Rick Carter

Hospital finance executives should focus on transparency, along with data, to gain physicians' trust and build productive discussions with physicians toward meaningful change.


At a Glance

Steps healthcare finance executives should take to develop a data-driven, transparent approach to working with physicians should include the following:

  • Show the assumptions behind the data.
  • Explain the rationale or methodology behind the assumptions and be sure there are no flaws in how conclusions are drawn from the data sets.
  • Explain why the metrics used are representative of the physician's practice.
  • Account for all data gaps in metrics or benchmarks, but explain how the data represent the best option for going forward.

Healthcare reform is dramatically increasing the number of meetings between hospital finance executives and physicians. Ideally, these meetings should be important steps in building collaborative business models around issues, such as supply cost, utilization, productivity, and compensation. Too often, however, they result in frustrating debates about numbers, rather than productive discussions toward meaningful change. Even when finance executives employ a data-driven presentation style, results are often the same-hospital leadership and physicians differing on an issue.

How can finance executives change this unproductive dynamic? First, they should do more than simply present data and metrics. They should also clearly state the assumptions and rationale behind the data and metrics, thereby advancing a data-driven approach built on transparency. This transparency helps build trust between finance executives and physicians so they can work together productively to improve healthcare delivery.

How Physicians Make Decisions: The Case for Transparency

Understanding the fundamental difference in how physicians and executives make decisions is the key to turning ineffective meetings into rewarding dialogues. Most important, by learning how to speak with physicians in a language they understand, hospital executives can help both parties meet their goals. Physicians often mistrust executives' conclusions because data are not communicated in a way the physicians can clearly understand. This mistrust occurs not because physicians do not understand economics, but because they use a different process to build trust.

To speak the language of physicians, hospital executives must understand how physicians make decisions and gain trust in the data that inform those decisions. Typically, an executive uses experience-driven decision making supported by data-that is, the executive draws on experience or judgment to make a decision and then looks at data to support the decision. By contrast, physicians often avoid basing decisions initially on experience or judgment, opting first to view the data in an effort to understand the assumptions and logical reasoning process behind the data. Understanding this approach can help finance executives engage physicians in fruitful conversations about business concepts, such as productivity or compensation.

Assumptions. Finance executives typically employ any number of assumptions in building a presentation. For example, in arriving at a particular conclusion, an executive might make assumptions about how a physician practices and therefore include certain data for comparison and exclude others: including physician visits, but not nurse practitioner or physician assistant visits; total visits for a year, but not the three months the physician was out on medical, or time teaching; visits from the practice billing system, but not the visits now recorded in the hospital system for the provider-based clinic; visits of one physician in a group, but not the activity of the other physicians that share patients and procedures. These assumptions might be based on previous experience with similar practices or tables they have seen in the past, but will prompt a "You don't even know how I practice" response from the physician. Excluding first-year data because the practice was just starting out might be a reasonable assumption based on experience. However, to build trust with physicians, a finance executive should first be transparent about the assumptions being used.

Logical reasoning: connecting the dots. The next step in transparent data-driven discussions is to show the logical reasoning that connects one assumption to the next and leads to the final number. This logical reasoning process, or rationale, should demonstrate that the executive understands how physicians think about their management practices and daily workloads. For example, an executive may want to show a group of physicians their work relative value units (RVUs) to start a conversation about productivity. But until the physicians see how those work RVUs were calculated (assumptions) and how those assumptions connect with the way the physicians perceive their workloads (rationale), it is likely they will not accept the RVU numbers or engage in a conversation about performance.

The central concept in a data-driven decision approach is that transparency-not data alone-builds trust. When data are used, logical reasoning should also be applied to the numbers to sustain them as a defensible argument to support the business concept at hand. Rather than first arguing the business concept, transparent data are used to set the stage for a collaborative discussion.

There are two main challenges with data transparency: accuracy and completeness. Executives often go into a meeting with data that are neither accurate nor complete to build a sufficient conclusion for a physician to consider changing behavior, and both they and the physicians are all too often aware of this deficiency in the data.

Finance executives who understand how physicians make decisions, however, will take a more strategic approach, admitting to the data gaps rather than pretending they don't exist and asking the physicians to go along with this exercise in denial.

Physicians will accept a more forthright approach because they are accustomed to extrapolating conclusions from incomplete data. They know how to take five bits of insufficient data and draw a sufficiently risk-adjusted decision. They do so every day in diagnosing and treating patients. But if they cannot see the reasoning used to reach a conclusion based on the data, the physicians will not value the conclusion or be receptive to further discussion of its implications.

Using Benchmarks

Benchmarking is one of the most common tools for presenting data. However, given challenges with data accuracy and completeness, most benchmark sources can be discredited. Once that happens, the opportunity to establish trust is compromised and the finance executive is left defending the numbers and discussing performance based on anecdotes and previous experience. On the other side, an executive who is transparent about gaps will be more effective and create change, as demonstrated in the following examples.

Example: Using RVUs to compare productivity. A finance executive who wants to engage a physician group in a conversation about increasing efficiency might present a productivity comparison using RVUs. Often in these conversations, however, only the summary RVU number is presented. In this scenario, physicians' first reactions will likely be dismissive or argumentative-especially given that physicians often calculate productivity differently (for example, tracking monthly charges rather than work RVUs).

By being transparent, however, the finance executive gains the opportunity to build the physicians' trust in the data. To this end, the finance executive should show physicians the underlying assumptions: the Current Procedural Terminology (CPT) codes that were used to calculate the RVUs, the volume of those codes, and the charges related to that volume. By explaining the processes and rationales used to arrive at the summary RVU number, the executive is able to prevent misunderstandings between the two parties.

A benchmark can also be used to compare productivity. Again, the assumptions and rationale should be clearly displayed: the benchmark source, the specific table in the survey that was used, and whether the final number reflects the median or the mean. By being transparent, an executive can use a benchmark that is incomplete without it being totally discredited. Rather than arguing why a benchmark is the gold standard in the industry, the executive can lead the discussion in a more positive direction and present the case that the benchmark is the best option, rather than rely on isolated experience or quotes from colleagues.

An executive can also mitigate the challenges with accuracy and completeness by using benchmark data from many sources. As shown in the exhibit below, work RVUs for an internist can be presented across four sources over a 10-year period.

Despite the flaws with this survey, as is the case with a majority of surveys used, most physicians will accept the preponderance of these data. At a minimum, an executive can make the case that internists do not generate, on average, 3,000 to 6,000 work RVUs, but more likely around 4,000 to 5,000. Showing the average over extended time also helps build trust in the data and the business concept the executive wants to advance.

Exhibit 1

f_carter_exh1

Example: Using average patient visits per day to measure productivity. This example illustrates another approach to creating a successful meeting around issues of productivity and compensation. Imagine that after a detailed analysis, a finance executive determines that a physician is handling 20 visits per day, on average. In a typical meeting, the physician would be presented with this one measure and little explanation on how it was reached. The meeting might derail if the physician argues that the number has no validity and the executive has no idea of how the physician's practice really operates.

What happens when the math is laid out for the physician, including the assumptions and rationale? The finance leader could show, for example, how 3,600 visits divided by 180 work days equals 20 visits per days, and then explain what criteria were used to arrive at the 180 days and the 3,600 visits. Once the physician understands how the calculation was performed, he or she will be more willing to start a conversation about productivity.

Expanding data will offer even more assumptions on which to base the final number, thereby strengthening the conclusion. For example, the finance leader could show numbers for one week, including numbers for each day in the week, and then divide the week by the number of days worked. This approach might disclose that the average number of patients per day for one week was 21, and for the next, it was 14-and that averaging the results of similar calculations across all 52 weeks produces the overall average of 20. In case the physician were to continue to dispute the numbers, arguing that accounting for half days and full days would alter the conclusion, the finance leader should be prepared to present the average using both half days and full days. This approach offers the kind of transparency that physicians find compelling and will demonstrate that the data truly reflect their practices.

Exhibit 2

f_carter_exh2

One of the critical mistakes many executives make is telling physicians that the business concepts and data are too complicated for them and should be left to the finance professionals. In fact, transparency in this case is similar to a physician showing a patient an X-ray after a diagnosis. A good physician does not say, "You have a broken leg and you need a cast." Rather, the physician displays the X-ray and supports the diagnosis by explaining the break in detail. The physician will take the time to help the patient understand the X-ray and explain how the image indicates a break and the bone's appearance differs from that of other bones surrounding it. If a physician did not offer this explanation, the patient would not be able to understand the full nature of his or her condition. In the same vein, a finance executive who tells a group of physicians that productivity is low but shows only the final number is not helping the physicians understand what low productivity really means.

A finance executive could also provide a legend to explain the assumptions behind a number. For example, a legend clarifying that a physician had 2,800 office visits in the previous year could show billing data using CPT codes 99201-99205 for new visits and 99211-99215 for established visits, including or excluding midlevel provider visits and non-RVU post-op visits. The physician might argue that this method of counting visits is inaccurate because not all patients coming into the office have a supporting evaluation and management (E&M) code. In fact, the physician might use scheduling data to track visits and include patients coming to the office for an injection without an E&M visit code. However, once the assumptions are transparent and communicated, the metrics are not as important as the logical explanations and reasoning behind the metrics.

Physicians are trained in fact- and evidence-based reasoning. They inherently respect methodology. Although they might not completely understand all of the inputs supporting those data, and they might not agree with the conclusion, physicians will respect an executive who is willing to explain the methodology, including the flaws. Transparency builds trust, thereby promoting collaborative conversation about change.

Speaking a Common Language

Developing a data-driven decision approach with physicians is not only about which data element or metric to use. Most important, a successful data-driven decision approach should show how those data were developed. To be transparent, an executive should consider the following steps:

  • Show the assumptions behind the data.
  • Explain the rationale or methodology behind the assumptions and be sure there are no flaws in how conclusions are drawn from the data sets.
  • Explain why the metrics used are representative of the physician's practice.
  • Account for all data gaps in metrics or benchmarks, but explain how the data represent the best option for going forward.

Hospital finance executives need to speak the same language as physicians if they are to build physician trust in data to promote improved productivity and quality of care. And that requires being transparent about the assumptions underlying the data. Only with such transparency can finance leaders engage in productive meetings with physicians to make the collaborative decisions that will be essential in an era of healthcare reform.


Rick Carter is president and senior consultant,Equation Consulting, Salt Lake City (rcarter@equationconsulting.com).

 

Publication Date: Wednesday, August 01, 2012

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