“Pharmacological Action” in PubMed has no True Equivalent in OVID MEDLINE

11 01 2012

Searching for EMBASE Subject Headings (the EMBASE index terms) for drugs is relatively straight forward in EMBASE.

When you want to search for aromatase inhibitors you first search for the Subject Heading mapping to aromatase inhibitors (aromatase inhibitor). Next you explode aromatase inhibitor/ if you are interested in all its narrower terms. If not, you search both for the general term aromatase inhibitor and those specific narrower terms you want to include.
Exploding aromatase inhibitor (exp aromatase inhibitor/) yields 15938 results. That is approximately twice what you get by searching aromatase inhibitor/ alone (not exploded). This yields 7434 hits.

It is different in MEDLINE. If you search for aromatase inhibitors in the MeSH database you get two suggestions.

The first index term “Aromatase Inhibitors” is a Mesh. It has no narrower terms.
Drug-Mesh are generally not arranged by working mechanism, but by chemical structure/type of compound. That is often confusing. Spironolactone for instance belongs to the MeSH Lactones (and Pregnenes) not to the MeSH Aldosterone Antagonists or Androgen Antagonist. Most Clinicians want to search for a group of compounds with the same mechanism of action, not the same biochemical family

The second term “Aromatase Inhibitors” [Pharmacological Action]  however does stand for the working mechanism. It does have narrower terms, including 2 MeSH terms (highlighted) and various substance names, also called Supplementary Concepts. 

For complete results you have to search for both MeSH and Pharmacological action: “Aromatase Inhibitors”[Mesh] yields 3930 records, whereas (“Aromatase Inhibitors”[Mesh]) OR “Aromatase Inhibitors” [Pharmacological Action] yields 6045. That is a lot more.

I usually don’t search PubMed, but OVID MEDLINE.

I know that Pharmacological Action-subheadings are important, so I tried to find the equivalent in OVID .

I found the MeSH Aromatase Inhibitors, but -unlike PubMed- OVID showed only two narrower Drug Terms (called Non-MeSH here versus MeSH in PubMed).

I found that odd.

I reasoned “Pharmacological action” might perhaps be combined with the MESH in OVID MEDLINE. This was later confirmed by Melissa Rethlefsen (see Twitter discussion below)

In Ovid MEDLINE I got 3937 hits with Aromatase Inhibitors/ and 5219 with exp Aromatase Inhibitors/ (thus including aminogluthemide or Fadrozole)

At this point I checked PubMed (shown above). Here I found  that “Aromatase Inhibitors”[Mesh] OR “Aromatase Inhibitors” [Pharmacological Action] yielded 6045 hits in PubMed, against 5219 in OVID MEDLINE for exp Aromatase Inhibitors/

The specific aromatase inhibitors Aminogluthemide/and Fadrozole/ [set 60] accounted fully for the difference  between exploded [set 59] and non-exploded Aromatase Inhibitors[set 58].

But what explained the gap of approximately 800 records between “Aromatase Inhibitors”[Mesh] OR “Aromatase Inhibitors”[Pharmacological Action]* in PubMed and exp aromatase inhibitors/ in OVID MEDLINE?

Could it be the substance names, mentioned under “Aromatase Inhibitors”[Pharmacological Action], I wondered?

Thus I added all the individual substance names in OVID MEDLINE (code= .rn.). See search set 61 below.

Indeed these accounted fully for the difference (set 62= 59 or 61 : the total number of hits in PubMed is similar)

It obviously is a mistake of OVID MEDLINE and I will inform them.

For the meanwhile, take care to add the individual substance names when you search for drug terms that have a pharmacological action-equivalent in PubMed. The substance names are not automatically searched when exploding the MeSH-term in OVID MEDLINE.

——–

For more info on Pharmacological action, see: http://www.nlm.nih.gov/bsd/disted/mesh/paterms.html

Twitter Discussion between me and Melissa Rethlefsen about the discrepancy between PubMed and OVID MEDLINE (again showing how helpful Twitter can be for immediate discussions and exchange of thoughts)

[read from bottom to top]

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PubMed’s Higher Sensitivity than OVID MEDLINE… & other Published Clichés.

21 08 2011

ResearchBlogging.orgIs it just me, or are biomedical papers about searching for a systematic review often of low quality or just too damn obvious? I’m seldom excited about papers dealing with optimal search strategies or peculiarities of PubMed, even though it is my specialty.
It is my impression, that many of the lower quality and/or less relevant papers are written by clinicians/researchers instead of information specialists (or at least no medical librarian as the first author).

I can’t help thinking that many of those authors just happen to see an odd feature in PubMed or encounter an unexpected  phenomenon in the process of searching for a systematic review.
They think: “Hey, that’s interesting” or “that’s odd. Lets write a paper about it.” An easy way to boost our scientific output!
What they don’t realize is that the published findings are often common knowledge to the experienced MEDLINE searchers.

Lets give two recent examples of what I think are redundant papers.

The first example is a letter under the heading “Clinical Observation” in Annals of Internal Medicine, entitled:

“Limitations of the MEDLINE Database in Constructing Meta-analyses”.[1]

As the authors rightly state “a thorough literature search is of utmost importance in constructing a meta-analysis. Since the PubMed interface from the National Library of Medicine is a cornerstone of many meta-analysis,  the authors (two MD’s) focused on the freely available PubMed” (with MEDLINE as its largest part).

The objective was:

“To assess the accuracy of MEDLINE’s “human” and “clinical trial” search limits, which are used by authors to focus literature searches on relevant articles.” (emphasis mine)

O.k…. Stop! I know enough. This paper should have be titled: “Limitation of Limits in MEDLINE”.

Limits are NOT DONE, when searching for a systematic review. For the simple reason that most limits (except language and dates) are MESH-terms.
It takes a while before the indexers have assigned a MESH to the papers and not all papers are correctly (or consistently) indexed. Thus, by using limits you will automatically miss recent, not yet, or not correctly indexed papers. Whereas it is your goal (or it should be) to find as many relevant papers as possible for your systematic review. And wouldn’t it be sad if you missed that one important RCT that was published just the other day?

On the other hand, one doesn’t want to drown in irrelevant papers. How can one reduce “noise” while minimizing the risk of loosing relevant papers?

  1. Use both MESH and textwords to “limit” you search, i.e. also search “trial” as textword, i.e. in title and abstract: trial[tiab]
  2. Use more synonyms and truncation (random*[tiab] OR  placebo[tiab])
  3. Don’t actively limit but use double negation. Thus to get rid of animal studies, don’t limit to humans (this is the same as combining with MeSH [mh]) but safely exclude animals as follows: NOT animals[mh] NOT humans[mh] (= exclude papers indexed with “animals” except when these papers are also indexed with “humans”).
  4. Use existing Methodological Filters (ready-made search strategies) designed to help focusing on study types. These filters are based on one or more of the above-mentioned principles (see earlier posts here and here).
    Simple Methodological Filters can be found at the PubMed Clinical Queries. For instance the narrow filter for Therapy not only searches for the Publication Type “Randomized controlled trial” (a limit), but also for randomized, controlled ànd  trial  as textwords.
    Usually broader (more sensitive) filters are used for systematic reviews. The Cochrane handbook proposes to use the following filter maximizing precision and sensitivity to identify randomized trials in PubMed (see http://www.cochrane-handbook.org/):
    (randomized controlled trial [pt] OR controlled clinical trial [pt] OR randomized [tiab] OR placebo [tiab] OR clinical trials as topic [mesh: noexp] OR randomly [tiab] OR trial [ti]) NOT (animals [mh] NOT humans [mh]).
    When few hits are obtained, one can either use a broader filter or no filter at all.

In other words, it is a beginner’s mistake to use limits when searching for a systematic review.
Besides that the authors publish what should be common knowledge (even our medical students learn it) they make many other (little) mistakes, their precise search is difficult to reproduce and far from complete. This is already addressed by Dutch colleagues in a comment [2].

The second paper is:

PubMed had a higher sensitivity than Ovid-MEDLINE in the search for systematic reviews [3], by Katchamart et al.

Again this paper focuses on the usefulness of PubMed to identify RCT’s for a systematic review, but it concentrates on the differences between PubMed and OVID in this respect. The paper starts with  explaining that PubMed:

provides access to bibliographic information in addition to MEDLINE, such as in-process citations (..), some OLDMEDLINE citations (….) citations that precede the date that a journal was selected for MEDLINE indexing, and some additional life science journals that submit full texts to PubMed Central and receive a qualitative review by NLM.

Given these “facts”, am I exaggerating when I am saying that the authors are pushing at an open door when their main conclusion is that PubMed retrieved more citations overall than Ovid-MEDLINE? The one (!) relevant article missed in OVID was a 2005 study published in a Japanese journal that MEDLINE started indexing in 2007. It was therefore in PubMed, but not in OVID MEDLINE.

An important aspect to keep in mind when searching OVID/MEDLINE ( I have earlier discussed here and here). But worth a paper?

Recently, after finishing an exhaustive search in OVID/MEDLINE, we noticed that we missed a RCT in PubMed, that was not yet available in OVID/MEDLINE.  I just added one sentence to the search methods:

Additionally, PubMed was searched for randomized controlled trials ahead of print, not yet included in OVID MEDLINE. 

Of course, I could have devoted a separate article to this finding. But it is so self-evident, that I don’t think it would be worth it.

The authors have expressed their findings in sensitivity (85% for Ovid-MEDLINE vs. 90% for PubMed, 5% is that ONE paper missing), precision and  number to read (comparable for OVID-MEDLINE and PubMed).

If I might venture another opinion: it looks like editors of medical and epidemiology journals quickly fall for “diagnostic parameters” on a topic that they don’t understand very well: library science.

The sensitivity/precision data found have little general value, because:

  • it concerns a single search on a single topic
  • there are few relevant papers (17- 18)
  • useful features of OVID MEDLINE that are not available in PubMed are not used. I.e. Adjacency searching could enhance the retrieval of relevant papers in OVID MEDLINE (adjacency=words searched within a specified maximal distance of each other)
  • the searches are not comparable, nor are the search field commands.

The latter is very important, if one doesn’t wish to compare apples and oranges.

Lets take a look at the first part of the search (which is in itself well structured and covers many synonyms).
First part of the search - Click to enlarge
This part of the search deals with the P: patients with rheumatoid arthritis (RA). The authors first search for relevant MeSH (set 1-5) and then for a few textwords. The MeSH are fine. The authors have chosen to use Arthritis, rheumatoid and a few narrower terms (MeSH-tree shown at the right). The authors have taken care to use the MeSH:noexp command in PubMed to prevent the automatic explosion of narrower terms in PubMed (although this is superfluous for MesH terms having no narrow terms, like Caplan syndrome etc.).

But the fields chosen for the free text search (sets 6-9) are not comparable at all.

In OVID the mp. field is used, whereas all fields or even no fields are used in PubMed.

I am not even fond of the uncontrolled use of .mp (I rather search in title and abstract, remember we already have the proper MESH-terms), but all fields is even broader than .mp.

In general a .mp. search looks in the Title, Original Title, Abstract, Subject Heading, Name of Substance, and Registry Word fields. All fields would be .af in OVID not .mp.

Searching for rheumatism in OVID using the .mp field yields 7879 hits against 31390 hits when one searches in the .af field.

Thus 4 times as much. Extra fields searched are for instance the journal and the address field. One finds all articles in the journal Arthritis & Rheumatism for instance [line 6], or papers co-authored by someone of the dept. of rheumatoid surgery [line 9]

Worse, in PubMed the “all fields” command doesn’t prevent the automatic mapping.

In PubMed, Rheumatism[All Fields] is translated as follows:

“rheumatic diseases”[MeSH Terms] OR (“rheumatic”[All Fields] AND “diseases”[All Fields]) OR “rheumatic diseases”[All Fields] OR “rheumatism”[All Fields]

Oops, Rheumatism[All Fields] is searched as the (exploded!) MeSH rheumatic diseases. Thus rheumatic diseases (not included in the MeSH-search) plus all its narrower terms! This makes the entire first part of the PubMed search obsolete (where the authors searched for non-exploded specific terms). It explains the large difference in hits with rheumatism between PubMed and OVID/MEDLINE: 11910 vs 6945.

Not only do the authors use this .mp and [all fields] command instead of the preferred [tiab] field, they also apply this broader field to the existing (optimized) Cochrane filter, that uses [tiab]. Finally they use limits!

Well anyway, I hope that I made my point that useful comparison between strategies can only be made if optimal strategies and comparable  strategies are used. Sensitivity doesn’t mean anything here.

Coming back to my original point. I do think that some conclusions of these papers are “good to know”. As a matter of fact it should be basic knowledge for those planning an exhaustive search for a systematic review. We do not need bad studies to show this.

Perhaps an expert paper (or a series) on this topic, understandable for clinicians, would be of more value.

Or the recognition that such search papers should be designed and written by librarians with ample experience in searching for systematic reviews.

NOTE:
* = truncation=search for different word endings; [tiab] = title and abstract; [ti]=title; mh=mesh; pt=publication type

Photo credit

The image is taken from the Dragonfly-blog; here the Flickr-image Brain Vocab Sketch by labguest was adapted by adding the Pubmed logo.

References

  1. Winchester DE, & Bavry AA (2010). Limitations of the MEDLINE database in constructing meta-analyses. Annals of internal medicine, 153 (5), 347-8 PMID: 20820050
  2. Leclercq E, Kramer B, & Schats W (2011). Limitations of the MEDLINE database in constructing meta-analyses. Annals of internal medicine, 154 (5) PMID: 21357916
  3. Katchamart W, Faulkner A, Feldman B, Tomlinson G, & Bombardier C (2011). PubMed had a higher sensitivity than Ovid-MEDLINE in the search for systematic reviews. Journal of clinical epidemiology, 64 (7), 805-7 PMID: 20926257
  4. Search OVID EMBASE and Get MEDLINE for Free…. without knowing it (laikaspoetnik.wordpress.com 2010/10/19/)
  5. 10 + 1 PubMed Tips for Residents (and their Instructors) (laikaspoetnik.wordpress.com 2009/06/30)
  6. Adding Methodological filters to myncbi (laikaspoetnik.wordpress.com 2009/11/26/)
  7. Search filters 1. An Introduction (laikaspoetnik.wordpress.com 2009/01/22/)




3rd Call for Submissions for “Medical Information Matters”: Tools for Searching the Biomedical Literature

8 05 2011

It takes some doing to breathe life into Medical Information Matters” (blog carnival about medical  information).
A month ago I wrote a 2nd call for submissions post for this blog carnival. Unfortunately the next host, Martin Fenner, didn’t have time to finish a blog post and has come up with a new (interesting) variation on the theme “A Wish list for better medical information”.

Martin asks you to philosophize, blog and/or comment about “Tools for Searching the Biomedical Literature.

You can base your contribution on a recent (editable) survey of 28 different PubMed derivative tools by Zhiyong Lu (NCBI) [1].

Thus, write your thoughts on the various PubMed derivative tools mentioned here or write about your own favorite 3rd party PubMed tool (included or not).

For details, see Martin’s blog post announcing this upcoming edition. The Blog Carnival FAQs are here.

And if you don’t have time to write about this topic, you may still find the survey useful, as well as the views of others on this topic. So check out Martin’s blog Gobbledygook once in a while to see if the blog edition has been posted.

Note [1]: If you have already submitted a post to the carnival, or would like to write about another theme, we will take care that your post (if relevant)  will be included in this or the next edition. You can always submit here.

Note [2]: Would you like to host “Medical Information Matters” at your blog? Please comment here or write to: laika dot spoetnik at gmail dot com. We need hosts for June, July, August and September (submission deadline first Saturday of every month, posting on the next Tuesday)

  1. Lu Z. PubMed and beyond: a survey of web tools for searching biomedical literature. Database. 2011 Jan;2011. doi: http://dx.doi.org/10.1093/database/baq036




Search OVID EMBASE and Get MEDLINE for Free…. without knowing it

19 10 2010

I have the impression that OVIDSP listens more to librarians than the NLM, who considers the end users of databases like PubMed more important, mainly because there are more of them. On the other hand NLM communicates PubMed’s changes better (NLM Technical Bulletin) and has easier to find tutorials & FAQs, namely at the PubMed homepage.

I gather that the new changes to the OVIDSP interface are the reason why two older OVID posts are the recent number 2 and 3 hits on my blog. My guess is that people are looking for some specific information on OVID’s interface changes that they can’t easily access otherwise.

But this post won’t address the technical changes. I will write about this later.

I just want to mention a few changes to the OVIDSP databases MEDLINE and EMBASE, some of them temporary, that could have been easily missed.

[1] First, somewhere in August, OVID MEDLINE contained only indexed PubMed articles. I know that OVID MEDLINE misses some papers PubMed already has -namely the “as supplied by publisher” subset-, but this time the difference was dramatic: “in data review” and “in process” papers weren’t found as well. I almost panicked, because if I missed that much in OVID MEDLINE, I would have to search PubMed as well, and adapt the search strategy…. and, since I already lost hours because of OVID’s extreme slowness at that time, I wasn’t looking forward to this.

According to an OVID-representative this change was not new, but was already there since (many) months. Had I been blind? I checked the printed search results of a search I performed in June. It was clear that the newer update found less records, meaning that some records were missed in the current (August) update. Furthermore the old Reference Manager database contained non-indexed records. So no problems then.

But to make a long story short. Don’t worry: this change disappeared as quickly as it came.
I would have doubted my own eyes, if my colleague hadn’t seen it too.

If you have done a MEDLINE OVID search in the second half of August you might like to check the results.

[2] Simultaneously there was another change. A change that is still there.

Did you know that OVID EMBASE contains MEDLINE records as well? I knew that you could search EMBASE.com for MEDLINE and EMBASE records using the “highly praised EMTREE“, but not that OVID EMBASE recently added these records too.

They are automatic found by the text-word searches and by the EMTREE already includes all of MeSH.

Should I be happy that I get these records for free?

No, I am not.

I always start with a MEDLINE search, which is optimized for MEDLINE (with regard to the MeSH).

Since indexing by  EMTREE is deep, I usually have (much) more noise (irrelevant hits) in EMBASE.

I do not want to have an extra number of MEDLINE-records in an uncontrolled way.

I can imagine though, that it would be worthwhile in case of a quick search in EMBASE alone: that could save time.
In my case, doing extensive searches for systematic reviews I want to be in control. I also want to show the number of articles from MEDLINE and the number of extra hits from EMBASE.

(Later I realized that a figure shown by the OVID representative wasn’t fair: they showed the hits obtained when searching EMBASE, MEDLINE and other databases in Venn diagrams: MEDLINE offered little extra beyond EMBASE, which is self-evident, considering that EMBASE includes almost all MEDLINE records.- But I only learned this later.)

It is no problem if you want to include these MEDLINE records, but it is easy to exclude them.

You can limit for MEDLINE or EMBASE records.

Suppose your last search set is 26.

Click Limits > Additional Limits > EMBASE (or MEDLINE)

Alternatively type: limit 26 to embase (resp limit 26 to medline) Added together they make 100%

If only they would have told us….


3. EMBASE OVID now also adds conference abstracts.

A good thing if you do an exhaustive search and want to include unpublished material as well (50% of the conference abstracts don’t get published).

You can still exclude them if you like  (see publication types to the right)

Here is what is written at EMBASE.com

Embase now contains almost 800 conferences and more than 260,000 conference abstracts, primarily from journals and journal supplements published in 2009 and 2010. Currently, conference abstracts are being added to Embase at the rate of 1,000 records per working day, each indexed with Emtree.
Conference information is not available from PubMed, and is significantly greater than BIOSIS conference coverage. (…)

4. And did you know that OVID has eliminated StopWords from MEDLINE and EMBASE? Since  a few years you can now search for words or phrases like is there hope.tw. Which is a very good thing, because it broadens the possibility to search for certain word strings. However, it isn’t generally known.

OVID changed it after complaints by many, including me and a few Cochrane colleagues. I thought I had written a post on it before, but I apparently I haven’t ;).

Credits

Thanks to Joost Daams who always has the latest news on OVID.

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Problems with Disappearing Set Numbers in PubMed’s Clinical Queries

18 10 2010

In some upcoming posts I will address various problems related to the changing interfaces of bibliographic databases.

We, librarians and end users, are overwhelmed by a flood of so-called upgrades, which often fail to bring the improvements that were promised….. or which go hand-in-hand with temporary glitches.

Christina of Christina’s Lis Rant even made rundown of the new interfaces of last summer. Although she didn’t include OVID MEDLINE/EMBASE, the Cochrane Library and Reference manager in her list, the total number of changed interfaces reached 22 !

As a matter of fact, the Cochrane Library was suffering some outages yesterday, to repair some bugs. So I will postpone my coverage of the Cochrane bugs a little.

And OVID send out a notice last week: This week Ovid will be deploying a software release of the OvidSPplatform that will add new functionality and address improvements to some existing functionality.”

In this post I will confine myself to the PubMed Clinical Queries. According to Christina PubMed changes “were a bit ago”, but PubMed continuously tweaks  its interface, often without paying much attention to its effects.

Back in July, I already covered that the redesign of the PubMed Clinical Queries was no improvement for people who wanted to do more than a quick and dirty search.

It was no longer possible to enter a set number in the Clinical Queries search bar. Thus it wasn’t possible to set up a search in PubMed first and to then enter the final set number in the Clinical Queries. This bug was repaired promptly.

From then on, the set number could be entered again in the clinical queries.

However, one bug was replaced by another: next, search numbers were disappearing from the search history.

I will use the example I used before: I want to know if spironolactone reduces hirsutism in women with PCOS, and if it works better than cyproterone acetate.

Since little is published about this topic,  I only search for  hirsutism and spironolactone. These terms  map correctly with  MeSH terms. In the MeSH database I also see (under “see also”) that spironolactone belongs to the aldosterone antagonists, so I broaden spironolactone (#2) with “Aldosterone antagonists”[pharmacological Action] using “OR” (set #7). My last set (#8) consists of #1 (hirsutism) AND #7 (#2 OR #6)

Next I go to the Clinical Queries in the Advanced Search and enter #8. (now possible again).

I change the Therapy Filter from “broad”  to “narrow”, because the broad filter gives too much noise.

In the clinical queries you see only the first five results.

Apparently even the clinical queries are now designed to just take a quick look at the most recent results, but of course, that is NOT what we are trying to achieve when we search for (the best) evidence.

To see all results for the narrow therapy filter I have to go back to the Clinical Queries again and click on see all (27) [5]

A bit of a long way about. But it gets longer…


The 27 hits, that result from combining the Narrow therapy filter with my search #8 appears. This is set #9.
Note it is a lower number than set #11 (search + systematic review filter).

Meanwhile set #9 has disappeared from my history.

This is a nuisance if I want to use this set further or if I want to give an overview of my search, i.e. for a presentation.

There are several tricks by which this flaw can be overcome. But they are all cumbersome.

1. Just add set number (#11 in this case, which is the last search (#8) + 3 more) to the search history (you have to remember the search set number though).

This is the set number remembered by the system. As you see in the history, you “miss” certain sets. #3 to #5 are for instance are searches you performed in the MeSH-database, which show up in the History of the MeSH database, but not in PubMed’s history.

The Clinical query set number is still there, but it doesn’t show either. Apparently the 3 clinical query-subsets yield a separate set number, whether the search is truly performed or not. In this case  #11 for (#8) AND systematic[sb], #9 for (#8) AND (Therapy/Narrow[filter]). And #10 for (#8) AND the medical genetics filter.

In this way you have all results in your history. It isn’t immediately clear, however, what these sets represent.

2. Use the commands rather than going to the clinical queries.

Thus type in the search bar: #8 AND systematic[sb]

And then: #8 AND (Therapy/Narrow[filter])

It is easiest to keep all filters in Word/Notepad and copy/paste each time you need the filter

3. Add clinical queries as filters to your personal NCBI account so that the filters show up each time you do a search in PubMed. This post describes how to do it.

Anyway these remain just tricks to try to make something right that is wrong.

Furthermore it makes it more difficult to explain the usefulness of the clinical queries to doctors and medical students. Explaining option 3 takes too long in a short course, option 1 seems illogical and 2 is hard to remember.

Thus we want to keep the set numbers in the history, at least.

A while ago Dieuwke Brand notified the NLM of this problem.

Only recently she received an answer saying that:

we are aware of the continuing problem.  The problem remains on our programmers’ list of items to investigate.  Unfortunately, because this problem appears to be limited to very few users, it has been listed as a low priority.

Only after a second Dutch medical librarian confirmed the problem to the NLM, saying it not only affects one or two librarians, but all the students we teach (~1000-2000 students/university/yearly), they realized that it was a more widespread problem than Dieuwke Brand’s personal problem. Now the problem has a higher priority.

Where is the time that a problem was taken for what it was? As another librarian sighed: Apparently something is only a problem if many people complain about it.

Now I know this (I regarded Dieuwke as a delegate of all Dutch Clinical Librarians), I realize that I have to “complain” myself, each time I and/or my colleagues encounter a problem.

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Medical Information Matters 2.8 is up!

15 10 2010

The new edition of Medical Information Matters (formerly Medlibs round) is up at Danielhooker.com.

The main theme is “Programs in libraries or medical education”.
Besides two posts from this blog (A Filter for Finding Animal Studies in PubMed” and more on the topic: An Educator by Chance) the following topics are included: a new MeSH (inclusion under mild librarian pressure), PubMed in your pocket, embedding Google Gadgets in normal webpages and experiences with introducing social bookmarking to medical students.
If you find this description to cryptic (and I bet you do), then I invite you to read the entire post here. I found it a very pleasant read.

Since we are already midway October, I would like to invite you to start submitting here (blog carnival submission form).

Our next host is Dean Giustini of the The Search Principle blog. The deadline is in about 3 weeks ( November 6th).

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Ten Years of PubMed Central: a Good Thing that’s Only Going to Get Better.

26 05 2010

PubMed Central (PMC) is a free digital archive of biomedical and life sciences journal literature at the U.S. National Institutes of Health (NIH), developed and managed by NIH’s National Center for Biotechnology Information (NCBI) in the National Library of Medicine (NLM) (see PMC overview).
PMC is a central repository for biomedical peer reviewed literature in the same way as NCBI’s GenBank is the public archive of DNA sequences. The idea behind it “that giving all users free access to the material in PubMed Central is the best way to ensure the durability and utility of the electronical archive as technology changes over time and to integrate the literature with other information resources at NLM”.
Many journals are already involved, although most of them adhere to restrictions (i.e. availability after 1 year). For list see http://www.ncbi.nlm.nih.gov/pmc/journals/

PMC, the brain child of Harold Varmus, once the Director of the National Institutes of Health, celebrated its 10 year anniversary earlier this year.

For this occasion Dr. Lipman, Director of the NCBI, gave an overview of past and future plans for the NIH’s archive of biomedical research articles. See videotape of the Columbia University Libraries below:

Vodpod videos no longer available.

more about “Ten Years of PubMed Central | Scholar…“, posted with vodpod

The main points raised by David Lipman (appr. time given if you want to learn more about it; the text below is not a transcription, but a summary in my own words):

PAST/PRESENT

  • >7:00. BiomedCental (taken over by Spinger) and PLoS ONE show that Open Access can be a sustaining way in Publishing Science.
  • 13:23 Publisher keeps the copyright. He may stop depositing but the content already deposited remains in PMC.
  • 13:50 PMC is also an obligatory repository for author manuscripts under various funding agencies mandates, like the NIH and the UK welcome trust.
  • 14:31 One of the ideas from the beginning was to crosslink the literature with the underlying molecular and other databases. For instance NCBI is capable of mining out the information in the archived text and connecting it to the compound and the protein structure database.
  • 16:50 There is a back issue digitization for the journals that are participating, enabling to find research that you wouldn’t have easily found otherwise.
  • PMC has become international (not restricted to USA)
  • The PMC archive becomes more useful if it becomes more comprehensive
  • Before PMC you could do a Google Scholar search and find a paper in PubMed, that appeared funded by NIH, but then you had to pay $30 for it in order to get it. That’s hard to explain to the taxpayers (Lipman had a hard time explaining it to his dad who was looking for medical information online). This was the impetus for making the results of NIH-sponsored results freely available.

PRESENT/FUTURE

  • 23:00 Discovery initiative: is the use of tracking tools to find out which changes to the website work for users and which don’t. Thus modifications should lead to alterations in users behavior (statistics is easy with millions of users). Discovery initiative led to development and improvement of sensors, like sensors for disease names, drug names, genes and citations. What is being measured is if people click through (if it isn’t interesting, they usually don’t) and how quickly they find results. Motto: train the machine, not the users.
  • 30:37 We changed the looks of PMC. Planning to make a better presentation on the i-phone and on broad monitors.
  • 31:40. There are almost 2 million articles in PubMed Central, 585 journals fully participate in PMC
  • 32.30 It takes very long to publish a paper, even in Open Access papers. Therefore a lot of people are not publishing little discoveries, which are not important enough to put a lot of time in. Publishing should be almost as easy as writing a blog, but with peer review. This requires a new type of journal, with peer review, but with instant feedback from readers and reviewers and rapid response to comments. The Google Knol authoring system offers a fast and simple authoring system where authors (with a Google profile) can collaborate and compose the article on the server. Uploading of documents and figures is easy, the article updates are simple and fast, there is a simple workflow for moderators. After the paper is accepted you press a button, the paper is immediately available and the next day PMC automatically gets the XML content. There is also a simple Reference Manager included to paste citations.
  • Principle: How you can start a journal with this system (see Figure). Till now: 60 articles in PLOS Currents Influenza. There are also plans for other journals: the CDC is announcing a Systematic Reviews journal, for instance.

QUESTIONS (>39:30):

  • Process by which “KNOL-journal” is considered for inclusion in NLM?
    • Decide: is it in scope?, implicit policy (health peer review being done), who are the people involved, look at a dozen articles.
  • As the content in PMC increases, will it become possible to search in the full text, just like in Google Scholar?
    • Actually the full text is searchable in PMC as apposed to PubMed, but we are not that happy with the full text retrieval. Even with a really good approach, searching full text works just a little bit better than searching PubMed.
      We are incorporating more of the information of PMC into PubMed, and are working on a separate image database with all the figures from books and articles in PMC (with other search possibilities). Subsets of book(chapter)s (like practice guidelines) will get PubMed abstracts and become searchable in PubMed as well.
  • Are there ways to track a full list of our institutions OA articles in PMC (not picking up everything in PubMed)
    • Likely NIH will be contacting offices responsible for research to let them know what articles are out of compliance,  get their assistance in making sure that those get in.
    • Authors can easily update the electornic My Bibliography (in My NCBI in PubMed).
    • Author ID project, involves computational disambiguation. Where you are asked if you are the author of a paper if you didn’t include it. It may also be possible to have automatic reporting to the institutions.
  • What did it took politically to get the appropriation bill passed (PMC initiative)?
    • Congress always pushed more open access, because it was already spending money on the research. Most of the initiative came more from librarians (i.e. small libraries not having sufficient access) and government, than from the NIH.
  • Is there way to narrow down to NIH, free full text papers from PMC?
    • In PubMed, you can filter free full text articles in general via the limits.
  • Are all the articles deposited in PMC submitted the final manuscript?
    • Generally, yes.

HT: @bentoth on Twitter