Budgeting Basics

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Budgeting Basic$ for Nurse Staffing NH Staffing Toolkit July 2010

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Money should be a tree

Transcript of Budgeting Basics

Page 1: Budgeting Basics

Budgeting Basic$

for Nurse Staffing

NH Staffing Toolkit July 2010

Page 2: Budgeting Basics

Nurse Staffing

• Overview• Budget• Schedule• Daily Staffing• Expected Fluctuation Plan• Peak Demand• Management Information

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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

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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– Average daily census is calculated by dividing total volume by 365.

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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 for new programs.

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Budgeting StaffRequired 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.

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Sample Budgeting StaffRequired Patient Care Hours

Re q u ire d P a tie nt C a re H o urs

P a tie ntC la ss ifi c atio n

N um be r o f P a tie nt D a y s H P P D T o ta l H o urs

1 15 0 0 2.5 3 75 0

2 37 0 0 4.7 1 7 ,3 9 0

3 24 0 0 8.0 1 9 ,2 0 0

4 9 0 0 1 2.2 1 0 ,9 8 0

5 5 0 0 1 9.0 9 50 0

T o ta l 90 0 0 6 0 ,8 2 0

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Sample Budgeting for StaffingRequired Patient Care Hours

7 2 00 R e qu ire d P a tie nt C a re H o u rs

P a tie ntC la ss ifi c atio n

N um be r o f P a tie nt D a y s H P P D T o ta l H o urs

1 63 0 0 9 .7 2 6 1 ,2 3 6

2 (1 :3 ) 1 9 0 9.8 1 86 2

3 (1:2 ) 9 1 3.8 1 24 2

4 (1:1 ) 1 2 5.8 2 5.8

5 (2:1 ) 0

T o ta l 65 0 0 6 4 ,3 6 6

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Budgeting Staff

• Used for budgeting core staff to a unit

Total FTE needed =

Total Patient Care Hours #productive hrs./FTE

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Budget for StaffingNon Productive Time

Productive Hours/Paid Hours=% Productive

% Productive X 2080 = #Productive hr/FTE

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Budgeting Staff

• Daily FTE required-used to plan daily staffing

Total Patient Care Hours = Daily Hours of Care 365

For 8 hour shifts Daily Hours/8For 12 hour shifts Daily Hours/12

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Budgeting Staff

• Total FTE Budget– Used to allocate core staff to units– Allocates staff to cover 24/7, vacation, sick, FMLA

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Budgeting Staff

• Daily FTE Needs– Used to develop basic staffing pattern– Divided by shifts– Divided by skill mix– Equals core staffing pattern

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Budgeting Staff

• Shift-to Shift Breakdown– 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

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Budgeted Staffing

• Skill Mix– Based on patient needs– ICUs usually 90-100% RN– General Care Units usually- > 60% RN– Rehab/Psych Units usually- ~50%

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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.

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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.

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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.

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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.

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Budgeting Staff-Indirect Caregivers

• Secretaries and non-nurses• Other Nurses

– Managers– Education– CNS, NP, CNM,

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II. Scheduling Staff

• Pattern of Core staff• Patient flow, placement guidelines• Unit Activity Monitors -ADT Factors• Vacation/FMLA• Policies & Procedures to support Staffing Plan

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III. Daily Staffing

• 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

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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

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IV. Expected Fluctuation Plan

• Internal Float Pools• Floating• PRN Staff• Overtime

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V. Low Census Management

• Policies & Procedures• Voluntary leaves• Hospital procedure for canceling shifts

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VI. 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

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Management Information Systems to Support Staffing

• Retrospective Analysis, cont.– Audits of schedules

• % unfilled• holes• OT• % agency• # requests granted/denied

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