Merging Metrics
 
Jennifer Feeken, MLIS
Cait Kortuem, MLIS
Mary Wittenbreer, MLIS, MALS
Regions Hospital Medical Library
In preparation for a healthcare system (and medical library) merger in 2014, Regions Hospital Medical Library standardized our literature search and resource usage reporting. Although the library merger was delayed, our work over the years has given us substantially better tracking systems.

Regions Hospital librarians have tracked literature searches since 2003. We originally tracked the number of search requests, how long it took to complete a search, the requestor's profession, and the purpose of the search, including clinical decision making, management/administrative decision making, policy change, research, continuing education or "other."

Our new system, implemented via Excel spreadsheet in March 2014, added two new search purposes, hospital initiative and quality, as well as a notes column for miscellaneous information. More importantly, we began rating search complexity. Anecdotally, the librarians had felt that search requests were becoming more difficult over the decade of tracking, but we did not have a way to quantify the increasing complexity of searches. Standardizing statistics between libraries gave us an opportunity to include this new metric.

After meetings betw.een both libraries, we arrived at a consensus:



For the next two years, we successfully used this method to track literature searches. However, our spreadsheet was growing more unwieldy as we added information about location, per management request. This involved many variables, as Regions Hospital Medical Library serves a large healthcare system with six hospitals, over 50 clinics, and a main corporate office building with multiple branches. The spreadsheet now had 18 columns, but it worked well for us until our Excel expert left - creating Excel charts and graphs was time consuming for the Excel challenged.

Then, by coincidence, a friend of the library invited the librarians to lunch with a fellow employee from Decision Support Services. We mentioned our spreadsheet and our plans to present our data collection methods at future library conferences. Our new friend kindly offered to look at our data.

Decision Support Services manages several applications for collection, integration, analysis, and presentation of data to assist with decision-making within the organization. The tool uses software designed by McKesson Performance Analytics. If we could organize our data so that it could be read by the application, we would no longer have to struggle with making charts and graphs. The software could provide instant data visualization based upon pre-set parameters. We happily sent our file and waited for her recommendations.

Our new spreadsheet was implemented in January 2017. Based on Decision Support recommendations we can track even more information than we did before. For example, a drop-down menu was used to identify 10 professions. Within professions, users are further defined by job title, location, and in some cases, particularly nurses, floor worked. This helped us further define the vague "Other Staff."

We also began connecting literature searches to service lines. The organization tracks revenue streams according to service line. There are no hard numbers associated with this connection, but it does provide us with a list of frequent users and help us to bring our own statistics in line with the wider organization.

We are also able to list more databases without fear of adding too many columns. This is helpful at renewal time, because now each search's complexity is partially measured by the number of databases needed to answer a search question. The number of times a database is searched now is connected to who requested the search and an actual search question.

Charts and graphs are instantly generated using built-in filters. It is a matter of checking and unchecking boxes. The spreadsheet is easily maintained by the staff and all software updates are done by Information Services and Technology.

Our current literature search data collection methods accurately track librarian time, search complexity, databases used, requestors' profession, location, and search reason. Partnering with Decision Support was lucky, but also happened because of networking within the organization. Most importantly, we have vital information to help us integrate library services throughout the organizat
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