Transcript Reducing Patients Who Decompensate within 24 hours of

Reducing the Number of Admitted Patients Who
Decompensate within 24 hours of Being Transferred
to the Floor from the Emergency Center
A Clinical Safety and Effectiveness Education Course Project by:
Stephanie Mundy, M.D. and Kent Walters, MBA, CMPE
The University of Texas M. D. Anderson Cancer Center
October 15, 2009
Rationale – Resource Utilization, Improve
Patient Care
 There is a need to improve how patient acuity is assessed in order to optimize our
patient care resources
 To improve patient care by reducing number of patients who decompensate and
are transferred to ICU within 24 hours of admission to floor from the Emergency
Center
 Decompensate = patient had cardiopulmonary arrest or severe decline in
physical status requiring emergent attention of the medical staff
 To optimize utilization of nursing unit, telemetry, and ICU beds through improved
assessment of patient acuity prior to transfer from the Emergency Center
 Based on limited bed resources (physical space and staffing) for all units identified
above
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Rationale – Problem Confirmation
 During the period January 2006 through mid-November 2006
there were 94 patients who transferred from the floor to the
ICU in less than 24 hours from admission from the
Emergency Center or 1.45% of total admissions from the
Emergency Center
 All patients transferred to the ICU were included, consisting
of postoperative patients, patients transferred for a procedure
or careful monitoring as well as those truly decompensated
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Rationale – Research
 “Nearly 85% of inpatients that had cardiac arrest showed
identifiable signs of deterioration during the previous eight hours.
Recognition of these signs and timely intervention may reduce
morbidity and mortality”.
Source: Bristow PJ, Hillman KM, CheyT, Daffurn K, Jacques TC, Norman
SL, Bishop GF, Simmons EG: Rates of in-hospital arrests, deaths and
intensive care admissions: The Effects of a Medical Emergency Team, MJA
2000;173:236-240.
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Background
 The Emergency Center admits 35% of all hospital admissions at
UTMDACC, which approximates 656 patients per month
 Emergency Center patient acuity is significantly higher than a non-cancer
specific emergency center:
Facility
UT M. D. Anderson Cancer Center
Non-cancer Hospital
% of Patients Admitted from EC
% of Admissions to ICU
35.0%
13.9%
(1) Source: National Ambulatory Care Survey: 2003 Emergency Department Summary. Advance Data. Number 358. May 26, 2005.
U.S. Department of Health and Human Services, CDC.
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7.0%
1.3% (1)
Background
 Project is first step in developing acute care scoring
system for all patients
 EC selected as pilot area given 35% of inpatient admissions
originate from the EC; and
 EC inpatient admissions represent a higher acuity patient
population with a greater chance of decompensating within 24
hours of being admitted to the floor.
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Aim Statement
 Decrease by 25%, the decompensation
rate (transfers to the ICU within 24h) for
patients admitted to the floor from the
Emergency Center, within 12 months.
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Multidisciplinary Team Approach
Physician
Nursing
Quality
Improvement
Pharmacy
Aim Statement
Reducing the Number of Admitted Patients
Who Decompensate within 24 hours of Being
Transferred to the Floor from the EC
Business
Administration
Information
Systems
Clinical
Informatics
Ishikawa Analysis
 Ishikawa analyzed for commonality in process areas to determine
an area of concern as viewed by all health care providers that
contribute to patient decompensating
 Ishikawa processes were identified by physician, nursing, clerical,
pharmacy, and business staff members through distribution of
cause and effect diagram and focus groups
 Each process then ranked (1 to 5, high to low) by each individual
relative to chief concerns
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Ishikawa (Fishbone) Diagram
Contributing Factors
Patient factors
Cancer Pts –
very complex
+ comorbidities
Neutropenic
Fever
Vital signs
questionable
HR 130, Sys < 90
Sicker Pt results in
higher % admitted
Bilateral pneumonia
Patient & family
satisfaction / dissatisfaction
w/process
No common language between care
givers to communicate pt acuity
EC frequently busy
ER / Enviornment
EC MD to adm MD
short, limited verbal handoff
Page operators –
unaware of updated
call schedule
Pager problems Rolling over
EC RN to patient
ratio 1 - 4
Priority to new EC Pt
Initiating Admission
Orders in EC
- process & timing
varies
EC MD to EC MD report ‘simply
admitted’ no status report
consultant but may not come until
after primary team has visited
EC team often desensitized
to how sick the Pts may be
Waiting for ICU/tele/floor
Process to get in ICU
beds to be available
Difficult – no consistent path
to communicate with
Admitting team
No Handoff to fellows – who cover
after clinic hours & on weekends?
No consistent process/criteria for EC RN
New EC patient vs Admitted to report admitted pt changes to EC MD
EC patient needs
Floor RN difficulty which
MD to call for orders
Admitted EC patient needs
admitting orders
RN -> RN handoff
How do they Prioritize?
Admitted EC patient needs
Requires > 40 % O2
to keep O2 sat. > 90%
Delays in getting tests
when busy
Delay in writing Admission
orders when EC busy
Communication
RN cares for sickest first Prioritize care for all patients
EC Record not always
available to floor
Admitting team challenge transfer of care occurred even
if pt still physically in EC
ICU/sickest patients require
more resources
Limited # EC MD’s
EC MD write Admission orders
for non-surgical pts
Care Delayed Consults do not come until
primary MD sees pt.
Frequency of V / S in EC
Patient admitted
through EC who
decompensates
on floor &
moved to ICU
within 24 hours
One EC MD from
1:00 am to 9:30 am
Variation of skill levels of
Healthcare providers
Pts often not seen
by Primary w/ in 24 hours
Primary attending
full house + rounds
clinic by 1300
Criteria for notification
vital sign changes
Methods
Staffing
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Ishikawa Analysis
80
76
72
70
Total Points
60
50
39
40
37
35
30
20
10
0
Waiting for
ICU/tele/floor beds to
be available
Cancer pts very
complex +
comorbidities
Vital signs
questionable
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Pts often not seen by Requires >40% O2 to
primary w/in 24 hours
keep O2 sat >90%
Ishikawa Analysis
Sorted Histogram of Top Reasons for Patients Decompensating within 24 hours of Admission to Floor from the EC
80
76
120%
74
72
70
100%
100%
86%
80%
Total Points
50
40
37
60%
58%
30
40%
20
29%
20%
10
0
0%
Waiting for ICU/tele/floor beds to Vital signs questionable e.g. sat
be available
level>02 required
Cancer pts very complex +
comorbidities
Reason for Patient Decompensating
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Pts often not seen by primary
w/in 24 hours
Cumulative Percentage
60
What We Uncovered
• Waste in how vital signs are
documented
•
Handwritten on EC note
•
Entered into ClinicStation
•
Entered into Whiteboard
• Likely need for improved ICU bed
resource and utilization
• Improved training needed on vital
sign monitoring
• Root cause analysis of why certain
units have higher decompensation
rate than others
Pandora by John William Waterhouse, 1896
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Intervention Options
 The cause and effect analysis resulted in intervention
options:
 All patients reevaluated by MD prior to transfer
 All patients reevaluated by RN prior to transfer
 Complex scoring system utilizing vital signs, comorbidities, type of
cancer, labs etc. – too time consuming
 ClinicStation be modified to signal (red flashing) when vital signs trends
are abnormal – not feasible at current time
 Vital signs to be taken every 2 hours with split of CNA every 4 hours
and RN every 4 hours and placed into ClinicStation – creative staffing
solution!
 Vital signs linked from bedside monitor to ClinicStation – technically
possible financially not
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Selected Intervention
 Criteria for selection was ease of implementation (people,
process, and technology) relative to direct and indirect costs
 Based on criteria and testing of options it was discovered
ClinicStation could print a vital sign trend in graph and table
format
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Intervention Implementation
Process
Variations
Manual Process
Most take all of the patients
vitals and write them on the
“old” vital sign board, then
enter the data into CS.
A few take the computer
door to door and enter the
data into CS immediately
after the VS are taken.
Moving from room to room
w/ the computer is faster.
Current Process Mapping
Logs into Clinic Station:
ID, Password (if the CNA
is registry, one of our
USC’s log them into
C.S.)
Type in the MR# of
the pt you wish to
take vital signs, hit
enter
New screen opens w/ list of
EC pts. Click on the name of
pt –again, in the new screen.
This opens the C.S. vital sign
sheet (SEE example page w/
#2 at the top)
Take the vital signs
Start New Patient
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Pt data screen opens.
Scroll down to NSG
DOCUMENTATION,
click the mouse.
Enter the information into the
boxes
Click save and complete.
Click close (same screen)
Screen returns to the list of EC pts.
Intervention Implementation
10/14/2009
Clinical Safety and Effectiveness Project
Reducing the Number of Admitted Patients Who Decompensate within 24 hours of Being Transferred to the Floor from the EC
EC Physician Patient Checkout Process Flow Chart
ER Physician Check-out
Process
(patient is ready to leave EC)
EC Physician
·
EC Physician prints out vital
sign trend graph in Clinic
Station and reviews trend.
·
Place graph on top of chart.
EC Physician
Graph is stamped by EC
Physician using his/her own
stamp
EC Physician
EC Physician writes next to
stamped signature:
OK for Discharge,
OK for Transfer to Floor,
etc.
·
Nursing Staff
Removes vital sign trend graph
(with MD stamp) and place it in
box in Pod A or B
Legend
Symbol
Count
Description
1
Main process
1
Event
1
Component
1
Process path
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Function
Key Patient Status Indicators:
1. Patient is DNR
2. Patient is borderline or unstable
3. Patient is neutropenic
Component Process
If Patient is admitted but
remains in EC greater than
2 hours post discharge i.e.
waiting for bed
Patient is ready to be
transferred from EC to
room
Nursing Staff
Print out updated
graph and review for
abnormal trend
No
Yes – Abnormal Trend
Nursing Staff
Inform appropriate physician of
trend
Physician and/or Nursing Staff
document intervention results
on trend graph
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Stamp updated graph and write:
OK for level of care or no
significant change
Staple updated trend to EC
physician trend graph in box on
either POD A or B
Intervention Implementation
1/6/2007
Clinical Safety and Effectiveness Project
Reducing number of patients who decompensate within 24 hours of admission to floor/unit
EC Patient Vital Sign Process Flow Chart
Routine patient vital signs
recorded into ClinicStation
every 2 hours
MD Arrives at patient room
CNA record vital signs at:
12a
4a
8a
12p
4p
8p
Nursing Staff (RN) record vital
signs at:
2a
6a
10a
2p
6p
10p
MD conducts
medical evaluation
and reviews vital
sign trend chart
Abnormal vital sign(s)
noted
NO
Medical decisionmaking by MD
No
Yes
Yes
CNA informs
RN of abnormal
vital sign(s)
RN rechecks vitals
and checks trend
chart
MD documents
orders in
ClinicStation
Abnormal vital sign(s)
verified
YES
RN notifies
MD via
Vocera
RN moves
yellow flag to
“out” position
RN leaves
room and
continues
normal work
process
RN reviews and initiates MD orders
Yellow flag moved flush to wall.
END OF PROCESS
Start at Beginning until patient discharged
from EC
Legend
MD receives Vocera
and responds with
confirmation ETA to
evaluate patient
Symbol
Description
Main process
Event
Function
Warning
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Intervention Implementation
 Intervention implementation required using the Plan
Do Check Act (PDCA) methodology
 A process diagram was developed based on the
perceived new work flow for reviewing vital sign trends
 Process flow charts posted in the EC and distributed to
EC physicians, RNs, and CNA
 Follow-up written and verbal communication occurred
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Selected Intervention
2 keystrokes total – review and print. Meets
process and technology objectives.
Table
Format
Graph
Format
Vital Sign
Review in
action
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Data Collection
 Data was collected at 3 points
 Initial period of 11/17/06 to 11/30/06 and 12/1/06 to
12/31/06, and 01/1/06 to 04/30/09
 First data collection period saw no change in percent of
patients who decompensate
 Though analysis determined sample too small to draw any conclusions as
to effectiveness of intervention
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Baseline Data
Percent of EC Admissions - 'EC-Floor-ICU within 24 Hours'
Baseline
VS EC P
# EC-Fl-ICU w/in 24 hr pts/ # EC adm pts
5
11 month decompensation rate = 1.45%
4
UCL=3.18
3
CL=2.30
1
0
Jan 06
Mar 06
Feb 06
May 06
Apr 06
Jul 06
Jun 06
Sep 06
Aug 06
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NovA 06
Oct 06
NovB 06
Data Collection – 2nd Point
Percent of EC Admissions - 'EC-Floor-ICU within 24 Hours'
Baseline
VS EC Project
5
# EC-Fl-ICU w/in 24 hr pts/ # EC adm pts
Intervention
11/17/06
4
UCL=3.16
2.28% to 1.89%
decompensation rate
3
CL=2.10
1
LCL=1.04
0
Jan 06
Mar 06
Feb 06
Apr 06
May 06
Jul 06
Sep 06
NovA 06
Dec 06
Jun 06
Aug 06
Oct 06
NovB 06
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Data Collection – Comparison by Baseline, New
EC, and EC Pod A
New average of 0.7% for a 47.5%
change since project inception
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Intervention Results
 Solid improvement achieved during second data collection period
compared to first data collection period
 During the project period there was 33% compliance with the
vital sign summary analysis, and only 33% of those patients
transferred to the ICU during both periods had the vital sign data
complete with indication of review
 Important to note data was more inclusive than exclusive during
first round of baseline data collection
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Obstacles Encountered
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Obstacles Encountered
 Throughout the intervention process several obstacles
encountered:
 Compliance with printing and signing vital sign trend graph
 High EC volume that contributed to reduced compliance on
certain days
 Inconsistency in using ClinicStation for vital sign entry
 Competing CS&E projects as well as other quality
improvement initiatives – information overload e.g.
remembering what to do when and for whom
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Obstacles - Communication
We said – CS&E
project; improve
patient care;
simple form; how
exciting!
They heard –
another piece of
paper; CS what?;
and I should be
concerned about
this because…
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Obstacles Encountered – Compliance Rate
90%
Average 6 week compliance rate = 33%
80%
78%
70%
61%
60%
49%
53%
50%
49%
48%
48%
43%
Compliance Percent
49%
46%
43%
40%
37%
35%
33%
30%
20%
26%
23% 22% 23%
27%
28%
30%
30%
26%
32%
29%
24%
20%
16%
36%
32%
31%
23%
18%
38%
26%
25%
20%
16%
10%
10%
0%
39%
37%
35%
45%
1%
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17%
How Obstacles Were Addressed
 Communicate, Communicate, Communicate!
 Constant communication (direct and indirect) increased
compliance rates significantly
 Compliance rate improved when Dr. Mundy
was working in the EC!
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ROI Analysis – Cost Basis
Average Cost per Day (H&C Only) and ALOS for Intensive Care Units
January 2008 - December 2008 Admissions
Medical ICU ALOS*
Medical ICU Avg Charge/Day
Medical ICU Avg Cost/Day
$ 15,081
$ 7,267
Pedi ICU ALOS*
Pedi ICU Avg Charge/Day
Pedi ICU Avg Cost/Day
$ 16,284
$ 7,877
Overall ICU Avg Cost Day
$
8,224
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5.91
4.92
ROI Analysis – Cost Avoidance
 The project has significant impact on cost avoidance.
 Avoided costs included ICU charges not reimbursed due to payor




(especially governmental).
In a DRG environment, this is key and critical.
The average ICU admission charge (bed, drugs, therapies, imaging)
can average ~ $15,081 per day.
The average ICU cost per day is $7,267.
Reducing ICU bed days (especially in a DRG environment) by 47%
results in an annual savings of ~$ 4,360,200.00 (600 ICU bed days
avoided multiplied by $7,267).
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ROI Analysis – Changes to Whiteboard and ClinicStation
 Process of charting vitals directly into ClinicStation eliminates
need for paper based progress notes. Productivity gains based
on time involved in using paper based systems and then retranscribing into ClinicStation.
 Other Benefits
 Improved patient safety by reducing transposition errors
 Increased nursing time with patient instead of paperwork
 Compliance in entering vitals into ClinicStation
 Decrease in patient to physician time, and
 Significant morale booster!
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Overall Conclusions
 Sustainability
 Monthly review of patient decompensating data to be presented by 3rd
Thursday of month at EC Management meeting
 Improvements to be made include adding time reviewed with signature
on medical record form (time stamp in ClinicStation now eliminates this
step)
 Institutional Learning
 Improved understanding of how clinical processes should leverage
technology to improve patient safety and maintain true patient centered
care.
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