Payers and providers continue their deadlock
Providers and payers have been in a zero-sum game for as long as I can remember. That is far from changing, if anything, there is plenty of examples all over the news. For example,
- UHC vs. John Hopkins: Despite both parties agreeing to rates / prices, John Hopkins is citing a termination of in network status because UHC is refusing to relax on terms related to prior authorization and denials, where-as UHC is citing disagreement due to terms related to right to refuse specific patients.
(Source: https://www.fiercehealthcare.com/payers/johns-hopkins-hospitals-clinicians-leave-unitedhealthcares-network-amid-contract-dispute) - Aetna vs. Duke: In NC, Duke sees over 700k+ patients from Aetna (notably the state's workers), with a very public contract-war, where according to Duke they have not received much rate hikes for the last few years, not even aligned to inflation. On the other hand, Aetna quotes Duke's $600M+ in profits for Duke.
(Source: https://www.carolinajournal.com/duke-health-requested-aetna-rate-hike-would-have-small-impact-on-state-workers/)
These are just two examples of the ever-going trend of zero-sum negotiations that rarely ever reflect a shared vision or goal.
There have been plenty of attempts to eliminate these dynamics, but none have really borne fruit to date, for example:
- Provider led-health plans: With the exception of Kaiser, most provider led health plans which you would believe would think would eliminate the zero-sum dynamics actually result in very poor financials
- Value-based care: There are plenty of reasons why the VBC model has not taken off with healthcare systems, but primarily it is driven by the fact that FFS economics for a healthcare system are just too lucrative, and there is rarely a concentration of primary care providers to make it value accretive
- Price transparency: CMS has attempted in the last few years to make prices transparent by committing payers and providers to publishing their pricing. But due to sub-optimal requirements, the published data was far from helpful (e.g., providers just published charge masters which mean nothing, payers overwhelmed their uploads with unclear pricing / bundling / modifiers)
- Narrow networks: When all else fails, payers attempt to narrow their networks, driving more volume to a limited set of healthcare systems while negotiating a lower rate with those systems (in exchange for the volume). But realistically, employers never want this so it really only works in Individual markets where consumers welcome the lower price in exchange for a narrower network.
Employers and patients eat the cost
I start by saying this is not always the case, but more often that not it is. In heavily negotiated contracts that result in higher rates or termination, you can end up with many unfavorable outcomes, for example:
- Payers hike rates and you end up with higher premiums, or the employer has to find another insurer until they have to rate hike as well
- The health system goes out of network and the patient ends up paying OON benefits to keep the provider or even worse – surprise billing
- Negotiations tend to occur on a line of business basis, so for example if a provider or payer is forced to give in on a given line of business, they will push for a higher rate on a different line of business resulting in the latter seeing higher premiums / rates / patient impact
AI will only make it more complicated
If you look at the healthcare space, three of the most rapidly growing use cases in AI are those that can lead to value extraction between payers and providers. Specifically,
- Scribing: Scribing allows automated transcribing of voice to text, but most of the value comes from the ability to then turn these notes into ready claims which may be "optimized" (e.g., upcoding of a DRG, adding specific diagnoses)
- RCM denial management: Providers historically have had a very low appeal rate, but with AI, the ROI of an appeal is much higher considering the time and effort taken to generate an appeal.
- Claims adjudication: On the other hand, payers are picking up automated processes to adjudicate claims, minimizing leakage and allowing them to deploy their denial rules at a much broader scale than ever before
It is also my personal read that providers are "winning" the AI race so far, for a wide variety of reasons but some of these reasons are:
- Despite the EMR fragmentation, there's 3-4 key EMRs and if you can integrate with them as an AI vendor you have a wide variety of access to healthcare systems
- RCM vendors are already embedded into health system tech stacks, so implementing an additional AI workload is not as challenging
- Providers are historically much more vocal and eager to explore value capture opportunities (e.g., protecting fee schedules and lobbying for them, RCM optimization and workforces, etc)
The opportunity – Transparency and regulation
The point of this article is not to paint a falling sky, but rather paint what seems to be a problematic arms race and reflect on opportunities that normalize it.
- Better price transparency regulated by CMS: CMS had the right idea but incorrect execution. Transparency into actual rates, pricing methodology on a local region stands to benefit negotiations significantly, allowing many negotiations to resolve to a market standard pricing.
- Contract transparency: There is far more in contracts than just rates, terms like hold harmless language, term lengths, etc are a big part of contract negotiations. Contracts are held close, but there is a substantial opportunity to anonymize and create transparency across regions.
- AI regulation: There is very little regulation and auditing of scribing, RCM AI, and adjudication today. The lack of this means the counter party is the one to regulate it, leaving less mature payer / providers at danger of being optimized against.