Connect for Health Colorado (C4HCO) sits midway between a government agency and a startup. As a government agency it purpose was defined to create an individual and small group marketplace for health insurance. As a startup it still had to find a “product market” fit or a method for actually creating the marketplaces and then once finding a product market fit scaling that method to reduce costs or increase the marketplace.
I can be argued that C4HCO has found a product market fit for individual health insurance but the recently released operating report doesn’t provide a good indication that C4HCO knows how this was done or how it will scale. Furthermore the operating report doesn’t provide a clear prioritization of the remaining “startup” tasks. Will C4HCO be focusing on scaling the individual marketplace? Does C4HCO believe that it has achieved product market fit in the individual insurance market? How does small group fit into all of this? Does C4HCO have an overall business model to organize all of these questions?
Last week I discussed some of the problems with some of the initial work around Connect for Health’s financial modeling. The next step is start breaking down the individual lines in the Connect for Health(c4H) . The first step is breaking down the top line revenue. An initial updated model can be found here.
There are two key assumptions in the revenue figures, enrollment and premiums, and a factor that is primarily in C4H control, the administrative fee for policies sold through the c4h. For the moment, we take the baseline enrollment figures as given and only make adjustments based on other modeling. That leaves the interaction between the administrative fee and premiums as the only remaining item to model.
As the number of enrollments in Connect for Health has come in lower than expectations some of the focus has shifted to the future sustainability of the organization. While some initial projections released last week show that even on the reduced enrollment figures there may not cause a dramatic increase in the administrative fees charged to carriers.
More problematic is the lack of dynamism in the projections. A lower enrollment number implies a higher admin fee. However, the higher admin fee is not reflected in a higher premium in the lower enrollment scenario which raises the question of whether the lower enrollment projection captures the possibility of death spiral at the lower enrollment leads to increasing admin fee leading to lower enrollments.
More importantly, the fixed operational and technical budget are never varied. One of the most important questions facing the current board is what types of projects should be green lighted to increase enrollment and decrease cost. Without some linkage between costs and enrollments it implies that enrollment is completely out of management’s hands.
The lack of modeling around the link between costs and enrollments also sidesteps difficult but important questions around the more fundamental nature of Connect for Health. What is a realistic customer acquisition cost Connect for Health? What is the customer retention cost for eligibility redetermination and re-enrollment? What happens if the cost of outreach or customer acquisition for a substantial number of eligible consumers is too high for what is seen as an acceptable revenue basis?
In many cases it is not the projection but the modeling that leads to the projection that are the key value of projection. This modeling leads to key assumptions that initially be hidden. The modeling also creates a great opportunity to build in early feedback cycles that enable a management team to alter outcomes.
Over the next few weeks I’ll be building some of the more detailed modeling to create more complete Connect for Health sustainability projection.
Connect for Health has released detailed metrics on enrollments through November and some summary data for the first week in December. Here are some of my thoughts on the metrics. Note that these are based on my general understanding of the industry and not an analysis of rate filings or other sources.
As the storm continues to gather around the healthcare exchange’s troubles, the news media is beginning to fixate on a new question: What happens if the young and healthy don’t come? At what date have Healthcare.gov and the state exchanges lost the young invincibles that are the key the law’s long term success? Won’t health care reform be doomed when Healthcare.gov crashes on black Friday?
The US healthcare system has been compared to a gigantic mega-tanker and that analogy is particularly apt in this case. The exchanges early floundering will certainly impact the course of health insurance rates. However unlike a modern tanker, health insurance carriers don’t have a GPS to pinpoint the course change but are still using tools closer to compasses and half completed current charts.
Venture Beat had a recent article on options for startups and venture capital and exchanges. While Exchanges present an opportunity, new stratups just entering the market should focus on the growing ecosystem around the Exchanges rather competing directly on or for the Exchanges.
- Backend support – While appealing from a public service standpoint, this isn’t a strong option for new investment. Your customer base for HIX back ends is public sector entities. This means long RFP cycles, budgets that are consistently under pressure, and customers whose priorities may change every two years. Brand new startups are unlikely to be able to compete in public sector procurements where references and high fixed cost investments like local staff or high liability insurance requirements.There are also several strong first mover advantages for the existing players. The first is risk aversion of the customer base. Public sector customers are more likely to choose a bad existing stable solution over new innovative solution since the rewards for innovation are relatively small but the penalties for failure are immense. A second concern is budgetary. The original appropriation for Federal grants to state based exchanges ended this year. While it is likely that some money will be available for the 38 states who are currently relying on the Federal Exchange there may be not be resources for a completely new system.
- Helping Private Exchanges with new branding – While it may be tempting to compete directly on an Exchange, public or private, it’s important to recognize that insurance product cycles are relatively long, even in private exchanges. All insurance products sold to individuals need regulatory approval by October of the year before they are sold. This means that a new product for 2015 have less than a year to be created, marketed, and approved by regulators. Products sold through large employers do not have the same regulatory deadline but have similar process deadlines where decisions on employer plans are often made over the summer. This is especially true with large changes that may require a coordinated communication plan o employees.At the same time health plans may seek better engagement tools mid year. Tools that can either raise an Exchange plans mind share like enhanced customer service or marketing tools may need to be deployed mid-year after the product development cycle because these pieces are often not required to be filled with regulators or require contractual adjustment with an employer’s workforce. Startups targeting larger contracts in this area also need to be aware of the Medical Loss Ratio(MLR) and whether a portion of the costs of the engagement tool may be considered a claims expense.
- Customer education & services – There is definitely a need for better informational products. The difficulty is developing a viable monetization and business strategy for direct to consumer services. Both public and private HIXs will also be working on educated consumers for free. Some Exchanges may seek help in developing these products many will see this activity as a core competency and key differentiator.At the same time HIXs are creating a new class of advisors, navigators. Navigators, health insurance brokers, and accountants, because of the complications of the tax credit, may have the resources to pay for differentiated informational products to offer their clients. These advisers also have a different needs than the average consumer and provide a niche for startups.
- Financial services for HIX world – This is another area where focusing on the small and medium enterprises may provide a better solution. Many larger health systems have been preparing for higher patient cost sharing under the guise of “revenue management”. Whether the solo practitioner realizes the impact and has a solution is an open question. An interesting problem/opportunity is the shear number of changes a small office will have to deal with in the next year from meaningful use, the potential changes in billing due to HIXs, and ICD-10. A new startup dealing with only one of these issues may not be able to gain much traction but there is an opportunity to partner with other organizations to provide the full solution suite.Providing direct to consumer tools may be harder and there may be a much more limited market than anticipated in the article. Medicaid and child health plan eligibility, which in most states is free, is based on monthly income so a family that loses the primary breadwinners paycheck may instead qualify for a free health plan rather than require a short term loan. The regulations also require subsidized individuals to have access to non-traditional payment methods offering some possibility for non-traditional payment sources. The regulations also provide for a 90 day grace period so many insurers rather than a third party may become credit supplier for more affluent customers with cash flow problems.
- Self-Triage Services – This area is another need but the trick is monetization.
While Exchanges offer compelling opportunities many of big obvious “whale” opportunities may have already passed. Instead new startups may want to focus on supporting the vast ecosystems that will be generated by the Exchanges.
While many people have expressed concerns over the administrations delay in implementing the ACA limits on the maximum out-of-pocket (MOOP), the MOOP delay is a broader reflection of the tension in the ACA between coverage and cost containment. Delaying a requirement explicitly for data linkages either shows the difficulty of moving the complex fragmented US healthcare system or signals an administration that is still focused on coverage and doesn’t have a clear focus on how to solve the cost problem.
For health care actuaries the next few years are likely to be taken up with various actuarial equivalences. Actuarial value is at its core an idea for expanding actuarial equivalence. HHS has indicated that modifications to essential benefits will need to be actuarially equivalent. Health plans will be developing new products in response to reform and need to provide some comparison to existing products describing their actuarial equivalence.
Actuarial equivalence is attempt to make describe how two separate policies are the same. Since all insurance products are fundamentally transformations of a random variable, the claim distribution, it makes sense to incorporate two important concepts from probability: equivalence in distribution and equivalence in mean.
Two policies are equivalent in distribution if they would pay out the same amount of benefits for any claim history. This is a strong condition basically requiring the policy to be the same. Actuaries are unlikely to see this type of equivalence when working on a subset of benefits in a health plan but may see it when developing completely new products. Actuaries may start with a completely new policy design but as the policy continues to evolve with input from stakeholders, the policy may end up with a complicated benefit formula that in practice pays like a standard deductible and coinsurance or deductible and copay plan. As a final check in product development in may be helpful to compare new products to a very simple existing product. If it takes some time to understand the scenarios in which the new policy would pay differently if may be time to rethink whether the value add in product complexity is useful. Alternatively, it may make communicating with outside stakeholders easier as there is an easy reference plan.
Equivalence in mean is more common and is typically used to evaluate changes in a smaller subset of benefits. Two alternate configurations are equivalent in mean if for a given claim distribution, the benefit payment will be the same. Actuarial value is the application of this idea to an entire policy but equivalence in mean is typically applied to portions of the benefit package. For example, if two physical therapy and occupational therapy1 each have a 20 visit cap, what would be the equivalent cap on both service types combined? The combined cap will be less than total because some members in the reference population will use more than 20 visits of one service but none of the other so combining the caps will pay for services that were not covered in the separate caps.
Equivalence in mean also produces winners and losers. The distribution used is typically a standard or representative population but this distribution may be composed of subdistributions that are affected differently. Some members will be better off under one of the benefit plans. In the physical vs occupational therapy example, policy holders who use both services extensively, for example major stroke victims, may benefit from the separate caps but policy holders who only use one type of service, some who has orthopedic work on knees, may benefit from the combined caps. Actuaries may increasingly need to work to determine who are the winners and losers in an actuarial equivalence to show that plans are using actuarial equivalence in a non-discriminatory manner.
Health actuaries will be called on to return to one of the core skills, determining when future payments are the same under uncertainty. Actuaries will need to understand when two policies are effectively same but provide an analysis of when two policies are similar but different how are they different.
1 Occupational therapy is therapy designed to restore the basic daily skills. An example would be helping some relearn how to hold silverware after a stroke.
While the evidence of coverage regulation issued last week is primarily a consumer information regulation, there are several provisions of interest for actuaries. The required distribution dates of the summary of benefits and coverage (SBC) to consumers may impact rate development timelines. Actuaries may also be asked to review or develop automated methods for pricing the coverage examples. Finally, actuaries may wish to standardize language around the uniform glossary to minimize confusion within and across organizations.
While many states have required renewal notification dates for products many employers particularly small employers may use the renewal notification to start shopping for the next year’s coverage so the required renewal dates tend to drive much of the rate making calendar.The notice of proposed rule making (NPRM) required group health plans to provide participants a new SBC 30 days before any changes to underlying benefits including plan design. This would have pushed the rate making calendar ahead as carriers moved to provide renewal notices at least 60 days in advance to provide employers with adequate time for analysis of the renewal and potential plan design changes. The new rule allows allows for a group to provide the SBC upon finalization of a contract if the contract is still under negotiation 30 days before the effective date. However, the negotiation process may be moved earlier as employers seek to finalize coverage decisions 30 days but without the hard deadline there may be less of a shift. Self funded plans must publish the SBC at least 30 days before renewal if there are any changes so smaller self-funded plans that may not have an open enrollment period will need to make sure plan designs are finalized at least 30 days before renewal.
There are two coverage examples that provide an example of the coverage offered by a particular benefit plan. The current coverage illustrations are for maternity and diabetes coverage. Each coverage example is a detailed listing of the services performed including CPT, DRG, and NDC codes as well allowed amounts. Actuaries may be tasked to build an automated system for generating the coverage examples. As part of this process actuaries may also be called on to evaluate the coverage examples for completeness and also for some repricing information. For example, the maternity example uses CPT code 59400 which is a bundled payment for maternity may be repriced as separate services and actuaries may be asked to review the repricing algorithm.
The uniform glossary contains simplified explanations of many terms used in health insurance. While almost all of terms are standard insurance terms actuaries should review the glossary to make sure there is a common insurance terminology used throughout the organization.
Medicine is a business. This is the Faustian bargain our society has made with medicine but we may be reaching the limits of the bargain as a Kaiser News Network article on the latest trend in hospital marketing highlighted. The hospitals mentioned in the article broke no laws when they used basic demographic and payment data to aid in developing new marketing campaigns but did they expose a fundamental conflict of interest?
The data was specifically used in a marketing project. How different would we feel if the same data or even more precise data was used by a nurse making calls for the same screening tests? Would it matter if the screenings were are of dubious public health value as the Kaiser article implies or recommended screenings? Would it make a difference if the nurse was actually more profitable because of a higher conversion rate?
As a society we are still struggling with understanding our digital exhaust. We have become inured to some of activities being quasi-private with Google and Facebook serving up personalized ads but what about our trusted advisers? As all of our transactions become loaded into systems that are more interconnected what can be used for what purpose? For example, the Society of Actuaries has sponsored a research project looking at the relationship between socioeconomic and other factors and medical costs. If a significant relationship is found between some marketing variable and health care should it be included in medical records? Should doctors include your magazines subscriptions in a medical record? What happens if a doctor uploads this information into an ad supported electronic medical record, will he find some new magazine to bring up during the appointment?
These questions will only increase with number of new consumer wellness services. Data from services like Runkeeper and The Eatery may have a legitimate place in medical records. Including this type of data makes a medical records more complex but infinitely more valuable. Techniques to sort through social media can easily be altered to mine the much more structured medical record for products or services with medical impact. In the near future, will we get a coupon for the new healthy casual dining restaurant opening down the street with our lose weight reminder?
We have traditionally held that health data needs to be protected between the patient and the provider but what happens why the provider becomes a distribution channel for other products? Most people have come to some kind of peace with the role that pharmaceutical advertising and sales forces have on providers but will we be able to handle providers pushing their own services or worse some tangential service? The rise of data aggregation and the uses that data can be put to will increase the need for providers to clearly state any conflicts of interest. Do we need to segregate doctors like we do financial professionals based on how they are paid? Will some doctors will accept only payment from the patient or the patients insurance to ensure no conflicts of interest while other’s accept payments from a variety of sources to minimize the cost to the patient?