IMPROVING INPATIENT DISCHARGE PROCESS TO REDUCE
READMISSION
Vanda Ametlli; Industrial & Systems Engineering, Wayne State University, Detroit, Michigan
Abstract
The cost of a preventable readmission is to a
hospital is estimated to be $7200. If a hospital
has 100 preventable readmissions in a year, it
incurs the loss of $720,000. Crittenton Hospital
Medical Center is a 290- acute bed healthcare
facility serving communities in Oakland,
Macomb and Lapeer counties in Michigan. The
hospital houses a Process Engineering
Department aimed at improving patient
experience through process improvement
projects. In Winter 2010,
the hospital
supported an interdisciplinary team of fifteen
members were assigned with the task of
finding solutions to reduce readmission rate in
order to provide clinical excellence for the
patient but avoid cost related penalties for
treating a readmitted patient with a similar
diagnosis. The team used Lean Six Sigma
methodology to reduce readmissions by
scheduling follow-up appointments for
patients, improving cycle time through better
communication cues among the discharge team
and increasing discharge completeness through
enhancements of the electronic medical record
system.
Introduction
Medicare Payment Advisory Commission
(MEDPAC) estimated that nearly 18% of
Medicare patients are readmitted within 30
days of discharge (Greenwald). Many
hospitals are or have already attempted to
improve their discharge process with the
expected
outcome
of
improving
readmission. The need to “re-engineer” the
discharge process has a two-fold reason; one
reason is to reduce discharge time for
patient in order to open up capacity for
patients coming with Emergency Room, and
other patients that need the resources of an
inpatient floor. Discharge process is also
looked at in terms of improving the quality
of discharge in order to reduce
readmissions. To identify a solution to
reduce readmissions at CHMC, an
interdisciplinary process improvement team
composted of nurses, social workers,
information systems project manager,
medical specialists under the guidance of
performance improvement specialists was
formed to identify improvements in order to
reduce readmission rate. Medicare defines a
patient readmission as “a part of consecutive
hospital admissions to the same hospital
where the time between discharge from the
first hospitalization and admission for the
second hospitalization was less than 30
days”. Current healthcare reform changes
have forced hospitals to review readmission
rate in order to be receive the most financial
benefit out of lowering the readmission rate
while improving patient care. According to
healthcare reform documents it is estimated
that “Hospitals with high rates of
readmission will be paid less if patients are
readmitted to the hospital within the same
30-day period saving $26 billion over 10
years”. National Health Care Reform is also a
reason why many hospitals are tackling
their discharge process. Improving the
current discharge process will ultimately
lead to a decreased rate of readmissions that
positively affects patient care and
Crittenton’s hospital financial viability. As
mentioned many hospital tackle the issue of
rehospitalization, however there is no
standard formula that will guarantee
decreased readmission. Different hospitals
have different solutions that align with their
strategic objectives and patient population.
The State of Michigan during 2007 and
2008, the best in class readmission rate for
Medicare patients was at 10% while the
hospital’s Medicare readmission rate was
21% as seen by the black line in Figure
1.
as quality indicators has identified measures
should be completed upon discharge to ensure
patient safety.
Project Objectives
The purpose of this project was to identify a
complete and efficient patient discharge
process while meeting core measure
requirements to reduce readmissions and
improve patient outcomes. To meet efficiency
and completeness requirements the team
defined the following metrics as project
deliverables:

Figure 1: Medicare Readmission Rate for 2009


To identify a solution to reduce
readmissions at CHMC, an interdisciplinary
process improvement team composed of
nurses, social workers, information systems
project manager, medical specialists under
the guidance of performance improvement
specialists was formed to identify
improvements in order to reduce
readmission rate.
Problem
A readmission can be defined as three separate
definitions
for
preventable
patients,
ameliorable patients and non-preventable
patients who might encounter unexpected
adverse events. Research has shown that 20 to
30 percent of adverse events following
instructions are preventable. Severity of
ameliorable patients can be reduced by 30% if
corrective measures were put in place in an
effective manner. In addition to the
readmission rate, the Center for Medicare and
Medicaid (CMS) Core Measurers which serve
Identify elements of a complete
discharge that meet core measures
requirements while improving patient
outcomes
Improve process inefficiencies
throughout discharge process to reduce
variability in discharge cycle time
Reduce readmissions while improving
patient care provided in Medical and
Surgical Units.
Methodology
Industrial Engineering Applications
This process improvement project was
completed using a mix of Improvement and
Change tools. The project utilized Lean Six
Sigma methodology along with Change
Acceleration tools. Through utilization of
Lean, the team would remove non-value steps
to the process. Application of Six Sigma
allowed statistically driven decisions to address
variations. Change Acceleration Tools (CAP)
assisted in process change implementation. The
discharge process is a very interdisciplinary
process. Physicians, nurses, clerks, physician
assistants, social workers and case managers all
have a stake in the outcome of the process. The
WorkOut session enhanced problem solving
from front line staff such as nurses and clerks.
The right mix of tools from each methodology
allowed the team to implement improvements
that provided the highest quality patient care
experience.
Different tools from different methodologies
were used by the project relied heavily on
following the path of a Six Sigma project. The
course of the project was a four month time
period. Each month, the team attended a oneday workshop where they were educated on all
the different tools that could help with their
project.
Team members also got the
opportunity to work on sample exercises to
better help with understanding of the topics.
The tools used in each phase of the Six Sigma
process are displayed in Figure 2.
Date
Phase
readmission rate of 21% for Medicare patients
was used for the project as well. No analysis
was completed on the readmission rate itself,
since there are many factors within it that
might
impact
readmission
such
as
completeness of a discharge.
Completeness of Discharge
The team identified six measures that made a
discharge “complete”. The hypothesis made
was that if a discharge is complete then patient
is less likely to return as readmit with the same
Tools Used
January
11th
Define
Threat vs. Opportunity Matrix, Stakeholder Analysis, SIPOC, Value
Stream Mapping, Process Mapping, Voice of Customer
January
12th
Measure Process Targets, Operational Definitions, Measurement System
Analysis, Data Sources Identification, Baseline Performance
Feb 9th
Analyze
Fishbone Diagram, Why/Why/Why Diagram, Waste Walk
March 9th
Improve Standard Operating Procedure, Failure Mode and Effects Analysis
April 13th
Control
Control Charts, Recognition Plan
April 30th
Team Final Presentation
Figure 2: Six Sigma Project Timeline of Tools
Data Analysis
Project data analysis was divided up in three
components:
1. Readmission Rate
2. Completeness of Discharge
3. Discharge Cycle Time
Readmission Rate
The readmission rate for Medicare patient was
provided by St. Pepper’s report. The baseline
diagnosis. The six elements were identified as
(1) Activity Level, (2) Diet Activity (3)
Follow-up Appointment (4) When to call
doctor or go to Emergency (5) Patient
Medication List Signed (6) Disease Specific
Education. Discharge elements were chosen on
their ability to meet Core Measures guidelines
and to allow for a safe discharge. For a patient
to have a complete discharge, it would mean
that all elements would be found in the patient
chart. Operational definitions of what a ‘Yes”
consisted for each elements were provided to
the data collector. The analysis completed on
the completeness of discharge on readmitted
patients found that “64% of November 2009
readmitted patients did not have a complete
discharge”. To further understand the elements
that needed to be reviewed by with greater
attention, a Pareto analysis on the elements was
completed. Figure 3 displays the Pareto
Analysis of 2009 readmitted patients based on
the element of not meeting the operational
definition.
doctor in 2 weeks”. This can be a very
frustrating expression to a patient that might
have more than one physician. In addition, the
patient might be aware of what physician to
see. The last element viewed in more detail
was the disease specific education. There was a
lack
of
disease
specific
education
documentation throughout patient’s length of
stay. Disease specific education can be very
beneficial to a patient that is at risk at being
readmit for the same diagnosis. It is a
preventive step that can assure the patient does
not get admitted. However, providing a patient
with a brochure alone or advocating for good
health choices might not be sufficient.
Follow-up Appointments
Figure 3: Pareto Analysis of Discharge Completeness
The Pareto analysis displayed disease specific
education, activity level, diet level and followup appointment as the key categories as not
meeting the core measure. In addition to the
statistical analysis, other elements were viewed
such as “Did the patient have a bed order and
when was it discounted”? Our analysis showed
that 48% of all Emergency Department
Admissions have an automatic bed ordered
when patient was transferred. This was a delay
on discharge day if a therapist was needed once
the discharge icon was put up. The other
element, which was viewed in more detail, was
the
information
regarding
“follow-up
appointments”. During the analysis, it was
found that 66% of the patient charts only
contained information such as “follow-up with
To understand the type of follow-up
appointment that the patient was given, chart
audits again took place. The follow-up
appointment chart
audit
focused
on
determining the quality of follow-up
appointment information that the patient was
given. The metrics measured to determine
follow-up appointment focused on how much
information
regarding
physician
name
provided, specialty of physician and timeframe
of when to visit the doctor. A general followup appointment note was defined as “follow-up
in two weeks”.
Discharge Cycle Time
The discharge cycle time was defined as the
physician order as start and end as patient
leaving the hospital. The physician order was
either electronic or handwritten. A handwritten
order had to be placed in the computer system
by the clerk to indicate discharge to the nurses
and social workers. A value stream map was
created to indicate inefficiencies occurring
from the cycle time. The baseline total process
time for discharge was found to be 194.24
minutes or around three hours in a half. In
addition to a very high cycle time, there was a
lot of variation in the discharge system. The
standard deviation was found to be at 137.20
minutes. The discharge process was found to
run at a 1.6 six-sigma level. A good process
runs at 6 six-sigma level, which allowed for
many improvement opportunities. Process
capability analysis on the baseline discharge
process was completed as shown in Figure
4.
Figure 4: Discharge Process Capability
discharge for physician to indicate upon
entering their discharge order.
3. Schedule follow-up appointments for
patients prior to their discharge to
improve
quality
of
follow-up
appointments
but
also
reduce
readmission rate. The implementation
was based that a patient with a
scheduled appointment is more likely to
follow up with their primary care
physician or specialist rather then
providing information such as “followup in two weeks”.
4. Nurses were provided with the ability to
enter patient appointment-scheduling
preference at their patient needs
adult assessment.
5. Implemented a standard procedure for
scheduling follow-up appointments.
6. Implemented a standard procedure for
after doctors’ office hours to schedule
patient appointments.
Process Improvements
7. Implemented a 24-hour continuous bed
rest evaluation to evaluate patient’s
action to reduce delays caused by
therapist consultations.
Through brainstorming sessions and using the
voice of the customer, which is not only the
patients but also the nurses and the physicians,
improvements that turned into an
implementation plan were focused at:
8. Improved communication between
interdisciplinary discharge team by
notifying social workers and case
mangers and unit clerks of patient’s
discharge order.
1. Improving Disease Specific Education
by implementing a 24-hour continuous
reminder to remind nurses to provide
patient with disease specific education.
2. Provide electronic submission of
patient’s activity and diet level, which
would be printed in their discharge
instructions by creating a field at
9. Created a consultant sign-off upon
completion in order to improve
communication across discharge time.
All the improvements listed impacted one
or more of the main three discharge
components.
Conclusions
The team developed a project control plan to
sustain changes and to measure changes in
process metrics. The four process metrics
tracked by team were:
1. Percentage of Appointment Scheduling
2. Discharge Cycle Time
3. Discharge Completeness
Recommendations
4. Readmission Rate
Due to the high request of Information
Systems changes needed to implement
follow-up appointment scheduling, the pilot
run began November 29th and available
data has not yet made available. The
discharge cycle time greatly improved from
the baseline data from 194 minutes to 162
minutes. At the same time, variation in
cycle time also decreased.
Discharge
completeness improved from 64% patients
not having a complete discharge to 30%
patients having a complete discharge.
As Figure 6 demonstrates, the discharge
completeness non-compliant elements greatly
reduced. Disease specific education is the only
element that displayed as having the highest
frequency of non-compliance. The next area,
which validates the importance of discharge in
reducing readmissions, is the readmission
rate.
Figure
6:
Implementation
Discharge
Completeness
black line, which is correlated with the
Crittentons’s readmission rate, shows a
decreasing trend in readmission rate for
Medicare patients. The readmission rate
decreased from 21.0% to 16.3%.
The
improvement is significant when the cost of a
preventable admission is estimated by CMS to
be $7200 per patient.
After
Figure 7, displays the Readmission rate from
fourth quarter 2007 to third quarter 2010. The
To provide best patient care experience and
minimize readmission reimbursement costs, a
hospital needs to evaluate not only their current
Figure 5: After Implementation Readmission Rate
discharge process but also contributing events
that are adding value to reduce readmissions.
While, not every readmission can be avoided,
there is a lot of opportunity in preventable
patients. Other areas such as community
education for common diagnosis causing
readmissions can be evaluated to avoid
readmission. Lean Six Sigma methodology was
critical to the problem solving process in
reducing readmissions. Future areas of
improvements stemming from this project are
implementing Lean Methodology to streamline
the discharge process in order to reduce cycle
time. Many hospitals are unable to meet
admission capacity from direct-admits or
Emergency Department admissions due to
unavailable capacity. This project highlighted
the large percentage of time contributed to
discharge in a patient’s length of stay. The
success of the results from this project can be
attributed to the continuous support of process
engineering team and executive leadership.
Acknowledgments
Karen Delaurier, RN, Medicinal/Surgical
Services Director, Sharon Ulep, SSBB, Quality
and
Outcomes
Management,
Kathleen
VanWagoner, RN, CNO, Heidi Blizzard, RN,
Nursing Information Project Manager, Carie
Cote, RN, 6E Manager, Angelina DiPiazza,
RN, Jenny Dudley, RN, Jackie Jones, NP,
Anna Pollack, Social Worker, Kelly Rogers,
RN, Sandy Russell, Case Manager, Gail Tack,
Medical Quality Specialist, Christine Juett, RN,
Biographical Sketch
Vanda Ametlli is a student majoring in
Industrial & Systems Engineering at Wayne
State University, Detroit, Michigan. As part of
her undergraduate internship at Crittenton
Hospital Medical Center she participated in a
Lean Six Sigma to improve readmission rate.
Vanda is pursuing her Masters degree in
Industrial & Systems Engineering at Wayne
State University with a specialization in Lean
Operations.