CASE STUDY 3
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Week6.pdf
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Making the Case for Quality
At a Glance . . .
February 2016
• In this case study involving an anonymous hospital, nursing department leaders sought to improve efficiency of their staff’s shift change assignments.
• Upon value stream mapping the process, team members identified the shift nursing report took 43 minutes on average to complete.
• Using DMAIC and other quality tools, team members improved the process’ sigma level from 0.7 to 3.3.
Using DMAIC to Improve Nursing Shift-Change Assignments
by Casey Hewes and Nina Costilla BSN, RN
Labor represents the largest expense for large metropolitan hospitals by far. According to Becker’s Hospital CFO newsletter, labor costs have typically averaged 50 percent of hospitals’ total operating revenue1 for the past decade. The American Hospital Association also reported in 2012 that growing labor costs are the most important factor increasing hospital care costs2, and found that wages and ben- efits accounted for more than 59 percent of hospital costs in 20143.
Wasteful practices must be scrutinized and contained to control hospital staffing costs while maxi- mizing operational efficiency. One area of opportunity involves the shift changes for nursing staff, a process that too frequently results in nurses staying later than their scheduled departure time. In 2010 the U.S. Department of Health and Human Services reported 54 percent of registered nurses surveyed said they worked more than 39 hours per week4.
A 600-bed hospital near Dallas, TX, initiated a project to improve its nursing shift change process to cut labor costs without negatively affecting the quality of patient care. This hospital has a formal opera- tional excellence department that primarily uses Lean Six Sigma methodology, following the define, measure, analyze, improve, control (DMAIC) approach. The project was approved and facilitated by this department as well as the service line director of nursing.
Working with Mark J. Davis, a Lean Six Sigma Black Belt as their mentor, the nurse manager and day nurse supervisor for a medicine and surgery (med-surg) unit led the project. The DMAIC approach helped the team uncover solutions that would allow nurses to leave work on time and encourage greater efficiency in the shift-change process.
Define
The shift-change nursing report is the primary tool used to ensure continuity of care as staff change happens every 12 hours. The report contains pertinent patient information, and is given to the arriving nurse before the previous nurse on duty leaves at the end of a shift. Nursing assignments are given to the arriving nurse, and include the list of patients they are to care for.
The charge nurse is responsible for making these assignments, which are typically subjective and based on many variables (patient acuity, blood sugar levels, and proximity to the nursing station, along with overall scheduling for the nursing floor, such as number of admissions and discharges, etc.).
The SIPOC map in Figure 1 sum- marizes the metrics by which nursing assignments are produced and shift changes occur.
On this particular med-surg unit, there are typically five registered nurses staffing the team. Often the five nurses from the day shift have to interact with each of the five nurses on the night shift as dictated by the patient assign- ments. If these nurses were to spend less time working on the shift-change nursing report, they could use the extra time to work with their patients, which would have a more direct impact on hospital consumer assessment of healthcare providers and systems (HCAHPS) scores. One of the key out- puts included in Figure 1, HCAHPS, is the mechanism through which patients can rate their medical care experience. Medicare payments to hospitals are, in part, tied to these scores—making them very important.
As designated by the hospital’s parent company, the change of shift report should take no more than 30 min- utes. Any report requiring more than 30 minutes was considered a defect. During any shift change, five nurses delivered the report and five received it. Therefore, each report involved an opportunity for five defects.
Measure
In order to measure improvement, the team decided to call upon the overall time it took to produce the nursing report. Conclusions were drawn from a total of 30 timed observations. These 30 observations were gathered by the nurse manager and day nurse supervisor.
The pair discretely timed nurses at shift changes in the morning and evening for several weeks. Both observers had a stopwatch function on their smart phone and a form to keep observations accurate and consistent. The observ- ers split the observations evenly for
day and night shift changes and both took on observation roles for both shifts. Due to the busyness or distractions of shift changes, they were not exposed because they would time the nurses from a distance. They were also a routine presence during this time period.
Based on the 30 observations measured, the shift-change nursing report was found to take an average of 43 minutes to complete.
The next step was to determine of the 43 minutes, how much accounted for nonvalue- added (NVA) steps. The team determined if the nurses were waiting and not delivering the shift-change report or listening to the report, the time could be categorized as NVA.
The value stream map (VSM) in Figure 2 revealed 23 minutes of the process was non- value added and was devoted to completing the shift nursing report as the arriving nurse waited for the previous shift nurse to depart. The oncoming nurse waited to receive
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Supplier Inputs Process Outputs Customers
• Staff • Staff • Time • HCAHPS • Employee
Satisfaction • Salary • FTEs
• Service Line Director
• Leadership • Staff • Patients
Providers of the required resources
Resources required by the process
Top-level description of the activity Deliverables from the process
Anyone who receives a deliverable from the process
Find 3 RN get report
Get assignments
Put away belongings
Find 2 RN get report
Find 1 RN get report
Staff punch in
Find 4 RN get report
Find 5 RN get report
Report with nurse 1
CT=10 sec CVA=0 BNVA=10 sec NVA=0
CT=6 min CVA=6 min BNVA=0 NVA=0
CT=2 min CVA=0 BNVA=0 NVA=0
CT=10 sec CVA=0 BNVA=10 sec NVA=0
CT=6 min CVA=6 min BNVA=0 NVA=0
CT=7 min CVA=7 min BNVA=0 NVA=0
Get assignment
Put away belongings
Report with nurse 2
Total lead time = 43 minutes Process time = 23 minutes Total NVA = 20 minutes
I
I
I
I
IReport with nurse 3
Staff punch in
10 seconds (Transaction 1)
5 minutes (Transaction 5)
2 minutes (Transaction 2)
5 minutes (Transaction 3)
5 minutes (Transaction 4)
Note: Three nurses are in the value stream map because that is the average.
Figure 1: SIPOC map for shift changes
Figure 2: VSM for shift change reports
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reports from an average of three departing nurses before she could begin her duties.
Analyze
To begin addressing potential solutions for NVA wait time, the team completed a failure mode and effects analysis (FMEA) chart (see Table 1). This analysis is a complete and quantified cause and effect chart that pinpoints potential reasons why the
shift-change report is taking so long to complete. Included in the FMEA is a risk priority number, which suggests the factors that should take the highest priority in promoting change.
The following are the steps for completing the FMEA:
1. Analyze what may be causing a long nursing report. • For example, the number of nurses involved will
influence the length of the report.
Table 1 — FMEA to identify reasons for NVA steps
Process or Product Name:
Staff Nurses Report Disection Prepared by: Nina Costilla, Casey Hewes
Page _1_ of _1_
Responsible: Project Team FMEA Date (Orig) 5/16/2015 (Rev) ____________
Process Step/ Input
Potential Failure Mode
Potential Failure Effects
Se ve
rit y
Potential Causes
O cc
ur re
nc e
Current Controls
D et
ec tio
n
R P N
Actions Recommended
Responsible
What is the process step or input?
In what ways does the process step or input go wrong?
What is the impact? What causes the process step or input to go wrong?
What are the existing controls and procedures that prevent either the cause or the failure mode?
What are the actions for reducing the occurrence of the cause, or improving detection?
Amount of nurses
Too many staff nurses to give report to
Delay in report because have to wait for or find next staff nurse
8
Charge nurse assignment 10
None
9 720
Territories Casey/Nina
PCTs in report Timing of PCT in report
Distracted PCTs and staff nurses respond to call lights
6 Change of shift design 10
None 10 600
Stagger ongoing/ outgoing staff
Casey
Standardization Report is given based on staff nurse preference
Varied time of report 7
Different staff nurses have different skill levels and areas of emphasis
10
Potential to offput offgoing/ ongoing nurse 8 560
Standardization of report
Laurie Robbins
Charge in report
Timing of charge nurse in report
Distracted charge nurses and staff nurses respond to call lights
5
Change of shift design 10
None
10 500
Stagger ongoing/ outgoing staff
Casey
Rapport vs. report
Relationship development versus actual report
Delay in report
5
Nurses choice
8
Potential to offput offgoing nurse 5 200
Education on communication style
Casey
Layout – Hamon vs. Main
Hamon has nooks or areas for nurses to watch their pod and more Medication Pyxis
Less walking for nurses
3
Lack of satellite Medication Pyxis. Less nooks. 10
None
5 150
Build out 615 and create nook
Casey/Nina
CareConnect inefficient
CareConnect report not optimized
Inefficient report and delay in report 5
CareConnect decision 5
Ability to work around CareConnect 5 125
Choice to use CareConnect or not
Debbie Van Sickel/Super user/Laurie Robbins
Not enough WOWs
Each staff nurse uses WOW for report
Delay in report
3
Can’t use CareConnect report or unable to bedside report
4
Adequate amount of WOWs 10 120
Keep WOWs operational
Night charge nurses
FTE/OT/Salary Doesn’t directly measure report time
Does not measure precisely 2 N/A 1
Don’t utilize report 1 2
N/A Casey
Clock in/ clock out
Doesn’t directly measure report time
Does not measure precisely 2 N/A 1
Don’t utilize report 1 2
N/A Casey
Main 6 West – Geographic Assignment 3 Territory #1 will be the charge assignment since there are nine rooms. If night is four nurses, three rooms from #3 go to #1 and two rooms from #3 go to #2.
Staff Elevators Boardroom 625 624 623 622 621 St
ai rs
2a 2b
Guest Elevators O
ffi ce
s
Py xi
s St
or ag
e
Nurse’s Station M
ed
Ro om 620 619 618 617 616 615
Waiting Room 601 602 603 604 605 606 607 608 609 610 611 612 614
1a 1b 2a 2b
5 Pods Pod #2 is charge assignment. If night is four nurses, will split pod #2.
Staff Elevators Boardroom 625 624 623 622 621 St
ai rs
4
Guest Elevators O
ffi ce
s
Py xi
s St
or ag
e
Nurse’s Station M
ed
Ro om 620 619 618 617 616 615
Waiting Room 601 602 603 604 605 606 607 608 609 610 611 612 614
1 2 3
2. Identify how the step can go wrong. • Too many nurses may be giving the report to each other
at the same time. 3. Identify what impact the step has on the nursing report.
• The problem is when there are so many nurses they have to wait for each other.
4. Determine potential causes for the problem. • The cause of this problem is that the way assignments are
done, nurses must give the report to several other nurses. 5. Assess potential controls that exist for the problem.
• There are no controls in place to manage this problem. 6. Identify how to reduce the likelihood of the problem.
• Create assignments where one nurse can give the report to only one other nurse.
Improve
Upon observing and analyzing the data, the team identified a key area for most effectively eliminating waste. It was clear the
most significant and controllable source of unnecessary payroll expenditures existed in the number of nurses involved in pro- ducing the shift-change reports.
Typically, this unit runs over budget by approximately $5,000 per month in payroll expenditures. This process most likely exists for the majority of hospital units across the United States because it has always been done this way.
In order to operate more efficiently in the reporting process, the team redesigned the layout so the nursing assignments are del- egated in clusters or by an emphasis on geography. By dividing assignments by territory, the team was able to maintain flexibil- ity while relegating assignments to a specific area.
Unit staff were presented with two solutions: “territory” or “pods.” As the force field analysis in Figure 3 illustrates, ter- ritory allowed more flexibility, and pods were very simple. Territories are more flexible because there is a range the nurses
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Scale importance - Balanced acuity - Continuity
of care
- Proximity - Speed/Ease of
assignments
1 = Less importance 5 = More importance
Flexibility
Our own
5
2
7 3
Confusing/ Interpretation
Slower assignments
1
2
Figure 3: Force field analysis of potential solutions, territory vs. pods
Easy
Can’t complain
3
1
4 4
Charge assignment
will be difficult
Inflexibility
2
2
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can be assigned, but the range is greatly reduced from the previous scenario. Pods are more rigid and straightforward because a nurse has a predetermined set range, i.e., beds 1-5 with no room for flexibility. The territory assignment began January 1 at midnight.
Control
The team tested the territory nurs- ing assignment methodology during a 30-day trial period for both shifts on the med-surg unit in question, and the results were extremely favorable. Under the territory framework, any given nurse will average one nurse, two at the maximum, to whom they must provide their shift change report.
To deploy the process change, com- munications were dispersed to all unit staff through informal discussions, emails, and in a staff meeting featuring extensive dialogue. Extra communi- cation and Q&A talking points were provided for the charge nurses.
Upon implementation of the new process, the average time it took to complete the report now stood at 30 minutes, thereby reducing needless waiting times significantly. Figure 4 illustrates the VSM for the improved process while Table 2 shows the sigma level for the process improved from 0.7 to 3.3.
Report with nurse 1
CT=10 sec CVA=0 BNVA=10 sec NVA=0
CT=2 min CVA=0 BNVA=0 NVA=0
CT=10 sec CVA=0 BNVA=10 sec NVA=0
CT=25 min CVA=25 min BNVA=0 NVA=0
Get assignment
Put away belongings
Total lead time = 30 minutes Process time = 25 minutes Total NVA = 5 minutes
I I
I
Staff punch in
10 seconds (Transaction 1)
2 minutes (Transaction 2)
3 minutes (Transaction 3)
Figure 4: Future state VSM (post-intervention)
Table 2 — Process improvement as measured by sigma level
Pre-Intervention Post-Intervention
The calculation of a sigma level, is based on the number of defects per million opportunities (DPMO).
The calculation of a sigma level, is based on the number of defects per million opportunities (DPMO).
In order to calculate the DPMO, three distinct pieces of information are required:
In order to calculate the DPMO, three distinct pieces of information are required:
a) the number of handoffs produced b) the number of defect opportunities per handoff c) the number of defects
Opportunity Defect/Opportunity Defect
a) the number of handoffs produced b) the number of defect opportunities per handoff c) the number of defects
Opportunity Defect/Opportunity Defect
The actual formula is: The actual formula is:
DPMO = (Number of defects x 1,000,000)
DPMO = (Number of defects x 1,000,000)
((Number of defect opportunities/unit) x number of units) ((Number of defect opportunities/unit) x number of units)
Defects Opportunities
Defect opportunities per unit
= 24 = 30 = 1
DPMO = 800,000 Sigma level = 0.7 (Max sigma level = 6.0)
Defects Opportunities
Defect opportunities per unit
= 1 = 30 = 1
DPMO = 33,333.33 Sigma level = 3.3 (Max sigma level = 6.0)
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The goal achievement graph in Figure 5 reflects a greater efficiency and produc- tivity as a result of process change. The nurses have also had a great experience and favor the new change, as some have particularly noted they are walking less throughout the day and delivering their reports more quickly.
The x-axis in Figure 5 represents produc- tivity and is used by the nurse manager to evaluate labor utilization. The blue line represents how many employees the finance department thinks should be required, given the census, and the red line is the actual amount used. To date, the improvement has been in place for six months and is self-sustaining.
There have been no interventions by the nurse manager or day shift supervisor. There have been discussions rolling this program out to other med-surg units, but this has yet to be executed. Currently, there are no other plans or discussions to improve this process.
Clearly, there is room for greater effi- ciency among the majority of hospitals across the country. This case study demonstrates an opportunity for similar
units to emulate since it could address an industry-wide problem. If other med-surg units took this shift-change project on and it became the norm, versus an outlier, we could positively affect healthcare costs.
References
1. Bob Herman, “10 Statistics on Hospital Labor Costs as a Percentage of Operating Revenue,” Hospital CFO, December 10, 2013, www. beckershospitalreview.com/ finance/10-statistics-on-hospital- labor-costs-as-a-percentage-of- operating-revenue.html.
2. American Hospital Association, “The Cost of Caring,” AHA.org, June 2012, www.aha.org/content/12/ CostofCaring2012.pdf.
3. American Hospital Association, “TrendWatch: Chartbook 2015,” AHA.org, 2015, www.aha.org/ research/reports/tw/chartbook/ index.shtml.
4. Sung-Heui Bae, “Nursing Overtime: Why, How Much, and Under What Working Conditions?,” Nursing Economics, March-April 2012.
For More Information
• To contact the author of this case study, email Casey Hewes at [email protected].
• To view this and other case studies, visit the ASQ Knowledge Center at asq.org/knowledge-center/ case-studies.
About the Authors
Casey Hewes has worked in healthcare for 12 years as a staff nurse and in management. He has a master’s degree in business administration with an emphasis in finance from the University of Hawaii.
Nina Costilla, a native Texan, received her bachelor’s degree in nursing from Texas Tech University. She is currently working toward a master’s degree in nursing from Texas Tech.
Flex Productive FTE Productive FTE
30
32
34
36
38
40
42
44
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May
Med-Surg Unit �ex and productive FTE
Figure 5: Goal achievement graphs
