Background: Clinical pathology laboratories increasingly use complex instruments that incorporate chromatographic separation, e.g. liquid chromatography, with mass detection for rapid identification and quantification of biochemicals, biomolecules, or pharmaceuticals. Electronic data management for these instruments through interfaces with laboratory information systems (LIS) is not generally available from the instrument manufacturers or LIS vendors. Unavailability of a data management interface is a limiting factor in the use of these instruments in clinical laboratories where there is a demand for high-throughput assays with turn-around times that meet patient care needs. Materials and Methods: Professional society guidelines for design and transfer of data between instruments and LIS were used in the development and implementation of the interface. File transfer protocols and support utilities were written to facilitate transfer of information between the instruments and the LIS. An interface was created for liquid chromatography-tandem mass spectroscopy and inductively coupled plasma-mass spectroscopy instruments to manage data in the Sunquest^® LIS. Results: Interface validation, implementation and data transfer fidelity as well as training of technologists for use of the interface was performed by the LIS group. The technologists were familiarized with the data verification process as a part of the data management protocol. The total time for the technologists for patient/control sample data entry, assay results data transfer, and results verification was reduced from approximately 20 s per sample to <1 s per sample. Sample identification, results data entry errors, and omissions were eliminated. There was electronic record of the technologist performing the assay runs and data management. Conclusions: Development of a data management interface for complex, chromatography instruments in clinical laboratories has resulted in rapid, accurate, verifiable information transfers between instruments and LIS. This has eliminated manual data entry that is prone to errors and enabled technologists to focus on analytical applications on the instruments.

Introduction: Historically, effective clinical utilization of image analysis and pattern recognition algorithms in pathology has been hampered by two critical limitations: 1) the availability of digital whole slide imagery data sets and 2) a relative domain knowledge deficit in terms of application of such algorithms, on the part of practicing pathologists. With the advent of the recent and rapid adoption of whole slide imaging solutions, the former limitation has been largely resolved. However, with the expectation that it is unlikely for the general cohort of contemporary pathologists to gain advanced image analysis skills in the short term, the latter problem remains, thus underscoring the need for a class of algorithm that has the concurrent properties of image domain (or organ system) independence and extreme ease of use, without the need for specialized training or expertise. Results: In this report, we present a novel, general case pattern recognition algorithm, Spatially Invariant Vector Quantization (SIVQ), that overcomes the aforementioned knowledge deficit. Fundamentally based on conventional Vector Quantization (VQ) pattern recognition approaches, SIVQ gains its superior performance and essentially zero-training workflow model from its use of ring vectors, which exhibit continuous symmetry, as opposed to square or rectangular vectors, which do not. By use of the stochastic matching properties inherent in continuous symmetry, a single ring vector can exhibit as much as a millionfold improvement in matching possibilities, as opposed to conventional VQ vectors. SIVQ was utilized to demonstrate rapid and highly precise pattern recognition capability in a broad range of gross and microscopic use-case settings. Conclusion: With the performance of SIVQ observed thus far, we find evidence that indeed there exist classes of image analysis/pattern recognition algorithms suitable for deployment in settings where pathologists alone can effectively incorporate their use into clinical workflow, as a turnkey solution. We anticipate that SIVQ, and other related class-independent pattern recognition algorithms, will become part of the overall armamentarium of digital image analysis approaches that are immediately available to practicing pathologists, without the need for the immediate availability of an image analysis expert.

Electronic health records (EHRs) have emerged as a major topic in health care and are central to the federal government's strategy for transforming healthcare delivery in the United States. Recent federal actions that aim to promote the use of EHRs promise to have significant implications for laboratories and for pathology practices. Under the HITECH (Health Information Technology Economic and Clinical Health) Act, an EHR incentive program has been established through which individual physicians and hospitals can qualify to receive incentive payments if they achieve "meaningful use" of "certified" EHR technology. The rule also establishes payment penalties in future years for eligible providers who have not met the requirements for meaningful use of EHRs. Meaningful use must be achieved using EHR technology that has been certified in accordance with functional and technical criteria that are set forth a regulation that parallels the meaningful use criteria in the incentive program. These actions and regulations are important to laboratories and pathologists for a number of reasons. Several of the criteria and requirements in the meaningful use rules and EHR certification criteria relate directly or indirectly to laboratory testing and laboratory information management, and future stage requirements are expected to impact the laboratory as well. Furthermore, as EHR uptake expands, there will be greater expectations for electronic interchange of laboratory information and laboratory information system (LIS)-EHR interfaces. Laboratories will need to be aware of the technical, operational, and business challenges that they may face as expectations for LIS-EHR increase. This paper reviews the important recent federal efforts aimed at accelerating EHR use, including the incentive program for EHR meaningful use, provider eligibility, and EHR certification criteria, from a perspective of their relevance for laboratories and pathology practices.