Optimizing Scheduling in Nursing

Concern over staffing ratios is not new.

But there is new vigor in the debate as health reform and economic pressures have made it increasingly difficult for hospitals and health systems to walk the fine line between providing quality care and maintaining an acceptable operating margin, i.e., keeping the lights on.

As important as this debate over staffing ratios is, it is, in truth, academic if you cannot coordinate scheduling to align with patient demand. Quite often a unit has the number of staff it needs to meet demand, but the scheduling patterns in place do not coordinate.

For instance, census on a certain unit will routinely be more on Wednesdays and Thursdays, but staff are not scheduled in accordance with this anticipated demand.

This inability to schedule to meet demand also typically has to do with how staff are allocated, i.e., how many staff work a set schedule versus how many are more flexible with their hours and shifts.

Nurses who are short staffed and feel they are not able to provide the care needed because of it is in many instances the fuel that feeds the staffing ratios debate. On the other hand, the rising costs of providing that care in the face of falling reimbursements has hospitals struggling to find ways to do more with less.


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At the end of the day, administrators and care staff want the same outcome: to provide outstanding care while keeping their institutions viable.


The key to achieving this mutual goal lies in planning and foresight. By proactively scheduling caregivers to an accurate forecast of demand, units can have the staff they need at a cost that is financially conducive to the operations of their hospital. There are two overarching strategies that are key to ensuring you have the staff available to meet patient demand – no matter what your nurse to patient ratio.

Analytics-Based Workforce Planning

How many staff do you need to handle patient demand? That is the basic question.

What complicates the answer is that patient demand fluctuates during the week, during the month, and over the years.

This necessitates the proper sizing of core staff and the right layering and types of contingency staff to flex up and down.

There is no magic formula for the right mix of core to contingency staff.

You’ll hear 85/15 as the “right” number, and it is for some, but not for all. It varies from hospital to hospital. The right number depends on the unique characteristic of your unit.

Simply stated, the right size for your core staff is the level that keeps them working to their FTE without the need to float or be canceled excessively.

By analyzing core staff behaviors and trends, historical census levels and predicted future census, payroll data, and various HR information you can determine this number unit to unit.

This analysis also helps determine the amount of contingency resources your organization needs to adjust to changing patient demand and staff behaviors (call-ins, FMLA, meetings, etc.) without relying on agency and overtime.

Across the country this approach has saved healthcare organization millions while never decreasing the number of staff on hand.


Mandatory Overtime in Critical Care

The associated risks of forced overtime are high for both patients and nurses.

Accurately Forecasting Patient Demand


Many workforce management software vendors are touting the forecasting capabilities of their solutions. Each claim a high level of accuracy, and each is using different methodologies to come up with their predictions – but how far in advance of the shift is that quoted accuracy?

In most cases it is no more than a couple of days.

This near-term accuracy is better than a shot in the dark, but it does nothing to get organizations out of what we refer to as staffing chaos – the 48 hours leading up to a shift where nurse managers are too frequently spending their time frantically trying to fill holes in the schedule.

For a forecasting feature to be game-changing it must be available at the time schedules are being built – it must drive the entire process. It must then be continually refined in the weeks leading up to the shift, with anticipated holes in the schedule being pushed out automatically with an open shift management module.

This increased accuracy of initial unit schedules along with a continually refined prediction of needs will put a unit in the best position to care for patients in an efficient and cost effective manner over the life of the schedule period.

Staffing vs. Workforce Management

This advanced planning approach is what differentiates “staffing” from “workforce management.”

It may sound like semantics, but the difference lies in the time paid to each in advance. The vast majority of actions taken to prepare for an upcoming shift should be occurring weeks before.

This is workforce management. This process should be rooted in strategies that leverage technology that make getting the right people to the right place at the right time an everyday, second nature occurrence.

Staffing then is associated with the tasks in the few hours leading up to the shift, e.g., deciding where contingency resources should be placed, assigning patients, etc.


Consumer-Driven Healthcare

Patient engagement is critical to meeting quality initiatives.

According to Avantas research and numerous industry surveys, most nurse managers are spending upwards of 50% of their time on staffing duties. This is far too much.

Instead of leveraging their experience to care for patients and lead and coach their staff, too many nurse managers are scrambling daily to piece together their care teams, making recruitment calls, pleading with staff to extend shifts, etc.

By developing a workforce plan that utilizes best practice labor management strategies and advanced forecasting methodologies your organization can develop sound staffing plans that ensure you can always meet your nurse to patient ratios, and do so cost effectively.

Jackie Larson is Senior Vice President of Client Services, Avantas www.avantas.com.

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