Identifying insurer areas of advantage (and weakness) in the commercial health insurance market

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Healthcare dynamics continue to change rapidly and, with the more regulated and volatile market that insurers are currently immersed in, it has become increasingly difficult to find a competitive edge to separate one entity from the rest. Changing patterns of risk are affecting all commercial carriers, and the risk pool of members has become less predictable than in years prior to the implementation of the Patient Protection and Affordable Care Act (ACA).

In the past, a competitive market position for a health insurer was typically achieved through the combination of optimization of underwriting tools and rating approaches, economies of scale to reduce administrative expenses, and critical membership volume for favorable provider discounts. Generally, (but not always) the overall strategy also gravitated toward building the healthiest membership base in a given year. Mandated risk adjustment and reinsurance programs, as well as the elimination of underwriting, have changed the determination of competitive advantage. Insurers that stay in the old mind-set and market to the healthiest individuals will not be able to thrive in this changing industry. Insurers have the opportunity to attract, enroll, and manage care for individuals with medical conditions that will be appropriately compensated by the market reforms.

A number of off-the-shelf segmentation offerings have been flooding the market to help insurers determine the type of member that a plan should ideally engage. However, very few of these are able to be customized for a given insurer. In order to be successful, a market segmentation must reflect a plan’s unique strengths and advantages, be able to evaluate member-level profitability, and then translate that measurement into an actuarially sound and actionable customer segmentation and outreach program.

Not a matter of "if," but "when"

There are primarily two schools of thought when it comes to member acquisition. Some carriers opt for quantity over quality and aim to first enroll as many members as possible, then segment those enrolled members in order to influence their behavior and resource use. Others gravitate toward putting greater up-front effort toward getting “better” members through the door in the first place. This is done by segmenting the prospective customer population, then working to attract those prospects identified as better. For both camps, the key to success is the need to do the appropriate up-front homework and the existence of an informed data-driven action plan regardless of whether the plan is implemented pre- or post-enrollment.

Identifying areas of advantage and weakness

To develop a customized profitability segmentation, one required input is the identification of systematic areas (and reasons) where a carrier’s experience has been consistently favorable. For example, are claims for members with certain medical conditions consistently above or below the average market cost?

The market advantage analysis begins with a retrospective claim data analysis at a member level. For each member, the difference (or gain/ loss) between actual claim costs and an “expected cost” (developed using a concurrent risk adjuster) is calculated. Risk adjuster scores from a commercial risk adjuster product represent a reasonable proxy for the average market cost for the set of medical conditions observed in the actual experience. Furthermore, typical risk adjuster models are calibrated on a large independent population, which makes them representative of prevailing cost trends in the market. Comparing the expected cost to the actual cost provides valuable insight from a cost perspective into the areas that an insurer excels in providing and delivering healthcare services. The gains and losses at a member level can be defined in this way:

Gain (Loss) = Expected Allowed Cost* – Actual Allowed Cost
* Developed using a concurrent risk score.

Preferably, the actual allowed cost will be net of the member’s expected (or actual, if known) contribution to the ACA risk adjustment transfer program, in order to more accurately reflect the fact that some portion of these costs is expected to either be recouped or increased through the program.

As we have mentioned above, identifying areas of financial strength and weakness relative to the market is key to determining where an insurer’s true market advantage lies. By the same token, identifying areas of weakness is just as important. These services are performed less efficiently than in the market. Carrier areas of loss could potentially be directly mitigated through increased care management, provider contracting, and using evidence-based practice, just to name a few.

The table in Figure 1 illustrates a sample calculation of this gain/loss metric at a member level. Once calculated, the gain/loss metric can be summarized into cohorts of interest, such as medical condition cohorts (e.g., diabetes, cardiovascular conditions, asthma) or other data dimensions.

Figure 1: Sample membership cohorts and risk/cost metrics

  Medical Condition  
Member Diabetes Cardio-Vascular Disease Asthma Total allowed cost, (a) Normalized risk score (b) Expected cost, c=Avg(a)x(b) Gain (loss),
d= (c)-(a)
1 1 1 1 $3,436 1.661 $4,569 $1,133
2 0 0 1 $4,040 0.824 $2,267 ($1,773)
3 1 0 0 $839 1.029 $2,829 $1,991
4 0 1 0 $1,738 0.413 $1,135 ($603)
5 0 1 0 $3,701 1.074 $2,953 ($748)
Average   $2,751 1.000 $2,751 ($0)

All figures are illustrative and are used to clarify the methodology but not the absolute value of the results.

The table in Figure 2 presents sample summarized metrics for each cohort. At first glance, the numbers show us that riskiest members are those who have had diabetes, which is due to the highest average risk score (1.34). Looking purely at the average allowed cost by cohort would suggest that the most expensive cohorts are those members with cardiovascular disease and asthma conditions. Finally, if we review the average gain/loss metrics (calculated at a member level and aggregated for each cohort), these figures suggest that savings are achieved for the diabetic members, despite the higher morbidity (risk scores) of these members. On the flip side, the greatest losses are observed for the members in the asthma cohort.

Figure 2: Summarized risk/cost metrics from Figure 1 by cohort

  Medical Condition  
Metric Diabetes Cardio-Vascular Disease Asthma Population Total
Average total allowed cost (a) for cohort $2,137 $2,958 $3,738 $2,751
Average normalized risk score (b) for cohort 1.34 1.05 1.24 1.00
Average expected cost (c) for cohort $3,699 $2,886 $3,418 $2,751
Average gain (loss) (d) for cohort $1,562 ($73) ($320) ($0)

All figures are illustrative and are used to clarify the methodology but not the absolute value of the results.

The framework presented above provides one way to analyze a variety of member attributes and characteristics as carriers identify the types of members that can be served efficiently and costeffectively. The reasons behind the savings could stem from a variety of business aspects, from better utilization management and care coordination to potentially more favorable provider contracts. Furthermore, the insight gained regarding potential areas of market disadvantage (or weakness) leads to the opportunity to make informed changes. For instance, the higher-than-expected cost of treatment of certain conditions may signal wasteful utilization of these services or unfavorable provider contracts in place or something else entirely. These potential causes could then be further investigated and acted upon.

Categorizing areas of gain and loss enables an insurer to develop cost-effective, highly targeted, and measurable programs based on unique consumer intelligence and create outreach programs that more closely align with consumer preferences and needs. This approach will allow health plans to influence the quality of their membership and serve individuals according to a plan’s strengths.

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