It’s been three weeks since I first stepped into Dr. B’s office as fresh-meat (also called an intern in professional-speak). The time spent since has created a sharp learning curve about a variety of topics like pharmacoeconimcs, pharmacovigilance, qui tam relators, Czech Republic health care, gadolinium based contrast agents, and most currently, rituximab-based progressive multifocal leukoencephalopathy. Quite the mouthful, I agree. And to be honest, I didn’t know what a single one of these subjects really meant coming in. However, I hope to share and discuss with you certain ideas that are relevant to public health as they come up. I’ll start with one of the most basic – the present state of health care.

This discussion is a review of a lunchtime lecture (not really exciting as it seems, the only resemblance to lunch-time of this event was that it started at 12:00 noon, no such ‘food-things’ were provided) given by a general surgery resident. Let’s call him Dr. K. Dr. K spent two years before his residency doing research with the American College of Surgeons National Surgical Quality Improvement Project and the Commission on Cancer’s National Cancer Data Base. He focuses on reviewing and implementing efforts that streamlines surgical care, making it safer and more cost-effective, particularly for cancer patients.

As a heads-up, much of this discussion will be from recollection. I do not mean to present false facts or propaganda, but to err is human, and I apologize ahead of time if my statements are false or seemingly unsubstantiated by numbers.

Here we go:

The Efficiency and Safety of Healthcare

There’s no doubt that health care is not something the United States likes to brag about. I mean, maybe we can brag that it isn’t quite as inefficient or ineffective as the US Postal Service, but that really isn’t saying much. Additionally, the amount spent by the government on healthcare far exceeds the amount that funds the postal service. Another way to look at the riskiness of health care is to compare it with deaths lost to car crashes, airplane mishaps, and bungee-jumping. The risk level of flying was lower that car crashes, which then was lower that bungee jumping and health care. Again, the amount of people receiving health-related procedures outsizes the amount of adrenaline-seeking bungee-jumpers out there.

Suggestions for Improvement

It is apparent that there has to be work done in improving the quality and safety of health care. The next topic that we broached was: how can we improve quality and safety? Several options were given:

1) Give doctors incentives to perform better and fine them when they mess up;

2) Funnel surgeries to high-volume hospitals that have a good performance rate?

3) Audit survival rates, cost, effectiveness, etc and provide feedback to all hospitals.

Discussion

All sound like decent ideas, right? Apparently not. Doctors disfavor the incentive/fine program. Next, if one funnels all surgeries to high-volume hospitals, the low-volume hospitals will only continue to get progressively worse because they are loosing ‘merchandise’ for the bigger-better competitor. This also leads to disparities in health care with respect to socio-economic standards as the low-volume hospitals become more risky; those who cannot afford to have a surgery at the ‘better’ hospital will suffer the consequences of the mass migration to high-volume cancer centers. There is a good idea in this though if we parse it out.

Optimize Outcome, Minimize Migration

Split patients seeking, let’s say – cancer treatment, into four risk groups: very high risk, high risk, medium risk, and low risk (all of this is determined by age, stage of cancer, comorbidities, etc). Then categorize hospitals as high-volume, specialty, or low-volume hospitals. Finally, compare the mortality rates after these cancer patients have been treated at these hospitals. Surprisingly, the data reveals certain trends that we can use to improve the mortality rates of cancer patients with minimizing the negative impacts on the lower-volume hospitals.

For some procedures that treat cancers of the breast, ovarian, prostate (it is in these instances, I know my memory is spotty, so think more generally of the ‘big picture’ rather than the minute details), the mortality rate really was not much different between the risk groups across all three types of treatment centers. For gastric and colon cancer, if the patient was of the very high or high risk group, the difference between mortality rates was significant when comparing high-volume and specialty hospitals against low-volume hospitals. And finally, for pancreatic cancer, every single risk group faired better when then were treated at a high-volume or specialty hospital.

Reflecting on this data, we can conclude that patients with pancreatic cancer should always be referred to the high-volume or specialty hospitals regardless of risk type and that patients with gastric or colon cancer should only be referred if they are high risk or very high risk. In general, patients with breast, ovarian, or prostate cancers do not need to be referred (of course, there are certain exceptions).

A side note: there are, too, patient barriers in transferring hospitals. For example, there are costs to traveling a further distance, especially when patients have to take off work and cannot afford to lose those wages. Or there are patients who don’t want to commute in the city, finding safety in a less-congested area. Patients also seek security in doctors that they know and don’t trust care-providers that aren’t familiar to them. This is where discrepancies in healthcare arise, often between educated and non-educated classes. But that is a whole other can of worms that hopefully, I will come to talk about in the future.

Anyway, the main point of this review was to see that we could increase the mortality of patients AND minimize patient movement by only mobilizing the patients who will benefit from treatment at a different hospital. In the statistic that Dr. K provided, we were able to determine that over half of the patients (originally advised to seek treatment at a high-volume and/or specialty hospital) did not actually need to be moved and were not upon review. This measure helped low-volume hospitals retain some of their clients while those truly needed better medical expertise received it.

Auditing and Feedback

The next topic – auditing and feedback to hospitals to make them improve their services. There is already a database out there called the SEER database that collects exorbitant amounts of minute, obscure facts and data about every treatment, surgery, and check-up out there. They try to remain consistent in their reporting by only allowing thoroughly trained nurses to input the data. So what to do with all these reports? One of the objects is to compare all of the hospitals and then give each hospital an ‘individual’ report of where they stand (i.e. 25^th percentile, 50^th percentile). If a hospital sees that it is underperforming and where other hospitals are, it’s natural instinct to do better than your competitors.

A good use of this data showed that, upon review of the SEER database, 12 lymph nodes have to be checked to assure whether or not a patient has cancer. They then showed how many hospitals were not performing the necessary 12 biopsies; many of which were 1) surprised by this data and then 2) easily implemented it into their treatment plans. So easy as that, by using widespread data, feedback services like this were able to make cancer diagnosis incrementally better.

Data can also reveal problems with respect to ratings system within healthcare. For instance, our current standards look at mortality rates within the first couple of days after surgery. The less likely you are to die from complications of the surgery within the first week or so, the better the ratings the hospital receives. There is the instance, however, that your chance of dying after being released from the hospital is much worse off. There are hospitals that are in the top quartile of survival rates immediately after the surgery who drop to the bottom quartile of survival rates once their patient is released! Not so appealing now, eh? Yet this risk is not noted in many hospital ratings. This indicates two things. 1) Hospital rating services must consider several sets of data before they publish their lists because a patient’s well being is at stake; but more so 2) hospitals need to realize where they are underperforming (i.e. survival rates after hospitalization) and identify why they are underperforming and then target their faults.

Finally, these stats can reliably create a “calculator,” inputting data about a patient (age, sex, comorbidities, type of cancer, etc) and hospital of treatment, which determines the predicted rate of survival and if, their hospital is on par with national treatment levels with respect to the patient’s individualized case. This tool could be another way to improve survival rates by identifying if a patient does or does not need to seek treatment at a different hospital.

A Final Note

In conclusion, these are not the only solutions to health care reform nor are they perfect. Our health care system is risky and inefficient, but we are not in desperation. By offering a couple of ideas and discussing both strengths and weakness of them, I hope to open channels of discussion. More so, if others start thinking critically of healthcare reform ideas in the same way we approached these topics, then perhaps, we can start inching our way towards a safer, more cost-effective system.