Developing a Staffing Budget
Nursing Resource Management
Staffing
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Overview
Budget
Schedule
Daily Staffing
Expected Fluctuation Plan
Peak Demand
Management Information
I. Staffing Overview
• Why is staffing so important?
– Nursing Salary & wages are 68% of the Nursing direct
expense budget.
– Nursing Salary & Wages are 15% of the hospital direct
expense budget.
– Scheduling is a major reason nurses change jobs
– Nurse Managers spend a lot of their time with staffing
issues.
Staffing Overview
• Overall staffing strategy
– addresses volume
– addresses staffing
strategies
Staffing Overview
• Certain census levels, up to the
ADC require a core unit staff .
• Probable census levels rely on
internal staff
• Possible census levels utilize
internal staff and increased
compensation
• Peak census may require
outside staff, expensive
compensation and limitation of
benefits.
Budgeting Staff-Direct Caregivers
• Volume X HPPD or HPV = Required Patient Care Hours
• Volume determination
– The cornerstone in calculating staffing needs
– The unit of service for most hospitals is patient days
– Some departments may use visits or procedures for their unit of
service
– Volume projections are not usually controlled totally by the Nurse
Manager
– ADC is calculated by dividing total volume by 365.
Budget Staff-Direct Caregivers
• Volume
– Volume must be forecast for the entire year
– The forecast must also include the distribution of
volume, by month, day of the week, etc.
– Forecasts are usually based on past history and
adjusted by the Nurse Manager.
– The Nurse Manager must add her expertise and add or
subtract volume based on her knowledge of the patient
population and programs being offered.
Budgeting Staff
Required Patient Care Hours
• Determine the total number of patient days (visits).
• Determine from your patient classification system
the number of days (visits) in each classification.
• Multiply the HPPD per classification, times the
number of days budgeted (or HPV times visits).
• Total the number of patient care hours needed.
Budgeting Staff
Required Patient Care Hours
Required Patient Care Hours
Patient
Classification
Number of Patient Days
HPPD
Total Hours
1
1500
2.5
3750
2
3700
4.7
17,390
3
2400
8.0
19,200
4
900
12.2
10,980
5
500
19.0
9500
Total
9000
60,820
Budgeting for Staffing
Required Patient Care Hours
7200 Required Patient Care Hours
Patient
Classification
Number of Patient Days
HPPD
Total Hours
1
6300
9.72
61,236
2 (1:3)
190
9.8
1862
3(1:2)
9
13.8
1242
4(1:1)
1
25.8
25.8
5(2:1)
0
Total
6500
64,366
Budgeting Staff
• Used for budgeting core staff to a unit
Total FTE needed =
Total Patient Care Hours
#productive hrs./FTE
Budget for Staffing
Non Productive Time
Productive Hours/Paid Hours=% Productive
% Productive X 2080 = #Productive hr/FTE
Budgeting Staff
• Daily FTE required-used to plan daily staffing
Total Patient Care Hours
365
= Daily Hours of Care
For 8 hour shifts Daily Hours/8
For 12 hour shifts Daily Hours/12
Budgeting Staff
• Total FTE Budget
– Used to allocate core staff to units
– Allocates staff to cover 24/7, vacation, sick, FMLA
Budgeting Staff
• Daily FTE Needs
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Used to develop basic staffing pattern
Divided by shifts
Divided by skill mix
Equals core staffing pattern
Budgeting Staff
• Shift-to Shift Breakdown
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Based on patient needs at different times of the day
Start by identifying census on the different shifts
ICUs usually D/E/N-.33/.33/.33
More units are moving to ICU-type breakdown due to
shorter LOS, increased acuity
Budgeted Staffing
• Skill Mix
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Based on patient needs
ICUs usually 90-100% RN
General Care Units usually- > 60% RN
Rehab/Psych Units usually- ~50%
Budgeting Staff-Patient Outcomes
• Needleman & Buerhaus et al. (2001) Strong consistent
relationships between nurse staffing and UTI, pneumonia,
LOS, UGI bleeds and shock. In major surgical patients
failure to rescue was also related to nurse staffing.
• Blegan et al. (2001) Decreased med errors with % RN up to
87%, no relationship to BSN, exp.
• Sasichay-Akkadechanunt et al. (2003) Total nurse staffing
was related to inpatient mortality. No relationship of
mortality to %RN, RN experience or % BSN.
Budgeting Staff-Patient Outcomes
• Potter et al. (2003) Decreased RN hours> patient’s
increased perception of pain & higher RN hours > higher
perception of satisfaction by patients.
• Cho et al. (2003) An increase of 1 HPPD associated with
8.9% decrease in odds of pneumonia, 10% increase in
%RN associated with 9.5% decrease in odds of
pneumonia, increased HPPD > higher probability of
pressure ulcers
Budgeting Staff-Patient Outcomes
• Aiken et al. (2002) Each additional patient cared for by a
nurse was associated with a 7% increase likelihood of
dying within 30 days of admission, and odds of failure to
rescue, a 23% increase in nurse burnout and a 15%
increase in job dissatisfaction.
• Rogers et al. (2004) Errors and near errors more likely to
occur when nurses work >12 hours.
• Estabrooks et al. (2005) Decreased mortality with
increased BSN & increased RN mix.
Budgeting Staff-Patient Outcomes
• Needleman et al. (2006) Increased skill mix to 75%
results in better patient care (decreased LOS,
deaths) and cost savings. Increasing care hours
and increasing care hours and RN % was not.
Budgeting Staff-Indirect Caregivers
• Secretaries and non-nurses
• Other Nurses
– Managers
– Education
– CNS, NP, CNM,
III. Scheduling Staff
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Pattern of Core staff
Patient flow, placement guidelines
Unit Activity Monitors -ADT Factors
Vacation/FMLA
Policies & Procedures to support Staffing Plan
IV. Daily Staffing
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24 hour plan
Consistent and continuous patient care
Ensure availability of competent staff
High value on cross training
Have employees work in primary unit, as much as
possible
• Reduce unfair competition between units
• Deal with special resource requirements
Daily Staffing
• Fine-tuning to cover volume changes acuity
changes, call offs
• Floating plan, plan to replace deficits
• Meeting increased/peak demand
• Low census management plans
– cancellation procedure, increased cost out first
• Plan for 7-10 days ahead
IV. Expected Fluctuation Plan
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Internal Float Pools
Floating
PRN Staff
Overtime
Expected Fluctuation Plan
Agency
Overtime
Travelers
Total
2001
2002
2003
2004
2005
2006
5.4%
5.4%
2.4%
5.3%
4.4%
5.1%
1.9%
5.6%
4.6%
4.4%
9.5%
5.3%
1.4%
4.2%
1.2%
3.5%
7.6%
5.6%
8.7%
15.2%
8.2%
13.2%
21.5%
16.0%
VI. Peak Demand Management
• Bonuses
• Agencies
• Use of other resources (Nurse Managers,
Educators, CNS, other staff)
• Diversion Plans
VII. Low Census Management
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Policies & Procedures
Canceling most expensive staff first
Voluntary leaves
Hospital procedure for canceling shifts
Lay-offs
VII. Management Information
Systems to Support Staffing
• Prospective data-operations budget
• Current data-daily management reports
– Actual versus required staff variance
– Actual versus budgeted census
• Retrospective-Productivity Analysis
• Benchmarking
• Quality data
• Budgeted versus actual
Management Information Systems to
Support Staffing
• Retrospective Analysis, cont
– Audits of schedules
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% unfilled
holes
OT
% agency
# requests granted/denied