EMERGENCY ROOM NURSE STAFFING:
ANALYSIS OF ACTWITIES AND DEVELOPMENT OFRESOURCE SIMULATION MODEL BASED ON A
PATIENT CLASSIFICATION SYSTEM.
Submitted By:
Maiisa R BahnScott A. Ehrenberger
Stephanie Brett HanksSusan L. Stefan
Industrial and Operations Engineering 481 :Projects in Hospital Systems
Instructor: Richard J. Coffey. Ph.DCoordinator Diane Taherzadeh
Clients: Arlene Greenlee. Joan Robinson
20 April 1987
I
AcknowIedemeyts
The members of this project team would like to thankthe following people for their time, elibrt. and support:
Arlene Greenlee. Head ER NurseDiane Taherzadeh, Management EngineerJohn Moore. Ph.D, Associate Professor
Professor Gaty Herrin, Ph.DThe Emergency Room Nurses
(
Table of Contents
C
0. Executive Summary 1
[. Irxluction 2
II. Data Collection Methodology 3
III. Data Analysis and Results 6
IV. Simulation Model 16
Appendix A 19
Appendix B 21
Appendix C 23
AppendixD 25
Appendix E 27
Appendix F 29
AppendixG 31
Appendix FL 33
Appendix I 35
Appendix 3 37
Ii
0. Executive Summary
The increase in patient volume and a continuing need for cost-effective operations has
necessitated reassessment of the current status of the University of Michigan Medical Center. In
response, the Emergency Services department is conducting a Nurse Staffing Project which will
result in a resource simulation model based on a patient classification system. The system will be
used to quantify nursing resource requirements and assist Emergency Services to better match its
nurse staffing with workloads.
A work sampling methodology with self-logging data forms was used to determine these
workloads. The analysis involved five general categories; Hands On Care, Patient Behalf Care,
Unit Support, Staff/Education Meeting, and Personal. Of these categories, Patient Behalf Care
utilized the most nursing time. In addition, an inverse relationship exists between Hands On and
Patient Behalf Care which implies that when Hands On care is low, the nurses appear to catch up in
their Patient Behalf Care activities. An inverse relationship also exists between Personal time and
the nurse to patient ratio. In most cases, it appears that the nurses are not taking their full allotted
meal and break times. Finally, a higher nurse to patient ratio does not necessarily increase the
Hands On care. In fact, on the weekday where the nurse to patient ratio was at its peak, Hands On
care fell to its minimum value. This result reveals the absolute necessity of further studies into the
impact of patient acuity on nursing time.
The simulation model takes into account both the patient classification and the work sampling
in order to determine optimal nurse staffing levels. When this model is in its final form, it can be
manipulated to show how different staffing patterns affect patient wait times and utilization of
nurses. However, additional information still needs to be collected to make this model complete,
specifically information regarding patient acuity. This information will be collected over the
summer and the simulation is expected to be completed sometime in December of 1987.
C i. Introduction
With the revisions in Medicare and Medicaid reimbursement policies and increased
competition within the Health Care industry, the University of Michigan Medical Center has been
forced to evaluate the cost-efficiency of its operations. The initial phase of the operations review of
Emergency Services was performed by Touche Ross consultants. Touche Ross identified a
decrease in the nursing staff as a potential opportunity for cost reduction.
The Emergency Room of the University of Michigan Medical Center is handling
approximately 25% more patients than last year. This increase in volume and the continuing need
for cost-effective operations has necessitated reassessment of the current status of this hospital.
Consequently, the Emergency Services department is conducting a Nurse Staffing Project. The
result will provide a resource simulation model based on a patient classification system. The
system will be used to quantify nursing resource requirements and assist Emergency Services to
better match its nurse staffing with workloads. This project falls under the Work Sampling heading
in the overall Emergency Services Nurse Staffing Project Plan, illustrated in Appendix A. This
overall project plan is expected to continue through December, 1987.
In order for this process to be implemented, it was necessary to determine the amount of
Emergency Room nursing time spent on hands on care and care rendered in a patient’s behalf.
Direct care time per patient classification was investigated in a previous study*. The purpose of
this project was to determine the average amount of time spent by Emergency Room nurses
performing patient behalf care and to refine the general model for the computer simulation. Patient
Behalf care and its relation to patient volumes and corresponding nurse staff levels wer also
examined. Additional activities were included to retain continuity and confirm the direct care times
found in the previous study These additional activities were categonzed as Hands On (Direct
Care), Unit Support, Staff/Education Meetings and Personal.
C*
“Emergency Services Classification System Project”, McCarthy, John A. and Reinhart, StephenP., May 5, 1986.
2
CIT. Data Collection Methodology
Because work sampling is an effective means of identifying the types of activities that staff
perform and the amount of time they spend on these activities, it provides the information managers
need to make decisions regarding appropriate staffing levels. Because this was the ultimate goal of
our project, work sampling was chosen as the method of data collection for our study. Work
sampling is based on the theory that with a large sample size of randomly monitored activities, the
percentages of time spent on various activities can be determined.
To accomplish this we designed a data collection sheet consisting of seven general categories
including; Direct Care (all working situations therefore being covered), Telephone Communication,
Paper Handling, Unit Management, Verbal Communication, Travel, and Personal (see Appendix
B). Note that within each general category several nursing activities are listed. To analyze the
nursing activities most accurately, these seven general categories were later revised into the five
new general categories as listed in Figure 1. The five revised categories include; Hands On, Patient
Behalf Care, Unit Support, Staff/Education Meeting, and Personal. Listed under these five
categories in Figure 1 are the sub-categories and its respective activities.
A self-logging approach was used because it provided several advantages over logging by
direct observation. First, self-logging provided a much greater sample size because it allowed
sampling 24 hours a day over the entire sampling period. Self-logging did not require any
observation by outside parties and therefore was a minimal interference in patient care. Also, there
was complete randomness as to who did the logging each shift on each day whereas direct
observation may not have allowed this amount of randomness.
Five random signal devices were used to indicate to the nurses when to mark the activity they
were performing. An average of 2.5 times per hour for the alann frequency was optimal in that it
would provide a sufficient sample size without distracting the nurses more than necessary. These
five alarms were distributed among the nurses in the following manner: one to the team leader, one
3
Revised General Categories / Sub-Categories / Specific Activities
Hands Ondirect patient careother
Patient Behalf CareTelephone Communication: information call
follow up calladmission processingpagingpoison callALS runother
Paper Handling: lab requisition fill-outprocess specimensnursing documentationcharge/sign out signother
Unit Management: crowd controlroom/unit cleaningother
Verbal Communication: staff/co-workerpatient/visitorfamily support during crisisother
Travel: patient transportationhelipad responsepatient care off-siteitem transportationother
Unit SuonortTelephone Communication: calls to cover staffing
troubleshooting
Paper Handling: ordering supplies
Unit Management: stocking
Staff/Education Mtgstaff/education meeting
Personalmeal/breakschedule adjustmentpersonal timerecording payrollother
Figure 1. Revised list of general categories, sub-categories, and activities
4
to the nurse attending the back hail, and three to critical care nurses. The triage nurse was not
considered in the study because triage time is considered to be constant. Only registered nurses
and the licensed practical nurses were included in the study; nurse aides were omitted.
At the beginning of each shift, the Emergency Room nurses filled out identification
information (name, start/finish time, assignment, etc.) at the top of a data collection form. Each
time the random alarm signaled, the nurse marked the activity she was performing at that time. At
the end of the nurse’s shift, she passed the alarm to a nurse coming on duty and placed the
completed form in a designated file.
Prior to data collection, our project team held informal training sessions to familiarize the
nurses with the alarms and the data collection forms. A one week pilot study was conducted during
the week preceding the actual data collection. During the pilot week an attempt was made to correct
any potential problems by encouraging the nurses to suggest improvements for the data collection
form. The actual data collection period ran three consecutive weeks: the day shift on Friday,
C February 27 to the day shift on Friday, March 20, 1987. The work sampling was conducted on all
three shifts each day reflecting the Emergency Room’s 24 hour per day operation.
5
ITT. Data Analysis and Results
A total of 197 data forms were collected during the sample period, resulting in a total of
2887 random samples. The results of the work samples are presented in order of general trends,
followed by breakdowns by day and shift and by the relationships between patient volume and
nurse staffing.
A. General Trends
Figure 2 illustrates the breakdown over the entire sampling period of the five general
categories by percentage of time. Patient Behalf Care occupies 47.4% of the ER nurses’ time,
which is slightly greater than Hands On Care at 38.9%. The Staff/Education Meeting value of
1.0% may be artificially low because very few nurses used the alarms in the daily shift report.
Figure 3 provides a breakdown of the categories within Patient Behalf Care. Verbal
communication and paper handling, the largest categories, occupy 42.9% and 38.8% respectively;
for each of these two, it’s size is attributable to a single activity. Talking with staff or co-worker
occupies 87.3% of the ER nurses’ verbal communication time. Similarly, nursing documentation
occupies 82.0% of the ER nurses’ paper handling time.
Figure 4 illustrates the percentage breakdown within Unit Support. The activity of stocking
is 65.0% of the Unit Support time while calls to cover staffing required only 0.8% of Unit Support
time. The activities of troubleshooting and ordering supplies had intermediate values of 26.8% and
7.3% respectively.
B. Day and Shift Results
Day and shift comparisons yield interesting insights. Appendix C shows the daily
percentages of general categories and Patient Behalf Care activities. Hands On Care peaks on
Monday (49.0%) and steadily declines through Thursday (32.9%). With the exception of Sunday,
it then increases from Friday through Monday. Patient Behalf Care is greatest on Thursday
6
(
Unit Support4.3% Staff/Education Mtg. 1.0%
Personal Time
8.5%
Hands On Care
38.9%
Patient Behalf
Care 47.4%
Figure 2. Emergency Room Nurse Time: Breakdown of General Categories
Source: Data from the Emergency Room of the Universityof Michigan Medical Center, 2(27/87-3/20/87
7
Travel 4.7%Unit Mgt. 5.5%
Telephone Comm.
8.1%
Paper Handling
38.8%
Figure 3. Emergency Room Nurse Time:Breakdown of Patient Behalf Care by Activity
Verbal Comm.
42.9%
Calls to Cover Staffing 0.8%
Stocking 65.0%
Ordering Supplies 7.3%
Troubleshooting
26.8%
Figure 4. Emergency Room Nurse Time:Breakdown of Unit Support by Activity
Source: Data from the Emergency Room of the University
of Michigan Medical Center, 2/27/87-3120/87
8
C (52.5%) and lowest on Monday (42.3%) but exhibits no clear trend between these extremes. Unit
Support has a low on Tuesday (2.5%), increases to a peak on Saturday (6.0%), and then declines
through Tuesday. The Staff/Education Meeting time is highest on Tuesday (2.0%), and is a very
small percentage throughout the rest of the week.
Personal time plays an important role in appropriate staffing. It is significant to determine the
actual amount of personal time taken in order to see if the allotted personal time is used. Personal
time accounts for 14.6% on Wednesday, while the other days range from 5.5% to 9.7%. Further
investigation (refer to Appendix D) shows that the average Personal time on the day shift of
Wednesday is 18.6%. In addition, the night shift average Personal time on Wednesday is 14.0%.
The category, Personal time, takes up a total of 8.5% of the ER nurses’ 8-hour shift. This turns
out to be 40.8 minutes per shift. The Meal/break activity within personal time takes up 4.7% of the
nurses’ time which is approximately 22.6 minutes per shift. Nurses are allowed a 30 minute meal
and two 15 minute breaks each shift; therefore, a total of one hour is allotted to each nurse for
combined meal and break times each shift. The 22.6 minute figure discovered in this project
appears extremely low; their entire personal time does not total the one hour standard.
The percentages by shift of each general category and Patient Behalf Care activities are
presented in Appendix E. Hands On Care is greatest during the evening shift (47.3%) while
Patient Behalf Care is highest during the night shift (51.0%). Similar to the day to day
comparison, Hands On and Patient Behalf Care demonstrate an inverse relationship from shift to
shift. Another significant point is that Unit Support is greater during the day shift (6.7%) than both
the evening and the night shifts combined (5.9%). Personal time remains fairly constant over all
three shifts. The evening shift has the highest percent of Hands On Care and correspondingly the
lowest percent of Patient Behalf Care and Personal time. The reverse is true during the night shift.
This trend may be the result of a higher nurse to patient ratio, a higher acuity level, or both during
the evening shift compared to the night shift. The validity of this trend will be explored in a later
c section.
9
C Figure 5 and Figure 6 compare Hands On Care to Patient Behalf Care by day. Figure 5
shows the qualitative patterns of Hands On and Patient Behalf Care while Figure 6 provides the
quantitative relationships. These two figures demonstrate a definite inverse relationship between
Hands On and Patient Behalf Care. Statistical studies confirmed the inverse relationship with a
correlation factor of -0.8 at 98% confidence (see Appendix F). Note that only on Mondays and
Saturdays is Hands On greater than Patient behalf Care. A comparison of the general categories by
weekday versus weekend provided in Figure 7 shows that the five general categories remain fairly
constant from weekday to weekend. Unit Support increases 31% and Staff/Education Meeting
decreases 60% from weekday to weekend; these changes are equivalent to only 0.7 minutes/hour
and 0.3 minutes/hour, respectively.
C Patient Volume and Nurse Census
As shown in Figure 8, the average nurse to patient ratio per day reaches its maximum on
C) Thursday (1 nurse to 10.9 patients) and its minimum on Tuesday (1 nurse to 7.9 patients). Figure
6 shows that Hands On care peaked on Monday while Patient Behalf care was at its minimum.
Considering this in relation to Figure 6, where Monday has a relatively high nurse to patient ratio, a
higher nurse to patient ratio seems to require more Hands On and less Patient Behalf care.
However, on Thursday when the average nurse to patient ratio is at its highest point, Hands On
care is at a minimum and Patient Behalf care is at its maximum. If the patients being treated on that
day have lower acuity and so require less Hands On care, this contradiction could be explained by
the difference in acuity level.
Comparing Personal time per nurse per day (Appendix C) with the average nurse to patient
ratio (Figure 8), a general inverse relationship between the percentage of Personal time and average
nurse to patient ratio can be seen. On Wednesday Personal time reaches its peak; however, both
Personal time and the ratio increase. With such a large percentage of Personal time, the average
nurse to patient ratio would be assumed to be relatively low or at a minimum.
10
60
- Hands On Care• Patient Behalf Care
I • I I I I- I
N TUES V THURS FRI SAT SUN
Figure 5. Emergency Room Nurse Time:Percentages of Patient Behalf Care to Hands On Care by Day
Figure 6. Emergency Room Nurse Time:Percentages of Patient Behalf Care to Hands On Care by Day
Source: Data from the Emergency Room of the Universityof Michigan Medical Center. 2127187-3/20187
50
40
30
• Hands On CarePBC
MDN TUES WED THURS FRI SAT SUN
11
0/I0
S WeekdayWeekend
3.8 5.0
____
1.1 0.7
46.6
8.6 8.2
Hands On Patient Behalf Unit Support Staff Ed/Mtg. PersonalCategory
Figure 7. Emergency Room Nurse Time:Percentages of General Categories on Weekdays vs. Weekend
Source: Data from the Emergency Room of the Universityof Michigan Medical Center, 2127/87-3f20/87
12
I
12 10.9
10
8
U,I
zC
0(l)- .-
2
0
Figure 8. Emergency Room: Average Nurse:Patients Ratio by Day
Source: Data from the Emergency Room of the Universityof Michigan Medical Center, 2(27,7-3/2O/87
10.2
MON ]1JES WED THURS FRI SAT SUN
13
C
(..
Patient acuity on Wednesdays may account for this discrepancy, since with lower acuity patients, a
nurse can care for a greater number of patients in a shorter amount of time.
Figure 9 presents the average nurse to patient ratio per shift. Recalling Appendix 5, it is
evident that during the night shift, when Hands On is at a minimum (34.3%) and Patient Behalf
Care is at a maximum (51.0%), the average nurse to patient ratio is a minimum (1 nurse to 4.9
patients). This trend suggests that a low nurse to patient ratio requires less Hands On care,
allowing more time for Patient Behalf care. However, during the evening shift, when Hands On is
at its maximum (47.3%) and Patient Behalf care is at its minimum (42.9%), the average nurse to
patient ratio is at its intermediate value (10.4 patients/nurse). Since we would expect the maximum
Hands On and minimum Patient Behalf care to occur at the maximum nurse to patient ratio, the
patient acuity level must affect the amount of Hands On and Patient Behalf care.
It is clear that the parient acuity level is affecting the nursing time spent on certain activities
and that the acuity levels during the sample period must be determined to verify the findings of this
study. Futhermore, the patient classifications must be determined as they will be used as
parameters in the Simulation Model.
14
N
C
20
0I!0
10
o
13.4
I 10.4
-F
-j
4.9
DAY E’iENIt’C NIGHT
Figure 9. Emergency Room: Average Nurse:Patients Ratio by Shift
Source: Data from the Emergency Room of the Universityof Michigan Medical Center, 2127/87-3f20/87
15
c IV. Simulation Model
The objective of the simulation model is to accurately depict the processes that take place in
the Emergency Services of the University of Michigan Medical Center. This process takes into
account both the patient classification that was previously developed and the work sampling that
was completed in this study. The model presented in Figure 10 is a simplified version of the final
model which will ultimately determine optimal nursing resource requirements and will show how
different staffing patterns effect waiting times and utilization of nurses. This final model can only
be developed after more information (i.e., patient acuity as it affects nursing care) is collected. The
expected completion date is December, 1987.
There are two processes which occur simultaneously in this simulation: the patient process
and the nurse process (see Figure 10). In the patient process, patients are generated into one of the
five acuity based patient classifications, each entering the system from a distinct distribution. The
process that the patients in each class follow is identical. However, each patient class is generated
from a separate distribution. When each patient enters the system, he/she is assigned a length of
stay based on their patient acuity. Then, the patient flows into the admission process. If the patient
is admitted, the admitting time must be added to the assigned length of stay. Admitting time
consists of time needed to obtain a bed and a room for the patient. If the patient is not admitted, the
length of stay remains the same as that initially assigned to the patient. Next, Hands On care time
is assigned according to patient classification. The final assignment of Patient Behalf Care is
dependent on patient class. These assignments are completed, at which time the patient is then
ready to obtain nursing care. The amount of nursing resources the patient needs depends on the
previous three assignments: length of stay, Hands On care, and Patient Behalf Care. When the
patient has been completely treated, he/she is released and exits the system. This completes the
patient process.
The second simultaneous process which occurs is the nurse process. In this segment of the
model, nurses enter the system depending both on the time of day and day of the week.
16
PATJ ewrS
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A&’MI%S ict4
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t4vgiE4
r4uRc6
ffHALF
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igure io. Emergency Services Simulation Model
TIM6 itLOS
Each is given an assignment of either thage, team leader, back hail or critical care nurse. Then each
nurse is assigned a shift length, either 4, 8, or 12 hours. This parameter will allow the nurse to be
released from the system when his/her shift is completed. After the two assignments are given, the
nurse enters report where she is delayed approximately 30 minutes to be updated on the Emergency
Room’s present patient situation. After joining the nursing resource pool, each awaits the arrival of
patients or treats those already in the system. When the shift is completed, the nurse is released
from the system.
As stated earlier, the model presented is simplified and will be expanded upon as information
is collected. In its finished form, the model will assist the Emergency Services in determining
optimal nurse staffing.
C
18
C
Appendix A
Emez.gency Services Nur Staffing Project plan
19
C
EMERGENCY SERVICES NURSE STAFFINGPROJECT PLAN
C
Appendix fl
Data Collection Fo
21
EMERGENCY SUITE WORK SAMPUNG DATA COLLECTiONNAME:
_______________
ASSIGNMENT:
___________
DATE: ..J.J87 BEEPER 1:SHIFT:Start aml( m1 Finish C ml oml- — — ‘ N — — — — — — — — — — —
ACTIVITY 124Se7t111112131415r — — — —
— — — — — — — — — —
Dfr.ctPaterttCar.
Q_ — — — — — — — — — — — —- —- —Cans Iocoverilatflnq — — — — — — — — —
trl1flrfl12IflI fl — — — — — — — — —
FotIowupcaflAdmissionprocesslnq
Ui Troubleshooting — — — — — — — — — — —
Paoino
8 oncafl• AIS Run — — — — — — —
Other — — — — — — — — — — —
OrderfnoSuoolles — — — — — —
Procesasoecimens —
tab reoulsitlon flit-out — — — — —
a. Nurlno documentation — — — — — — — — —
ChnISIn tit tgn — - — — — — — —
(‘$t,ar — — — —
Stockino - — - —
StafflEducatlon mb. — — —
Cmwd nntrni — — — — — — — —
Room1lJnht deanlna — — — — — — — — — — — —
S — — a — — — — — — — — — — — —
, StaffICo-worker — — — — — — — — — — — —
P2tL.nhIVt.I?nr — — — — — — — —
Famysport
Patient transoorlatior, — — — — — — — — — — — — — —
HedresoonsaPatient care off4fte — — — — — — — — — — — — — — —
fllhar :::::::::zzz:zMeeilBresk — — — — — — — — — —
Schedule Mhjstrnent — — — — — — — — — — — — — —
PerôrteiT1rneRecordinoPayrofiOther
— — — — — — — — — — — — — — — —
22
C
Appendix cTabled Bred0of Gene Catego by Day
23
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Tabled Breakdown of General Categories by Shift
25
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Appendix E
Tabled Breakdown of General Categories by Shift and Day
27
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Appendix F
C) Correlation Statistics
29
Results from Correlation/Repress ion:
c Studies were done on the by day data, not the by shift data.
Variables Covanance Correlation R-Squared B1slope) prob.
P:N vs. HOC 0.499 0.094 0.009 0.016 0.841P:N vs. US 0.242 0.166 0.028 0.105 0.722P:N vs. Pers. -0.634 1.208 0.043 -0.063 0 .655P:N vs. PBC -0.565 -0.144 0 .021 -0.034 0.758
PVvs. Pers. -13.11 -0.478 0.229 -1.3 0.278PV vs. HOC 32.03 0.671 0.451 1.05 0 .099PV vs. PBC -16.11 -0.457 0.209 -0.966 0.303PV vs. US -0.257 -0.197 0.039 -1.123 0.672
PBC vs. HOC -18.79 -0.833 0.694
30
C
APpendix G
Average patient volume per shift and per day
31
40
30No. of
Patients20
Ave. Patient Volume Per Day150
123.7
100
No. ofPatients
50
0
50 r
Ave. Patient Volume Per Shift
4
10
0
p
99.0 103.0110.7
p104.5_- 105.7
- 98.7 -
SAT SUN Day£v$DN T1JES WED THURS FRI
Source: Data from the Emergency Room of the Universityof Michigan Medical Center. 2/27/87-3/20/87
32
C
Appen, B
Average nurse vo1un per shift and per day
33
4No. ofNurses
3
2
Source: Data from the Emergency Room of the Universityof Michigan Medical Center. 2/27/87-3/20/87
34
Ave. Nurse Volume Per Shift5
No. ofNurses
3
2
1
0DAY EVENNG NIGHT
Ave. Nurse Volume Per Day (for any given shift)
54.1 4.2
1
0MDN TUES WED THURS FRI SAT SUN
C
Appendix I
Raw data for each activity
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CALCULATIONS AND METHODS IN DETERMINATION OF RESULTS
C MIDAS was used to provide the statistical information of the number of occurences of a specificactivity (n) and mean (x) and std. deviation of beeps for all occurences of that specific activity (SeeActivity Statistics). Multiplying (n) times (x) gave the total number of beeps or samples for aparticular activity. The percentages of each activity or category were calculated by taking the ratioof the number of samples per activity or category divided by the total number of samples.
When entering the data from the data collection forms, it was first necessary to convert all of thetwelve-hour shifts into 1.5 eight-hour shifts. This was accomplished by taking the proportions ofeach activity on the data form. If the shift ran from 7am-7pm, two thirds of the sample size wereallotted to the 7am-3pm (day) shift, and the remaining third of the sample went into the 3pm-1 1pm(evening) shift as a half shift. The proportions for a 7pm-7am shift ran the other way, with onethird of the sample grouped with the evening shift and two thirds with the night shift percentages.
The patient volume was determined by averaging the number of patients over the specific daysduring the collection period. The patient volume was averaged per day (Mon,Tue, Wed, Thu, Fri,Sat, Sun) and per shift (Day, Evening, Night).
The nurse census was determined for shift averages by summing all the nurses working on aparticular shift for the collection period, and dividing by 21 (# days in period). Triage nurses werenot included. For the day averages, the nurse volume per day was summed and averaged with theother nurse volumes for the same day, i.e., all the Monday nurses were added up and divided by 3,since there were three Mondays included in the sample period. For split shifts, such as 3 nursesworking 4 hours of a shift and 4 nurses working the second four hours, an average of 3.5 nurseswas used. Subtracting out the triage nurses leaves the real average for the described shift, 2.5nurses.
Patient to nurse ratios were calculated by taking the number of patients divided by the number ofnurses for a particular shift or day.
In the graphs, all figures were rounded off to two decimal places.
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