Counterpoint

The most important elements of value in healthcare services are cost, quality, safety and convenience.  

The British are refreshingly honest about the challenges of defining a “quality outcome” in determining value: 

“Any assessment of a health service ought to examine indicators of the value of the ‘output’ it creates. Traditionally, two classes of outcome are considered important in healthcare: clinical outcomes expressed in terms of the health gains created by the system, and the quality of the patient experience, independent of health outcomes, expressed in concepts such as ease of access to care and responsiveness. 

Some health outcomes indicators – such as life expectancy rates, infant mortality rates and cancer mortality rates – are available. However, improvements in these are a function of many factors over which the NHS often has little influence. The relative scarcity of readily accessible outcome data specific to the NHS forces any analysis to rely heavily on process indicators, on the assumption that they provide a reasonable proxy for health outcomes (Emphasis added).”¹ 

In contrast, health economy stakeholders in the U.S. have adopted a haphazard set of process measures, patient perception and adverse events as “quality.” In addition to a lack of government-mandated quality outcomes measures, the venture capital graveyard is filled with companies that did rigorous work to measure quality outcomes and failed to find customers among health insurers, employers and providers. Like many things in healthcare, everybody talks about quality, but no one is willing to pay to measure it. 

William Farr, a British epidemiologist, famously stated that “death is a fact; all else is inference.” As such, mortality is the ultimate measure of quality, making it the most important quality metric in determining value, which exists at the intersection of quality and rate. Twenty-five years after the Institute of Medicine’s To Err is Human, post-hospital discharge mortality in the United States is stubbornly high, and health system performance on quality measures is relatively average. In fact, an unbiased observer might question whether CMS and other health economy stakeholders actually care about quality when fewer than 50% of hospitals report the most basic mortality measures that CMS implemented in 2007, especially as mortality is increasing for COPD and pneumonia. 

More importantly, there is no observed correlation between price and quality, i.e. value, in healthcare services at the national or local level, as measured by common quality measures reported to CMS and the corresponding in-network rate paid by national commercial payers for select high-volume DRGs.  

Correlation is a measure of the relationship, or lack thereof, between two things. For example, height and weight have a strong correlation; height and eye color do not. Our correlation analysis included the following common measures: 

• Pearson’s Product Moment Correlation Coefficient, which measures the strength of the linear correlation between two variables; 

• Spearman’s Rank Correlation Coefficient, which measures the strength of the monotonic correlation between two variables; and 

• Mutual Information (MI), which measures non-linear relationships between two variables.^2,3  

For our analysis, we compared the in-network negotiated rates with the 30-day post-discharge mortality for DRG 190 – COPD, DRG 193 – Pneumonia, DRG 280 – Acute Myocardial Infarction and DRG 291 – Heart Failure, respectively, for hospitals in Boston, Chicago and New York. In each correlation analysis below, the X-axis represents quality and the Y-axis represents the in-network rate, for which a lower number is better for each axis. As a result, in these correlation analyses, the ideal correlation would be -1, which would demonstrate that as the rate increases, so does quality. Conversely, a correlation of 1 would demonstrate that as rate increases, quality decreases. In all but one example, the slope of the regression line is “good,” but the correlations are “weak,” as revealed by the deviation of the values from the regression line. Notably, the slope of the regression lines for hospitals in Boston are the least “good,” and, for pneumonia, the slope is “bad.” 

The analysis presented above is based upon public data, which means that any health economy stakeholder could perform this analysis. The fact that CMS hasn't performed this analysis calls into question everything else that CMS does. How can CMS claim to be concerned about quality when failing even to enforce the actual reporting of their mandated quality measures? How can anyone in the "value-based care" business claim to be serious about "value" when mortality is this high and this random? And, no, "your patients" aren't sicker.  If this is the best that health economy stakeholders can deliver with respect to mortality, then we should stop kidding ourselves about ACO Reach and MSSP and every other "value-based care" program. Rearranging the deck chairs around on the Titanic didn't save any passengers, and shared savings don't seem to be saving many lives.