People have the tendency to cut corners sometimes. This might come as a surprise to some, but in some cases doctors are no exception.
That said, cutting corners doesn’t necessarily mean that the job is done lazily. For a doctor this can happen because they are pressed for time, they are making an inference based off of prior experience, even outside forces could be pressuring them to fill in a number here and there.
When cutting corners like this becomes routine, we get institutional bias.
Our interview with Dr. John Alchemy covers institutional bias, why it happens, and what doctors could do to avoid dragging out their claims by letting their bias get the better of them. Listen to the podcast on iTunes here.
If you’re a workers’ compensation provider, adjuster, or case manager check out RateFast Express: the service that writes your impairment reports for you!
Institutional Bias (noun) – when an individual or institution’s practice interferes with the accurate delivery of an impairment rating
Stakeholder (noun) – in a workers’ comp claim, the injured worker, the physician, the employer, the employer’s insurance company, and sometimes the attorneys of both the injured worker and the employer’s insurance
Dataset (noun) – the data on an injury collected by a doctor from a patient when filling out an impairment report
Narrator: Welcome to the California Work Comp Report, a podcast hosted by Arun Croll and Claire Williams, featuring Dr. John Alchemy.
Arun: Hello, everybody. Welcome to the California Work Comp Report. Today is Monday, March 9, 2015, my name is Arun Croll, and I’m here today with Claire Williams and Dr. John Alchemy to discuss institutional bias in impairment rating and workers’ compensation. So, Dr. Alchemy, what is institutional bias? How would you define that term?
Dr. John Alchemy: Institutional bias is a process where either an individual or an institution’s practice interferes with the accurate delivery of an impairment result. So that process may be either willful or basically part of a policy that either a doctor, an insurance company, a referral source, or an employer may do that may limit or impair the accurate and correct collection of data, or alter the opinion of an impairment rating.
Arun: Great. And we obviously don’t want our impairment rating to be impaired, so institutional bias is generally, you might say, something you want to avoid. You want accurate impairment ratings, not biased impairment ratings. Would you agree?
Dr. John Alchemy: Yeah, I think that’s a good point. So the biggest challenge is understanding where the bias is in the system, how it’s being done, and how to avoid it. And once the parties understand that, you’ve gone a long way to delivering a more accurate impairment rating.
Arun: Definitely. And there’s a lot of different stakeholders in any given workers’ compensation claim. Would you say that it’s prevalent, that it’s common that some sort of bias sneaks into the impairment rating and makes it more or less accurate than it actually should be, or just something that pushes it one way more than the other? Because some person, some institution has the power or the incentive to push it in that direction?
Dr. John Alchemy: Yes. The most common one I’ve seen, personally, has been the issue where the impairment ratings can be complicated, particularly if you’re trying to follow the letter of the law and the letter of the AMA guide. So what has happened over time in some instances is that when a number is presented in a PR-4 report because either the dataset is incomplete or the calculations are so complex that the people reviewing the calculations as “valid” are unable to, for lack of knowledge and understanding of the AMA guide, they respond to the number with a tolerance, meaning “Well, I believe that a back claim that’s nonsurgical should not be more than 10 percent” or “a shoulder injury that hasn’t had surgery should not be more than 5.” Or “shoulder surgery shouldn’t have any weakness,” or vice versa. And so what happens is that we tend to start judging these impairment ratings not on the merits of the data any more, but on the merits of our expectations, because we’re unable to check the accuracy, for multiple reasons. And that is probably in my experience the greatest source of institutional bias, is where people just say “Well, this doesn’t seem right” or “The number’s too high, based on all the other cases I’ve seen, this can’t be right. Let’s order a QME exam, let’s get another opinion, let’s challenge this,” et cetera. That’s one example of institutional bias.
Claire: And John, you mentioned two contributing factors where institutional bias comes into play. Incomplete datasets and invalid calculations. Can you describe worst-case scenario, what happens with institutional bias and those things being incomplete and invalid? What’s at stake here, for our listeners and people reading our newsletter?
Dr. John Alchemy: It’s really all about time. If you have a rating that’s accurate and it’s deemed not accurate simply because the stakeholders reviewing it don’t like the number, and they decide “We need to challenge this, get another case, get another opinion,” that really drags out the cost of the claim. That rating may actually be correct, but the fact that it can’t be checked or hasn’t been accepted based on reasons other than the data presented really drags out that claim. And then now, let’s also talk about the claims that get settled with the incomplete datasets. So the number is acceptable to the parties, it may not be correct, it may not be reproducible, but the number may be within a range that’s acceptable to all the stakeholders, then that goes ahead and gets settled. But now it’s the patient who hasn’t had a chance to have their impairment fully documented and realized, as the system has intended.
Claire: So it seems like all the stakeholders, with this expectation that creates the bias, is everybody involved in the work comp claim besides the injured worker, is that correct?
Dr. John Alchemy: That’s right. And I’m not pointing a finger to anyone causing it in particular, but I will say that given the system that we’ve chosen to accept, because it is complicated and requires a lot of study and a lot of detail, we kind of inbred this process into case settlement and case assessment and pricing because there just has not been a good way for us to compare apples to apples when it comes across Insurance Desk A versus a different Insurance Desk B, versus Doctor A and Doctor B being compared. It can all be highly variable, the outcomes of their reports, and so other mechanisms and workarounds may have come into place now to replace the gap in knowledge because these reports are missing data.
Arun: Right. So, it seems like a lack of reproducible results allows the space for some sort of institutional bias or the expectations of the stakeholders to interfere with what the injured workers’ level of impairment actually is. Would you say that’s right?
Dr. John Alchemy: Yeah, I would agree with that. And what’s also interesting is that, even in a report where all of the data is present and it’s been correctly validated and calculated, even in those situations, there may be some stakeholders that are incapable or unable to reproduce that rating, again lack of knowledge and lack of experience for reproducing those calculations. So it’s really a tough situation to try to get people around. Big educational piece.
Arun: Definitely. It seems like there’s multiple roadblocks in place. I mean, getting an accurate dataset is a challenge in itself, like you just discussed, but then having everybody involved on the same page as far as interpreting that data to come out with an impairment rating that’s precise according to the AMA guides, that’s this whole other problem, and everybody’s going to have different ideas about it.
Dr. John Alchemy: Yeah, I agree with that. I also think doctors are under great time constraints, and the expectation that they’re going to have all the resources to be able to consistently gather the same datasets in completeness from one patient to the next can be a great challenge in the clinic.
Arun: So in your professional experience, what’s a typical scenario when institutional bias, either from an employer, the insurance company, whoever, has interfered or gotten in the way of an accurate impairment rating? Maybe even one that you were involved with or that you generated?
Dr. John Alchemy: Let’s create a scenario here. So let’s say Dr. Smith has an occupational medicine practice. And Dr. Smith receives a lot of her business from a particular employer in the community. And that employer is always complaining that their work comp rates are going up, et cetera, and indicates that “Some of the cases you’re settling are causing my premiums to go up.” Now Dr. Smith may also get business from this employer in the way of [inaudible], respirator physicals, all kinds of other business referred from this employer. So it does set up a situation where Dr. Smith may not want to turn in a high or accurate report when it is appropriately higher than maybe what’s expected by the employer. So the doctor is actually altering the result of the impairment report in a favorable way that may encourage more referrals from that employer in the future. Again, I’m making this up, but this would be an example of an institutional bias situation where a particular value is being delivered with the expectation of more business being sent, or business being taken away.
Arun: It occurs to me that the reason why the doctor in that situation would be able to pander to the interests of the employer is because the other people involved in the claim aren’t going to check the impairment rating or the doctor’s calculation with the rigor that they might if they were fully acquainted with the AMA guide. I mean, hopefully they’ll be checking according to the rules, but it sounds like that’s usually going to be a [inaudible]
Dr. John Alchemy: That’s what one would hope, but you’re absolutely right. To have the skillset to accurately and efficiently check reports, that’s not always available. And the system sometimes breaks down.
Claire: But it seems that these kinds of conversations where it’s brought out into the light is very important and it’s been a pleasure to have this one today with you, Arun and Dr. Alchemy. Any final closing comments or did you have something, Arun?
Arun: Dr. Alchemy, is there any general advice that you would have for the different stakeholders in a workers’ comp claim, about how to avoid embodying, consciously or unconsciously, some sort of bias? Like for the [inaudible], the provider can obviously speak to the doctor’s experience, and what the doctor can do, which is, as we’ve talked about, [follow] the book and gather complete data. But on the part of anybody else involved in the claim, what can they do?
Dr. John Alchemy: The first thing I think we need to understand is that there’s a teaching opportunity for all the stakeholders in the process. When an insurance company is unhappy with a rating result, there needs to be dialogue and some education between the provider and the claims adjuster to clarify why that is the case, that this number just wasn’t pulled out of the air, it’s required by the rules in the book. Likewise, when an insurance company gets an incomplete rating, they have a responsibility to let the doctor know. And if they’re passing these ratings and allowing them to be passed on and claims to be settled, the doctor’s really not getting an education out of that process, and that doctor may think it’s okay to either cut a corner or that this test isn’t really necessary, or “This section of the book has never been applied before, so why should I apply it now?” What is the solution to this? Well, I believe the solution is creating a system where everyone knows what the standard question should be when doing an exam on a shoulder, when doing an exam on a back. It becomes very transparent and very easy to know when someone leaves a section out of a history or a physical exam. So that I think is going to be the solution, or at least part of the bigger solution, for helping to minimize this concept of institutional bias.
Arun: Maybe if you’re a claims adjuster and you’re receiving impairment ratings, you’d always do well to ask for a justification that proves where the number is coming from, from the provider. And on the flipside of that, if you’re a provider, always have a reason backing up every number that you’re throwing out there so that you can communicate to an insurance carrier, anybody else involved, where exactly the impairment rating is coming from.
Dr. John Alchemy: Absolutely. And I also think good adjusters who are out there, if they get an incorrect impairment report, even if that impairment report should appear “favorable” to them, they understand that passing and processing an incorrect report is not doing anyone a favor. It’s dragging out the claim, the employee may just go and get an attorney, and heap a bunch of time and cost onto a claim when it doesn’t need to be there and it could be a very simple discussion and a few additional pieces of information in the report would make it a legitimate report. So there are situations out there where I’ve come across adjusters and they’re like “Well look, I know this rating is this, but I have concerns that this was left out or this wasn’t done correctly,” and I like those adjusters because they never talk about the impairment value, they talk about the content of the report before them. And once everyone can agree that the content is accurate and complete, the impairment result is simply a very mechanical process and the number is what it is.
Claire: It seems the takeaway may be “content before impairment.”
Dr. John Alchemy: Absolutely. But again, a lot of people are hobbled by the fact that they don’t understand when content is missing, or when all the content is there. And I think if we had a little bit more of that in the industry, this podcast probably wouldn’t be happening. [laughs]
Claire: Well, we can’t have that. [laughs] Well thanks for joining us today, and we will continue this discussion in the meantime until a conversation starts happening more often everywhere else. Until then, thanks, guys.
Dr. John Alchemy: Okay, have a good one. Thank you.
Arun: Thank you.
Narrator: Thank you for joining us for this episode of the California Work Comp Report. We look forward to next week in continuing our discussion of work comp claims in California. Questions or comments? Got a great workers’ compensation story to share? Find us on Twitter at @ratefast or at rate-fast.com.