Journal:Best practice recommendations for the implementation of a digital pathology workflow in the anatomic pathology laboratory by the European Society of Digital and Integrative Pathology (ESDIP)

From LIMSWiki
Revision as of 20:01, 5 December 2021 by Shawndouglas (talk | contribs) (Saving and adding more.)
Jump to navigationJump to search
Full article title Best practice recommendations for the implementation of a digital pathology workflow in the anatomic pathology laboratory by the European Society of Digital and Integrative Pathology (ESDIP)
Journal Diagnostics
Author(s) Fraggetta, Filippo; L'Imperio, Vincenzo; Ameisen, David; Carvalho, Rita; Leh, Sabine; Kiehl, Tim-Rasmus; Serbanescu, Mircea; Racoceanu, Daniel; Mea, Vincenzo D.; Polonia, Antonio; Zerbe, Norman; Eloy, Catarina
Author affiliation(s) European Society of Digital and Integrative Pathology, Azienda Sanitaria Provinciale Di Catania, University of Milano-Bicocca, Imginit SAS, Charité – Universitätsmedizin Berlin, Haukeland University Hospital, University of Bergen, University of Medicine and Pharmacy of Craiova, Sorbonne Université, University of Udine
Primary contact Email: celoy at ipatimup dot pt
Year published 2021
Volume and issue 11(11)
Article # 2167
DOI 10.3390/diagnostics11112167
ISSN 2075-4418
Distribution license Creative Commons Attribution 4.0 International
Website https://www.mdpi.com/2075-4418/11/11/2167/htm
Download https://www.mdpi.com/2075-4418/11/11/2167/pdf (PDF)
Emblem-important-yellow.svg This article should be considered a work in progress and incomplete. Consider this article incomplete until this notice is removed.

Abstract

The interest in implementing digital pathology (DP) workflows to obtain whole slide image (WSI) files for diagnostic purposes has increased in the last few years. The increasing performance of technical components and the Food and Drug Administration (FDA) approval of systems for primary diagnosis led to increased interest in applying DP workflows. However, despite this revolutionary transition, real-world data suggest that a fully digital approach to histological workflow has been implemented in only a minority of pathology laboratories.

The objective of this study is to facilitate the implementation of DP workflows in pathology laboratories, helping those involved in this process of transformation with: (a) how to identify the scope and the boundaries of the DP transformation; (b) how to introduce automation to reduce errors; (c) how to introduce appropriate quality control to guarantee the safety of the process; and (d) addressing the hardware and software needed to implement DP systems inside the pathology laboratory. The European Society of Digital and Integrative Pathology (ESDIP) provided consensus-based recommendations developed through discussion among members of the broader scientific committee. The recommendations are thus based on the expertise of panel members and on the agreement obtained after virtual meetings. Prior to publication, the recommendations were reviewed by members of the ESDIP Board. The recommendations comprehensively cover every step of the implementation of a digital workflow in the anatomic pathology department, emphasizing the importance of interoperability, automation, and tracking of the entire process before the introduction of a scanning facility. Compared to the available national and international guidelines, the present document represents a practical, handy reference for the correct implementation of a digital workflow in Europe.

Keywords: digital pathology, anatomic pathology workflow, whole slide imaging, laboratory information system

Introduction

The interest in implementing digital pathology (DP) workflows to obtain whole slide image (WSI) files for diagnostic purposes has increased in the last few years. This is in part due to the opportunities offered by WSI, e.g., telepathology and image analysis, including computational pathology tools based on artificial intelligence (AI) methods. The increasing performance of technical components and the Food and Drug Administration (FDA) approval of systems for primary diagnosis[1] led to increased interest in applying DP workflows. Moreover, in the last few years, several studies evaluating performance demonstrated the non-inferiority of WSI compared to conventional light microscopy[2][3][4] for primary histological diagnosis. This may help to alleviate concerns about the possible risk of DP-related diagnostic errors.[5] Indeed, the restrictions suffered during the COVID-19 pandemic, the reduction in the number of pathologists, and the increase in workload, along with a rising number and complexity of clinical cases, also raised the interest in DP.

Several definitions for DP have been proposed so far[6][7], a common opinion being that DP encompasses the photographic documentation of the macroscopy of the specimens (“gross pathology”), the digitization of glass slides (virtual microscopy), and telepathology. By some definitions, DP involves merely the digitization of glass slides. In this study, “DP” is significantly distanced from the reductive paradigm of only glass slide digitization, moving towards a more integrative approach that comprises interventions in all stations of work in the pathology laboratory, introducing and supporting innovation. DP implicitly consists of all the associated technologies to allow improvements and innovations in workflow, including, for instance, laboratory information systems (LIS), digital dictation, dashboard and workflow management, electronic specimen labelling and tracking, and synoptic reporting tools.

The objective of this study is to facilitate the implementation of DP workflows in pathology laboratories, helping those involved in this process of transformation to: (a) identify the scope and the boundaries of the DP transformation; (b) introduce automation to reduce errors; (c) introduce appropriate quality control to guarantee the safety of the process; and (d) implement the hardware and software needed to implement DP systems inside the pathology laboratory. Since several recommendations and guidelines have already been proposed, primarily focusing on the validation of WSI for clinical purposes or on the technical environment, this paper mainly covers DP implementation and all the prerequisites for a pathology laboratory to change from an analogue to a digital workflow.[8] Considering all that has been reported about DP workflow implementation and its associated benefits, it is anticipated that this new methodology has many advantages that should be attractive and convenient for all pathology laboratories worldwide, independently of their dimension, workload, number of pathologists, or type of activity (e.g., academic/nonacademic, private/public).[6][7][9][10][11]

So far, there are several possibilities to transit and to manage “images” in a digital workflow: an LIS-based approach[12][13], a scanner vendor approach[7], or an intermediate software approach (e.g., Linköping University[14]). Independently of the type of strategy chosen, in order to switch towards a digital visualization of images (whether LIS-centric, vendor-based, or third-party software), the new system should be able to integrate every possible instrument (e.g., one or more scanners from the same or different vendors, with the possibility to manage different images from a variety of sources), preferably associated with a tracking system because of automation and innovation. The cost-effectiveness of DP has already been documented in implementation models that discuss the scope of investment, the potential return on investment, and cost-savings of DP, as well as any proposed income deriving from the adoption of WSIs.[15] Moreover, the adequate adaptation of a routine clinical workflow can finally lead to an optimization of resources (e.g., space, time, personnel, and equipment). These are intended as recommendations and suggestions for the implementation of the full DP workflow in the routine clinical practice of anatomic pathology laboratories. The introduction of a DP workflow even allows the implementation of computational pathology tools such as AI.

The following sections explain, point-by-point, the steps needed for the progressive, secure, and efficient transition into a DP workflow. Regarding cytopathology, there are several barriers that still need to be overcome for routine cytopathology to go digital and support wider adoption and sustainability. Therefore, the present study mainly focuses on histopathology and the justification (Box 1) for its transition to a DP workflow.


Box 1. The justification of transitioning histopathology workflows to digital pathology workflows.
1. Digital pathology is pathology, a holistic approach that comprehends interventions in all stations of work at the pathology laboratory, introducing innovation.

2. Digital pathology is attractive and convenient for pathology laboratories worldwide.
3. Digital pathology represents a safer and more efficient way of working and should be considered the new standard in pathology.
4. Implementation of a digital pathology workflow is a key milestone to patients fully benefiting from the potential of WSI and a prerequisite for the application of AI in routine diagnostics.

Involvement of the team in the digital pathology transformation of the laboratory

The implementation of digital pathology requires a multidisciplinary approach from the very beginning. The leading team should involve in-house participants (e.g., pathologists, laboratory technicians, administrative staff) and the hospital’s IT and technical services.[6] IT services might be organized in different ways depending on the size of the department and depending on local or national policies. For example, IT services may be provided by individuals, by a separate department, or by a subcontractor. The most important thing is that these groups work together and that they form a team.

Subsequently, close collaboration with companies providing the digital pathology system and the LIS will become necessary. Especially in larger departments, digital transformation will usually be organized as a project that includes a project manager, a steering group, and different working groups. There are several ways of introducing the topic and designing the appropriate options for the laboratory at hand, and it might be useful to visit pathology departments with digital workflows to learn from their successes and failures. There are a couple of papers that share such experiences and provide valuable information.[6][7] Describing user scenarios is another method to both understand the needs of one’s own laboratory and communicate those needs to the IT and technical departments, as well as potential vendors. In addition, before starting a tender, it is helpful to gather information about suppliers and products.

To obtain a successful implementation of DP and to avoid deficiencies, the multidisciplinary team that is going to lead the “digital revolution” in each department should follow some crucial steps, as previously reported. In particular, for the correct and rapid implementation of DP in every department, it is advisable to create awareness and appropriate work conditions, incentivize participation, encourage communication among the team members, and monitor the outcomes of this revolution. This approach could help in facing the heterogeneous patterns of reactions that different actors of the team could express, including the “enthusiasts,” the “sceptics,” and the “undecided.” All the possible measures to increase the trust and involvement of pathologists should be applied to all staff members.

To establish a successful DP workflow, a thorough stakeholder analysis should be carried out, and a communication strategy should be established based on this analysis. The team must ensure that all internal stakeholders (including pathologists, laboratory personnel and administrative staff) are continuously informed from the beginning. In this setting, sharing the vision of DP with laboratory and administrative personnel, encouraging them to provide feedback, expressing potential concerns and suggestions (e.g., using frequent meetings on-site), and providing appropriate discussion during all phases of the deployment will facilitate a safe and effective implementation. The team must be aware that DP should be perceived as an integral part of the laboratory workflow rather than an “add-on.”[6] The contingent situation due to the COVID-19 pandemic can be further leveraged to boost the implementation of DP in the laboratories, stressing the need to maintain pathology services by making it possible for pathologists to work from home.[16]

Implementing DP as the standard laboratory practice also requires learning new technical skills to capture all the advantages of this technology. Just as significant as consulting the internal stakeholders is the involvement of IT services. IT will be crucial in many aspects of the project (e.g., handling LIS adaptations, integrations, storage, testing etc.). The involvement should start in the early phases of the transition. For example, consider conducting a laboratory office tour to establish communication with the other components of the project, using clear language. This gives your team the opportunity to understand what is expected and what is potentially achievable from your deployment, and what each professional group will be expected to contribute in terms of time and staff. Explain your ideas for future digital workflows and see what potential dependencies and solutions your IT colleagues can generate.

Optimization of resources in the DP workflow

In a fully digital laboratory, the processes and records are electronic file-based and the environment is paperless, with glass slides being substituted at the end of the workflow by WSIs. The optimization of resources—namely time, space, people and instruments—creates conditions for increased efficiency and, consequently, decreased costs. The LEAN approach represents a valuable strategy to optimize the workflow, leading to a more logical distribution of the spaces to minimize staff and sample traffic inside the laboratory. It also allows for a more harmonic and well-planned articulation between human resources and available instruments, which results in time and cost-effectiveness. And, although it is not a strict prerequisite for adopting DP, it could further allow for better allocation of resources.[17]

This reallocation could start from a more rational disposition of the spaces or offices inside the pathology laboratory. An inefficient arrangement of the physical spaces, typical of the old, “analogue” workflow, can partly impair the smooth crosstalk among the different components of the process. Previous experiences in implementation models stress the need to analyze the pre-existing workflow before implementing DP.[6][7] A careful analysis of the pre-existing analogic workflow before the transition should consider the flow of the samples (workstation location) in the laboratory and time intervals (hands-on and waiting times) for each workstation, verifying the information technology support and establishment of adequate quality control checkpoints. The lack of structural organization of some pathology laboratories, including the physical placement of the different workstations, may contribute negatively to the desirable, efficient crosstalk between workstations. The reorganization of such a laboratory structure with the intent to decrease unnecessary movements of the staff, and time loss, can be useful for every laboratory, independently of DP implementation. For instance, the scanning workstation should be located near the staining and mounting instruments, accelerating the production line but far from the microtome area to avoid the interference of paraffin with the scanning mechanisms. After this retrospective analysis and reorganization of the structure, the optimal choices for the automation of each workstation must be made, namely by the introduction of a reliable tracking system, and different instruments would preferably work in a coordinated fashion, connected (mono- or bi-directionally) to the LIS or laboratory information management system (LIMS).

The role and potentialities of laboratory informatics resources

Independently of the system employed to manage the WSI, pathology laboratories mainly depend on a laboratory information systems (LIS) to support their operation and, ultimately, carry out their patient care mission. For these reasons, one of the crucial points is to ensure the full integration of the systems involved in the digital transition. Although many LISs have evolved with sophisticated and more user-friendly software over the past few decades, supporting a broader range of functions, many others have not evolved, thus preventing possible integration with other technologies deployed in pathology laboratories. A modern LIS plays different roles in all phases of patient testing, including specimen and test order entry, specimen processing, and specimen tracking. They track and organize the laboratory’s workflow, mainly through event logs and histology protocols. The maintenance of such logs can follow the default configurations of the system or can be customized by each laboratory to display the most useful information. A typical example of the system’s default configuration for a log (e.g., routine histology) includes accession number, timestamp, patient and specimen data, histology protocol(s) ordered, other stains ordered, and comments about the specimen or the request.

An LIS now incorporates multiple features that, until recently, were either unavailable or required a significant customization effort to be obtained. The Association for Pathology Informatics produced a comprehensive list of basic and advanced LIS features that may be used to evaluate LIS capabilities.[18] Moreover, the next generation LIS should be able to link digital images to the respective cases appropriately. With the rising use of WSI for clinical purposes, a consensual increase in capabilities to connect and integrate WSI systems and LIS is to be expected (e.g., being able to open WSI from the LIS, log the viewed areas/magnification on all WSI, or even apply image analysis and store result data). Further advances in the development of the LIS are expected in the future, starting from the integration of more sophisticated tools to support data mining and the analysis of pathology and clinical data sets. The LIS may evolve into a multimodality “pathologist cockpit” that not only provides LIS functions but also displays pathology imaging and other medical imaging, supplies analytical tools, provides access to clinical data (e.g., through an electronic health record [EHR][19]) as well as other data sources.[20] A more recent guideline paper[21] underlined the importance of digital pathology interoperability, with a LIS being able to connect all the instruments present in the laboratory to support critical DP use cases. Moreover, increasing requests for molecular and genetic tests on pathology specimens (e.g., next-generation sequencing) impose further innovation on the LIS to integrate and optimize these data with the traditional pathology report for optimal patient management[22] in an integrative model. Finally, the transition will allow information integration from grossing, enable collaborative work, and incorporate quality control results.

Automation of workflow and tracking system

Automation and using a robust tracking system can significantly reduce errors related to handwriting transcription and misspelling that can cause samples to be dissociated from a particular patient (“mismatching”). Automation is a “strong recommendation” emanating from these recommendations, as it can benefit both pathology laboratories using DP and those using glass slides for diagnosis. Besides the introduction of a suitable LIS or LIMS that can help monitor the instruments’ performance connected to each specimen, further automation can be introduced in the lab's workstations. This includes tracking the reagents used and tracking all the staff that were at any point involved in specimen processing by differential log-ins or scanning of individual ID codes at all workstations. Yet the possible automation of workstations obviously depends on budget, existing instruments, and the experience of the technical staff. Devices such as a robotic stainer and a cover-slipper will bring consistent slide quality, avoiding frequent re-staining and ongoing readjustments to scanning protocols. The same is true for the automation of embedding and cutting processes, for which available systems on the market appear promising. However, these are not yet widely used in practice[23], perhaps in part due to cost.

The goals of any tracking system in the laboratory are to keep the specimen automatically, correctly, and permanently labelled during the time that it circulates in the laboratory. The identification of the specimen—using labels on the containers, printed in the cassettes/paraffin blocks, printed on the glass slides and present in the WSI files—is a best practice rule that is recommended to be adopted for the use of the WSI. In this setting, the perfect compatibility (interoperability) of the instrumentation used to label and to process the specimens within the anatomic pathology laboratory, and with the other laboratories in the same institution, is crucial to avoid possible issues (e.g., blurring or shading of the labels during subsequent processing of specimens/slides). The specimen identifiers, of which there are usually several (see the next section), should be managed automatically and electronically connected to the patient’s LIS entry. The integration between the tracking system and LIS with an electronic interface between the LIS and the printers is essential to maintaining continuity of identification. The link established between the asset (tissue container/cassette/block) and the LIS will help reduce errors and can be achieved by printing different data types on the assets, such as barcodes or 2D (QR) codes. These can be linked to different types of data in the LIS. Eventually, other systems with code reader compatibility will be able to read them.[24] The introduction of radiofrequency identification (RFID) technologies is also a promising method to track the assets, although cost and system integration barriers still limit their implementation.[25][26] In the case of pathology laboratories, introducing at least one barcode reader per workstation is recommended. Tracking an individual sample with the combined use of printers and code readers accelerates the work at the microtome stations, helping histotechnologists track each block and slide, ensuring the adequate identification and concordance between the individual block and slide labels.[27]

An LIS typically offers laboratories some capability to customize the format and content of their slide labels. As will be further explained in the subsequent sections of the document, the employment of unequivocal 2D barcodes can have a multitude of applications in the proposed digital workflow, significantly reducing the operations time and error rates. The impact of such implementation can be noted starting from the accessioning phases, where the sample is assigned its unequivocal code that will be used later during the processing and reporting steps. This can further help in the creation of tissue cassettes, in the production of tissue glass slides, in the automatic request of additional histochemical and immunohistochemical (IHC) stains, as well as in the double check that should be carried out at every checkpoint to ensure correspondence among received material, grossed specimen, embedded sample, and cut sections. This is facilitated by the additional use of barcode readers and by the implementation of newly introduced instruments to capture the cut surface directly from the paraffin block[28], which is at this point essential to guarantee a sustainable and reliable quality control process (see the next section).

Quality control program and definition of checkpoints

Quality control of products from a pathology laboratory is essential to guarantee that a patient receives a correct diagnosis. In Europe, the certification and accreditation of laboratories are not equally and uniformly performed across the territory. Instead, many laboratories design their own quality control program, more or less simplified, often involving only segments of sample processing adequate to their intent. Although adopting a quality management system is not strictly required in all countries as a prerequisite for implementing DP workflow, laboratories with a robust system of quality management may find the DP workflow easier to implement as they are already aware of the critical control checkpoints through the analogue workflow. To support those laboratories that are not yet familiar with quality control programs, a detailed description of some suggested checkpoints suitable for adaptation to each laboratory are provided. The checkpoints described here derive from the need to control the performance of a new instrument in the pipeline—the scanner. They also originate from introducing new standard operative procedures (SOPs), tools, instruments, and quality control of the processes (Figure 1).


Fig1 Fraggetta Diagnostics21 11-11.png

Figure 1. Differences among analog and the digital workflows (created with BioRender)


References

  1. ↑ Evans, Andrew J.; Bauer, Thomas W.; Bui, Marilyn M.; Cornish, Toby C.; Duncan, Helena; Glassy, Eric F.; Hipp, Jason; McGee, Robert S. et al. (1 November 2018). "US Food and Drug Administration Approval of Whole Slide Imaging for Primary Diagnosis: A Key Milestone Is Reached and New Questions Are Raised" (in en). Archives of Pathology & Laboratory Medicine 142 (11): 1383–1387. doi:10.5858/arpa.2017-0496-CP. ISSN 0003-9985. http://meridian.allenpress.com/aplm/article/142/11/1383/102979/US-Food-and-Drug-Administration-Approval-of-Whole. 
  2. ↑ Snead, David R. J.; Tsang, Yee-Wah; Meskiri, Aisha; Kimani, Peter K.; Crossman, Richard; Rajpoot, Nasir M.; Blessing, Elaine; Chen, Klaus et al. (2016). "Validation of digital pathology imaging for primary histopathological diagnosis" (in en). Histopathology 68 (7): 1063–1072. doi:10.1111/his.12879. ISSN 1365-2559. https://onlinelibrary.wiley.com/doi/abs/10.1111/his.12879. 
  3. ↑ Goacher, Edward; Randell, Rebecca; Williams, Bethany; Treanor, Darren (1 January 2017). "The Diagnostic Concordance of Whole Slide Imaging and Light Microscopy: A Systematic Review" (in en). Archives of Pathology & Laboratory Medicine 141 (1): 151–161. doi:10.5858/arpa.2016-0025-RA. ISSN 0003-9985. http://meridian.allenpress.com/aplm/article/141/1/151/65950/The-Diagnostic-Concordance-of-Whole-Slide-Imaging. 
  4. ↑ Mukhopadhyay, Sanjay; Feldman, Michael D.; Abels, Esther; Ashfaq, Raheela; Beltaifa, Senda; Cacciabeve, Nicolas G.; Cathro, Helen P.; Cheng, Liang et al. (1 January 2018). "Whole Slide Imaging Versus Microscopy for Primary Diagnosis in Surgical Pathology: A Multicenter Blinded Randomized Noninferiority Study of 1992 Cases (Pivotal Study)" (in en). American Journal of Surgical Pathology 42 (1): 39–52. doi:10.1097/PAS.0000000000000948. ISSN 0147-5185. PMC PMC5737464. PMID 28961557. https://journals.lww.com/00000478-201801000-00006. 
  5. ↑ Evans, Andrew J.; Salama, Mohamed E.; Henricks, Walter H.; Pantanowitz, Liron (1 July 2017). "Implementation of Whole Slide Imaging for Clinical Purposes: Issues to Consider From the Perspective of Early Adopters" (in en). Archives of Pathology & Laboratory Medicine 141 (7): 944–959. doi:10.5858/arpa.2016-0074-OA. ISSN 0003-9985. http://meridian.allenpress.com/aplm/article/141/7/944/65708/Implementation-of-Whole-Slide-Imaging-for-Clinical. 
  6. ↑ 6.0 6.1 6.2 6.3 6.4 6.5 Treanor, D.; Williams, B.; Hussain, B. et al. (July 2018). "The Leeds Guide to Digital Pathology" (PDF). University of Leeds. https://www.virtualpathology.leeds.ac.uk/research/clinical/docs/2018/pdfs/18778_Leeds%20Guide%20to%20Digital%20Pathology_Brochure_A4_final_hi.pdf. Retrieved 10 November 2021. 
  7. ↑ 7.0 7.1 7.2 7.3 7.4 LabPON Laboratorium Pathologie Oost-Nederland (October 2016). "How to Go Digital in Pathology" (PDF). LabPON Laboratorium Pathologie Oost-Nederland. https://www.usa.philips.com/c-dam/b2bhc/us/landing-pages/pdxus/how-to-go-digital-in-pathology.pdf. Retrieved 10 November 2021. 
  8. ↑ Retamero, Juan Antonio; Aneiros-Fernandez, Jose; del Moral, Raimundo G. (1 February 2020). "Complete Digital Pathology for Routine Histopathology Diagnosis in a Multicenter Hospital Network" (in en). Archives of Pathology & Laboratory Medicine 144 (2): 221–228. doi:10.5858/arpa.2018-0541-OA. ISSN 0003-9985. http://meridian.allenpress.com/aplm/article/144/2/221/433661/Complete-Digital-Pathology-for-Routine. 
  9. ↑ Fraggetta, Filippo; Garozzo, Salvatore; Zannoni, GianFranco; Pantanowitz, Liron; Rossi, EstherDiana (2017). "Routine digital pathology workflow: The Catania experience" (in en). Journal of Pathology Informatics 8 (1): 51. doi:10.4103/jpi.jpi_58_17. ISSN 2153-3539. PMC PMC5760840. PMID 29416914. http://www.jpathinformatics.org/text.asp?2017/8/1/51/221132. 
  10. ↑ Fraggetta, Filippo; Caputo, Alessandro; Guglielmino, Rosa; Pellegrino, Maria Giovanna; Runza, Giampaolo; L'Imperio, Vincenzo (16 October 2021). "A Survival Guide for the Rapid Transition to a Fully Digital Workflow: The “Caltagirone Example”" (in en). Diagnostics 11 (10): 1916. doi:10.3390/diagnostics11101916. ISSN 2075-4418. PMC PMC8534326. PMID 34679614. https://www.mdpi.com/2075-4418/11/10/1916. 
  11. ↑ Eloy, Catarina; Vale, João; Curado, Mónica; Polónia, António; Campelos, Sofia; Caramelo, Ana; Sousa, Rui; Sobrinho-Simões, Manuel (15 November 2021). "Digital Pathology Workflow Implementation at IPATIMUP" (in en). Diagnostics 11 (11): 2111. doi:10.3390/diagnostics11112111. ISSN 2075-4418. PMC PMC8620597. PMID 34829458. https://www.mdpi.com/2075-4418/11/11/2111. 
  12. ↑ Sinard, John H.; Castellani, William J.; Wilkerson, Myra L.; Henricks, Walter H. (1 March 2015). "Stand-alone Laboratory Information Systems Versus Laboratory Modules Incorporated in the Electronic Health Record" (in en). Archives of Pathology & Laboratory Medicine 139 (3): 311–318. doi:10.5858/arpa.2013-0711-SO. ISSN 1543-2165. http://meridian.allenpress.com/aplm/article/139/3/311/193668/Standalone-Laboratory-Information-Systems-Versus. 
  13. ↑ Sepulveda, Jorge L.; Young, Donald S. (1 August 2013). "The Ideal Laboratory Information System" (in en). Archives of Pathology & Laboratory Medicine 137 (8): 1129–1140. doi:10.5858/arpa.2012-0362-RA. ISSN 1543-2165. http://meridian.allenpress.com/aplm/article/137/8/1129/65418/The-Ideal-Laboratory-Information-System. 
  14. ↑ Asa, SylviaL; Bodén, AnnaC; Treanor, Darren; Jarkman, Sofia; Lundström, Claes; Pantanowitz, Liron (2019). "2020 vision of digital pathology in action" (in en). Journal of Pathology Informatics 10 (1): 27. doi:10.4103/jpi.jpi_31_19. ISSN 2153-3539. PMC PMC6704755. PMID 31516758. http://www.jpathinformatics.org/text.asp?2019/10/1/27/264400. 
  15. ↑ Lujan, Giovanni; Quigley, JenniferC; Hartman, Douglas; Parwani, Anil; Roehmholdt, Brian; Meter, BryanVan; Ardon, Orly; Hanna, MatthewG et al. (2021). "Dissecting the business case for adoption and implementation of digital pathology: A white paper from the digital pathology association" (in en). Journal of Pathology Informatics 12 (1): 17. doi:10.4103/jpi.jpi_67_20. ISSN 2153-3539. PMC PMC8240548. PMID 34221633. http://www.jpathinformatics.org/text.asp?2021/12/1/17/313004. 
  16. ↑ Hanna, Matthew G.; Reuter, Victor E.; Ardon, Orly; Kim, David; Sirintrapun, Sahussapont Joseph; Schüffler, Peter J.; Busam, Klaus J.; Sauter, Jennifer L. et al. (1 November 2020). "Validation of a digital pathology system including remote review during the COVID-19 pandemic" (in en). Modern Pathology 33 (11): 2115–2127. doi:10.1038/s41379-020-0601-5. ISSN 0893-3952. PMC PMC7306935. PMID 32572154. http://www.nature.com/articles/s41379-020-0601-5. 
  17. ↑ Zarbo, Richard J. (1 September 2012). "Creating and Sustaining a Lean Culture of Continuous Process Improvement" (in en). American Journal of Clinical Pathology 138 (3): 321–326. doi:10.1309/AJCP2QY1XGKTSNQF. ISSN 0002-9173. https://academic.oup.com/ajcp/article-lookup/doi/10.1309/AJCP2QY1XGKTSNQF. 
  18. ↑ Tuthill, JMark; Friedman, BruceA; Splitz, Andrew; Balis, UlyssesJ (2014). "The laboratory information system functionality assessment tool: Ensuring optimal software support for your laboratory" (in en). Journal of Pathology Informatics 5 (1): 7. doi:10.4103/2153-3539.127819. ISSN 2153-3539. PMC PMC3986538. PMID 24741466. http://www.jpathinformatics.org/text.asp?2014/5/1/7/127819. 
  19. ↑ Petrides, Athena K.; Bixho, Ida; Goonan, Ellen M.; Bates, David W.; Shaykevich, Shimon; Lipsitz, Stuart R.; Landman, Adam B.; Tanasijevic, Milenko J. et al. (1 March 2017). "The Benefits and Challenges of an Interfaced Electronic Health Record and Laboratory Information System: Effects on Laboratory Processes" (in en). Archives of Pathology & Laboratory Medicine 141 (3): 410–417. doi:10.5858/arpa.2016-0146-OA. ISSN 0003-9985. http://meridian.allenpress.com/aplm/article/141/3/410/65705/The-Benefits-and-Challenges-of-an-Interfaced. 
  20. ↑ Krupinski, ElizabethA (2010). "Optimizing the pathology workstation "cockpit": Challenges and solutions" (in en). Journal of Pathology Informatics 1 (1): 19. doi:10.4103/2153-3539.70708. ISSN 2153-3539. PMC PMC2956171. PMID 21031008. http://www.jpathinformatics.org/text.asp?2010/1/1/19/70708. 
  21. ↑ Dash, RajeshC; Jones, Nicholas; Merrick, Riki; Haroske, Gunter; Harrison, James; Sayers, Craig; Haarselhorst, Nick; Wintell, Mikael et al. (2021). "Integrating the health-care enterprise pathology and laboratory medicine guideline for digital pathology interoperability" (in en). Journal of Pathology Informatics 12 (1): 16. doi:10.4103/jpi.jpi_98_20. ISSN 2153-3539. PMC PMC8240547. PMID 34221632. http://www.jpathinformatics.org/text.asp?2021/12/1/16/311870. 
  22. ↑ Roy, Somak; Pfeifer, John D.; LaFramboise, William A.; Pantanowitz, Liron (1 September 2016). "Molecular digital pathology: progress and potential of exchanging molecular data" (in en). Expert Review of Molecular Diagnostics 16 (9): 941–947. doi:10.1080/14737159.2016.1206472. ISSN 1473-7159. https://www.tandfonline.com/doi/full/10.1080/14737159.2016.1206472. 
  23. ↑ Phelan, Sine M (2014). "Impact of the introduction of a novel automated embedding system on quality in a university hospital histopathology department" (in en). Journal of Histology and Histopathology 1 (1): 3. doi:10.7243/2055-091X-1-3. ISSN 2055-091X. http://www.hoajonline.com/histology/2055-091X/1/3. 
  24. ↑ Hanna, Matthew G.; Pantanowitz, Liron (1 March 2016). "Bar Coding and Tracking in Pathology". Clinics in Laboratory Medicine 36 (1): 13–30. doi:10.1016/j.cll.2015.09.003. ISSN 1557-9832. PMID 26851661. https://pubmed.ncbi.nlm.nih.gov/26851661. 
  25. ↑ Bostwick, David G. (1 October 2013). "Radiofrequency identification specimen tracking in anatomical pathology: pilot study of 1067 consecutive prostate biopsies". Annals of Diagnostic Pathology 17 (5): 391–402. doi:10.1016/j.anndiagpath.2013.04.007. ISSN 1532-8198. PMID 23796559. https://pubmed.ncbi.nlm.nih.gov/23796559. 
  26. ↑ Lou, Jerry J.; Andrechak, Gary; Riben, Michael; Yong, William H. (2011). "A review of radio frequency identification technology for the anatomic pathology or biorepository laboratory: Much promise, some progress, and more work needed". Journal of Pathology Informatics 2: 34. doi:10.4103/2153-3539.83738. ISSN 2153-3539. PMC 3162748. PMID 21886890. https://pubmed.ncbi.nlm.nih.gov/21886890. 
  27. ↑ Snyder, Susan R.; Favoretto, Alessandra M.; Derzon, James H.; Christenson, Robert H.; Kahn, Stephen E.; Shaw, Colleen S.; Baetz, Rich Ann; Mass, Diana et al. (1 September 2012). "Effectiveness of barcoding for reducing patient specimen and laboratory testing identification errors: A Laboratory Medicine Best Practices systematic review and meta-analysis" (in en). Clinical Biochemistry 45 (13-14): 988–998. doi:10.1016/j.clinbiochem.2012.06.019. PMC PMC4518452. PMID 22750145. https://linkinghub.elsevier.com/retrieve/pii/S0009912012003232. 
  28. ↑ L'Imperio, Vincenzo; Gibilisco, Fabio; Fraggetta, Filippo (2021). "What is Essential is (No More) Invisible to the Eyes: The Introduction of BlocDoc in the Digital Pathology Workflow". Journal of Pathology Informatics 12: 32. doi:10.4103/jpi.jpi_35_21. ISSN 2229-5089. PMC 8529340. PMID 34760329. https://pubmed.ncbi.nlm.nih.gov/34760329. 

Notes

This presentation is faithful to the original, with only a few minor changes to presentation, spelling, and grammar. In some cases important information was missing from the references, and that information was added.

Retrieved from "https://www.limswiki.org/index.php?title=Journal:Best_practice_recommendations_for_the_implementation_of_a_digital_pathology_workflow_in_the_anatomic_pathology_laboratory_by_the_European_Society_of_Digital_and_Integrative_Pathology_(ESDIP)&oldid=45185"