To add to this comment. An analogy would be trying to drive highway speeds on a crowded downtown roads with heavy foot traffic, street vendors, open stores. Noticing inefficiencies in how cars are passing through is missing the point. The point of highways is to move people quickly. The point of crowded downtowns streets is to move people slowly so they can shop, interact and spend money.

If this efficiency-optimizing author were to take his SV mindset to tackle thise inefficiencies at industry scake, what this author will quickly find out is that it is an impossible task. The industry itself is necessarily slow and its not by accident. It can be fast when it absolutely needs to be e.g Covid vaccines. That alone should let you know those inefficiencies are only inefficiencies to you because you are naive to what the industry is actually optimizing for.

At best, you sound like the impatient driver honking on a crowded street, aggressively driving into every available opening thinking you're optimizing for efficiency. You arent.

This isn’t the government, it doesn’t need to be painfully slow to ensure it continues working properly. I’m having a hard time responding in a constructive manner because it’s a bit infuriating to hear someone make excuses for such a corrupt industry. Have you ever worked with one of these companies? I just don’t see how it’s possible for someone to see it firsthand and then come to the conclusion that the inefficiencies and high rate of error in data collection/management are not just preferential, but even required outcomes.

I will note that you addressed none of the points made in the article. My assumption is that either you feel the need to attack the authors conclusion, having no defense of your own, or you’ve foregone reading the text altogether.

I read the text. The author sees the trees, misses the forest. At the micro level, the inefficiences are glaringly obvious and pervasive. But they exist and continue to exist for a reason. It isn't because people are stupid or corrupt, it is because that's what the industry optinizes and incentvizes for. That doesn't mean things can't get better or there aren't things to improve on, it's just that this author doesn't seem to understand the big picture yet which makes me very dubious of such a person's ability to execute any meaningful changes

Just to be clear on this point — you think that the healthcare industry optimizes for inefficiency?

Edit: After looking at your post history, I realize you just want to tell people they are wrong and you are smarter than them. Don’t bother responding, I don’t care what you have to say.

yes tech people are often ill-informed about medical world. And i do end up posting a lot on topics where such gross misinformation is on full display. I read tons and tons of posts on here, I respond to a very tiny few. And I stay away from commenting on areas outside of my competence. And yes, the ones I comment on are predominantly, ones where people with incomplete (or totally absent) perspective of a field that's outside their area, feel overly confident enough to comment on those areas. So many of my posts is indeed calling out the naivety of such posts.

It's only an "inefficiency" from the perspective of the person who doesn't understand what the system is optimizing for. This author is ML engineer commenting on a field he is relatively new to and doesn't yet fully understand. To a person wanting to drive highway speeds in a crowded downtown street, everything would seem 'inefficient'. In reality, they aren't. The objectives are just different. Once you understand the larger objective, you start seeing what the true problems are, you start understanding that some things that look like inefficiencies at first glance, are actually features serving a purpose within a larger context, that you initially didn't understand.

As someone fairly familiar with the medical world-- IME HN is generally very far off the mark about medical related issues. They don't understand that regulations in this industry are written in blood, and they often fail to realize how incredibly complex these problems are. Another issue is people also need to be able to trust healthcare-- if people felt the way they do about Facebook towards makers of antibiotics we'd have a huge issue(moreso than we already do with the current number of medicine skeptics). The Doctors running these trials can't afford to make these mistake, nor do they want to considering they generally do have a lot of face to face time with their 'customers' unlike in tech.

Thank you for explaining what I am trying to say. Reading comments on HN on anything medical (or how they can use tech to improve medicine), I just have to continue shaking my head at the ignorant hubris on display, and the confidence with they are said. There's a reason all the big boys in tech who have tried making incursions into health industry have left with their tails tucked despite their considerable talent and money. The tech world attitude and ethos can not work in the medical world.

Can you share specific things that need to happen slowly and why that slowness helps protect study participants?

Some things mentioned in the article clearly increase risk to participants: manually re-assembling translated documents, using custom software and paper forms, and diluting important documentation with boilerplate. Other things seem to purely increase cost: starting meetings with smalltalk, overcharging for server hosting, and cronyism.