Designing the Future, Engineering Reality: Prototyping in the Emergency Department - Starnino, Dosi, Vignoli

ServDes 2016 – Copenhagen, Denmark !
DESIGNING THE FUTURE,
ENGINEERING REALITY
Prototying in the Emergency Department
Clio Dosi, Antonio Starnino, Matteo Vignoli
University of Reggio Emilia and Modena, Reggio Emilia, Italy

Body Level One!
Design innovation branch of the University of
Reggio Emilia and Modena, Department of
Management engineering.
SECTORS:
•  Healthcare
•  Food technology
•  Embedded design thinking in organizations
•  DT Education
DESIGN THINKING UNIMORE!

EVALUATIVE SERVICE PROTOTYPING
IN AN EMERGENCY DEPARTMENT
Our case study explores the role of
service prototyping to test
complex service systems.
In particular, we explore the role
of evaluative holistic prototyping.

SERVICE PROTOTYPING:
HOLISTIC AND SINGLE
SINGLE
PROTOTYPE! HOLISTIC!
Several touchpoints are
tested at the same time.!
Single artefacts or
interactions!
We observe
interaction with
touchpoint !
We observe
emerging human
behavioral patterns

PROBLEM: OVERCROWDING IN THE ED!
Crowding occurs when
no inpatient beds are
available in the
hospital. Over time it
can lead to stressful
environments and staff
burnout, and in worst
cases mortality.!

KEY ISSUES WE UNCOVERED
Unpredictable access of patients
Ambulatory as a bottleneck
Aging demographic

SOLUTION IN A NUTSHELL
!
Vertical
(Experimental Zone)!
Horizontal
(Critical care area)!

SERVICE OUTCOMES!
Increase in amount
of patients!
Percentage of patients
satisfied with their
experience!
Average waiting time
reduction (of low
complexity patients)!
Average length of stay
time reduction ( of low
complexity patients)!
186
patients!
206
patients!
75.35
min!
120.4
min!
164
min!
211.15!
38%!
22%!
10%!

ARCISPEDALE SANTA MARIA NUOVA (REGGIO EMILIA)!
70,000+
Patients a year!

ARCISPEDALE SANTA MARIA NUOVA (REGGIO EMILIA)!
Last restructured in 1990’s
One of the first hospitals to have triage in Italy!

KEY ISSUES WITH THE ASMN EMERGENCY DEPARTMENT
‘Old’ non flexible structure that creates a lot of ‘dead time’.
Increasing waiting time, and patients
Burnout amongst staff especially amongst the nurses.
1!
2!
3!

STAKEHOLDERS
UNIMORE Facilitators (Service designer + Management engineer)
15 person working group (composed of nurses, doctors and
management of varying seniorities)
100+ staff of the emergency department (doctors, nurses, aid
nurses)
Internal Stakeholders (Hospital administration, engineering
department)
Emergency department patients (totalling about 70,000 a year)

PROJECT PROCESS
Redefine the
problem!
Need finding and
benchmarking!
Brainstorming!
Test!
Prototyping!
Client onboard
from the very
beginning that we
design with
prototypes,
understanding it
as a nessecary step

ETHNOGRAPHIC AND
SECONDARY RESEARCH
Our research took place over a
period of 4 months with the
aim of understanding the
‘human’ needs and included:
•  70+ hours of direct observation
•  14+ interviews with internal
stakeholders
•  5 patients interviews
•  Extensive comparative analysis of
similar cases.

ORGANIZATIONAL RESEARCH!
“As doctors sometimes we don’t
even know who else was on shift
with you.”
“Sometimes there is this
pressing by older nurses even
when it's not necessary”

PATIENT CENTERED RESEARCH!
“I felt as if they were cold to me,
they saw me crying and did
nothing.”

KEY NEEDS
Know whats happening around you
Lack of collaboration between doctors
Maintain concentration.
High number of low acuity patients make it difficult for triage nurses
to concentrate
Feel taken care of (Patients)
Anxiety and distress caused by lack of staff /patient contact

PROTOTYPES
Area for low complexity patients
An open space with the staff and waiting patients in the same room
Family room
Room dedicated to family members while patients are treated
Process nurse
A nurse that looks over the entire ED and manages internal flow.

DESIGN PHASES
Scenario building
Creating a base service experience to build from
Co-design and planning
Working with internal and external stakeholders to define the service
and data anlysis to determine its size.
Departmental communication
Communicating to gather feedback, buy-in and manage expectations

BENCHMARKING
A Better A&E
by Lloyd Peterson
Rapid Assessment Zone
by the Jewish General
Hospital Montreal
!
a & e!

CODESIGN AND PLANNING (INTERNAL)!

FINAL CONCEPT
Open space ambulatory that places
waiting patients and doctors
together in a more flexible and
dynamic treatment environment,
reducing dead time, and giving
patients a more guided process.
!
Features:
• 2 Doctor nurse teams instead of one’
• Comfortable waiting area for those waiting for exams or simple treatment
• A ‘kanban’ process making it easier for doctors to track and see patients.

FINAL CONCEPT
!
DISCHARGE PHASE
Where patients would
wait as they were
awaiting discharge.!
TREATMENT AND EXAM PHASE
Where patients would wait to be
seen by the doctor!
DOCTOR VISITING PHASE:
Where patients would wait
to be seen by the doctor!
FASE 1FASE 2FASE 3
Area di presa
in carico del
paziente e visita
Area di eventuale
trattamento e attesa
risultati diagnostici
Area di
dimissione

EVALUATIVE PROTOTYPING DECISIONS

HOW ARE WE GOING TO TEST OUR PROTOTYPE?

PROBLEMS INHERENT WITH SERVICE DESIGN
Intangibility of services as design material
Inconsistency in service delivery
Authenticity of behaviours and contexts
Validity of the evaluation environment
Conceptualising Prototypes in Service Design, Blomkvist, 2010

We converted the old
waiting area into…

Phase 1 Phase 2
PHASES IN REALITY

How to run the holistic testing, today?
READY TO START TESTING

HOW TO RUN HOLISTIC PROTOTYPE TODAY?
!
The objective was to test whether this solution would
shorten the Length of Stay and the Waiting Time, while
providing a comfortable solution for patients and staff.
At the same time, we needed to adjust the
prototype to the needs that emerged while
testing this new solution.
We settled on a 5 week long continuous testing
(22nd April - 31st May 2015).

LIVE PROTOTYPE AS AN ITERATIVE CYCLE
!
Observation!
Weekly
meetings!
Changes
communicated!
We planned a feedback
strategy to be able to
understand all issues and
emerging practices that
arose during the testing,
adjusting the prototype
accordingly.

LIVE PROTOTYPE WEEK BY WEEK
!
•  We identified
eventual critical
disrupted elements
•  General Impressions!
OBSERVATIONANDDATA
COLLECTED!
ITERATIVEDESIGN
ADJUSTMENTS!
Week 1!
We adjusted the elements
that could make the
experiment fail!

WEEK 1: CRITICAL ELEMENTS Doctors try to hide themselves behind
dividers or columns. We reposition the
dividers inside triage.

!
•  Identified additional
critical points
•  First ‘hacks’ emerge
as well as common
behaviours!
OBSERVATIONANDDATA
COLLECTED!
ITERATIVEDESIGN
ADJUSTMENTS!
Week 1! Week 2!
We adjust the smallest
critical points
We support or
suppress the hacks or
behaviours that
emerged!
eventual critical
disrupted elements
that could make the
experiment fail!

WEEK 2: FIRST HACKS “More than rarely we need the patient to be
undressed. One visiting box is not enough: we need
two boxes for the area.”

WEEK 2: FIRST HACKS Creating new tools

WEEK 2: DIALOGUE Shared responsibility putting effort on doctors as
much as nurses
“After awhile staying up on your
feet all day is tiring.” – Doctor
“My legs are a lot more relaxed
now that I don’t have to walk back
and forth all day.” - Nurse

WEEK 2: DIALOGUE Limit complaining, more open dialogue
“It’s a lot easier now to
ask for advice and
collaborate with my
collegues.” - Doctor

!
OBSERVATIONANDDATA
COLLECTED!
ITERATIVEDESIGN
ADJUSTMENTS!
Week 1! Week 2! Week 3!
We suggest eventual best
practices!
critical points
as well as common
behaviours!
critical points
We support or
behaviours that
emerged!
eventual critical
disrupted elements
that could make the
experiment fail!
•  After getting used to the
new service, the first
improvement
suggestions emerge
•  Shared best practices
emerge.
•  First data analysis!

WEEK 3: DOCTOR TO PATIENT Emerging best practice: Save time and
deliver better feedback if you go directly to
patients.

WEEK 3: SPACE CHANGES Common behavior. “There’s no need for phase
3” & We start sharing the first data results

!
•  Smaller changes
implemented
•  Data is analyzed!
OBSERVATIONANDDATA
COLLECTED!
ITERATIVEDESIGN
ADJUSTMENTS!
Week 1! Week 2! Week 3! Week 4!
Live prototype closed
and learnings applied!
•  After getting used to the
new service, the first
improvement
suggestions emerge
•  Best practices emerge.
•  First service data
collected!
We suggest eventual best
practices!
critical points
as well as common
behaviours!
critical points
We support or
behaviours that
emerged!
eventual critical
disrupted elements
that could make the
experiment fail!

WEEK 4 & 5: NOISE Attempt to reduce noise levels

FINAL PRESENTATION TO DEPARTMENT AFTER
!
1.  Showed the results,
with photos and
documentation.
2.  Shared an updated
blueprint from the
engineering
department
3.  Got final feedback
from everyone, with
shared decisions.

OUR RESULTS AFTER 5 WEEKS
!
Stop the experiment due to its temporary nature the noise
levels were too high, requiring the need for final structural
implementation.
Lowered waiting time and length of stay overall while
increasing patient satisfaction.
Implemented more private spaces (boxes) into the final
blueprint of the space – potentially saving thousands of
dollars in restructuring costs.
1!
2!
3!

OUR LIVE PROTOTYPING PRINCIPLES
à Experience prototyping, role playing, design games, … were not enough
à Feedback from 150 employees, with very different expertise and capabilities
Authenticity of behaviours and contexts.
à How can I gain authentic feedback notwithstanding the fact it is a prototype?
Validity of the evaluation environment.
à How can we ensure the prototype recreates real world conditions?
2!
1!
3!
4!

Inconsistency in service delivery.
Testing parts is not like testing holistically.
Conceive your prototyping as a learning experience for
the organisation (and for you !), not as a material
artefact.
1!

Don’t get scared if you see the
organization losing part of its
competences in the first weeks,
and be ready to restore them.
“In bananas” - The first 2 weeks are
the most expensive in terms of
energy and stress.”
Inconsistency in
service delivery
1!

Be ready to reassure users that
new behaviors could emerge and,
if needed, they will be structured
and officialised.
“I can’t manage to stay behind
everything, including the teams.”
1!

How can I gain feedback from 110 employees,
considering that everyone of them is going to
change his mind at least twice while he
experiences the prototype, and that the
prototype is lively changing?
2!

Identify your Networking Angels (NA),
•  NAs are from your the groups that participated into the design process,
because they need to know why design choices were made as they are
•  NAs need to cover each profession, so that doctors can answer to doctors,
nurses to nurses, aid nurses to aid nurses.
•  Among each professional cathegory, you need to have at least a senior
professional.
2!

Coach your Networking Angels. Those actors are your
referents on the field, and answer to colleagues’ questions/
feedbacks (sometimes aggressive questioning!).
•  Prepare them to: Encourage, receive and look for positive feedback
•  Bring the general perspective: Explain ‘why’ some choices were made
•  Support them, they put their face in the project and are going to be overloaded by
expectations “No, listen, I am going to have a heart attack !”!
2!

Choose a testing length so that:
•  Everyone can test it at least 3 times “Until, it’s a one
week simulation that’s ok, but I won’t accept that
forever”
•  You gain data significance “Two weeks are not enough”
3!

•  Make the decisional process on the prototype as
transparent as possible. It has to be clear to the whole
organization why changes in the prototypes are made.
•  Live test in a safe and ordered way. The entire staff has
to know how and who to contact in case of questions for
change, and weekly report are disclosed to everybody and
summarized by Networking Angels.
3!

The validity of the prototypes depends
on how similar the test and
implementation contexts are.
4!

Do not surrender to short cuts to make your testing life easier:
•  Do not change shifts to include only the smartest people during the test. We
asked for extra time of an expert staff to help in case of coaching.
•  Do not ask for extra resources or only put the smartest people to test the
prototype if you are not sure you are going to have them
•  Do not let assumptions derail testing. “This is not a very big town, people
want to decide, relatives will never accept to be divided
4!

THANK YOU!
Clio.dosi@unimore.it, matteo.vignoli@unimore.it,
antoniostarnino@gmail.com
!

Designing the Future, Engineering Reality: Prototyping in the Emergency Department - Starnino, Dosi, Vignoli

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