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Don’t Reinvent the Milk Carton

25 Nov
US Patent 1,157,462

US Patent 1,157,462

One morning last week, as I poured the last bit of milk out of the carton and onto my raisin bran, I looked at the plastic spout poking out of the “roof” like a chimney and wondered to myself, “Who ever decided that this was an improvement on the original milk carton design?” I thought about how John R. Van Wormer’s ingenious idea to make a self-contained container – a single object that both held milk AND unfolded to give you a spout – somehow became “not good enough.” Why? Whoever thought that a carton needed a second spout, complete with three other small pieces of plastic that now, multiplied by a gazillion, take up space in landfills? What the heck was ever wrong with unfolding the spout?

I’ve thought about this for days. Literally. I’ve mentioned it to a couple of friends and/or colleagues. I’ve asked them if they know why this “improvement” came along? They don’t. And neither do I. But I’ve thought so much about what it represents that I’ve decided my new mantra is “Don’t reinvent the milk carton!” I even printed off a picture of the image shown here and gave it to my supervisor so that she could hang it on her office door. I’m bringing the message to the people.

But I bring this up on my “Library Hats” blog not so much because I feel like the research team that I’ve worked with the past year is engaging in such an act, but more because as my time as an informationist on the team winds down, I’ve begun to look back on the project and take note of some of the bigger (and maybe a few smaller) lessons that I’ve learned along the way. And one of these lessons does remind me of the milk carton mantra.

When we first approached the research team to discuss with them different ideas, options, projects, etc. that we thought an informationist could bring to their work, it initiated a terrific time of “big picture” thinking. Once we explained what an informationist is and what skills and/or services I could bring along with me to the team, we came up with all sorts of ideas for things to do. “It would be great if we could …” and “We’ve wanted to do …” were phrases that came up often. This was just what we wanted and we proceeded to write up several aims and a lengthy list of tasks and projects to undertake in order to accomplish them. These were all new things thought to improve the overall research project, not necessarily things to create extra work for the team. Work for the informationist, yes, but not more work for an overworked team.

That was our design, anyway.

As I prepared a report for tomorrow morning’s team meeting, updating everyone on the status of where I am related to the aims of the grant, I began to think about my milk carton metaphor and wondered if maybe we didn’t wreck a good design with the addition of me. Like the addition of that plastic spout to the perfectly perfect milk carton, throwing me on the top actually has created more work for everyone on the team. The projects that we thought about, particularly related to performing thorough reviews of the literature and examining information technology issues in research… these ideas were things that the team may well have wanted to work on, address, and delve into with an informationist on board, however I’m not sure we really considered how much of their time would be required to accomplish them. Like the milk carton, they were a single, self-contained unit that worked pretty well. Add me, the plastic spout, and now you’ve added the spout, the cap, and the little pull-tab plastic piece that you have to remove before you open the carton the first time. One thing becomes four. Better design? It’s debatable. 

I do think that I’ve provided some valuable tools for the team (and future teams) to use, i.e. the data dictionary, data request forms, and a growing catalog of relevant articles for their field of work. But writing a review article is another project. Writing a systematic review is, in its purest form, an entire research project in and to itself. Similarly, planning a conference or investigating big-picture issues like how research happens in teams… maybe these are terrific aims, just not necessarily aims for supplemental work. I think that this is something we need to consider in the future when drafting our proposals for these type of services. 

In a time when people, dollars, and all resources are stretched to the limit, we don’t need to be making extra work – or plastic waste – for ourselves.

 

Trees, Forests, and Other Fall Metaphors

6 Sep

What a few weeks it’s been! Regular readers of this blog know all about the changes in my library of late. Suffice it to say, the load of emotions and thoughts and tasks have kept the wheels spinning, both literally and figuratively. The result, in terms of this week’s blog post, is a bunch of bits and pieces – a collection of some of those thoughts and experiences that hopefully you find worthy of reading and/or commenting.

Missing the Forest for the Trees

First, let me give you an update on my informationist work with the mammography study. It seems like it’s been too long since I’ve done that. September marks a year that I’ve been embedded in the research team. I have about 5 months to go on the grant funding and a whole slew of deliverables to deliver between now and then. Thankfully, the project coordinator has taken it on as a priority to make sure that I get all of the things done that we said I’d get done, thus she is putting me on the agenda every week from here on out, encouraging me to keep everyone on task with the things that they need to do to insure my success. I realize that Mary Jo has to be the ideal project coordinator for any informationist and/or embedded librarian to come across when looking for success in this new role. All along, the team has been welcoming and encouraging of me, but a good coordinator keeps everyone accountable to everyone else, and thus to the overall goal of the research project. As I mentioned during last night’s weekly #medlibs tweetchat, it’s this level of accountability that distinguishes librarian support from librarian embeddedness.

Which brings me back to the one deliverable that has stumped me from early on, the data dictionary. As I’ve described in previous posts, the data for the mammography study comes from various sources. Helping team members to communicate more efficiently and effectively about the data was Aim 1 of my role. We envisioned that a comprehensive data dictionary would be the key to reaching this goal and so I set about collecting the different codebooks and related documentation, compiling them into a single file with the hope that I’d be able to easily see overlap in terms, discrepancies between definitions of the same terms, gaps in terminology, etc. It seemed simple enough.

What I found, however, was less than simple. I found a lot of tools that already existed, yet weren’t being used. As an example, the codebooks were there, yet weren’t always referenced during data requests between team members and the analyst. People continued to use their own chosen vocabulary, despite the ongoing confusion that it caused. More than once I’ve heard the phrase, “So and so uses ‘x’ to describe ‘y’, but we all know what s/he means.” If you think about it, we all operate like this to varying degrees. If/when you work or live with another person long enough, you figure out what s/he means regardless of what s/he is saying. Except when you can’t figure it out. And that’s when the communication breaks down. It’s why we have dictionaries and standards in the first place, particularly when it comes to technical research.

I literally went for months, scratching my head and being utterly confused (and often exasperated) over the amount of time spent talking about the algorithmic logic behind exclusion variables and which flags turned off or on in the system when. I couldn’t for the life of me figure out how the data dictionary that I was putting together was going to help make that hang-up in the study go any better.

Until this week.

Finally, during a conversation with Mary Jo about the dictionary that involved sharing the work with her and walking through my understanding of it, along with hers (something that I see now I should have done MONTHS ago), she mentioned that if I could add to the dictionary how each variable functions within the system, it would be a really helpful document. FUNCTION! It was like a light bulb went off. I’d been so stuck on names and definitions that I either never heard this word or I had completely missed the concept, all the previous months. For whatever reason, this dimension to the dictionary had escaped me. I went back to the spreadsheet, added the columns for the different functions that we identified, and began working through the different scripts, assigning each variable its proper function. Now the goal is to have it all together by next Tuesday so that I can present it to the group for feedback and evaluation.

Going Out on a Limb

“We all hear that it takes 20 years for something new to be implemented in medicine, but how long does it take us to de-implement something?” I’m paraphrasing a cardiologist who spoke something to this effect in a meeting that I attended this week. Basically he was asking, “How do you stop doing something once you know it no longer works?” It’s a great question and cuts at the heart of all of my personal curiosities and interests around human behavior and why we do (or don’t do) the things that we do. I wrote in my notebook, “The Challenge of De-Implementation” and tucked it aside as a possible question for thought – perhaps even some kind of research project – in the future. It’s certainly pertinent in my profession right now.

When do we take the chances that we need to take? What finally prompts us to stop doing what we know no longer works? What’s worth giving up and what is worth fighting for when it comes to health sciences libraries and librarianship as a profession? 

Money Doesn’t Grow on Trees

In the mid-90s, at arguably the peak of their success as a band, REM released a less-successful, commercially speaking, CD entitled, “Monster.” It’s not my favorite, yet I did find myself pulling it off the shelf this morning to listen to one song in particular during my morning commute (I generally have about a 3-song commute). “King of Comedy” has a catchy little closing refrain,

 

I’m not king of comedy,
I’m not your magazine,
I’m not your television,
I’m not your movie screen
I’m not commodity

(King of Comedy, Berry/Buck/Mills/Stipe, 1994)

The irony is, of course, that the band was very much a commodity by that point. Like it or not, their huge success made them no longer individuals, per se, but an entity that could be bought and sold. What happened to REM is pretty much what has happened to information over the past couple of decades. With the rise of the Internet and the ease with which we can/could find and share and access information, its power and profitability has grown in ways likely no one ever imagined.  Once something freely shared by say, your local library, is now out there generating a bunch of money for Google. “But Google is free!” you cry. Really? We gave up a lot to be bombarded with advertising, with product, with noise; to have personal information about ourselves be retrieved and resold to others for a profit. We are commodity.

What does this have to do with libraries? Oh, I’ve just been thinking about the move towards entrepreneurship in our profession. I’ve been thinking about just what is it that I’m selling to patrons. What is the real value of me as an embedded librarian – is it me or is it my skill set? I know that it’s a combination, but is one piece worth more? I once heard the story of a law firm in Chicago that, upon acquiring Westlaw, decided that they no longer needed a law library and the librarian who worked there. She was, like many of our colleagues, let go. Within a few months, however, the firm came back to her, offering her the position she once held. They realized that her value was actually more than the resources she provided. She considered their offer and rejected it, opting instead to hire herself back to them as a consultant (with no library), charging them much more for the work that she had always done. 

You might think this is a great lesson in entrepreneurship and I can’t argue that it’s not, at least not for this individual and her personal value (financial status), but what does it say about the direction that health sciences librarians could take? Is our allegiance to the library, to the research team, or to ourselves? Again, I know that there is no one answer and that we hold a certain amount of loyalty to each, but if we do move towards a more independent and consultant-type model as embedded librarians, what will be the ramifications on the library – and on our profession – as a whole? There are pros and cons for being a commodity.

The Power of Branching Out

Sally and AmyI love social media. For those who have rejected the power of blogs, Twitter, Facebook, et al for both professional and personal gains, I give you another chapter in the story, “Sally Meets Fantastically Cool People Through Twitter.” If you missed the previous chapter on my Twitter friendship with Rosanne Cash, you can catch up here. This past week involved finally getting to meet the one and only Amy Dickinson; the voice behind the syndicated advice column, “Ask Amy,” the author of the NY Times bestseller, The Mighty Queens of Freeville, and a regular panelist on the always funny NPR news quiz show, Wait Wait Don’t Tell Me

I started tweeting back and forth regularly with Amy Dickinson about a year or so ago. I liked her as a writer and humorist, and followed her on Twitter. She tweeted something funny one day, I tweeted back, she back to me, and so on. Eventually, she started to follow me on Twitter, too. I became a fan of hers on Facebook. I offer up comments to the letters that she posts online. We got to know each other about as much as a librarian from Worcester gets to know a somewhat famous personality via these outlets. 

Last Friday night, after appearing on the panel of Wait Wait that taped at Tanglewood the night before, she gave a book talk at the Lenox (MA) Public Library. I had a gig scheduled with my band, but after a week (more like a month, but a really horrible week) of dental trauma, I was a scratch in the band lineup. Rather than sitting home yet one more evening, wallowing in my tooth pain, I decided that I’d drive out to Lenox, a nice, quiet 2-hour ride from Worcester, and take the opportunity to meet – and especially thank – Amy in person. 

Like my desire to meet Rosanne, I think it’s really special if/when we ever get the chance to say “thank you” to those people who fill up a bunch of our hours, days, even years. For me, these special people are most often writers and musicians (or a combination of both). Think about it. When I read Amy Dickinson’s memoir, I spent hours with her. She took the time to write a story and share it. I took the time to read it. Like taking the time to listen to a song and learn the lyrics, you have to give up something of yourself (a lot of your time) to accept all that the artist has given. As the hours unfold and you read an author’s book, particularly a memoir, you come to know them. It may be a little one-sided, but you still know them. 

I got to the talk and Amy saw me walk in. She recognized me from my pictures on Twitter and Facebook. I recognized her from the same, plus the fact that she was at the front of the room, next to the podium. We made eye contact and waved to each other. She gave a great talk, funny as expected, and answered a bunch of questions about her work as a columnist and a radio personality. I had my hand up to ask a question and finally, at the very end of the evening, she looked my way and wrapped up by saying, “I need to introduce Sally.” And then… Amy Dickinson introduced me! Really. Before I could ask my question, she told everyone all about how we met via Twitter, how I was a librarian with a wonderful blog (she said that), how I’d offered her some help in terms of pointing her towards reputable folks in health care for reference in her letters, and how I was the first friend that she’s made completely through social media. Amy Dickinson called me her friend. 

Several years ago, before the age of social media, I gave a talk where I introduced the “top ten” people that I wanted to be a personal librarian for. I did actually have a radio personality on my list, though (sorry, Amy) it wasn’t Amy Dickinson. It was Terry Gross. I think even Amy would take that gig. Who wouldn’t want to look up all of the cool stuff about all of the fascinating people Terry Gross interviews on Fresh Air?! Still, never did I imagine at that time that a day would come when I actually would be a bit of a personal librarian to the stars. But there was Amy, last Friday night, telling the audience about how powerful social media is in its ability to connect us with people and resources and ideas like we never could before. She said that while she’d been a bit late coming to it, she now sees what a rich tool it can be to help you do your job – be your job writing advice, sharing good information with others, promoting yourself, or connecting with people. 

This blog has helped me share a lot of ideas and experiences with an awful lot of people over the past year. It’s helped me to reach some folks that I never would have reached in traditional means like writing journal articles or even posting on listservs. My presence on Twitter has connected me with researchers, science writers, other librarians across many disciplines, and even a few musicians and writers that I admire immensely. It’s not the one tool that will make or break my success as an informationist, but it’s certainly proved more than worth its value to me. Amy Dickinson introduced me as her friend. I rest my case. 

 

Larry, Darryl, and Darryl

17 Jun

[A Monday afternoon editorial.]

 

Sometime within the past couple of months, the National Institutes of Health decided to start enforcing the requirements of its public access mandate that went into effect in April of 2008. On the one hand, it was nice of NIH to give its funded researchers a year or two or five to come around to following the rules. Yet on the other, the recent applied pressure has sent a flurry of befuddled and irritated biomedical researchers, clinical researchers, research coordinators, administrative assistants, and any number of other folks my way, usually in a deadline-induced panic, trying to figure out what the heck they’re supposed to do to get in compliance with the law.

For awhile, I was slightly irritated myself – at the researchers, that is. When it comes to “the Mandate,” I’ve been announcing and instructing and updating and troubleshooting ad nauseum for these past years. I’ve sent out countless invitations to talk to departments, to labs, to admins, to the staff in research funding (and to their credit, many – though hardly a majority – took me up on it). I have made it my business to know every in and out and upside down aspect of this Policy since before it became law, lo those many years ago now. And so, over the past couple of months, I’ve stifled more than one, “What rock have you been living under?!” retort to more than one, “NIH has instituted another new thing!” whine landing in my email inbox or coming across my phone line.

All of this said, as I have worked to smooth and soothe and clean up messes these past weeks, I can’t help but come to the conclusion that NIH, and more, the National Library of Medicine, could have done us all a HUGE favor if they had taken just a moment to think through the naming conventions that they chose for the various resources and tools associated with this Policy. Why, for the love of Pete, did you name PubMed Central, PubMed Central? Why is there something so crucial as “My Bibliography” buried within “My NCBI”? Why are there “journal publishers that submit articles on behalf of authors,” as well as “journal publishers that submit manuscripts on behalf of authors”?

If you think that I typed the same thing twice there, read again. Closely. Which is EXACTLY what you have to say to researchers over and over and over again.

And that’s kind of my point. In one of the most basic textbooks of library science, Richard Rubin’s, Foundations of Library and Information Science, every aspiring librarian learns a handful of principles related to information management and organization. As Rubin warns, “Unless there are ways to organize it,it (information) quickly becomes chaos.” (p. 171)

Perhaps one can make a strong argument that the conundrum that is the naming conventions of NIH/NLM resources and tools isn’t really a naming convention problem at all. There certainly are distinctions between them. “My Bibliography” is not the same as “My NCBI.” PubMed is a completely different database than PubMed Central. How hard is this to grasp?!  I argue, harder than the average librarian and/or programmer and/or chief resource namer of highest level (aka CRNHL – pronounced “colonel” – on Twitter) ever realizes.

I bring this topic up on my informationist blog because I find it pretty funny (in a black humor, ironic sort of way) that one of the primary reasons I was placed on a research team was because of my expertise in information organization. Librarians are the experts in applying the standards, language, and processes that help people communicate, find, and access information more easily and efficiently. This being the case, I can’t help but wonder why we shot ourselves in the foot here, choosing labels that are so easily confused and swapped one for the other. Like homology, homography, or holograms and homograms… who can’t help but get these mixed up? And when there is a compliance officer, grant funding, and a deadline all in play, well, we in the information arena could do better to make things a little easier on everyone.

Let’s Ask the Expert

26 Mar

Normal Distribution

The research team has a new statistician; not a new analyst, but new statistician. If you look at it as a pecking order, the statistician oversees the analyst. Our former statistician retired recently, leaving the team to find a replacement. The University has a relatively new Quantitative Health Sciences Department and many of the services once procured through individual department statisticians are now going through QHS. Or at least this is how I think it’s going. These are things that I don’t necessarily need to know and as I have plenty of things occupying my “need to know” gray matter right now, I can just follow along here.

The significance of the new team member, to me, was that it generated the need for a meeting so that he could be brought up to speed on the project. This meeting happened this afternoon. I believe it was good for him (as well as the Chair of the Quantitative Methods Core, his boss, also in attendance). I know that it was good for me. I’ve now heard the project and its various aspects described on a number of occasions, and each time gain some new insight. Today, that insight was that I have a pretty good grasp on where the data for this study comes from, the different sources that generate it, how it’s stored, where it’s stored, who’s managing it, and so forth. I also had a pretty clear understanding of where the problem spots and/or issues with it are (mostly gone over, yet again, in today’s morning meeting).

I decided to pay close attention during the meeting on the questions that the statistician asked. I imagine that these are the kinds of questions that an informationist, embedded librarian, or anyone concerned with data management and planning would ask a research team. Here are some that I noted. If you’re doing an interview with a researcher about his/her data, are you asking these questions?

  • Is the data in one place or multiple places? 
  • Do the different sources merge together easily?
  • Are the variable names consistent across the sources?
  • Where is the merged data stored and how?
  • When and/or how often do you do data pulls from the sources?

Additionally, the statistician said that he wanted to be walked through the process. He wanted to generate a visual for himself of how everything works together. I found this request confirmation of much of what I’ve been reading and thinking about in terms of how we best see, understand, and communicate systems and processes. Visuals are important. I remember meeting with one of the chief programmers a few months back and how helpful it was when he pulled out a marker and drew us a picture on the whiteboard to explain all of this.*

*NOTE: If you’re interested in the art of explanation, check out The Art of Explanation by Common Craft founder, Lee Lefever. I’m pretty sure I mentioned this a few posts back, but in case you missed it… Also, Common Craft has made wonderful templates of their cut-out characters available for free to download and use in your own creations. Give it a try and see how well you do at explaining a concept or problem. Make a little video and share it with me.

So, if you’re keeping up with the process of the research study, the next step for the statistician is to collect data from the first cohort and start to play with it; see what it shows so far; see if it identifies any gaps of missing data and/or holes in the process that need to be addressed. It’ll be a couple of months, at least, before we hear back, but it was obvious that the team was excited about this move.

A few questions that I’m left with, following today, are:

  • What’s the difference between an analyst and a statistician?
  • What is my role, if any, in this aspect of the study?

One last interesting aside – When we went around the table to introduce ourselves and I said, “I’m from the library, serving as the informationist,” Dr. Barton, the Director of the Quantitative Methods Core said, “Oh, good.” I’m the only one who got an “Oh, good.” I’ve no idea what he meant by it, but I like to see it as a positive sign that my library is engaged in this kind of work. Regardless, it was a nice gesture.

Repeat After Me

13 Mar

Quote from Science

Preparing for some upcoming work, I took part in a webinar on systematic reviews yesterday morning. It was a brief, but good, review/overview of the process and the roles librarians and/or information scientists have in it. One thing that stuck out for me was the reminder by Dr. Edoardo Aromataris of the Joanna Briggs Institute, one of the program’s speakers, that a systematic review is a type of research and as such, it needs to be reproducible. He noted that the search strategy ultimately constructed in a review should yield pretty much the same results for anyone who repeats it.

Replication is a hallmark of the scientific method. As Jasny et al state in the above-referenced quote from a special issue of Science on data replication and reproducibility, it is the gold standard of research. Science grows in value as it builds upon itself. Without the characteristic of replication, such growth is thwarted and findings become limited to a study’s specific subject pool. If a study’s design becomes so complicated and the research question(s) keep changing along the way, the study’s value gets clouded, if it remains at all.

I remember during my master’s thesis defense, one of my advisers asked me why I hadn’t done a particular statistical analysis to answer another question about the data I collected. I admit that the question threw me, but after thinking about it for a moment, I said, “Because that isn’t what I said that I would do.” My statistics professor, who was also sitting in on the defense, said calmly, after I hemmed and hawed and tried to defend my answer in a long and drawn out way, “That’s the right answer.” In other words, when I proposed my study and laid out my methodology, I stated that I would do “x, y, and z.” If I later decided to do “q” simply because I thought “q” was more interesting, I wouldn’t have necessarily answered the research question that I set out to answer, nor would my methods be as strong as I initially put forward.

I bring all of this up this week because as I’ve been sitting in on the weekly meetings of my research team these past months, I can’t help but notice how often new questions are asked and how often those questions result in an awareness that the data needed to answer them is missing. This fact then leads to a lot of going back and gathering the missing data. Sometimes this is possible and sometimes it isn’t. For instance, you might go to see your doctor one time and you’re asked the question, “Do you smoke?” But the next time you visit, the nurse doesn’t ask you that same question. Usually, you’re asked something like, “Are you still taking (name the medication)?” You answer, “Yes,” but you fail to mention that you’ve changed dosage. Or that your doctor changed the dosage sometime during the past year. Is that captured in the record? Maybe, maybe not. And further, some insurance carriers require certain patient information while others do not. If you’re drawing subjects for a study from multiple insurance carriers, you’d better be sure that each is collecting all of the data that you need, otherwise you cannot compare the groups. As the analyst on our study said yesterday, “If you can’t get all of the data, you might as well not get any of it.”

Now please remember that I am working as an informationist on a study led by two principal investigators and a research team that has being doing research for a very long time. They have secured any number of big grants to do big studies. They are well-respected and know a whole helluva lot more about clinical research than me and my little master’s-thesis-experienced self. I’m not questioning their methods or their expertise at all. Rather, I’m pointing out that this kind of research – research that involves a lot of people (25+ on the research team), thousands of subjects, a bunch of years, several sources of data (and data and data and data…), and a whole lot of money over time – is messy. Really, really messy! In other words, an awful lot, if not the majority, of biomedical and/or health research today is messy. And as an observer of such research, I cannot help but wonder how in the world these studies could ever be replicated. As that issue of Science noted, research today is at a moment when so many factors are affecting the outcomes that it’s a time for those involved in it to stop and evaluate these factors, and to insure that the work being done – the science being done – meets high standards.

More, as a supposed “expert” in the area of information and a presumed member of the research team, I’m feeling at a loss as to what I can do, at this point in the study, to clean it up. Yes, I admit that yesterday just wasn’t my best day on the study and maybe that’s coloring part of my feelings today. I didn’t have anything to offer in the meeting. I didn’t feel like much of a part of the team. It happens.

So can I take a lesson from the day’s events? The answer to that is equivocally “YES!” and here’s why…

In the afternoon, I had a meeting with a different PI for a different study. We’re exploring areas where I can help her team; writing up a “scope of work” to embed me as an informationist on the study. It’s a very different kind of study and not as big as the mammography study (above), but it still involves multiple players across multiple campuses, and it ultimately will generate a whole bunch of data from a countless number of subjects. The biggest difference, though, is timing. And this is the take-away lesson for me in regards to what brings success to my role. When a researcher is just putting together his/her team, when s/he is just beginning to think about the who and what and where and why of the study, if THEN s/he thinks of including an individual with expertise in information, knowledge, and/or data management, the potential value of that person to the team and to the work is multiplied several fold.

This is because it’s in the beginning of a study when an informationist can put his/her skills to use in building the infrastructure, the system, and/or the tools needed to make the flow of information and data and communication go much more smoothly. It’s hard to go back and fix stuff. It’s much easier to do things right from the beginning. Again, I’m not saying that the mammography study is doing anything wrong, but building information organization into your methods from the get-go can surely help reduce the headaches down the road. And fewer headaches + cleaner data = better science, all the way around.

He Said, She Said (and who can possibly remember?)

13 Feb

One of the tasks I have as an informationist on the study team is to help improve communication. In fact, it’s Aim #1 in the proposal we wrote to the National Library of Medicine for the grant: “Develop tools to improve data specification and communication.” For most of the past month or so, I’ve been working on a data request form. Back and forth and back and forth we go with iterations of it. Last week, it finally went through a test-drive as one of the principal investigators used it to request several analyses from our analyst. (Isn’t it convenient for an analyst that s/he does analyses? So clear. An analyst analyzes. A librarian… librarianizes? We should be so lucky.)   It’s back in my hands now to make a few more tweaks based upon her feedback, but it’s coming along nicely. Hopefully, it will become a well-used tool in the future, making the communication of statistical analyses between requester and analyst  more efficient.

As I sat in on yesterday’s meeting, I heard in the conversation another area where a tool would help improve communication between team members. Much of the history of this study can be found in email correspondence. Often, someone will say something like, “I remember that we changed such and such to so and so back in 2010,” and the indication is that somewhere in the virtual mound of emails of 2010, there exists documentation of this change. Everyone remembers the email, the discussions during team meetings, the outcome, etc. but the details are sometimes lacking. When it comes to writing articles, however, a lot of these details become very important pieces of information needed to describe exactly what happened and when. I began to wonder if we had a searchable archive of all of the email involved in the study, would it be a useful tool for the team. I posed the question later in the afternoon (via an email, of course!) and heard back from several people that they agreed.

To figure out how to accomplish this task, I began searching for things like communication log software, email exporters, and tools for Outlook. I also revisited Zoho Creator to see how and if it could work to create a database for these things. Basically, my thinking was to export pertinent fields like date, sender, and body of the email; index them (using tags); and make them searchable. Then, if someone was curious about the development of the phone counseling system, s/he could do a search for “MCRS” in all of the emails and receive a nice, chronological report of everything communicated about the process during the software development. “This is good!” I thought.

Screen Capture of search results.

Screen Capture of search results. A mini test.

I set to work downloading the add-on tool for Outlook that I decided on, Code Two Outlook Export. It was pretty straightforward, no hiccups or frustrations. Then I practiced exporting the “Informationist” folder in my email inbox. The export gave me a csv file that I then opened in Excel. I didn’t get exactly what I wanted, so I tried a few other export field options until it looked right. At this point though, I could tell there will be a good bit of cleanup to do in the Excel file. We have a lot of stuff in the body of emails – stuff that runs all together in an Excel cell. I decided to delete content in the body of the emails that was irrelevant and/or redundant. This helped a lot. Once I had the spreadsheet the way I wanted it, I then uploaded it into a new application in Zoho Creator, did some more tweaking here and there, and eventually got something that worked!

Admit it. It’s always a rush when you create something, isn’t it? 

I sent some screen shots to the team members and asked for feedback. Already I’ve heard from several who think it’s a great idea! It will take some doing to collect and cleanup several years of emails related to the study from everyone involved, but I think it will be a real help. Also, the system will be in place for future studies. As a matter of fact, I already have laid out in my mind how I can use this with the new CER group that I’m going to be embedded in soon. As their email list is fairly new, it will be a much easier start-up.

If you decide to try either of these tools – or if you’ve instituted a similar email archive to help with communication within a group – I hope you’ll share your experience in the comments section here. It will be great to hear what works for others.

First Day of School

5 Sep

September 4, 2012

This isn’t my first day meeting with the team. We met to collaborate on the grant proposal, of course, and I’ve met with several team members here and there over the past month, but today marked the official beginning of my time on the project. You can probably guess what it started with… as with most anything at work, it started with a meeting. Two of them, in fact.

First, was the monthly meeting where many of the people involved (there are approximately 25 people across 4-5 campuses and/or institutions working on this study!) either attend in person or call in. It’s an update call, a time to document the progress on everything from the number of participants recruited and/or interviewed, to the number of glitches in the various computer programs fixed.

Mostly, it is a time for Process Evaluation. This is an important term, I quickly learn. A large research study is continually evaluated to insure that each step, each part, is producing the data required to ultimately answer the research question. In this case, the National Cancer Institute is giving the researchers a substantial amount of money over several years to investigate what type of intervention works best and is the most cost-effective to insure that women get mammograms, a proven measure in the early discovery and treatment of breast cancer. Without the correct data, the question will go unanswered – or worse, answered incorrectly.

For me, the interesting aspect of the emphasis on process evaluation is that it is the reason the PIs were most excited about adding an informationist to their team. With multiple people and multiple sources of data involved in the study, communication – or better put, troubles with it – are a big concern. My first, and perhaps primary, role on the team is to discover, create and implement the tools necessary to decrease these miscommunications. People are using different terms to describe the same thing. Variables lack clear definitions. We need some controlled vocabulary. Now there’s a good librarian word! And with it, I can see my value pretty quickly.

Meeting #2 involves talking about this role more specifically. My first task is spelled out, “Create for us a Data Dictionary.” Fortunately, I have about 10 months to do this, but by next week, I’m to present my ideas on how I’m going to do this. What am I going to create? What software might I need? What will work best?

I spend the rest of my day thinking about this. I read the grant proposal again. I read a published paper on the study. I sketch out a picture of the methodology, trying to figure out when and where each data source comes into play. It’s no easy task. We have 4-6 (depending on who’s describing it to me) sources of data; 4-6 codebooks; countless variables in total. And of course, they are interconnected in countless ways.

In the end, I determine that I need to make something interactive, something that will allow the users to see not only the definitions of the variables, but also where and how they relate to others. A static document won’t do. I wish I had the programming chops to use ThinkMap (the software behind the Visual Thesaurus), but lacking that, I take time reviewing some other mind mapping and/or visualizing tools. I download a free trial of MindJet and play around with it for awhile. This might work, but I’m not ready to recommend it yet. There are other things out there, I know. I need to look at them, too.

Bottom line: This first day of class was WAY more than a “just hand out the syllabus and leave” day. I think I deserve a new pencil!

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