If you Google “narrow networks,” you will find a lively discussion on the topic from their introduction with HMOs in the 1990s, their current use among insurance and exchange plans, and their recent adoption by large employers. Bloggers, analysts and political activists have all outlined the pros and cons of narrow networks — and stated predictions on their sustainability as healthcare reform marches on.
Narrow networks are designed to keep costs down through careful selection of providers using various criteria (some pertaining to quality) for who is allowed membership in the network. In the post-acute care arena, these membership criteria often derive from public data.
There are limitations to the public data (think Five-Star Ratings, but I could go on). The Five-Star nursing home system recently underwent major revisions, adding additional quality metrics and rebasing the system, resulting in Five-Star scores that cannot be compared to previous scores (and have weak correlations to rehospitalization rates).
Many network builders use Five-Star as a gatekeeper to narrow networks. Suddenly, the new definition of “top performers” caused a shift in narrow network membership.
Basing a narrow network on public data like Five-Star is like using a paper roadmap from 1978 when you have a GPS available. These data and metrics assume all residents and all SNFs are the same. On the aggregate, a SNF can score high marks in whatever metric you choose, but that SNF might have no proficiency in diabetes care or congestive heart failure, for example. A low-risk resident can quickly become high-risk in the wrong facility, even a “preferred facility,” and that’s just not smart.
In a recent study at PointRight, we examined 4- and 5-star SNFs, along with their case-mix adjusted rehospitalization performance. We found that 49% of these “superstar” SNFs have at least one cohort where rehospitalization performance is among the nation’s worst (bottom quintile).
The right data and analytics shift the conversation from narrow networks to smart networks; creating a network that is resident-centric, dynamic and data driven. In a smart network, the resident goes to the “right” SNF with demonstrated proficiency in that specific type of resident (not just diagnosis but also comorbidities) vs. the “preferred,” which offers no such guarantees. Providers take note: These same metrics can identify your strengths and weaknesses. Market using the former and fix the latter.
What would a smart network look like? A smart network uses several types of data, process and outcome measures, and matches resident’s risk for unwanted outcomes to a SNF who have been measurably successful in managing those risks.
In the same study referenced above, we isolated excellent SNFs that performed in the top 20% in adjusted rehospitalization. We found that 13.51% had at least one cohort (diagnostic sub group like CHF) where they performed in the bottom 20%. Again, relying on a single metric isn’t enough.
“Narrow” has never had positive connotations: think “narrow minded” or a “narrow chance.” Success in healthcare reform will be delivered on the broad shoulders of payers and providers that collaborate to develop smart networks where the SNF of choice won’t be defined by a single metric for convenience sake, but driven by a multifaceted metric that considers resident needs, strengths and limitations along with SNF performance.
Steven Littlehale is a gerontological clinical nurse specialist, and executive vice president and chief clinical officer at PointRight Inc.
