Developing a Staffing Budget Nursing Resource Management Staffing

Developing a Staffing Budget Nursing Resource Management

Staffing • • 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

Budgeting Staff Required Patient Care Hours

Budgeting for Staffing Required Patient Care Hours

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 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 – Used to develop basic staffing pattern – Divided by shifts – Divided by skill mix – Equals core staffing pattern

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 – More units are moving to ICU-type breakdown due to shorter LOS, increased acuity

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

IV. 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

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 • • Internal Float Pools Floating PRN Staff Overtime

Expected Fluctuation Plan

VI. Peak Demand Management • Bonuses • Agencies • Use of other resources (Nurse Managers, Educators, CNS, other staff) • Diversion Plans

VII. Low Census Management • • • 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 • • • % unfilled holes OT % agency # requests granted/denied