Staffing and Scheduling – Part I
HCM 540 – Operations
Management
Labor Resource Management
“[Nurse] Staffing is one of those timeless
topics that has meaning in every type of
health care environment and situation.”
Staffing costs are the largest component of
most healthcare delivery organizations

managers are obligated to develop, use and
maintain a high quality staffing process that
balances service levels and costs
General staffing principles
Details depend on specifics of department
and institution
High Level Staffing Framework
Budgeting and
Planning
• Annual or as needed
• Planned capacity
• Staffing/scheduling
policies
Tactical Staff
Scheduling
Analysis
Budget, staffing plan, policies
Operational
staffing/scheduling
• Every 2-6 weeks
• Target staffing levels
• Create employee
schedules for core staff
Realized shortages
and surpluses
Staff schedule
Daily allocation
• Ongoing
• Reacting to staffing
variances
• Floating staff,
overtime, contract
staff, agencies
Adapted from Abernathy et. al. (1973),
Hershey et. al. (1981), Warner et. al. (1991)
Labor Resource Management
Framework
Quantify Staffing
Requirements
4. Ongoing
Management
of Resources
3. Developing
Staff
Schedules
Labor
Resource
Management
Framework
1. Understanding your
Workload
2. Converting
Workload to
Staffing Requirements
Staffing Related Challenges
Hospital downsizing
Qualification level of caregivers decreasing
Hospital trained “generalist” caregivers replacing
specialist, professional caregivers
Specialist caregivers taking on wider range of tasks
and responsibilities
Patient acuity levels increasing
Nursing shortage
Patient focused care model


decentralization of support services, new staff types (e.g.
care partner), redefined roles
jury still out on impact on quality of care, patient safety, cost
New JCAHO Requirements to assess Staffing
Effectiveness (July 1, 2002)
JCAHO Staffing Effectiveness
Screening Indicators
Staffing Effectiveness is defined as the number,
competency, and skill mix of staff involved in
providing health care services.
Links between staffing effectiveness and patient
safety have become the focus of national concern
JCAHO has concluded that mandating specific staffto-patient ratios will be unsuccessful to address the
issues
An approach based on the use of screening indicators
to monitor staffing effectiveness, analysis of the data,
and action based on that analysis would be more
successful.
JCAHO Staffing Effectiveness
Screening Indicators
Each organization
selects and
implements a
minimum of 4
screen indicators



one HR screening
indicator
one clinical / service
screening indicator
2 additional
Overtime (HR)
Family Complaints (C/S)
Patient Complaints (C/S)
Staff vacancy rate (HR)
Staff satisfactions (HR)
Patient Falls (C/S)
Adverse drug event (C/S)
Staff turnover rate (HR)
Understaffing as compared to organization’s staffing plan (HR)
Nursing care hours per patient day (HR)
Staff injuries on the job (HR)
Injuries to patients (C/S)
Skin breakdown (C/S)
On-call or per diem use (HR)
Sick time (HR)
Pneumonia (C/S)
Post-operative infections (C/S)
Urinary tract infection (C/S)
Upper gastrointestinal bleeding (C/S)
Shock/cardiac arrest (C/S)
Length of stay (C/S)
Labor Resource Management
There is a science and an art to labor resource
management
The Science:



measuring and predicting workload demand
translating demand to staff
scheduling
The Art:


the “People” dimension of staffing
choosing proper model or approach to specific
staffing problems
Staffing Methods Depend on the
Nature of the Work System
Inpatient Nursing
Episodic care

ER, Surgical Recovery, Surgical Suites, Short Stay
Unit, LDR, OP Clinics, Card. cath, PT/OT, Resp.
care
Lab, Imaging, Pharmacy
Medical records, transcription, financial
services
Appointment scheduling, other call centers
Maintenance, transport, materials
management
About Labor Resource
Management . . .
No single staffing method or model is the
right one
Hundreds of ways to organize staffing
How do you measure success of a model?


Are standards for quality and customer satisfaction
met?
Is staffing delivered at an affordable and
sustainable cost?
Factors of
Labor Resource Management
Workload volumes are budgeted or projected
annually

Actual Workload will be variable
Staffing plans are driven by workload requirements


But staffing response plans must be flexible and variable
Increased Staff Flexibility is necessary and desirable
Costs must continue to be stable or decrease


Managers are accountable for labor cost per unit of service
Resource management must be tough on costs, and
particularly tough on “waste”
How do organizations
traditionally staff?
Starting with the Budget . . .
Budget the Same Number of FTEs Each Month
Unit budgeted for an
ADC of 18 across
both busier months
and traditionally
slower months.
ADC
Hours
Required
FTEs
Required
HPPD
Anywhere Hospital
2001 Nursing Salary Budget
Unit: 3 South-Medical
Jan
18
Feb
18
Mar
18
Apr
18
May
18
Jun
18
Jul
18
Aug
18
Sep
18
Oct
18
Nov
18
Dec
18
4,026
4,026
4,026 4,026 4,026 4,026 4,026 4,026 4,026 4,026 4,026 4,026
23.3
7.2
23.3
7.2
23.3
7.2
Where did the workload
driver for the budget come
from in the first place?
23.3
7.2
23.3
7.2
23.3
7.2
23.3
7.2
23.3
7.2
23.3
7.2
23.3
7.2
23.3
7.2
23.3
7.2
Same number of
FTEs allocated to
each month
How do organizations
traditionally staff?
Many organizations staff according to a fixed
number of shifts.
Hospitals usually have 2 or 3 shifts per day,with
pre-specified durations and starting times.
The majority of the staff are often full-time, 40
hour per week employees.
Ignore or simplify details of time of day based
staffing needs as well as service level
requirements such as test turnaround times
and patient wait times.
How do organizations
traditionally staff?
A Struggle to Staff Each Day
Significant reliance on
expensive overtime
and agency labor to
staff up quickly
Daily Census
30
Medical Unit Daily Census
Unit often ends up
running short-staffed
when census spikes,
a big dissatisfier for the
staff.
25
20
Budgeted
ADC =18
15
10
5
0
What should the core
staff level be? The
mean, the 75th, 85th,
95th percentile?
Staff sent home or
floated, or unit remains
overstaffed when
census drops.
How to meet the daily
staffing demand
Full-time & part-time, regular (“Core”)

Float pool

Overtime
Contingent
Agency
Contingent

& Agency OT
Part-time
What you don’t want to do . . .
1. Understanding your
Workload
What are the primary workload drivers for your department?
What does it look like on week-ends vs. week-days?
Shift based vs. time of day based? Size of planning period (e.g.
½ hourly, hourly, 4-hour, 8-hour etc.)
What does it look like by time of day and day of week?
Has the workload shifted over time? Trend up or down?
Is your workload seasonal?
Do you utilize a tool to collect, track and trend your workload?
Why not?
Different classes or types of workload?
Service levels by class? Different priorities?
Degree of scheduling of work?
Operations Analysis Before
Staffing Analysis
Just as we don’t want to IT
What is being done?

classification of workload
enable a bad process, we don’t
want to staff a bad process.
Should it be done?

appropriateness, practice pattern variation
How is it done?

methods analysis, work measurement, workplace design
Who is doing it?

appropriate skill level
When is it done?

time of day, day of week,
When must it be done by?

response time
How well is it done?

quality
Charting Workload – A 1st Step
Monday
Preop/Post-op Space Planning - Option 1
Preop B Simulated Occupancy
Preop for Area A and Phase 2 for Area C
25
Avg Phase 2
Avg Preop
20
95%ile +10% Growth
Patients
14
15
T otal 95%ile
13
10
Avg
12
95th %tile
11
10
5
Simulated preop
occupancy based on
average preop time of 90
minutes. Though
capacity exceeded by
95%ile under 10% growth
scenario, results for
Preop D suggest 90
minute preop time too
long.
Capacity=9
9
8
0:
00
2:
00
4:
00
6:
00
8:
00
10
:0
0
12
:0
0
14
:0
0
16
:0
0
18
:0
0
20
:0
0
22
:0
0
Occupancy
0
7
6
5
Time of Day
4
3
2
Avg Visits per Day
1
350
M
9:
00
A
M
10
:3
0
A
M
12
:0
0
PM
1:
30
PM
3:
00
PM
4:
30
PM
6:
00
PM
7:
30
PM
9:
00
PM
10
:3
0
PM
M
A
7:
30
M
A
6:
00
M
4:
30
A
M
A
A
3:
00
12
:0
0
1:
30
A
M
0
Time of Week
302
300
Total
264
247
No. of Visits
250
235
70
209
Avg Volume
60
200
50
150
40
Total
30
100
Mon
Tues
Wed
Day of Week
Thurs
Fri
20
10
0
1
2
3
Area A
4
5
6
7
1
2
3
4
5
6
7
Area A/Trauma Resusc
1
2
3
Area B
4
5
6
7
1
2
3
4
5
6
Area C/Pediatric Car
CheckInLoc DayOfWeek
7
1
2
3
4
5
6
Area C/Prompt Care
7
1
2
3
Area D
4
5
6
7
Productivity and Productivity
Management
See Chapters on Productivity and
Staffing that I handed out.
Related concepts





work measurement
work simplification
operations analysis
staffing analysis
workforce planning
Output
Productivity 
Input
Many ways to define the
outputs and inputs
depending on the
situation
Labor Productivity Inputs
Usually expressed in labor hours or $
Subdivide into productive and non-productive
Data usually available from time & attendance or
payroll systems (e.g. Kronos)
Total labor hours = worked hours + non-worked paid hrs
 more control over
worked hrs
 worked hrs usually used
in productivity
calculations
 non-prod. hrs may be
included as “tracking
variable”
 Managers & sec’s often
treated as fixed





regular
OT
premium
agency
contingent




vacation
sick
personal
holiday
Labor Productivity Outputs
Multitude of output measures depending on dept.
Implicitly, the measures are usually related to time or $
Data may be available from one of numerous
departmental or hospital information systems
Nursing units
LDR
General surgery
Recovery room
Emergency Dept.
Hematology
Ambulance service
Physical Therapy
Radiation Therapy
Radiology - Dx
Admitting
Appt Center
OP Clinic
Patient days (by acuity)
# deliveries, # c-sections
Patients, procedures, surgical hours
Patients (by acuity)
Visits (by acuity)
patients, procedures, CAP SBTs
Trips, miles
Modalities
Patients, procedures
Procedures (type)
# admissions, # transfers
appts scheduled
visits, RVUs
CAP
Work Measurement Techniques
Time studies




standard time required for a trained employee to
produce one unit of output at an acceptable
quality level using the approved method
direct measurement of task duration
take many samples and use statistics to develop
“raw time”
apply personal, fatigue and delay (PFD)
allowances (5-15%) to inflate raw time and create
“standard time”
Work sampling
Expert judgement

low volume tasks
Time Standards in Healthcare
Attempts since the 1960s to apply industrial
work measurement techniques to healthcare
Use “time studies” to estimate standard
amount of time to do some task
Success has depended on the nature of the
department




degree of similarity with manufacturing
simultaneity of tasks complicates things
difficult to capture assessment and decision
making tasks
some areas such as lab have had many years of
R&D put into development of accurate standards
Time standard based productivity systems
can be very difficult to maintain
Work Sampling
“a measurement technique for the quantitative analysis of nonrepetitive or irregularly occurring activity”
observer takes series of random observations on a “thing” of
interest (e.g. clinic staff) and observes its “state” (direct patient
care, indirect patient care, stocking supplies, on break,
answering phone, etc.)
appeal to statistical sampling theory to conclude that:
# Observationsi
 proportion of time doing activity i
 # Observations j
j
Easier to perform than time study, especially for irregular work
such as health care delivery
Difficult to capture “knowledge work” such as nursing
assessment
Used, along with time studies, in the development of nursing
classification systems, estimation of indirect or constant
activities
HME members interested in Palm PC and Handheld PC as data collectors:
We now have put our "Computer-Aided Work Samplng [CAWS/E] Manual (COMPLETE)"
up on the COMPUTER page of the C-FOUR website << http://www.c-four.com
for anyone to download (if you have Adobe Acrobat).
>>
We plan to have our
Computer-Integrated Time Study [CITS] Manual (COMPLETE)" up sometime next
week.
Both systems use either the handheld PC (H/PC) or the Palm PC as data
collectors.
These are fairly technical manuals that may be of interest to
the more advanced Mgt. Engineers.
There are some other downloads available from that page also.
Carl
Carl R. Lindenmeyer
VP and President Elect, IIE Chapter #247 (Upstate SC)
Professor Emeritus of Industrial Engineering
President, C-FOUR
102 East Main Street, Post Office Box 808
Pendleton, SC
29670-0808
(864) 624-1234 (voice)
(864) 646-2450 (fax)
website:
http://www.c-four.com
HME Yahoo Group
Variable and Constant Tasks
Variable tasks are dependant on workload

total time required related to volume of procedures,
patients, patient days, tests, etc.
Constant tasks are less dependent on workload



in-service, orientation, staff meetings, supply mgt, quality
assurance, other admin
total constant activities can be converted to total hours per
day
constant time actually related to staff size and thus should
be modified as staffing levels change
N
W   siVi  cD
i 1
W = total hours of workload in D days
si = standard hours for work type i
Vi = volume of work type i in D days
c = constant task hours per day
D = # of days
Aggregate vs. Disaggregated Workload
Use 80/20 principle to classify workload into a
manageable number of types





different workload types may require vastly
different levels of resources
productivity monitoring is less sensitive to changes
in workload mix
can assess effects of changes in workload mix
make sure you can get the data for each workload
type you define
can apply labor standards, RVUs, or other detailed
resource adjustment methods to disaggregated
data
Sources of Workload Data
Department Information Systems



Lab Information System (LIS)
Radiology Information System (RIS)
Patient census & acuity system
Hospital Systems


Registration System (hospital admissions, patient
visits, etc.)
Billing Systems
Log sheets, tally sheets


Examples: OBLog Spreadsheets
Use Data Validation rules if collecting data with
Excel
Example Productivity
Monitoring System Report
appt99c.xls
1999 CORPORATE APPOINTMENT CENTER PMS REPORT
So, what’s the target?
Standard hours based on weighted average
time standards for numerous appt types
Productivity Monitoring Report
25,000
76.0
75.0
74.0
20,000
73.0
15,000
71.0
70.0
10,000
69.0
68.0
5,000
67.0
66.0
0
65.0
January
February
March
April
May
June
July
% Productivity
72.0
Units
Actual Hrs
Productivity
The Labor Hour Inputs
Bi-weekly pay data rolled
carefully into monthly data
173
1492
1162
2347
849
945
530
599
795
344
118
163
1349
954
1436
1267
105
1397
132
95
1338
2632
751
1054
518
602
727
306
816
2727
1103
1179
550
709
819
460
1303
1118
2526
918
1068
529
600
810
292
1111
1330
1160
2333
921
927
450
444
478
250
842
1378
1163
2696
1000
1089
609
572
739
312
847
107
1250
1047
2496
938
1054
599
479
628
269
1006
1394
89
1322
1139
2846
994
1162
604
560
717
321
149
1342
1215
3079
1099
739
523
569
659
288
870
111
1289
1066
3104
1071
881
453
497
687
335
1201
231
1297
1138
2959
1112
1017
432
393
654
223
1241
0
0
0
0
0
0
0
0
0
0
0
Anesthesia
0.12
7.36
Advanced
Cat
Mammo-
Testing
Scan (CT)
graphy
0.19
0.20
11.52
11.73
0.18
10.7
MRI
0.22
13.12
Ultrasound
0.16
9.6
Endo-
Nuclear
OB
scopy
Medicine
Ultrasound
0.12
7.03
0.14
8.6
0.15
8.97
Outpatient
Inpatient
0.14
8.34
Surgery
0.17
10.49
21.22
286.46
227.17
418.55
185.65
151.20
62.10
85.86
118.85
47.82
233.93
14.47
259.01
186.51
469.37
164.22
168.64
60.69
86.29
108.69
42.53
142.66
19.99
275.71
247.70
486.32
241.19
188.64
64.44
101.62
122.44
63.94
227.81
12.88
268.22
218.57
450.47
200.74
170.88
61.98
86.00
121.10
40.59
194.24
16.19
255.36
226.78
416.05
201.39
148.32
52.73
63.64
71.46
34.75
147.21
11.65
264.58
227.37
480.79
218.67
174.24
71.35
81.99
110.48
43.37
148.08
13.13
240.00
204.69
445.12
205.11
168.64
70.18
68.66
93.89
37.39
175.88
10.92
253.82
222.67
507.54
217.35
185.92
70.77
80.27
107.19
44.62
243.72
18.28
257.66
237.53
549.09
240.31
118.24
61.28
81.56
98.52
40.03
152.11
13.62
247.49
208.40
553.55
234.19
140.96
53.08
71.24
102.71
46.57
209.97
These volumes & standards are NOT accurate; for illustration only
Using Productivity Reports
Tracking general trends in workload, labor use, and productivity



large changes trigger deeper investigation
combine with service or quality measures
graphs along with tabular data
Can be very difficult to develop a “goal” or “target productivity”




depts with highly variable workload and significant response time
or turnaround time constraints (service level targets)
100% productivity is NOT necessarily a good goal
May need queueing or simulation models to address service level
effects
May need optimization models to address scheduling issues
Basis for staffing analysis and labor budgeting

time standard based outputs facilitate this
Benchmarking

use of commercial systems or widely used workload measurement
methods facilitates comparisons with other institutions (e.g. LMIP
from College of American Pathologists or HMC)
Why Not 100% Productivity?
Service level constraints for systems
with significant queueing component
Minimum required staffing levels

e.g. 2 RNs in PACU at all times
Peaks and valleys in demand
Staff scheduling inefficiencies
Total control of labor supply is
impossible
Staffing Analysis
Preview
Corporate Appointment Center
Estimated Staffing Needs
Variable and Constant Workload
variable workload
driven by incoming
phone calls for
appts
Queuing model
used to find
staffing levels to
meet STA
targets.
Average
Standard
Split
Hours/Month (1)
22
1738.0
23
592.0
24
669.0
Constant
511.6
Utilization
Goal (2)
65%
65%
100%
#N/A
Total Actual
Hours/Month
Needed (3)
2673.8
910.8
669.0
511.6
Full Time Equivalent
=40 hrs/wk
FTEs (4)
15.4
5.3
3.9
3.0
Subtotal A
27.5
+ Coverage (5)
2.5
Subtotal B
30.0
+ Benefit Allowance (6)
3.1
Total (based on 30 second STA goal)
33.1
Note: A 60 second STA would require approximately 1.5 FTEs less.
Target Utilization (7)
(1)
(2)
(3)
(4)
(5)
(6)
(7)
70.1%
From scheduling
analysis (next time)
Percentage of working days
in year subject to paid time
off (vacation, holiday, sick,
personal). Typically around
10-15%
effect of service level on staffing
weighted avg of split specific goals
Based on Volumes reported in 1999 Productivity report.
Utilization goals less than 100% reflect the 30 second speed to answer service level.
Standard hours/utilization goal
Total hours needed/173.8 hours per month per FTE (4.345 wks/mo)
Reflects staff needed due to peaks and valleys in workload and staff scheduling constraints.
Based on Vacation/Sick report.
The weighted average overall utilization goal. The average standard hours per month used
to calculate this utilization was increased by 137 hrs/month to take into account the address
cards that are filled out during idle times for Split 22.
Patient Classification (Acuity) Systems
A widely used approach to help manage staffing and define
services in nursing units, recovery rooms, EDs

Develop patient classes and associated indicators defining each
class
 weights (times) associated with each class
 direct and indirect patient care components


How many hours of nursing labor at what skill level are needed
which balance patient outcomes and rational resource use?
1-3 shift ahead staffing predictions, retrospective staffing analysis
for budgeting
The “First” PCS – Wolfe and Young, “Staffing the Nursing Unit”,
Nursing Research, Summer 1965, 14, 3.



3 classes – 1.Self-care, 2.intermediate care, 3.total care
I = 0.5N1 + 1.0N2 + 2.5N3 (total direct care index estimate)
Patient acuity = I + 20 (20 hrs of indirect care per 8hr shift per 30
bed unit)
 work sampling to develop direct/indirect relationship
Issues with PCS
Traditional time study roots– discrete standardized tasks,
frequency, standard times, census by class, non-productive time
 realities of nursing











high task variability
admissions/disch/transfer impacts
physical, social, ethical, emotional, financial interactions
clinical decision making
non-linear nature of the work
patient plays role in care
Multi-tasking
Variability across caregivers (delivery and rating)
acuity creep
standards maintenance
massive distrust of many systems in practice
Commercial Systems
OneStaff
GRASP
ENEPCS
Home grown (50%-70%)!!!
Evolution of Nursing PCS
1970s – Historic nurse to patient ratios

no cost incentive to adapt to census
1980s – Industrial based PCS emerges

DRGs, managed care, provide incentive
1990s – Incremental improvements to PCS


hospital downsizing vs. call for legislated minimum
nurse:patient ratios (California AB 394, 1999)
shortcomings of industrial based PCS still not
addressed
Minimum Nurse Staffing Ratios in California
Acute Care Hospitals www.chcf.org
“minimum, specific, and numerical licensed nurse-to-patient
ratios by licensed nurse classification and by hospital unit”
Some evidence that higher n:p are related to a number of
positive outcomes
Currently wide variation in delivered n:p, RN HPPD
Implementation issues




relationship to mandated PCS (Title 22 of Cal. Code)
will the min become the average? if so, so what?
nursing shortage in California
cost implications for hospitals staffing below the min (4.6%-30.7%)
on already stressed system
Different groups (nurse union based and hospital based) are
proposing widely different ratios


See Table 1
PCS are attacked as being manipulated for budgeting purposes and
are “acuity fraud”
Recent version of law
seems to indicate 1:5
ratio
SEIU is the Service
Employees
International Union
CHA is the California
Hospital Association
http://www.calhealth.org/
PCS – The Next Generation?
Malloch et al.
Proposed Framework



time/motion + expert nurse estimation
clear job descriptions
expert caregivers – categorization, allocation,
validation, outcomes
 Table 4. Comprehensive Unit of Service



standardized nursing nomenclature (NIC, NOC)
incorporate caregiver variability
low cost, implementable software (good luck)
Many (over 1000) PCS
Applications
PACU (ASPAN)


Typically 3-6 classes with associated nurse to
patient ratios
admit – monitor – discharge phases
Inpatient OB

ACOG standards
Emergency Nursing

EMERGE (Medicus based)
Cardiac Cath Lab

Urbanowicz, “An evaluation of an acuity system as it applies
to a cardiac catheterization laboratory”, Computers in
Nursing, 16, 3, 1999, 129-134.
One Use of PCS - Inpatient Unit
Staffing Requirements – The “GRID”
These staffing ratios
are for illustration
purposes only
2. Converting Workload to Staffing Requirements
Detailed methodology depends on the specific
situation, but general approach (see Appointment
Center example on previous slide):
1. convert forecasted future work to minimum core staff
required staff using time standards (variable & constant
tasks, HHPPD), classification/acuity systems, nurse to patient
ratios
2. do the above for the “appropriate” time interval (hourly, shift,
daily, etc.)
3. make necessary upward adjustments to account for service
level constraints
1. simple normal distribution of work assumption (analogous to
choosing an overflow percentage limit in bedsizing)
2. queueing or simulation models
3. before doing this, back out constant activities and variable
activities that are NOT time sensitive (i.e. can be delayed and
done when time permits)
2. Converting Workload to Staffing Requirements
(cont)
4.
Do “Scheduling Analysis” to develop a workable set of
scheduling policies and practices that allow you create
schedules that meet your staffing requirements, conform to
institutional work rules, attempt to satisfy preferences of the
staff, and do it at minimum cost


5.
Steps 3 and 4 gives you some excess staff that may be utilized
for constant activities or other less time sensitive variable
activities
•
6.
can be very complex; we’ll do this next time
realities of scheduling will often lead to a small upward adjustment
of total staff needed
make judgment as to whether excess staff is sufficient for such
activities; if not, add additional staff based on hours of work
needed
Finally, calculate Benefit Allowance as a percentage of total
working days per year that are eligible (or taken) as paid time
off and increase the total paid staff budget by this amount.
A Few More Staffing Examples
Inpatient OB, PACUs, short stay units, emergency






forecasted volume by patient type based on historical data and/or
trends in patient demographics
used nurse:patient ratios by patient type (ACOG)
used simulation model to estimate distribution of staffing needs
used an upper percentile of staffing needs and reduced it by
managerial judgment of “degrees of freedom” available to cope
with high demand
scheduling analysis to match staff with demand
similar approach but using Hillmaker instead of simulation can be
used with retrospective data
Operating room nurses and techs



hours of operation for each OR
nurse & techs needed by OR (service dependent)
additional staff as “floaters”
A Few Staffing Examples
Appointment center, hospital operators, registration
areas




historical volume data from ACD, hospital IS
time standards for high volume work classes
used queueing models to estimate staffing needs subject to
service level targets
scheduling analysis
Other approaches


use FTE:workload indicator ratios based on benchmarks
from other institutions and/or managerial judgement
Time standards for high volume procedures with productivity
goal adjusted based on work sampling or managerial
judgement
 just like target occupancy for beds
Staffing a Centralized Appointment
Scheduling System in Lourdes Hospital
Very nice application of a simple queueing model to appt center
staffing (class project)
Advantages of centralized scheduling?
Service dissatisfiers? Impacts?
Prior emphasis on “high staff utilization” was the wrong goal
Well accepted approach of using M/M/c queueing model with time
of day specific arrival rates

found service time were NOT exponential but that M/M/c worked very
well anyway (insensitive to actual distribution of call time)
Created staffing tables to facilitate managerial use (see Table 2)
Used heuristic (common sense and trial and error) approach to
adjust staff schedules to implement new staffing patterns with no
staff adds
Interfaces 21:5 Sept-Oct 1991 (pp. 1-11)
The Challenge of Staff Scheduling
1
Postpartum Staffing Needs
45
40
Nurses
35
30
25
20
15
10
5
Sat 06 pm
Sat 12 pm
Sat 06 am
Sat 12 am
Fri 06 pm
Fri 12 pm
Fri 06 am
Fri 12 am
Thu 06 pm
Thu 12 pm
Thu 06 am
Thu 12 am
Wed 06 pm
Wed 12 pm
Wed 06 am
Wed 12 am
Tue 06 pm
Tue 12 pm
Tue 06 am
Tue 12 am
Mon 06 pm
Mon 12 pm
Mon 06 am
Mon 12 am
Sun 06 pm
Sun 12 pm
Sun 06 am
Sun 12 am
0
So…, how much staff is needed and how should they by scheduled?
2
Position
Tour Type
FTE Sun Mon Tue Wed Thu
Fri
Sat
Tour Type Tot FTEs 3
1
2
3
4
5
6
7
(8 hrs, 5 days/wk)
(8,5)
(8,3)
(10,4)
(10,4)
(12,3)
(12,4)
1.0 O
1.0 O
0.6 O
1.0 O
1.0 O
1.0 O
1.0 7a-7p
FTE = Full Time Equivalent (40 hrs/wk = 1.0 FTE)
7a-3p
3p-11p
8a-4p
7a-5p
7a-5p
O
7a-7p
7a-3p
3p-11p
8a-4p
7a-5p
8a-6p
7a-7p
O
7a-3p
3p-11p
8a-4p
O
7a-5p
7a-7p
7a-7p
7a-3p
3p-11p
O
7a-5p
O
O
7a-7p
O
7a-3p
3p-11p O
O
O
7a-5p
O
8a-6p
O
7a-7p
O
O
O
(8,5)
(8,3)
(10,4)
(12,3)
30.0
6.6
4.0
22.0
62.6
Staff Scheduling - It’s a Problem
Policies and practices affect total labor cost.

little “tactical” scheduling analysis done
Overstaffing increases labor costs while understaffing may impact
quality of care or service
Presents difficult combinatorial problems.
Consumes costly managerial time and effort; ad-hoc methods are
the rule.
Bias often to favor employee over institutional needs.
Large impact on employee dissatisfaction and turnover
Not only in healthcare - police, fast food, call centers, airlines
Computerized systems under-utilized and often require inputs
which themselves are the solution to a difficult scheduling
analysis problem.