The best-of-breed LIS vendors have only been partly successful during the last decade in providing adequate support for molecular and genetic labs. This was due, in part, to the rapidly changing technology/science deployed in these labs. I became aware of the fact that the informaticians supporting these labs were a breed apart when I heard them referring to their systems as LIMSs rather than LISs. LIMS, laboratory management information systems, was the preferred term for the systems used in "scientific and industrial" labs as opposed to the LISs in hospital labs. These informaticians tended to have a closer relationship to companies like Luminex than to IVD vendors such as Roche or Siemens.
I recently read an article in the Dark Daily suggesting that the information systems used to support molecular and genetic labs are being referred to as Molecular Information Management Systems (MIMS) rather than LIS modules (see: Molecular Information Management Systems (MIMS) Are Newest Tools to Help Clinical Laboratories Perform and Report Molecular and Genetic Test Results). Below is an excerpt from this article:
Steady improvements to next-generation genetic sequencing, lab-on-a-chip technologies, and lab automation are triggering substantial increases in the volume of data generated at medical laboratories and pathology groups....However, over the past decade, the volume of data generated by molecular and genetic testing has outpaced the organization, reporting, and interfacing features of popular LISs....Particularly in the past 10 years, advances in molecular diagnostics and genetic testing outpaced the capabilities of traditional laboratory information systems. And, because during most of this time, it was typically a handful of medical laboratories that performed advanced molecular and genetic testing, this market was not big enough to justify IT companies developing more sophisticated LIS products to serve what was, at that time, a small market segment. Consequently, for the past 15 years, clinical labs that developed and performed sophisticated molecular and genetic tests often found it necessary to create their own software code to support their unique menus of tests....Meanwhile, what has changed in the molecular and genetic testing marketplace during the past 48 months is the availability of more multi-analyte assays, load-and-walk-away analyzers, and automation that enable pathology groups and community hospital labs to establish and offer a growing menu of molecular assays and genetic tests.
....To meet the demand for laboratory information systems that competently and capably manage the high volume of data generated by the current generation of molecular and genetic tests, most LIS providers and vendors are scrambling to add capabilities to their traditional LIS products. ....[M]edical labs performing molecular and genetic tests are turning to new best-of-breed solutions known as Molecular Information Management Systems (MIMS) to help streamline and manage laboratory workflows, reporting, billing, and other essential aspects of daily operation. These software products are designed to enable labs to handle the growing volume of molecular and genetic data that powers personalized medicine. By design, they have capabilities that go beyond the traditional LIS products, mostly because of the often huge volumes of raw data they must collect, store, and analyze. In addition, best-of-breed MIMS software must do more than help manage data within the clinical laboratory environment.
To a large extent, the best-of-breed (BOB) LIS vendors have also been outperformed by smaller lab software companies in providing analytics software (see: Leveraging Lab Analytic Data to Include Actionable Details to Improve Quality; Lab Analytics Emerges as Hot Area for Software Development; Using Lab Analytics Software to Manage Customers Relationships in the Clinical Labs). I believe that the next major trend in clinical lab software will be predictive analytics (see: Identifying Patients for Remote Monitoring with Predictive Analytics; Relevance of Lifestyle Analytics for Healthcare Organizations) and big data/deep learning (see: Allscripts Launches a Subsidiary, 2bPrecise, Focusing on Genomic Testing). Like the just described MIMS scenario, I don't think that the the LIS vendors will lead the pack in these new areas. One of the dominant goals of predictive analytics software will be is the analysis of LIS data supplemented by clinical data from the EHR to generate patient diagnoses. As noted in a recent blog note I believe that in perhaps five years, the role of pathologists, radiologists, and clinicians will be primarily the management of lab, radiology, and hospitals predictive analytic systems rather than generating most of the diagnoses themselves (see: Radiologists and Pathologists as Information Specialists; Merger of the Specialties?).