PCMHs Don’t Work–Or Do They? Insights From Two Recent Studies (Of the Same Program)

This post was originally published on Project Millennial.

A month ago, a JAMA study rocked the health wonk world by showing provocative evidence that Patient-Centered Medical Homes do not work. Evaluating 32 practices in the PA Chronic Care Initiative over a three-year period (2008-2011), the authors found that achieving NCQA PCMH recognition did not statistically reduce utilization or costs, and only improved one of 11 quality measures (nephropathy screening for diabetes). Aaron Carroll summarized the study and accompanying editorial over at The Incidental EconomistMainstream media and health wonk blogs alike declared the death of the “touted medical homes model”.

That’s why I was surprised to read this headline last week:

Study: Medical homes cut costs for chronically ill members

The punch line: these two studies evaluated the same PA pilot project over the same time period (albeit with different practices and patient populations).

Medical Homes Work—But Only for High-Risk Patients

A close read of the studies reveals that their conclusions are not incongruous. Indeed, the more recent AJMC study found no significant decrease in utilization or costs across all patients, just as the JAMA study did. However, when the authors limited their analysis to the top 10% highest risk patients (defined by DxCG risk scores), they found significant decreases in inpatient utilization in all three program years, and significant decreases in costs in the first two.

We can’t discern if the JAMA study would’ve found the same significant effects if they did a sub-analysis of the highest risk patients. (Interestingly, they state in the Methods section, “we repeated our utilization and cost models among only patients with diabetes,” but the results of that analysis are nowhere to be found.)

These results underscore an insight that’s becoming increasingly clear: cost savings from care management are concentrated in the highest risk individuals.

But we can go one step further.

Cost Savings Came ONLY From High-Risk Patients

Among the 654 high-risk patients, the PCMH produced adjusted savings of $107 PMPM in the first year. That roughly comes out to an estimated $69,978 in overall savings. Almost all of this (and then some) came from an estimated 40 avoided hospitalizations (654 patients x 61 adjusted avoided hospitalizations / 1000 patients).

Among 6940 patients overall, the PCMH produced (statistically insignificant) adjusted savings of $10 PMPM in the first year—an estimated $69,400 in overall savings. Across this entire patient group there were an estimated 41-42 avoided hospitalizations.

In other words, this study didn’t just find that savings are concentrated among high-risk patients. Essentially all of the cost savings and avoided hospitalizations came from the top 10% high-risk patient cohort.

This doesn’t mean that other PCMH models couldn’t squeeze savings out of lower risk patients. It just means that this and many existing models haven’t found out how to.

How to Achieve “Risk-Targeted Population Health”?

That finding raises a broader question that these studies can’t answer: What prevented the hospitalizations among the high-risk patients, and more importantly, were those key interventions limited to only the high-risk patients?

For example, were the crucial interventions ones that were only used for high-risk patients, such as a dedicated care manager, targeted outreach messages, and special appointments for high-risk patients?

Or were they interventions that were indiscriminately used on all patients, such as standard patient education or practice-level infrastructure that all patients enjoyed (even if only high-risk patients “benefited” in terms of reduced hospitalizations)?

This question is important because all interventions (and the infrastructure to support them) have a cost. Developing patient registries, expanding EHR capabilities, maintaining after-hours access, and investing in new training all represent substantial financial investments. Less than $70,000 in savings among high-risk patients—while extremely meaningful and significant—would be wiped out by the $20,000 “practice support” and average $92,000 bonuses paid out to each PCP by the medical home program.

If all of the benefits and savings are coming from the high-risk patients, we need to devise ways to concentrate our costs as well. Implementing such “risk-targeted population health” may be the only way to make the financials work.

Some practices are trying to do this by using dedicated care managers for high-risk patients within their existing patient panels. Others are trying to create separate clinics entirely dedicated to high-risk patients—which would allow them to limit fixed costs to high-risk patients as well. In fact, the NHS in England announced this January they are piloting this latter approach, creating “complex care practices” of 400-500 high-risk patients drawn from surrounding practices.

Whichever approach proves most effective, one thing is clear from these two studies: we need to rethink our current PCMH model.