Trip Database Blog

This is the fourth in the series exploring how Trip compares with the most popular medical database – PubMed. In relation to a previous comparison we received the following comment recently:

I like this comparison, but I wonder if it would be more meaningful to compare TRIP with a PubMed Clinical Queries search (Clinical Queries – PubMed). I still think TRIP would “win” because of your emphasis on the evidence hierarchy, inclusion of SRs and EB guidelines, but I think it would be a more refined comparison.

ChatGPT describes PubMed Clinical Queries as “…a feature of PubMed designed to help users quickly find evidence-based information relevant to clinical practice. It focuses on filtering search results into predefined categories tailored to specific clinical needs. This tool is especially useful for healthcare professionals seeking high-quality and focused information to aid in patient care.“

So, sounds like more of a fair challenge, so, lets try it on the search migraine prevention. Clinical Queries (CQ) allows you to select different query types so for this test I selected ‘Therapy’ and after that you have two choices – broad or narrow. Broad maximises sensitivity (trying to identify all possible results) while narrow maximises specificity (trying to identify the most relevant articles). Here are the top five for each database:

To try the search for yourself, here are the links:

• Trip search for migraine prevention
• Clinical Queries Broad search for migraine prevention
• Clinical Queries Narrow search for migraine prevention

For the test I will actually use the top ten results for each database and ask ChatGPT to rate them based on clinical relevance, quality of the evidence and recency. The actual prompt used was:

Below are 3 set of results for a search for ‘migraine prevention’. Comment on quality of evidence, recency of articles and applicability to answering questions on the topic. And give an overall view on which database is likely most useful to a busy health professional.

ChatGPT’s comparison:

Another win for Trip….

This is the third in our series comparing Trip to PubMed. The first two prostate cancer screening and asthma diagnosis are still available!

We took a representative clinical question and ran it through Trip Pro, PubMed Best Match (the default algorithm) and PubMed Most Recent. We then exported the top ten results from each – our assumption was that it’s a busy health professional who doesn’t have lots of times to look through pages of results!

The clinical question this time related to the use of use and safety of SSRIs during pregnancy. For each database we used the search terms SSRIs AND pregnancy – you can try the search yourself using these links:

• Trip Pro (NOTE: this assumes you have access to Pro)
• PubMed Best Match
• PubMed Most Recent

We then asked ChatGPT to compare the results using this prompt:

Below are three set of results for a search for ‘SSRIs AND pregnancy’ with a view to answering the question about the use and safety of SSRIs during pregnancy. Comment on quality of evidence, recency of articles and applicability to answering the question. And give an overall view on which database is likely most useful to a busy health professional.

It made the following assessment for each database:

Trip Pro: This database provides up-to-date and practical information with fewer older references, making it suitable for answering clinical questions efficiently.

PubMed Best Match: This database offers a mix of high-quality and relevant evidence but includes some outdated material. Its focus on SSRIs in pregnancy makes it useful, but its age range might require careful selection of the most recent and relevant articles.

PubMed Most Recent: This database excels in recency and breadth but may be less practical for quickly answering focused clinical questions due to its diversity and inclusion of less clinically relevant research.

And it gave this final comment:

Recommendation for Busy Health Professionals
Trip Pro is likely the most useful due to its balance of recency, applicability, and practicality. It provides high-quality, up-to-date evidence without being overly broad or outdated, making it ideal for answering focused clinical questions about the safety of SSRIs during pregnancy.

If you’d like a trial of Trip Pro please get in touch: jon.brassey@tripdatabase.com

2024 was a great year for Trip.

We continue to have a impressive impact on care around the globe, helping support millions of decisions with evidence-based content. This is Trip’s core function, as such, it’s ‘business as usual’. However, we have continued to improve the site as much as we can and 2024 was full of significant improvements (BTW this opening section is identical to last year’s review – apart from the update to the year)!

Across the year our Rapid Review (RR) service has brought us great joy and an equal amount of challenge. Doing RRs for sectors we’ve not usually worked with has been particularly interesting. Given our experience and skills we can produce great rapid reviews at a much lower price than most, so if your organisation needs a RR undertaking in 2025, then send us an email: rapidreviews@tripdatabase.com.

January 2024
We spent a lot of time working with LLMs to get to grips with Q&A. Our initial attempts were really encouraging and we know – nearly 12 months later – a lot more of the potential for LLMs.

February 2024
More work on LLMs, this time with a latest evidence feature. This was great fun and is now a live project on Trip (see here), and this is likely to expand in 2025.
We also added a large number of new guideline scores to Trip. The title of the announcement Disappointing guideline scores, sums up our thoughts!

March 2024
Many of our searches are really simple so it was great to better understand the motivations of our users with by launching a survey. We also had a blast from the past, courtesy of the Internet Archive, with the original 25 publishers included in Trip:

April 2024
More fun with LLMs including extracting recommendations from guidelines and systematic reviews and using them to analyse clickstream data.

May 2024
This was a really significant month. We moved our infrastructure onto the cloud and made a really big change to our search results.

June 2024
Another user survey, this time asking our users about their thoughts on our use of AI.

July 2024
As well as releasing the results on the AI survey we improved our inclusion of full-text documents (for Pro users) with over 85% of our journal articles linking to full-text.

August 2024
A quiet month with a simple announcement regarding miss-spelling!

September 2024
We released the mis-spelling feature mentioned above but more importantly we broke a record for the number of systematic reviews we link to, with over 550,000!

October 2024
Latest evidence was launched! This is going down really well and so we’re looking to expand to areas outside of primary care.

November 2024
Trip is often asked how to we compare with PubMed. To help we created a comparison based on an example search. We have now done two comparisons (one and two). We used ChatGPT to undertake the analysis – felt it was less biased than asking ourselves. If you’re interested in answering clinical questions using high-quality evidence then the results are clear….

December 2024
We released some important design changes (see here and here). Many were small but boosted transparency and usability of the site.

We also started working with Mind Maps, really amazing feature that we hope to roll out in early 2025. This combines LLMs and a lovely graphical interface.

If we had to summarise 2024 it would be the year we got comfortable with LLMs (as you’ll see in 2025) and the year we continued to push out new features to make Trip a better service for our users. And, in the spirit of this year and next, we asked ChatGPT to summarise our year:

In 2024, Trip Database focused on leveraging LLMs for innovation, enhancing infrastructure and usability, and expanding evidence-based features like “latest evidence.” User feedback and AI played central roles in refining offerings, while milestone achievements and transparency-driven updates set the foundation for future advancements.