Dissecting a Mantra: Doing More With Less
Whenever the economic aspects of business get tough, do more with less is a phrase heard everywhere. Of course, doing more with less just means becoming more productive. There is no scarcity of literature on productivity, and some authors claim to have identified more than 20 definitions for productivity. Economists use the term to measure the capacity of nations to use their human and physical resources to produce economic growth. A simpler definition, though, is that productivity equals output divided by input. The output is the product or service delivered, and the input is what was consumed in creating the output. Many different inputs are consumed in producing a product or delivering a service, but it’s simplest to consider one at a time. The output of an imaging operation could include procedures performed, patients served, reports signed, revenue generated, or even something more abstract, such as RVUs generated. Input is most often expressed as some measure of labor; this could be hours, FTEs, or labor dollars. Even for this simple definition, there are still many analysis options. Which outputs and inputs should be used depends on your reasons for measuring productivity, as well as on who will be using the measurement. Measuring Productivity Why measure productivity? If the goal is to do more with less, you won’t know whether you have achieved the goal without a measurement. When you consider declining reimbursements and rising salaries/benefits, maintaining profitability becomes a concern. Imaging operations are characterized by large fixed costs that are not easily lowered. One quickly realizes that the salaries/benefits area is one where there is a possibility of improvement. Probably the best reason for measuring productivity is to substantiate your success at improving it. This idea highlights an important aspect of measuring productivity: You need to take multiple measurements over time. The absolute value of the productivity measurement is less important than how the measurements are trending. Figure. Drivers of improved productivity in the imaging workforce. Consider a few examples. The first example takes a high-level financial view. Two readily available numbers, for many operations, are the revenue generated and the total dollars spent for salaries/benefits. Revenue is the output, and salaries/benefits dollars are the input, so our high-level productivity measure is revenue divided by salaries/benefits. If your revenue for the month was $500,000, and you spent $100,000 on salaries/benefits, the productivity measurement would be five: For every dollar spent on salaries/benefits, you generated $5 in revenue. This single measure is not all that useful, but if you checked it every month, you could identify the trend in labor productivity. This financial measurement really does not tell you why productivity is trending the way it is, nor does it say much about how hard your people are working. Financial productivity could be trending downward because reimbursement for the service offered is decreasing, for example, or because the cost of benefits for your employees is going up (and both are likely scenarios for imaging operations today). The next example yields another high-level performance measurement that is not monetary. This example employs RVUs as the output and FTEs as the input. RVUs are very useful in considering multiple modalities at the same time because they account for the differences in complexity of the exams. One FTE equals 40 hours of labor, but when I calculate FTEs, I usually exclude paid time off (since as-needed staffing and overtime are used to cover the person on vacation, who is not producing any output). The formula, then, is RVUs divided by FTEs. If your center produced 1,000 RVUs in a week, with 20 FTEs, your productivity number would be 50 RVUs per FTE. By watching this number from week to week, you get a feel for the natural variation in the measurement and can determine the trend. This measurement focuses on the performance of people and removes (or, as some might say, hides) the effects of declining reimbursement and the rising cost of salaries/benefits. It is still a high-level measurement, and it does not provide much insight into what is causing changes in productivity. An obvious refinement would be to group the FTEs into functional areas. In this example, FTEs are broken into groupings of those performing clinical work (technologists and nurses) and those working in business-office functions (scheduling and registration staff). Clinical work can then be broken down by modality. As the measurement looks at smaller and smaller groups of workers, what is causing productivity changes should become clear. The measurement becomes easier to understand as well. If we are just considering a single modality, exams can be substituted for RVUs, and the productivity measurement becomes exams per technologist FTE. For the business office, one might want to use patients instead of exams, creating a productivity measurement of patients per scheduling FTE. The main requirement of this type of productivity measurement is the ability to track labor hours and outputs (RVUs, patients, or exams) over common time periods (weeks, months, or pay periods). You might find this requirement somewhat challenging. Improving Productivity Once productivity is being measured, how to improve it can be considered. There are two different ways to improve productivity. You can increase the output (using the same amount of input), or you can produce the same output with less input. In more operational terms, this means adding volume without increasing labor hours or maintaining volume while reducing labor hours (see figure). The figure is loosely based on a slide from the Advisory Board Co (Washington, DC). It shows how the drivers of productivity can be grouped either as factors that increase volume or as factors that reduce labor hours. If you have equipment that is idle during operating hours, you can increase your marketing efforts to add to your volume, or you can reduce operating hours and subsequently reduce labor hours. If your equipment is in full use, you can look into throughput enhancements or adding capacity. A key point: Productivity improvement is not just making people work harder. Along the same lines, you cannot just assume that increasing throughput will increase productivity. If your center is open for eight hours, but the current volume can be handled in five hours, increasing throughput so that the same volume can be managed in four hours will add capacity, but it will not increase productivity. Remember to watch the trends, not single data points. High-level productivity measures are good, but you need to drill down to understand how you can make improvements. Consider what drives productivity and your operational situation when developing an improvement strategy. A word of caution: productivity improvement must always be done within the guardrails of customer and employee satisfaction. Having a highly productive organization full of unhappy employees, who then provide lousy service to patients and referring physicians, is a recipe for disaster. As with many things in life, the trick is to find the right balance. David A. Dierolf is vice president of performance improvement, Outpatient Imaging Affiliates, Nashville, Tennessee.