Trip Database Blog

Our automated review system seeks to locate the PIC elements of PICO.  We didn’t have the resource to do the ‘O’ (outcomes) which seems a shame.  But we want to explore incorporating it and an important starting block is having a list of outcomes.  Such a list doesn’t – obviously – exist.  I put an email request to the EBHC maillist and got a number of responses that have started me down the route of attempting to compile a list that might prove useful to me and others.

Another option to explore is scraping the outcomes listed in ct.gov, a fairly straightforward task but the outcomes aren’t ‘clean’.  By that, if you look at these example outcomes from the site they’re quite long, which can be problematic!

• Measure Metformin Induced effects in phosphorylation of S6K, 4E-BP-1 and AMPK via immunohistochemical analysis
• Antibody response rate to measles at 6 weeks postvaccination
• Change in Maximum Forced Expiratory Volume at One Second (FEV1)
• Biomarkers will be identified to help predict future prostate cancer risks and patients likely to benefit from preventive strategies

A further option is the COMET Initiative (Core Outcome Measures in Effectiveness Trials) and I’ve reached out to them for help.

So, very much a work in progress! As I type/write this we have just one list but we are hopeful that we’ve located two other lists, one in CVD and one in schizophrenia.

List to date:

From the SONG Initiative (Standardised Outcomes in Nephrology)

fatigue
cardiovascular disease
vascaular access
mortality
ability to travel
ability to work
anemia
blood pressure
anaemia
depression
dialysis adequacy
dialysis-free time
drop in blood pressure
hospitalization
hospitalisation
impact on friends
impact on family
infection
immunity
mobility
pain
potassium
target weight
washed out after dialysis
anxiety
stress
bone health
calcium
cognition
cramps
financial impact
food enjoyment
taste
itching
nausea
vomiting
parathyroid hormone
phosphate
restless legs
sexual function
sleep
insomnia

We’ve just rolled out a broad range of upgrades to the site:

Latest and greatest – for a given topic you can now easily view the very latest for a topic as well as those most frequently visited (within the last 12 months).

Tour – to help make it easier to orientate yourself to the site, available via the top navigation bar:

How to use Trip is now clearer and easier to use.

Top of the results has been tidied up with the images and videos being moved to the ‘refine’ area of the results page (on right-hand side).

Sort by popularity is now possible via the following drop-down:

Differences between free and Pro more clearly laid out – click here to view.

Search engine optimisation (SEO) to make it easier for users to find our content via Google and other search engines.

Trip Answers, our repository of clinical Q&As has been refreshed to make it more user friendly.

We get asked this fairly regularly and due to the breadth of coverage it’s really difficult to succinctly answer.  But this image is our best attempt at capturing it:

Note our use of the evidence pyramid!

With regard PubMed (and PubMed Central) this is a bit more information:

• All content from the top 500 journals only (based – broadly – on impact factor)
• All the RCTs in whichever of the 5,000+ journals are in PubMed
• All systematic reviews in whichever of the 5,000+ journals are in PubMed (Trip Pro only)
• All peer-reviewed full-text articles from PubMed Central (Trip Pro only)

I suspect this page will be a ‘living’ document, frequently edited to improve it. So, if you have any questions please let me know – jon.brassey@tripdatabase.com

As part of the KConnect project we were able to create a wonderful set of analytic tools to analyse how people use the site.  My current favourite is one we’re calling ‘topics’.  For a given search terms it analyses all the article titles that users have clicked on and groups them based on meaning.

This is important as searches for ‘alcohol’ reveal they are interested in the term, but it is only when they click on a title do they ‘reveal’ there likely intention.  That is because search terms are typically 1-3 terms while document titles contain many more terms.  Below is an analysis of search for ‘alcohol’:

This shows that the most popular subject relates to alcohol withdrawal (as that is the major topic in the most popularly clicked titles).  But we can look at even more detail.  So, within alcohol withdrawal we can see that baclofen, dexmedetomidine and benzodiazepines are the most popular sub-topics.

I hope this is clear!

My conclusion is that this gives a clear insight into the Trip user (almost exclusively health professionals are and mainly using Trip to obtain trusted answers to their clinical questions).  But, more than that it surely reflects the uncertainties/questions of the health service, making it an important component of research procurement – ensuring the topics funded meet the needs of the eventual users.

Oh yes, if you want me to generate some examples for topics of your interest then let me know.  I’m sure I can find time to generate a few more examples!

We’ve revealed our automated review system but it’s still not ready for everyone to use but we now have a timeline:

• End of November – all the variables used are generated automatically and all of these are having significant work done on them to improve them.
• December – the images we’ve shown do not do it justice so we’ve employed the services of a data visualisation expert.  She’s in demand so will not start till December and will deliver the results by the end of the month.
• January – all systems will be plugged in and then released to a small number of people to beta-test
• End of January – system released to the world.

So, there you have it, just over three months time we should have our currently good system made truly amazing.

Below are some search tips to help users get the most out of Trip! If we’ve missed anything then please let us know by emailing jon.brassey@tripdatabase.com. Thanks to Igor Brbre for assisting with this! We’ll highlight:

• Boolean
• Truncation
• Phrase searching
• Proximity searching
• Date range
• Title versus body of text
• Other key ways to maximise results in Trip

Boolean

We support simple and complex boolean searches using the operators AND, OR and NOT:

• Prostate AND cancer (technically not needed as we, by default, insert ‘ANDs’ between terms)
• zinc OR calcium
• breast NOT cancer
• cancer AND (breast OR prostate OR colon) AND (NOT brain)

Trip’s advanced search (Pro only feature) tends to make this easier!

NOTE: this is no longer working! Truncation 

Use the asterisk:

• cardio*

Phrase searching

Use quotation marks:

• “malignant hypertension”

NOTE: we’ve found that hyphens interfere with phrase searching!  So, if you’re looking for e-learning it’s best to search for “e learning” NOT “e-learning” (a difference of 666,721 results)!

Proximity searching

This finds terms that are close to each other, how close is up to you:

• “elderly falls”~3 finds matches where the term ‘elderly’ is within 3 words of ‘falls’
• “elderly falls”~5 finds matches where the term ‘elderly’ is within 5 words of ‘falls’

Date range

• prostate cancer from:2010 to:2017 finds articles on prostate cancer between 2010 and 2017!

Title versus body of text

By default Trip searches all of the document that we have indexed (so this might be an abstract or the full-text, depending on what the publisher has made freely available) but you can restrict to title only:

• (title:prostate cancer)
• (title:prostate cancer) screening psa

In the latter examples it retrieves articles with ‘prostate cancer’ in the title and ‘screening’ and ‘psa’ anywhere in the body of the text.

Advanced search (Pro only feature)

Advanced search makes all the boolean much easier:

Combination searches (Pro only feature)

As ‘combination searches’ is too long for the navigation, we’ve called in ‘recent’ (open to suggestions for a better term!).  It allows you to combine complex searches:

Other stuff!

See image below for a number of key features:

NOTE: below each result there is a line of tools:

• Tweet this – if you’re on Twitter you can tweet the result
• Star this – if you’re signed in this will save it to view later (via the ‘Starred‘ link at the top of the page)
• Report broken link – if you find a dead link, press this and let us know
• Related – finds related articles
• ‘clicks’ – Pro feature only, shows how many times an article has been clicked

Other features

• Smart Search – helps prevent you missing vital references, really easy and powerful feature
• Assessment of bias – for all controlled trials we use the latest automation techniques to assess trials for bias (critical appraisal)
• Answer engine – using various algorithms we find the best available answer to the question (which we’ve also inferred from your search terms)

In my previous post on our automated review system I concentrated on describing the product. This is all fine, but one quotation I’m trying to remember in my day-to-day life is:

So, why do what we’re doing?  The reasons are multiple and include:

• Years ago I had a conversation with someone and I ended up sending them a link to a set of Trip search results.  They said that was fine, if he had a few hours to read them – which he didn’t.  I started to wonder if there was a way of automatically scanning the literature to allow people to really easily get a feel for a topic area.  So, you might want to see what interventions are useful for a given condition (perhaps the first line has failed).  Our system will automatically generate a list of interventions with an estimate of likely effectiveness.
• The Trip Answer Engine is hugely popular and we can use the technology to boost the content.  So, it solves a problem for Trip (how to boost coverage) and it solves the problem of quick access to information for a specific clinical question.  So, a user might want to search for acne and lasers we can pull through an answer along the lines of “Lasers have been studied in 12 RCTs and have been broadly favourable” we can link to all the articles (if the user has the time) but we can also rank the intervention, saying something like “Lasers are ranked 3 out of 8 for interventions in acne“.  This seems incredibly useful to me.
• Updating guidelines and reviews are problematic.  With our system you could ‘watch’ an intervention and get alerts when new evidence is generated.  Or, even more useful, when new research is published that contradicts the previous findings.
• Rapid reviews are increasingly important and the automated system could form a core part of any semi-manual rapid review tool.
• Intellectual challenge!

So, one product – multiple problems solved!