Applying Lean principles to create a high throughput mass COVID-19 vaccination site

Abstract

A high throughput COVID-19 vaccination site was created using Lean principles and tools. Mass-vaccination sites can achieve high output by creating a standard physical design for workspaces and standardised work protocols, and by timing each step in the vaccination process to create a value stream map that can identify and remove all wasteful steps. Reliability of the vaccination process can be assured by creating a visual checklist that monitors the individual steps as well as by building in second checks by downstream personnel. Finally, productivity can be closely monitored by recording the start and completion time for each vaccination and plotting run charts. With 78 personnel working efficiently and effectively together, a maximum throughput of 5024 injections over 10 hours was achieved. As compared with other published COVID-19 mass-vaccination sites, our site attained threefold–fourfold higher productivity. We share our approach to encourage others to reproduce our vaccination system.

Full text

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FromanMN, etal. BMJ Open Quality 2022;11:e001617. doi:10.1136/bmjoq-2021-001617
Open access
Applying Lean principles to create a
high throughput mass COVID- 19
vaccination site
Meghan N Froman,1 Matthew P Walser,1 Michael Lauzardo,1 Mark Graban,2
Frederick S Southwick 1
To cite: FromanMN,
WalserMP, LauzardoM, etal.
Applying Lean principles to
create a high throughput
mass COVID- 19 vaccination
site. BMJ Open Quality
2022;11:e001617. doi:10.1136/
bmjoq-2021-001617
►Additional supplemental
material is published online only.
To view, please visit the journal
online (http:// dx. doi. org/ 10.
1136/ bmjoq- 2021- 001617).
Received 19 July 2021
Accepted 15 January 2022
1Department of Medicine,
University of Florida College of
Medicine, Gainesville, Florida,
USA
2Lean Enterprise Institute,
Boston, Massachusetts, USA
Correspondence to
Dr Frederick S Southwick;
southf@ epi. u. edu
Quality improvement report
© Author(s) (or their
employer(s)) 2022. Re- use
permitted under CC BY- NC. No
commercial re- use. See rights
and permissions. Published by
BMJ.
ABSTRACT
A high throughput COVID- 19 vaccination site was created
using Lean principles and tools. Mass- vaccination sites
can achieve high output by creating a standard physical
design for workspaces and standardised work protocols,
and by timing each step in the vaccination process
to create a value stream map that can identify and
remove all wasteful steps. Reliability of the vaccination
process can be assured by creating a visual checklist
that monitors the individual steps as well as by building
in second checks by downstream personnel. Finally,
productivity can be closely monitored by recording the
start and completion time for each vaccination and
plotting run charts. With 78 personnel working efciently
and effectively together, a maximum throughput of 5024
injections over 10 hours was achieved. As compared with
other published COVID- 19 mass- vaccination sites, our
site attained threefold–fourfold higher productivity. We
share our approach to encourage others to reproduce our
vaccination system.
PROBLEM
The COVID- 19 pandemic continues in many
regions of the world because of low vaccina-
tion rates. As a consequence, new variants
continue to be generated that can partially
escape the vaccine and have prevented
countries from achieving and maintaining
herd immunity. The highly contagious delta
variant originated in India at a time when
the percentage of the population vaccinated
was only 10% and more recently the even
more contagious omicron variant emerged
in South Africa at a time when less than
30% of the population was vaccinated. Can
Lean manufacturing principles be applied
to improve the efficiency and effectiveness of
mass- vaccination sites to more rapidly achieve
vaccine- induced worldwide herd immunity
and to reduce the emergence of SARS- CoV- 2
variants?
BACKGROUND
The speed of COVID- 19 vaccination is a crit-
ical parameter for achieving herd immunity1
and mass- vaccinations sites were recently
highlighted as effective approach for
achieving this goal.2 One small country with
a unified system of healthcare delivery has
achieved high vaccination rates3; however,
detailed descriptions of their vaccina-
tion procedures have not been published.
Government websites also emphasised the
importance of mass- vaccination sites and
have provided suggestions for their struc-
ture.4 For example, the United States Centers
for Disease Control and Prevention (CDC)
recommends conducting ‘frequent time-
motion studies and staff utilisation reviews to
maximise staff roles’5; however, further details
are not provided. A UK government website
recommends drawing on the logistical exper-
tise of the armed forces, and quotes a Lieu-
tenant Lambert, a Logistics Sea Trainer: ‘As
advisor to the vaccination operation, (I have
engaged) various stakeholders to enable
information flow, understanding and early
identification of emerging issues. This has
included helping design an operational view
of the programme by identifying key perfor-
mance indicators to aid us in spotting poten-
tial problems and providing solutions in a
timely fashion’.6 While some are able to do
so, many local vaccination sites are unlikely to
be able to recruit military logistics or manu-
facturing experts to continually maximise
efficiency and effectiveness.
Given the limited resources and health-
care personnel in many regions of the world,
we strongly recommend that Lean princi-
ples7 and continual learning be applied to
create high throughput vaccination sites.
These approaches can be conveniently
learnt through massive open online courses
(MOOCs) that describe how Lean principles
can be applied to healthcare and are available
through Coursera and the English National
Health Service.8 9 We describe in detail a real-
world example of how we applied Lean prin-
ciples and tools to create a mass- vaccination
site in the hopes that others will emulate our
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2FromanMN, etal. BMJ Open Quality 2022;11:e001617. doi:10.1136/bmjoq-2021-001617
Open access
approach as mass vaccinations are conducted around the
world.
MEASUREMENT
The time of arrival at precheck- in and the time that vaccine
injection was completed were recorded for all recipi-
ents and the lead time calculated for each vaccinee (the
interval between arrival at precheck- in and vaccination
completion) and representative values from each station
were periodically entered into a cloud- based spreadsheet.
The number of vaccinations for each 10- hour session was
tabulated.
DESIGN: CREATION OF A MASS-VACCINATION SITE
On 5 April 2021, the State of Florida released COVID- 19
vaccines to all residents 16 years and older. The sudden
eligibility of over 52 000 University of Florida students
represented a major operational challenge. To create a
mass- vaccination site, we identified a 32 000 square foot
space in our football stadium, the Evans Champions
Club, designed a vaccinee flow pattern with 8 vaccination
stations (online supplemental figure S1) and created a
standardised work sheet for each individual work station
(figure 1) that defined the movement of each vaccinee
and the 5 individual steps or work cycles in the vaccina-
tion process: (1) precheck- in, (2) online check- in, (3) fill
out the consent form, (4) verify the consent form and (5)
vaccinate. To further clarify our procedures, a process
map was created that illustrated how these steps were
combined to achieve timely vaccinations (online supple-
mental figure S2).
STRATEGY
We next conducted a series of plan–do–study–adjust
(PDSA) cycles to maximise individual productivity, reduce
unnecessary motion and eliminate time delays. These
improvement cycles were performed on days 1–6 and the
resulting process improvements were implemented on
day 8. To save time, PDSA cycles were conducted simul-
taneously by those conducting each work cycle in the
vaccination process. Online supplemental table S1 lists
the individual PDSA cycles conducted during this period.
For example, initially, we had two precheck- in people for
each station; however, based on feedback following our
early sessions, we learnt that one person was idle half the
time. Therefore, we eliminated one precheck- in person
per station and found that there were no time delays for
the vaccinees. On creation of our value stream map (see
above), we realised that the critical step for assuring effi-
cient flow was the vaccination step. Our frontline observa-
tions revealed that some of our vaccinators were carrying
on prolonged conversations (3–5 min) with their patients
creating unnecessary bottlenecks. For our intervention,
we created a 60- second script for all vaccinators that
included a question about allergies to past vaccinations,
the arm preferred for their injection and a summary of
the potential short- term side effects of the vaccine (local
pain, influenza- like syndrome with possible muscle aches,
fatigue, headache, chills and fever) followed by advice
to seek medical attention if these side effects persisted
for over 72 hours. The script reduced excessive conver-
sations reducing vaccination times. We also conducted
multiple PDSAs to arrange the locations of each work
cycle within the vaccination station. We discovered that
keeping distances to the minimum dictated by infection
control practices (6 feet) minimised walk times reducing
wasted motion. On day 8, we implemented an improve-
ment bundle that included all of changes derived from
our PDSA learning cycles (see the Results section).
Because of the short time frame for the development
of our mass- vaccination site (1 week), involvement of
patients in the development of our site was not possible.
During registration and while being observed following
vaccination, patient comments were shared with two of
our authors (MNF and MPW) and patient suggestions for
improvement were incorporated into our PDSA cycles.
Time observation sheets recorded the five individual
work cycles six times for each workstation (online supple-
mental figure S3). An observer used a stopwatch to time
six individual subjects going through a vaccine station.
We measured walk times and the time spent to complete
(1) precheck- in, (2) online check- in, (3) filling out the
consent form, (4) verification of the form and (5) vacci-
nation. All times were entered on an Excel spreadsheet
and the mean time for each step or work cycle was calcu-
lated. Using these mean times, a value stream map was
constructed documenting a realistic ideal state for the
process (figure 2). The time required to fill out the
consent form was shortened by 2–3 min for those who had
filled out the online form before arrival (approximately
Figure 1 Standardised work sheet showing the individual
vaccine station lay out with the ve work areas, and vaccinee
movement. The diamond symbols mark the locations where
a quality check was performed and the cross symbols mark a
safety check. Each step or work cycle is numbered.
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one- fourth of vaccinees). Because the 5 areas were 6
feet apart, walk times were only 2–3 s. Reconstituting the
vaccine was performed by a pharmacist team as previously
described following the manufacturer’s instructions10 and
represented a separate process that was conducted in a
site adjacent to the vaccine stations (online supplemental
figure S1).
Vaccinations began on 5 April and occurred each
Monday, Wednesday, Friday and Saturday for 10 hours.
For the first week, all vaccinations were prescheduled by
online appointments, allowing an accurate estimate of
the vaccine demand for each day. As the appointments
began to decrease, we also accepted walk- ins, 150–200/
day. Our highest vaccine demand occurred during
the 1st week and consisted of 5000 appointments/day
(online supplemental table S2). To meet the demand of
5000 vaccinations over 10 hours, we calculated that the
maximum time for each vaccination needed to be 7.2 s
(36 000 s/5000=7.2 s). Our time observation sheet (online
supplemental figure S3) revealed the time required for
one vaccinator to complete one injection varied from
73 s to 138 s (mean: 97 s). To meet the 5000 vaccines
in 10- hour demand, we calculated that we would need
between 10 vaccinators and 19 vaccinators (73/7.2=10.1;
138/7.2=19.1). To assure we had an adequate number of
vaccinators, we chose to recruit 20 vaccinators per session
and set as their goal to inject one person every 144 s or
25 vaccinees/hour. To assure smooth work flow, all other
steps needed to take no longer than 144 s and as shown
on the time observation sheet (online supplemental
figure S3) and value stream map (figure 2): this condi-
tion was met.
Figure 2 Value stream map: a standard workow diagram that describes the work being done in each cycle, the expected
time to complete each work cycle and the percentage of the work that is of value. Consent forms lled out before arrival
enhance the value of step 3.
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To encourage all volunteers to follow a standardised
work protocol, each job was completely described
during morning orientation. Online supplemental table
S3 provides complete descriptions of the four key jobs
(precheck- in, online check- in, consent verifier and vacci-
nator). The precheck- in consisted of filling out a lami-
nated card that served as a visual control to monitor each
vaccinee’s progress (online supplemental figure S4). In
addition to the person’s last name and birthdate, the
time they arrived at the precheck- in table and time of
vaccination were transcribed on the laminated sheet, as
was the type of vaccine P for Pfizer, M for Moderna, 1
for first shot and 2 for second shot. A box was checked
when online registration was completed and once the
consent form was verified. The verifier then directed the
individual to one of the two vaccinators who reviewed the
allergy history, described possible early side effects from
the vaccine, prepared the designated right or left deltoid
with an alcohol wipe, injected 0.3 ccs of vaccine and
placed an adhesive bandage over the injection site. Indi-
viduals with a history of past allergic reactions were then
observed for 30 min and all others observed for 15 min
as recommended by the US CDC. After completing the
injection, the vaccinator entered the time the vaccine
was administered, and the time the observation period
would end on the laminated card, and finally, signed the
consent form.
The laminated cards were collected by an individual
designated as the ‘runner’ who entered the time of
precheck- in and the time of vaccination in a cloud- based
spreadsheet and then returned the cards back to the
precheck- in desk where the card was erased and reused.
The cloud- based shared spreadsheet was monitored real
time by an administrator. If one station was consistently
demonstrating delays, the administrator went to the site,
identified the sources of delay and solved the problem
with the team.
The runner was also responsible for transporting the
signed consent forms to the end- of- the- line inspection
station (online supplemental figure S1). At this site, forms
were inspected to assure that all parts of the form were
completed before delivery to the county health depart-
ment. Finally, the runners were responsible for continu-
ally monitoring vaccine supply and transporting prefilled
syringes from the pharmacy, replenishing the stock when
the number of syringes dropped below 5. One runner was
assigned to each station.
Other support personnel included ushers who directed
the vaccinees, that included one person in a golf cart
who transported those who had difficulty walking from
the adjacent parking lot to the vaccine site. The total
personnel required for each session was 78: 20 vaccina-
tors, 20 check- in personnel, 10 consent form verifiers, 8
runners, 6 ushers, 2 end- of- the line inspectors, 8 phar-
macists and 4 administrators. With the exception of the
administrators, all others were volunteers from the health
centre and/or the community.
RESULTS
The average time from precheck- in to receipt of vaccine
(lead time) varied from session to session. Following the
implementation of our set of improvements based on
multiple PDSA cycles, we observed a significant reduc-
tion in vaccination times as documented by a shift in the
run chart median vaccination lead time from 13.2 min to
9.2 min (figure 3). For days 26–40, we experienced some
difficulties recruiting volunteers and the presence of new
less experienced recruits during this time may explain
the wider variation of lead times. Additional PDSA cycles
combined with paid permanent personnel could help
reduce the amount of variation in the process and over
time achieve an ideal waste- free state.
By creating vaccine stations that minimised motion,
standardising job descriptions and using a visual control
(the laminated card) to monitor performance, we were
able to achieve a maximum daily output of 5046 vaccina-
tions (online supplemental table S2). From 5 April to 14
May, we vaccinated a total of 35 453 individuals. Although
our county represents only 1.2% of Florida’s population,
our vaccination site alone was able to perform 2% of the
total vaccinations in the state during this time period,
attesting to the effectiveness of our mass- vaccination site.
LESSONS AND LIMITATIONS
Multiple mass COVID- 19 vaccination sites have been
described in the medical literature4; however, few peer-
reviewed reports have included detailed logistics or
delivery performance measures. One modest- sized
site used a large conference room and 5 vaccinators to
perform 250–300 vaccinations/day. Vaccinations were
administered for 14 hours each day, therefore, each
vaccinator performed 4–5 injections/hour or less than
one quarter the output per vaccinator of our system.10 A
Figure 3 Run chart showing the median for the daily mean
vaccination lead time (the mean time from precheck- in to
vaccination) before and after implementation of bundle of
improvements (arrow).
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mass- vaccination site in San Diego took place in a 280 000
square foot parking lot and used 300 as compared with
our 78 personnel to deliver 5000 vaccines/day,11 our
approach achieving 3.4- fold higher productivity. Another
parking lot vaccination programme in Florida applied
PDSA cycles, but did not use value stream mapping to
achieve an average output of 8.6 vaccinations/vacci-
nator/hour.12 In Italy, vaccine stations were established in
a large open parking lot and achieved a similar output of
8 vaccinations/vaccinator/hour.13 A college in Montana
created a vaccination site for students and faculty and
conducted two 1- day sessions that vaccinated 807 and 776
individuals. This site achieved a maximum productivity
of 8.2 vaccinations/vaccinator/hour.14 These last three
vaccination programmes achieved comparable produc-
tivity levels that were one- third of the productivity of our
vaccine programme.
We used the work sheets downloaded at no cost from
the Coursera MOOC entitled ‘Fixing Healthcare Delivery
2.0 Advanced Lean’ to design and improve our mass-
vaccination site.8 The stardardised work sheet was used
to design the physical layout of our vaccination station
(figure 1), the time observation sheet to record the times
to complete the individual work cycles and walk times
(online supplemental figure S3), and a value stream map
to assess the value of each process and identify opportu-
nities for improvement8 15 (figure 2). For example, our
analysis revealed that filling out the consent form prior
to arrival at the vaccination site had the potential to
shorten the lead time by 2–3 min, which would increase
the number of vaccinations per hour by 20%–30%.
To assure that registration, consent forms and allergy
histories were accurate, error proofing was designed
into our system: precheck- in was verified by the online
check- in person, the vaccinees consent form was reviewed
by the verifier, allergy history confirmed by the vaccinator
and finally the end- of- the- line inspection for all consent
forms was conducted at the inspection desk prior to these
forms being sent to the health department.
Mass- vaccination sites are particularly suitable for the
application of Lean principles and the US Naval Academy
applied Lean principles to improve the efficiency of
annual vaccinations for 1200 new naval cadets reducing
vaccination lead times (time of check- in to receipt of
the vaccine) from 55 min to 11 min.16 Very recently, a
team from the NHS applied the lessons taught in their
Lean MOOC to improve vaccination lead times in a
small beta test involving 16 individuals.9 More recently,
this same team applied Lean principles to create a mass-
vaccination site that enabled 8 vaccinators to inject 1500
individuals/12- hour shift achieving an output of 15.6
vaccinations/vaccinator/hour.17 We have now applied
this same approach to deliver up to 5046 vaccines over 10
hours using 20 vaccinators achieving an individual output
of 25 injections/vaccinator/hour. Like the NHS team, we
have provided detailed descriptions of each improvement
step so that others inexperienced in Lean principles can
emulate our example.
A limitation of our project was the application of our
Lean improvement tools to a single vaccination site rather
than multiple sites. Second, we depended on volunteers
that often worked for only three–four sessions, a condition
that could compromise the consistent application of stan-
dardised work. However, the first 30 min of each session
consisted of a detailed orientation that included breakout
sessions for each individual job. The orientation instruc-
tors were a stable team of paid healthcentre employees
who were present for all the vaccine sessions, a condition
that maintained continuity and encouraged standardised
work. The impact of a single bundle of improvements
rather than multiple sequential improvement steps was
documented by a formal run chart. Because the semester
ended in mid- May, the time window was narrow for vacci-
nating a significant percentage of student body and
this time limitation required us to accelerate change
by combining multiple rapid PDSA cycles into a single
bundle of improvement interventions. Finally, because
times were entered by the runners, it is remotely possible
that they favoured entering shorter times; however, this
bias would be expected to have been present throughout
the study and, therefore, relative differences between
early, mid and late sessions should be equally impacted.
One of our authors (MG) is a renowned Lean expert who
did not participate in the mass- vaccination site design and
served as an objective referee to curb positive bias.
CONCLUSIONS
Our experience reveals that Lean tools can be applied to
mass- vaccination sites to achieve high output by creating a
standard physical design for workspaces, timing each step
in the vaccination process and creating a value stream
map to identify and remove all wasteful steps. When Lean
principles are fully implemented, experts estimate that
productivity can be increased by fourfold and compared
with other published COVID- 19 vaccination sites who did
not employ Lean principles, our output per individual was
threefold–fourfold higher. Reliability can also be assured
by creating visual checklists that monitor the successful
completion of each individual step.18 These principles
can and should be applied throughout our healthcare
systems to reduce waste and improve reliability.
To effectively achieve herd immunity in each region of
the world, we encourage other mass- vaccination sites to
follow our example of applying Lean principles to maxi-
mise efficiency and productivity to accelerate achieve-
ment of the ‘last mile’.”19
Twitter Frederick S Southwick @FS_Southwick
Acknowledgements We would like to thank the many volunteers who generously
gave their time to help our community achieve herd immunity.
Contributors FSS wrote the main draft, lled out the time observation sheets,
created the standardised work sheet and value stream map. MG reviewed
the material and made multiple suggestions for improvement and edited the
manuscript. MNF, MPW and ML designed the original vaccine centre and applied
plan–do–study–adjust cycles to continually improve the processes. They made
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Open access
suggestions for improvement of the manuscript and approved the nal paper. FSS
was responsible for overall content as the guarantor.
Funding The authors have not declared a specic grant for this research from any
funding agency in the public, commercial or not- for- prot sectors.
Competing interests FSS is a paid infectious diseases consultant for Toyota of
North America.
Patient consent for publication Not required.
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement All data relevant to the study are included in the
article or uploaded as supplementary information.
Supplemental material This content has been supplied by the author(s). It has
not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been
peer- reviewed. Any opinions or recommendations discussed are solely those
of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and
responsibility arising from any reliance placed on the content. Where the content
includes any translated material, BMJ does not warrant the accuracy and reliability
of the translations (including but not limited to local regulations, clinical guidelines,
terminology, drug names and drug dosages), and is not responsible for any error
and/or omissions arising from translation and adaptation or otherwise.
Open access This is an open access article distributed in accordance with the
Creative Commons Attribution Non Commercial (CC BY- NC 4.0) license, which
permits others to distribute, remix, adapt, build upon this work non- commercially,
and license their derivative works on different terms, provided the original work is
properly cited, appropriate credit is given, any changes made indicated, and the use
is non- commercial. See:http://creativecommons.org/licenses/by-nc/4.0/.
ORCID iD
Frederick SSouthwick http://orcid.org/0000-0003-4941-8240
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