The first laboratory information systems (LIS) were derived from diagnostic instrument vendors who developed software applications to manage the orders and results that were run on the instrumentation. Today, there are still many of these applications that handle orders and results directly, but they now fall into the category of laboratory middleware. Those applications have also expanded into managing Quality Control, maintenance, automation, and other instrument specific workflows, while the LIS, in addition to incorporating instrument workflows, have further expanded into managing within and between departments of the laboratory and beyond.
Before the LIS started to expand outside of managing orders and results and producing patient reports, selecting a system was a matter of identifying functions and features to accommodate the needs of the laboratory with regard to recordkeeping and ensuring that lab results reached the caregivers within the hospital. It was simpler to select among available products since they basically provided the same level of functionality when the LIS first emerged.
In terms of the current state of healthcare information technology, LIS have become more sophisticated; in addition, enterprise vendors that previously focused on providing solutions at the hospital level have also begun to offer LIS, adding more options to the selection process.
Although there are many factors to take into consideration when selecting an LIS, it is necessary to focus on a few key capabilities to decide whether to choose an enterprise-level or a best-of-breed LIS. These criteria have evolved with the needs of the laboratory and patient care.
Clinical workflow management
As the LIS started to specialize and focus on the broader and deeper needs of laboratories, such as managing workflow, which entailed adding rules and algorithms, incorporating billing capabilities, and creating management reports (among other things), it became more difficult for lab leaders to compare the benefits of one LIS to another. The need to manage the clinical workflow, which has come to be expected as more responsibilities have been placed on all areas of the hospital, has added another level of complexity.
The patient’s history, previous results, and other related health information are used to determine the validity of the result and help with the treatment of the patient. This type of insight into the patient’s health becomes more important in specialized patient facilities. A cancer center, for instance, depends on the patient’s history and records of previous treatment more so than, say, a 50-bed community hospital that refers most of the patients to tertiary care facilities.
The level of integration of clinical information into the laboratory workflow and operations varies and is driven by the type of hospital and patient population served. What level of clinical information integration is needed? How much should the LIS support this integration?
Quality management
QC, TQM, CQI, PI, LSS, and so on—the evolution of different methodologies for managing quality will continue as the demand for the best patient care at less cost increases. Quality Control used to be a matter of making sure the results from the control material fell within the expected or published range. Over time, other areas of operations became part of the determination of the quality of laboratory services. Turnaround time began as the measurement of the time it took from specimen collection to result reporting, but it came to be recognized that part of TAT was identifying areas where improvements could be made to decrease the time to report patient results; more metrics needed to be measured from several starting points to many end points.
In addition to time stamps, time studies following each step of the process became another factor to consider in identifying areas for improved efficiency. For example, continuous depletion of inventory may be found to impact productivity but is not evident from looking at timestamps. How do you find that out? What information do you need to track in order to obtain the data to monitor productivity and determine areas for improvement?
Data mining and reporting
Millions of data points are generated every day in the laboratory. Even prior to the time a specimen is collected from a patient, a patient record is created or an existing one is retrieved. This information accompanies the laboratory order, which is the first touch point for the lab. Patient name, date of birth, gender, ordering and admitting physician name, location of the patient, and other data from the patient record are used by the laboratory for various operational reasons, such as knowing where to send the patient report, which reference ranges to use, and so on.
The specimen is now ready to be processed in the laboratory. Pre-analytic information such as how many specimens have been received, which specimens need to be centrifuged, what tests need to be sent to an outside reference laboratory, and other data are generated. In the analytic process, the volume of results reported, the number of rejected specimens, and timestamps of when a specimen went from one workstation to another are produced. Once the specimen has been tested and is ready for storage, the location of the specimen in the refrigerator or freezer and the accession number of the specimen are compiled and stored. Finally, a patient result is produced and a report generated.
Throughout the pre-analytics, analytics, and post-analytics processes, valuable data is being gathered and stored that could be used in many ways. For the clinical laboratory professional on the bench, this data is mainly used for managing the daily workload; the data can reveal not only processes that are working well, but also processes that are not working well.
Drilling down into the details of the information and being able to produce statistics and reports provides a quantitative view of laboratory operations. Are there areas within your laboratory where metrics could help recognize the impact of the services provided by the laboratory? Are stakeholders asking for information outside the laboratory that can’t be produced?
Ultimately, it is best to consider both features and cost when selecting a laboratory information system that fits the lab’s needs, but when factors outside the walls of the laboratory have an impact on the selection, that complicates the decision process. If an LIS does not provide all the functionality you need but is less expensive, what are the repercussions of not having those capabilities in the product? Are the workarounds easily implemented to compensate for the deficiencies?
Return on investment
Trying to determine the ROI when it comes to purchasing an LIS can be very challenging. After all, how do you put a value on the results that are generated from a system that saves patients’ lives?
Best-of-breed vendors, regardless of the industry, focus on depth and coverage of their domain. Their vision and strategy is built with the focus of being the experts in their area. Enterprise vendors cover a wider span within the industry. They serve up offerings that may be comprised of one or two products in several domains. The ability to manage the workflow, quality management, data mining and reporting capabilities, and cost are not the only criteria when comparing the two models, but are examples of what needs to be taken into consideration beyond the traditional feature-to-feature comparison and checklists used in the selection process.
