omation mbers - Society for Laboratory Automation and Screening

9:00 am Thursday, February 5 Clinical – Informatics 2 Room C1
Hunter Bagwell
Roche Diagnostics
9115 Hague Road
P.O. Box 50457
Indianapolis, Indiana 46250-0457
hunter.bagwell@roche.com
Middleware Solutions – Optimizing People, Processes, and Platforms
Today’s laboratory faces more challenges and tighter financial scrutiny than ever before. While workloads are
increasing and reimbursements are declining, labs are expected to find qualified personnel from a shrinking labor
pool while trying to grow volumes with limited resources. As an answer to these issues, Roche Diagnostics has
developed Middleware Solutions. Middleware Solutions powered by Data Innovations connects your existing LIS
and instrumentation allowing you to automate information and fill the gaps in your current information system. By
providing advanced features such as auto verification you can eliminate up to 80% of the labor associated with
results review and allowing better utilization of your scarce resources. The advanced archiving package allows you
to find samples in less than a minute, saving you over 60% of the labor associated with retrieving samples and
removing mundane tasks. At the heart of the system is rules based decision processing. Rules are constructed
through an easy-to-use graphical user interface that allows you to build compound IF / THEN statements to
customize your information workflow. This allows you to incorporate your client’s testing criteria automatically
providing tailored solutions for your customers. Bottom line, Middleware Solutions from Roche Diagnostics allows
you to quickly optimize the performance of your people, processes and platforms without added complexity.
9:30 am Thursday, February 5 Clinical – Informatics 2 Room C1
Jay Burton Jones
Geisinger Health System
Geisinger Medical Center 01-31
Danville, Pennsylvania 17821-0131
JBuJones@geisinger.edu
Data Mining From the LIS With Simple PC Tools
A practical, accessible, and user friendly “data mining” toolset is described that extracts 15 designated data
fields from the Laboratory Information System (LIS) via a Crystal ad hoc report writer and exports comma
delimited (.csv) files to a network secure PC. These extracted clinical lab results are “data mined” with MS Access
and MS Excel and subsequently graphed in standard MS Excel format. Histogrammed clinical lab data assists
in verifying reference ranges (age/sex stratified), judging utilization statistics, performing moving average quality
control studies, and comparing analytical methods on actual patient data. “Data mined” population data from
a large rural HMO will be presented for thyroid, lipid, diabetes, and point-of-care testing (POCT). LIS results
(typically N=100 – 300K) are put through the Crystal extraction process in 1 – 3 hours and “data mined” at the PC
workstation in 4 – 8 hours. The Crystal extraction process is automated and placed under user control. Since the
LIS is the “source of truth” data warehouse for archived POCT as well as central laboratory results, “data mining”
may help verify their relative accuracy. POCT glucose tests (y; N= 410K) are compared to central lab glucose
tests (x; N=1.1M), sorted for those tested on the same patient within 10 minutes (N= 14.3K), and correlated in
MS Excel.(y = 0.99x + 5). These data suggest over-utilized glucose “double testing” and that real-time POCT
may provide more useful real time information. These readily available “data mining” tools (essentially “back-end
middleware”) may form the basis for peer comparison of LIS data in the future.
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PODIUM ABSTRACTS