Melanitis et al.
present a materials informatics approach applied by the Hellenic Naval Academy in this 2021 paper published in MATEC Web of Conferences
. Their approach resulted in NAVMAT, developed "by integrating materials engineering and informatics under a platform of knowledge management." After providing some background on the topic of materials informatics and the management of research information associated with it, the authors describe their system architecture and key features, along with its potential applications. They conclude by providing six expected outcomes associated with the platform, adding that NAVMAT "aims to optimize naval materials failure analysis management and support decision making in maintenance and repair operations (MRO), materials supply management, and staff training."
In this 2022 paper published in Laboratory Animal Research
, Yoon et al.
, representing multiple healthcare entities in South Korea, present a study of their developed and implemented COVID-19 non-clinical trial LIMS. The LIMS, which was developed due to not finding systems "allowing multiple institutions to participate simultaneously in research related to COVID-19," was deployed at six animal Biosafety level 3 (BSL-3) institutions. After providing background on their impetus for developing the LIMS, the authors present the specifics of their solution and then discuss its applications at its participating BSL-3 institutions. They conclude that the system not only enables more "efficient and reliable documentation, management, and reporting of non-clinical COVID-19 test results," but it also "can be adapted to different research projects."
In this 2022 case study by AbuHalimeh, de-identified data quality dimensions (DDQD) in two real-life clinical systems are examined to better understand discrepancies and requirements for their correction in order to improve data quality for clinical researchers. After a brief introduction to the topic of clinical informatics and data quality, AbuHalimeh presents a case study using patient count data from a TranSMART Foundation i2b2 and Epic SlicerDicer system of "a healthcare organization that wanted to have the ability to ingest other sources of research-specific data." After discussing the methodology and results, the author proposes a series of eight steps to improve data quality generated from de-identified system." Those steps "together form guidelines for a methodology of manual and automated procedures and tools used to manage data quality and data governance in a multifaceted, diverse information environment such as healthcare organizations, as well as to enhance data quality among data housed in de-identified data systems," the author concludes.
Following up on 2021 research
on heavy metal contaminants in the South African cannabis market, Vivierset al.
similarly describe solvent residue contaminant found in the same market in this 2022 paper published in Journal of Cannabis Research
. Noting a dearth of such research in the South African market, the authors acquired 279 samples and had them analyzed in duplicate for a specific set of Class 1–3 solvents. The authors turned to headspace gas chromatography–mass spectrometry (HS-GC-MS) analysis , the United States Pharmacopeia (USP) <467>, and the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) Q3C to guide their analyses. After a brief discussion of materials and methods, the authors present their results and conclusions. They found among its analyzed 279 samples, "a total of 111 samples had at least one solvent analyte that failed the USP
and ICH specification limit (37% failure rate)," with the failure rate increasing 2% for summed solvent concentrations. They conclude that "when assessing solvent residues present in samples against a set of pharmacopeial safety limits, it is evident that a large fraction of cannabis-based products in South Africa exceeds these limits."
In this 2021 paper by Bohn et al.
, a review of the utility and limitations of clinical laboratory electronic tools is given, along with a use case of the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) online database. After a brief introduction, the authors examine both tools that are useful to the medical provider and tools useful to the patient, as well as a few caveats on their use. They then discuss CALIPER, a tool " aimed to improve blood test result interpretation in children by establishing accurate and robust pediatric reference intervals for important biomarkers of health and disease." They discuss the system in the framework of how such clinical electronic systems can assist doctors and patients through the laboratory. They conclude that "clinical laboratories should be leading and actively engaged in electronic diagnostic tool innovations that improve laboratory data communication and reduce post-analytical errors in test result reporting and interpretation," while at the same time considering "[i]nherent biases to data-driven technologies."
In this 2022 paper published in Journal of Pathology Informatics
, Dundar et al.
of University of Iowa Hospitals and Clinics describe an add-on for their laboratory information system (LIS), an electronic intradepartmental consultation system for anatomic pathology (AP), and how it impacted their facilities. After a brief introduction and background, the authors describe the methods used to adapt an AP consultation system into Epic's AP Beaker. Noting that 7.3% of all case work was consultation, they broke down the results of implementing the more automated system and discussed how the new system improved management and documentation of the consultation process. After discussion of their results, the authors conclude that their more automated system implemented in the AP Beaker LIS improves their processes and documentation, provides better tracking of consultation cases, which in turn plays "a vital role in preventing misdiagnosis and improving pathology reporting and trainee education."
The interoperability of health care systems—especially electronic health records (EHRs)—has long been a focus of regulators, medical personnel, and other key stakeholders. Interoperability helps ensure data communicated from one system to another are sufficient for the receiving system to work with, i.e., have the same meaning to the recipient as they do the sender. This is not always an easy task, as noted by Sachdeva and Bhalla in this 2022 paper published in Information
. Also noting the value in clinical information exchange, the authors examine formal methods of making interoperability work better, as well as considerations interoperability experts should be making in successfully transforming data across different EHR standards. After laying out their research work and findings on cross-conversion of archetypes such as XML, ADL, and OWL, the authors conclude both that "terminology binding must established through archetypes" and "mappings between different standardized EHR systems must be established." Each archetype has its drawbacks and benefits, depending on what you're trying to accomplish, and this research "can contribute to helping EHR system vendors and developers to choose the appropriate technology for the required purpose, keeping in mind semantic interoperability."
As the analytical landscape for laboratory measurement of cannabinoids in a variety of matrices continues to evolve and standardize, the demand for more rapid yet accurate point-of-testing solutions for cannabinoids continues to grow. This demand comes from not only the cannabis cultivator but also the law enforcement community. One potential path to meet demand is the electrochemical sensor, as suggested by Amini et al.
In this 2022 paper, the authors briefly describe the demand issue and how electrochemical sensors have been applied by other researchers. They then focus in on sensors for oral fluid specimens and how they have been successfully applied. The authors conclude that this technology has potential for "roadside drug testing, cannabis product quality control, and cannabis crop evaluation," but not without challenges to proper implementation, including "nonspecific interaction and the interference of compounds and species from the heavy plant matrix or oral fluids."
In this 2021 article published in the journal Information
, Alruwaili presents their framework "for better and more secure evidence preservation and handling" in digital forensics: CustodyBlock. Noting the importance of evidence management and the complexities that come with it, the author's framework turns to "private blockchain protocol and smart contracts to support the control, transfer, analysis, and preservation monitoring of forensic evidence." After discussing the related research and justification for such a framework, Alruwaili briefly covers research methodology, digital evidence custody, and the architecture and algorithm for their framework. After a brief discussion of the results, the author concludes that the framework demonstrates strong protection of the evidence chain and a more robust handling methodology, with the potential to handle information beyond that of digital forensics.
Continuing from last week's theme of agriculture data management, this week's journal article from Wong et al.
examines the need for consistent "minimum thresholds" for FAIR (findable, accessible, interoperable, and re-usable) data in the agricultural research community. They discuss this in terms of their "community-governed federation approach" called AgReFed (Agricultural Research Federation), which has been piloted since 2018. Using a variety of datasets and research use cases, the authors go on to discuss their methodology for developing and testing FAIR thresholds in their pilot community, as well their governance and implementation. The authors close out their work by discussing the benefits of the approach to founding partners, including "being an exemplar of FAIR best practice at the institutional level, making access and re-use easier for end-users, and being able to combine data types for research insights." Data providers "benefited from metadata guidance through education resources, library, and licensing support." However, the authors note that expansion of such a framework to other coops, corporations, etc. understandably may require additional incentivization.
As the promise of "smart farming" and "precision agriculture" begins to emerge, it is increasingly clear that—like other areas of research and industry—effective data management, analysis, and visualization is increasingly important. In the case of sustainable farming and other agricultural similar endeavors, this means tapping into wide varieties of data to improve operational efficiency, crop yields, and automated tasking. In this 2021 paper by Giray and Catal, a data management reference architecture providing common vocabulary and templated solutions for agriculture software developers is discussed. The authors note their reference architecture is based off three agriculture-specific use cases, as well as other related reference architecture studies. After describing the domain scoping and modeling aspects of their data management reference architecture, they discuss its validation and practical use. They conclude that while the study focused on sustainability within agricultural domains, "it can be extended to a larger context by covering other critical aspects of agriculture," demonstrating "that the proposed data management reference architecture is practical and effective."
In this 2020 paper published in JMIR Medical Informatics
, Cecchetti et al.
of the Joan C. Edwards School of Medicine at Marshall University present their health informatics platform, the Appalachian Informatics Platform (AIP). Designed to support "research efforts by enabling curation and analysis of data using the different components," the platform is described in detail following the presentation of necessary background information on the unique informatics and healthcare challenges of the Appalachia region. After describing their methodology and results, the authors discuss the perceived utility of AIP and conclude that AIP is indeed useful in "enabling seamless and secure data access, model development through an analytics engine to explore novel and unexpected hypotheses, and simple yet effective communication of all findings via interactive visualization."
In this 2022 paper published in Separations
, Hewavitharana et al.
examine a more simplified means of quantifying cannabinoids using liquid chromatography–mass spectrometry (LC-MS) with a low flow rate rather than a more expensive ultra-high-performance liquid chromatography (UHPLC) system. After descrribing their materials and methods used, the authors discuss the optimization of their extraction method, as well as the optimization of chromatographic separation and mass spectrometry, and how the processes were validated. They conclude that "the main advantage of using this approach is that the method can be easily adapted to use with a simple HPLC-MS (single quadrupole) system," and that "the method is well suited for routine phytocannabinoid analysis across a range of applications in a variety of laboratory settings."
In this 2022 paper published in the journal Information
, Sachdeva and Bhalla of the National Institute of Technology Delhi examine electronic health records (EHRs) and their requirement for interoperability from a semantic and archetype point of view. After providing an overview of EHRs and their standards for semantic interoperability, the authors discuss how to better achieve more secure and more accurate data interoperability through the use of semantic-based archetypes. They then discuss knowledge representation and the five most common approaches to it, addressing specifically ADL, XML, OWL, and other formalisms. They then evaluated some of the best approaches and discussed their strengths and drawbacks. After brief discussion, the authors conclude that while semantic interoperability is essential to "evidence-based healthcare across heterogeneous EHR systems," areas of study are still lacking in regards to "direct support for mapping to formal ontologies." They suggest that ADL and OWL have their own strengths, compared to XML that has more weaknesses despite being a more global standard.
We hear case studies of laboratory automation implementations from time to time, usually in larger facilities that can afford the expense. But what of smaller labs in developing countries? With sensors and open-source technologies gaining ground—and application development becoming more commonplace—automating small labs in small ways isn't so distant a reality. This 2022 paper by Mwambe et al.
of the Nelson Mandela African Institution of Science and Technology demonstrates this, providing details of their smart laboratory information management system (LIMS) and hardware-based automation solutions in their labs. After introducing the concept behind their software+hardware solution, the authors go over the design and implementation of their smart LIMS. They conclude that their system of LIMS, RFIF, IoT, and sensor networks effectively "automate recurring tasks in laboratories, aid in monitoring, and eliminate paper-based record keeping. Using such a smart LIMS, researchers can better plan research activities."
There are many approved methods for analyzing the cannabinoids from a given sample of the Cannabis
plant, though some of them have downsides for the analyst. This is particularly notable in sample with significant quantities of acidic cannabinoids, which decarboxylate to their neutral cannabinoids with heat. This usually requires more non-destructive methods, such as near-infrared spectroscopy (NIRS). In this 2022 journal article, Jarén et al.
of Universidad Pública de Navarra and Genscore Navarra S.L. in Spain provide their take on using NIRS methods combined with chemometric techniques to get quality results in analyzing cannabinoids, in comparison to using high-performance liquid chromatography (HPLC). After introducing the current background on analytical methods for cannabinoid analysis, the authors describe their methodology and results. They conclude that "[t]he results obtained here demonstrate that NIR spectroscopy offers speed and simplicity unmatched by other traditional techniques." They add that "[a]ccordingly, it was tested as an alternative to conventional HPLC analysis for the evaluation of cannabinoid content, with promising results."
In the United States, Europe, and other parts of the world, the application of health informatics technologies continues to mature. However, in emerging economies such as India, China, and Bangladesh, the concept of health informatics and its application is still relatively new. In this 2022 paper published in Frontiers in Public Health
, Yogesh and Karthikeyan discuss health informatics from the perspective of such emerging markets, the challenges those markets face, and the policies and standards required to ensure positive public health outcomes. The duo first introduce the topic health informatics and the breadth of technologies affecting it, including machine learning and deep learning. They also provide a few examples of related work on the topic before getting into how the Health Level 7 FHIR architecture plays an important role in health informatics. The authors then provide further perspectives on the current state of the art and future trends in health informatics, including from the perspective of India's medical system. They close by discussing a number of challenges India and other countries face in adopting health informatics tools, concluding that despite its promise, health informatics implementations are rarely straightforward. "There are no proven design blueprints for such a comprehensive infrastructure, and the goal is always shifting due to the nature of real-time patient, medical, and equipment data collection from a variety of sources," they add.
This April 2022 Technical Note from the National Institute of Standards and Technology (NIST) and its Material Measurement Laboratory investigates the laboratory information management system (LIMS) within the scope of the laboratory's strategic mission and goals "to support a wide array of research disciplines." Greene et al.
provide a roadmap of implementing LIMS and related technologies and adapting their research workflows to get the most of LIMS while also taking advantage of FAIR Data Principles. After a brief introduction, the authors describe both their short- and long-term objectives towards the lab's vision of implementing LIMS effectively, along with the associated challenge of meeting those objectives. They then discuss the related stakeholders and how they impact implementation of the LIMS roadmap. The authors also discuss LIMS architecture and quality metrics associated with its implementation, before concluding that their "next-generation LIMS will provide standards for interoperability and collaboration, further enabling scientific investigation spanning across experimental groups."
In this 2022 paper published in The Journal of Molecular Diagnostics
, the Molecular Pathology Section of Cleveland Clinic describes its collaboration with Semaphore Solutions in order to customize a laboratory information management system and other tools to meet the needs of Cleveland Clinic's molecular pathology department. The authors first describe their goals, technology approach, and software approach within the framework of project development and management, including validation steps. They then provide details about how their implementation affected their work. They conclude that "a significant amount of customized software engineering" was required to get a system that met their needs, as was a Scrum-based development approach, "which may be emulated for scalable and cost-effective laboratory-authored software." They also add that "[a]n important lesson learned in executing the LIMS project was the concept of a minimally viable product (MVP)."
In this 2022 paper published in the journal Diagnostics
, Temprana-Salvado et al.
of the Catalan Health Institute present the initial results of their DigiPatICS program, implemented across eight hospitals in the network. DigiPatICS, a digital pathology implementation initiative, was initiated "to increase patient safety and quality of care, improving diagnosis and the efficiency of processes in pathological anatomy departments of the ICS using digital pathology and AI tools." However, it was not a straightforward process, requiring significant planning, After describing their planning steps, the project scope, and tender process, the authors describe multiple aspects of their approach, including the instruments, hardware, software, laboratory information system (LIS), networking, data centers, imaging standards, and AI components. After discussing the results of their implementation, the authors concluded though "[t]he digital transformation of a pathology department represented a technological, organizational, and functional challenge ... [it] provided an effective and safe diagnostic tool with clear benefits for diagnosis quality and patient safety."