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?
While many people blame the fee for service system for many of the problems in the health care system there is a reason why the system developed in the first place and remains the primary payment method in many portions of the country. Fundamentally, we don’t understand what quality care is. This controversial statement doesn’t imply that we don’t know what substandard care is, we can certainly agree on never events, but actually reducing most medicine to an algorithm, Watson not withstanding, is beyond our reach.
For most goods and services, only understanding the outcome is fine. We don’t need to completely understand how something works as long as we can repeat the outcome, but the goal in medicine is not to do something but ideally not doing something. We want health which in many cases is the absence of care not a specific service. How can someone outside the doctor patient relationship understand if lack of activity is a really good outcome because a patient never needs a doctor vs. a really bad outcome because the patient can’t see the doctor?
Fee-for-service provides a remarkably effective solution for this problem. A provider is paid for what they do. If a provider does nothing then the provider is paid nothing. The “natural” incentive for patients to avoid care should limit unnecessary care. But today’s patient’s don’t have an aversion but an affinity for care. As patients we think there is a solution to all of our ails and seek out the cure. Any payment reform has to deal with this issue, patient lead care vs. provider care. Fee-for-service may not hinder this care seeking but when expanded to patients, through co-pays or deductibles, it at least gives everyone a little skin in the game.
Patients not only want care but choice. What happens when a specific group of providers have been paid for an outcome, a healthy knee following an ACL surgery, and the patient wants to substitute the physical therapist? Is it the patient responsibility to pay for the physical therapy? Once again fee-for-service makes this system easy to handle. Each member of the group is paid for the services that are provided. Patients can slice and dice care seeking their definition of health.
Incentives and choice make for a power inertia built into the present system. Newer payment models will need provide a convincing reason for behavior change from both provider and the patient. Fee-for-service may induce bad incentives in providers but payment reforms also need to take realistic views of what patients get out of the current fee-for-service system.
In the first part of the series, I discussed how direct pay medical homes (DPMHs) might integrate in health plans sold to larger employers. In this post, I’ll discuss the additional challenges to including DPMHs in health plans sold in the individual and small group markets. These challenges include needing to adequately address how the services and costs of the DPMH are included but also include significant information exchanges between the DPMH and the health plan.
Health plans coordinating with a DPMH in the individual and small group market face the same challenges of including the services of the DPMH in reporting for the health system as the ERISA plans discussed in the first part. Health plans will need to understand how DPHM services are included in actuarial value calculations. Health plans sold in the Exchanges will also need to include the subscriber fee of the DPMH in the premium of the plan for accurate comparison shopping.
Health plans in the small and individual market also need to collect and pass onto health plans diagnostic information for risk adjustment. The risk adjustment program in the the post 2014 marketplace will require health plans to report information relating to the risk of their members. Health plans who enroll only low risk members will need to transfer money to health plans who enroll high risk members. The goal of risk adjustment is to disincentivize health plans from cherry picking healthy members.
Direct Pay Medical Homes (DPMHs) are provider lead alternate payment models. The patient pays the provider directly a monthly fee and in return receives as many basic services such as office visits, basic labs, and X-rays for no additional fee. While there is a provision in the Patient Protection and Affordable Care Act (PPACA) allowing for DPMHs to be included as a portion of a qualified health plan (QHPs) or insurance products offered on the state based Health Exchanges. However, there are a variety of hurdles to be overcome before such plans can be developed. Some of these hurdles include understanding how DPMHs will count for ensuring that QHPs provide robust coverage and the information flows that must flow between DPHMs and insurance companies.
Before looking at how DPHMs could be included in QHPs, it is actually easier to understand how a DPHM might be included in a plan sold outside the individual and small group markets. These plans are sold to employers and allow for more flexibility. The key requirement these plans need to meet are the employer responsibility provisions. An employer needs to offer a plan that covers “60% of the allowed medical costs” of participants and meets an affordability requirement. How would a DPMH interact with these provisions?
Creating a typesetting for an ordered dictionary in LaTeX is rather the harder than one would expect. LaTeX offers a variety of ways to create lists that highlight the opening phrase or provide for numbering but combining requires a variety of techniques. For example, creating something like this:
- Bold a heavy typeface
- Italics a slanted typeface
requires a fairly sophisticated approach.
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