Capacity and Workforce Management

Forecasting in Healthcare: Align Staffing with Predicted Patient Demand

5 essentials for patient demand forecasting

One of the best ways to sustainably reduce labor costs is to forecast demand far enough in advance to match staff and resources without incurring last-minute expenses. How can you ensure you have the right mix of staff on any given day unless you can accurately predict the number and types of patients that staff will be caring for?

A reliable system provides the tools required to monitor progress against the forecast and adjusts as necessary to stay on course. It quickly enables you to see where you will be understaffed or over bedded — and plan accordingly.

Planning Across Horizons When Forecasting in Healthcare

A patient demand forecasting tool must be accurate enough to help drive strategic, budgetary, scheduling, patient flow and staffing decisions. An optimal forecast enables you to plan continuously over multiple time horizons:

  • Strategic (3–5 years) and budgetary (1–2 years) forecasts are used for long-term planning based on historical trends
  • Scheduling (1–4 months) and operational (today to 7 days out) projections enable resource managers to adjust near-term plans by also accounting for current hospital status

Even a 3–5 day view into future demand and resource requirements gives leaders more time to consider a variety of less expensive options for workforce optimization. For example, rather than adding last-minute staff to cover a spike in demand, you may be able to delay elective surgeries or re-sequence scheduled tests. If you still need to increase staff, you can do so based on straight time.

Long term planning, weekly & monthly planning, daily planning

Forecasting Hospital Demand to Anticipate Peaks and Valleys

“Nursing units operate more efficiently when they're at full capacity with dedicated unit staff. As we move through the year, we plan to flex beds on two overflow units according to census fluctuations.” – Director of Nursing,
460-bed Level II Trauma Center

Demand forecasting also improves patient throughput and operational efficiency. When you can anticipate peaks and valleys, you can schedule the right staff—and even flex units up and down well in advance. Armed with consistently accurate demand forecasts, planners can notify resource managers of predicted low census periods in time for them to reconfigure units and redeploy staff. Units with seasonal occupancy can be closed and repurposed as an observation unit or another specialty unit. Units with consistently low censuses can be merged to create economies of scale.

Workforce Optimization Through Flexible Scheduling

Moving to staggered shifts based on forecasted patient demand is one of the most effective ways to eliminate inefficiencies, such as routine overstaffing, that are inherent in budget-driven schedules with preset intervals.

An effective hospital capacity planning tool should be able to forecast patient arrival times and flow throughout their stay and translate this anticipated activity into facility and staffing requirements:

  • Planners can staff accordingly, moving from 8-hour to 4-hour shifts where appropriate to match resources more closely to fluctuating demand
  • Shifts changes can be designed to avoid peak arrival and discharge patterns
  • In addition to forecasts, the system should provide nurse managers with information on real-time patient arrivals by the hour, with adjustments to the staffing plan already incorporated

Data Accuracy: Essential to Building a Proactive Culture

Some accuracy analyses compare the average monthly census of the model to the average actual census. This aggregation trick can make a model appear much more accurate than it will be in practice. To be statistically valid, accuracy calculations must be based on an absolute daily comparison of the forecast to what actually happened.

Your forecasting methodology should be transparent to all stakeholders so that they trust the data and resulting projections. It should enhance the skill of clinical leaders by pointing out needed actions in advance and expanding the options available to solve operational problems. As staff see the forecast tracking to actual demand and begin to experience a less chaotic environment, a proactive culture built on healthcare analytics can take hold.