For many years, healthcare organizations were able to fly under the radar without providing full accountability for their operating costs - but those days are gone. Now, if a healthcare organization is to survive, costs must be fully accounted for and budgets must serve as more than a gentle guideline.
As labor represents over 50% of operating costs in an average medical practice, staffing costs need to be scrutinized to see where excesses can be curtailed. These excess costs can appear in the form of overtime, undertime, hiring of locums and a thousand other details involved in the administration and compensation of staff.
What ties all this together, however, is that the information needed to curtail these costs has not historically been available. It has taken modern technology to be able to provide clarity on staffing costs at large healthcare systems. Truth be told, most healthcare organizations have been struggling to survive without any solid information as to where their staffing dollars are going.
Costs of Running a Hospital
In a typical hospital, it is possible to call up data on salaries and rates of differential pay. However, there is no ability to track compensation by cost center, let alone use that information to forecast and control costs.
A primary reason for this is that, despite there being a plethora of information on staffing, the data are all stored in separate silos. Scheduling data is in the schedules. Time tracking data is in the time & attendance system. Wage information is in the payroll system. Credential information is in the human resources system.
Tons of data - none of it presented in a way that would allow healthcare leaders to see where their costs are going.
Even if this data were all in one place, there would still be two more obstacles to using it. One, the data is rarely available in real time and, two, the data is not available to the people who need it for decision-making in the field.
That's quite a series of obstacles: data in multiple systems, none of which communicate with one another; out-of-date and inaccurate data; and data that is inaccessible to the people who need it, when they need it.
Perhaps we should be less surprised that healthcare organizations do not know where their money is going and more surprised they are able to manage their costs even as well as they do.
Use Your Data to Control Healthcare Operational Costs
Suppose for a second that you run a healthcare organization that is able to compile all the data you need, in the way that you need it - then what? How does this data actually impact the costs of running a hospital or medical practice?
Let's start with staff utilization. Clearly, if staffing costs are such a large percentage of operating costs, then the best way to use your staffing dollars efficiently is to make sure you are using your staff efficiently. This ties directly into issues - and costs - related to overtime and undertime.
One of the main reasons overtime costs become excessive is that, since data from all relevant systems (staff schedules, time tracking, payroll) is not pulled together in real time, no one knows how much is being spent on overtime until after payroll is cut.
Think about that. Managers carefully build budgets that spell out how much overtime is acceptable, yet there is no way to control those costs until it's too late. Clearly, knowing that information before the end of the payroll period - in other words, when there is still time for the data to make a difference - would make a huge impact on overtime costs.
The flip side of overtime, of course, is undertime, but it is given far less attention. Undertime occurs when a salaried provider works fewer than their expected hours. This means they are getting paid for hours they did not work. Worse, when the necessary systems are not correctly working together, it is often the case that other providers are simultaneously working overtime to ensure adequate coverage.
Financially, this is called paying double. Once for the salaried provider's hours and once for the other provider's overtime. Actually, it's more like paying double and a half, as overtime costs more than regular work hours.
These are the kinds of situations that can bleed a healthcare organization dry. When times were flush, no one noticed. Now that times are lean, it's a hole that needs to be plugged.
Another area where money disappears without anyone noticing is time tracking. Clocking in/out can be logged slightly incorrect for any number of reasons. Maybe people self-report time and somebody rounded the number. Maybe someone stopped to chat with a colleague for 15 minutes before remembering to clock out. Whatever it is, those little differences add up. The answer here is to provide a system for clocking in/out that is easy to use and always accessible - for instance, via a mobile app.
Taking it one step further, you need to explore what happens when people work differently than scheduled. Maybe a case took longer than expected so the physician leaves late. Maybe it was a slow night and some departments sent providers home earlier than scheduled.
In these cases, you can easily wind up with inaccurate data on how much time is required for different cases and how many providers are needed to staff each department. However, when the proper data is available and accessible, you can make strategic decisions confidently. For instance, you can alter your schedules based on how long different cases actually take. You can change your staffing model for different departments based on how many people you need at different times. You can track compensation by cost center and see which areas cost the most to run and where you could improve.
The right data in the right hands at the right time is the key to reducing operating costs in healthcare organizations.
Reduce Staffing Costs in Healthcare with Better Data
Staffing costs do not need to exist as an uncontrollable factor in reducing operating costs in healthcare budgets. By pulling the data together and putting it in the hands of those who need it, major aspects of labor costs can be brought under control.
Healthcare organizations already have the data; now is the time to use it.