Analytics February 1, 2014

At All Cost?

by Barry P Chaiken, MD

During the dot-com boom, many new companies based their business plans upon the volume of website visits. The revenue models assumed that by capturing the attention of users as measured by clicks on the company website, the organizations would generate wild profits through…something. Companies offered free products and services claiming that these Internet visits would deliver market share and otherworldly revenue. In fact, many of these companies never thought through their business models nor understood their real costs. Instead, they focused on the wonders of the Internet and considered web traffic a surrogate for revenue. As we now know, unrealistic revenue projections and the focus on website traffic turned out horribly wrong for investors as exhibited by the dot-com stock crash of 2000.

For more than a half century, the healthcare industry applied the same confidence in similarly flawed models. Volume-based reimbursement tied revenues to volume, so organizations that maximized volume, maximized profits. There existed little incentive to focus on costs as organizations just inflated their charges to account for what they calculated as a rough estimate of their costs. If their calculations proved wrong for a particular line of business, they just upped the fees the following year to make up for it. Surely some organizations ran their businesses more effectively and set charges in line with their perceived costs, but they too had the luxury of correcting miscalculations with subsequent increases in fees.

Perverse incentives

How crazy was this model? For many years, physicians received reimbursement of up to 90% of usual and customary fees for similar specialists within a circumscribed region. Those physicians charging under the 90% threshold soon learned to raise their fees to the 90% threshold or above, which in turn raised that 90% threshold the following year. In did not take long for physician reimbursement to increase wildly out of control until the government and insurers changed the formula used to pay physicians. Hospitals also lived under similar circumstances until DRGs were introduced in 1982.

The passage of the Affordable Care Act (ACA) dramatically changed the healthcare marketplace and the economics driving it. No longer could provider organizations indiscriminately raise prices to increase revenue and cover their costs. The ACA set rules strongly encouraging provider organizations to take on risk and deliver measurable quality of care.

For example, hospitals no longer receive reimbursement for Medicare beneficiaries readmitted within 30 days for the same condition. Additionally, ACA incented the formation of Accountable Care Organizations (ACO), whether for Medicare/Medicaid or group health beneficiaries, which require these organizations to accept financial risk for patient care. Under this environment both quality and cost matter like never before.

An $8 hospital bill

Recent reports from New York State and detailed in The New York Times show how variable and out of control healthcare costs are. The report listed hospitals with their charges and costs for a variety of conditions during the period 2009 to 2011. (Please do not ask me to define the difference between revenue, charges, fees, and costs as that is at the root of the entire problem.) According to The New York Times article:

In 2011, prices ranged from the $8 bill at Benedictine Hospital in Kingston, N.Y., for treating a case of gastritis (cost: $2), to a $2.8 million charge for a blood disorder case at University Hospital of Brooklyn that cost it $918,462 (Bernstein, 2013, Dec. 9).

Without even knowing the details of the case, it is hard to believe the $8 bill for gastritis is correct and the cost of the treatment was only $2. If the gastritis case lacks credibility, the same must be said for the blood disorder case.

How does an industry survive—and how can our society expect healthcare costs to be reasonable—when hospitals do not know their costs of production or reasonableness of the bills they send to patients and insurance companies? How do organizations realistically set prices, compete in the marketplace, and accurately plan for their own survival and growth?

As Deming famously espoused:

“You can’t manage what you can’t measure.”

and

Quality= Results of Work Efforts/Total Costs (Deming, 2014)

Without knowing the actual costs of care and the quality of clinical outcomes delivered, organizations fly blind in their effort to deliver affordable, high quality healthcare. With healthcare costs approaching 20% of GDP, this blind approach to healthcare delivery fails to meet the needs of a changing and increasingly competitive global economy and hampers our ability to compete internationally for business.

As noted above, this new reality of value-based reimbursement requires organizations to closely monitor cost and quality. Professional and regulatory organizations, such as The  Joint Commission, NCQA, and AHRQ, have focused on quality metrics for many years and delivered excellent results, but approaches to measuring costs trail in their sophistication. Most current cost modeling depends upon extended lists of assumptions that put the entire cost model in question.

Although supply chain software improved our ability to track supplies used in patient care, the ability of existing applications to track staff members, who represent upwards of 60% of the cost of care, uses research assumptions rather than actual data to measure staff costs. These assumptions derive from expert panel recommendations that are generalized to very different institutions, clinical professionals, and variations in patient mix.

Leverage transactional data

Although the best available approach at the time for these first- and second-generation applications, cost accounting tools now require a much more sophisticated approach that takes advantage of existing data sources to more accurately measure the impact of professional services on the cost of care. Fortunately, the expansion in the use of electronic medical records provides a valuable data pool for use in cost accounting. A third-generation system tool will effectively leverage existing data sets created through the use of transactional systems and produce results that represent the actual cost of care.

In order to thrive in the era of value-based reimbursement, healthcare organizations require tools that allow them to measure their outcomes. The marketplace for metrics measuring clinical outcomes remains both strong and robust with new measures appearing regularly. It is clear that researchers recognize the value of the expanding clinical data sources and continue to leverage their value.

In contrast, healthcare organizations need a reliable, third-generation healthcare information technology tool that allows them to measure the true cost of care while linking it to their clinical outcomes. Only then will they be able to deliver the highest quality of care at a reasonable cost to a deserving American public.

References

  1. Bernstein, N. (2013, December 9). New York state hospital data exposes big markups, and odd bargains. The New York Times. Available at http://www.nytimes.com/2013/12/10/nyregion/new-york-state-hospital-cost-data-expose-big-markups-and-odd-bargains.html?hpw&rref=health&_r=0
  2. Bernstein, N. (2013, December 11). Bargain-basement prices at a New York hospital prove too good to be true. The New York Times. Available at http://www.nytimes.com/2013/12/12/nyregion/bargain-basement-prices-at-a-new-york-hospital-prove-too-good-to-be-true.html
  3. Edwards Deming. (2014, January 1). In Wikipedia, The Free Encyclopedia. Retrieved January 3, 2014, from http://en.wikipedia.org/w/index.php?title=W._Edwards_Deming&oldid=588603838

Excerpts from “At All Cost” published in Patient Safety and Quality Healthcare

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