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Reducing the high cost of overtime

With so much attention on data from strategies and ownership to data centralization, integration, mining and ethics  it can be easy to overlook the power of simple data sets. Staffing decisions have significant financial implications, and because overtime is one of the more visible drains on healthcare budgets, it tends to get the most attention.

However, for most healthcare managers, preventing overtime is a massive challenge. If overtime data is sitting in a report somewhere, managers don’t have real-time access to that data when they need to make a quick decision.

Even if you are doing an outstanding job of collecting and maintaining staff data, it may not be enough to reduce overtime and the associated costs. Healthcare managers must have easy access to meaningful data at the moment they are making staffing decisions.

Solving the overtime conundrum

Overtime occurs because of two reasons: the decision maker didn’t know the person would go into overtime or the decision maker knew about the overtime and made the decision anyway.

While setting policies on overtime use and approval processes can help reduce overtime, a better solution is to make readily available the tools and data necessary for informed staffing decisions.

Something as simple as displaying an alert that an employee is or will be in overtime prompts decision makers to look for other options. Assessing those options can be quicker and more efficient with an Avoidable Overtime function, like the one that is integrated into ABILITY SMARTFORCE® Scheduler. The feature displays other qualified staff members who aren’t at risk of going into overtime, so the manager can make a quick, informed decision.

Consider the difference:

John is a manager in the ICU, and he is looking at the staffing for the next shift. He has had two admissions and the unit is busy. He has his hands full and the evening shift is short one RN.

  • Scenario 1: John asks one of the nurses from the day shift to stay over. Expensive, but efficient.
  • Scenario 2: John opens his iPad and instantly sees staffing for his unit showing that he is down an RN. With one tap, he gets a view of staffing in the other ICUs and sees that none of them have extra staff to offer. He taps back to his shift and receives a list of available nurses. Two of the three have an indicator letting him know that they would be in overtime if selected. He taps on the third and instantly sends a text offering her the shift.

In the second scenario, John had easy access to the data he needed to make a cost effective decision, including:

  • Visibility into other units that are staffed with the same skill type he needed
  • Who was available
  • Who was in overtime
  • Who last called off
  • Seniority

Plus, he could contact a nurse to fill the open shift, all in a matter of seconds. That data enables John to manage overtime costs, while also allowing him to be fair and in compliance with the seniority policy. He also minimizes risk by avoiding having a fatigued nurse giving care.

With the availability and affordability of staffing applications on the market, you simply can’t justify staffing practices that are not supported by data. So, if you are still using paper-based scheduling, spreadsheets or outdated staffing technologies, contact us today to learn more about Schedule Management, a cloud-based application that streamlines staffing and provides you with instant access to the data you need to make the right decision fast.

To see it in action, request a demo now.

Inovalon and design®, Inovalon® and ABILITY SMARTFORCE® are trademarks of Inovalon, Inc.

By Inovalon