutesSlide46
Waste #5: Patients arrive to clinic > 5 minutes late
Kidney Stones and UTI Patients had Highest Percentage of Late PatientsPercentage
of late patient by stratification type
Source: Time study data 10/21/16 - 11/15/16; N = 594
Interviews reveal kidney stone patients undergo a radiology screening before going into urologySlide47
Waste #5: Patients arrive to clinic > 5 minutes late
Lack of Standardized Management of Late Patients
May
lead to high variability in patient time in clinic
No rules, up to
provider discretionSlide48
Summary of Conclusions
Value Stream Mapping
MiChart
Data
Pareto Chart
RV
procedurals
spend the longest time in
clinic
Mondays
, Tuesdays, and Wednesdays see a higher average wait time for
MA’s
Longest
wait time occur while waiting for Nurse, MA for vitals, and Providers, respectively
RV
p
atients
with elevated PSA diagnosis spend the longest time in clinic
Top
3
Wastes:
Patients spend >60 minutes in the
clinic
>5 minute wait for
MA
> 5 minute wait for providerSlide49
Summary of Conclusions
54 % spend > 60 minutesLarge variations by providerBig opportunity for improvement (goal <60)#1: Patients spend >60 minutes in the clinic
#2
: >5 minute wait for MA
49% wait > 5
minutes
Large outliers
High wait times at the start of the day and lunch hours
#3
: > 5 minute wait for provider
Large outliers
Variation between providers
15 minute allotted time is exceeded when indirect care is considered
No standardization for indirect care or add-on proceduresSlide50
Summary of Conclusions
#4: Prep time exceeds scheduled prep time by > 5 minutes15 minute mean and median exceed30 minute mean and median
exceed
– but
closer
Over
50% of total prep time is spent waiting for
staff
Varies
by procedure but most are scheduled as 15 minutes
#5:
Patients arrive to clinic > 5 minutes late
27.5% of patients were late, 70% of those late were more than 10 minutes
late
Patients
with kidney stones and UTI have the highest percentage of late
patients
No
standardization in dealing with late patientsSlide51
Recommendations
RV Procedural Patients Integration of TasksCurrently there are 6 staff interactionsCut down number of interactions by integrating tasks
Ex. MA’s are trained to obtain consent for procedures
Parallelization
Currently clinic is conducted serially
Conduct tasks concurrently to reduce wait times
Ex. Nurse obtains consent while MA finishes vitals and interviewSlide52
Recommendations
Longer MA Wait Times on Mondays, Tuesdays and Wednesdays
Revise
Staffing
L
evels
Cope with greater amount of patients
Reassign Providers
Move providers to less busy days
Smoothen out demand for MA’sSlide53
Recommendations
Longer Nurse Wait Times
Assign Nurses to Roles
Versus
Providers
One role to assist any providers (obtain consent and nurse teaching)
Other role is nurse visitsSlide54
Recommendations
PSA Patient Spend Longer Times at the Clinic
Conduct a Follow-up Study
Clearly identify why these patients spend more time in clinic
May need to change scheduling of PSA patientsSlide55
Recommendations
Excess Wait Times for MA’s
Begin
Appointments
at 8:30 AM
Versus
8:00 AM
Allow more time for MA’s to prepare exams rooms
Increase Staffing at the Start of the Day
Assign some MA’s to clinic set-up and others to attend to patients
Examine
Assignment
of MA to
Patients
for Vitals
Determine if there are any inefficiencies in the current MA assignment processSlide56
Recommendations
Excess Wait Times for Providers
Increase 15 Minute
A
ppointment
T
imes
Increase by increments of 5 minutes
Evaluate wait-times as consultation time increases
Standardize Indirect Patient Care Tasks
Complete immediately after each patient is seen
Reduce variability between providers
Standardize Add-on Procedures
Schedule patients for add-on procedures during breaks in a provider’s schedule – not immediately after consultSlide57
Recommendations
Actual Prep Time Exceeds Scheduled Prep Time
Implement recommendations to reduce MA and Nurse Wait Times
Wait time constitutes ~50% of prep time
Study effects of recommendations on prep time
Increase prep time
Increase by increments of 5 minutes
Evaluate Prep times
as consultation time increases
Conduct Study on Prep Time by Procedure
Insufficient data for team to provide accurate estimations
Enough variation is apparent for a studySlide58
Recommendations
Late Patients
Arrange for Scheduled Radiology Scans for Kidney Stone Patients
Avoid walk-ins due to variability
Standardize Handling of
Late Patients
See patients at the scheduled pre-arrival and appointment time, rather than when they arrive (early or late)
If a patient is late, they should be seen at the next available breakSlide59
Project Goals
Goals: Identify Wastes and Opportunities for Improvement
Quantify Current Patient FlowSlide60
Expected Impact
Describe the current patient flow process and where waste resides
Provide
clear visualization of the overall patient process
Guide the clinic in future process improvement effortsSlide61
Thank you!
Questions?Slide62
Appendix
Value Stream Maps
Staff Survey Results
ReferencesSlide63
Value Stream Map: New PatientsSlide64
Value Stream Map: Return Visit ConsultationSlide65
Value Stream Map: Return Visit ProceduralSlide66
Value Stream Map: Nurse VisitSlide67
Waste #2: MA Wait Times
Frequency chart of MA wait times
Source
: Time study data 10/21/16 - 11/15/16; N = 519
Slide68
Waste #3: Provider Wait Times
Wait time for provider when providers were late to the appointmentSource: Time Study Data 10/21/16 - 11/15/16, N = 79Slide69
Waste #5: Late Patients
Histogram of Patient Late Times for Patients That Arrived Past Pre-Arrival Time
Source: Time Study Data 10/21/16 - 11/15/16; N = 63Slide70
Staff SurveysSlide71
Staff SurveysSlide72
References
[1] Matt Bovberg et al., “Analyzing Patient Flow and Process Waste in the General Thoracic Surgery Clinic”, IOE 481 Senior Design Projects, Winter 2014, April 2014 [2] Altarium Institute, “Applying Lean to Improve the Patient Visit Process at Three Federally Qualified Health Centers”
, July
2011
[3]
Lori
Rutman
et al.,
“Improving Patient Flow Using Lean Methodology: an Emergency
Medicine Experience”
, Springer International Publishing, October 28th 2015.[4] B. T. Denton and D. T. Brian, Handbook of healthcare operations management: Methods and applications. New York, NY
: Springer New York, 2013, ch. 3, sec. 2.[5] L. Jiang and R. E. Giachetti, "A queueing network model to analyze the impact of parallelization of care on
patient cycle
time," Health Care Management Science, vol. 11, no. 3, pp. 248–261, Dec. 2007
.
[6]
A
. M. Association, "How to handle patients who are always late," 2009. [Online]. Available:
http
://
www.amednews.com
/article/20090413/business/304139998/5/. Accessed: Dec. 6, 2016
.
[
7] R. R. Lummus, R. J. Vokurka, and B. Rodeghiero, "Improving quality through value stream mapping: A
case study of a physician’s clinic," Total Quality Management & Business Excellence, vol. 17, no. 8, pp. 1063–1075, Oct. 2006.