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Autosynthesis – update on progress

The autosynthesis project is an attempt to create automatic evidence reviews; automatically synthesising RCTs and systematic reviews.

We’re making great progress and the visualisations are stunning (see below). In fact the whole interface is amazing, allowing users to interact with the data (compared with the traditional, static, forest plot)!

NOTE: the underlying data is not accurate/calibrated but the point of sharing is purely to show how it’ll look.

Level One

This is the high level view – showing all the interventions for a given disease.  Each blob represents an individual intervention.  The horizontal axis represents likelihood of effectiveness and the vertical axis is a measure of bias for the evidence used.  Blob size is proportionate to the sample size – the bigger the blob the more trials/SRs.

Level Two

Click on a blob and it shows the constituent elements of the blob!  Different colours distinguish between RCTs and systematic reviews.  Again blob size is proportionate to sample size (for RCTs).

We’re hoping it’ll be available by February.

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Trip and 2017 – improving care, globally, on a massive scale

As we enter a new year it’s tradition to look back at the previous year.  So, for 2017, so here we go:

  • 981,510 separate sessions (separate visits to the site)
  • 618,082 separate users
  • 3,573,702 page views
  • 5mins 5 seconds – average session duration
  • 4,989,342 minutes spent on the site over the year by all our users
  • 12.66% reduction in bounce rate (people who come to the site and only look at the page they land on)
  • Most popular country for visitors: USA (21.3%), UK (11.0%), Spain (6.8%), Australia (5.2%) and Canada (4.6%)

Those figures relate to people coming to the site but we allow third party sites to use our service via an API.  As such we get used a lot more.

Given that over 40% of our searches support improved patient care (see here and here) we can be sure we’ve had a massive impact on global healthcare.  Previously we’ve tried to quantify our impact so here goes for 2017:

  • If we assume 1.25 searches per session on the site = 1,226,887 searches
  • Assume we gain another 33% of searches via our API = 408,921
  • Total searches = 1,635,808

We estimate 40.8% of searches result in improved patient care which equals 667,410.

So, globally, Trip has improved care 667,410 times.

Updated coverage graphic

With the inclusion of DynaMed Plus to Trip I felt it was time to update the graphic that attempts to convey what users search when they use Trip.  It’s a tough ask and below is my attempt (slight update on a previous graphic).  Comments welcome!!

 

DynaMed Plus added to Trip = Trusted Answers

DynaMed Plus is one of the most sought after resources in EBM.  As such we’re absolutely delighted to announce that DynaMed Plus content has been added to Trip.  And, what’s even better, if you’re not a subscriber to DynaMed Plus you can get ten free ‘views’ per month.

As you’ll see from the above graphic, DynaMed Plus is – like Trip – focused on supporting rapid question answering.  So, having both Trip and DynaMed Plus should maximise your chances of obtaining trusted answers to your clinical questions.

Autosynthesis – timeline to release

We’ve just had a meeting with the technical team and as a result we’re updating the timeline to release.  The plan is as follows:

Phase 1 – integrate improvements to data used to generate the synthesis (sample size, PICO identification etc).  This should be finished by the end of December and will interact with the current ‘front end’.

Phase 2 – integrate the new design. End of January

Phase 3 – integrate features that allow people to edit/modify the results. End of February.

We’re not sure when the full release will be, but I suspect we’ll allow people to interact with the system sometime in early 2018.

List of outcomes

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

Upgrade to the site

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.

Sources searched by Trip

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

How searches for ‘alcohol’ reveal clinical interest/uncertainty

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!

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