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Broad feature set of a pathology information management solution

A pathology information management solution (PIMS) ...


  • automated reflex testing: Some PIMS vendors include pre-loaded, customizable lists of reflex tests associated with certain pathology procedures and their associated diagnoses. Optimally, these reflex texts are automatically suggested at specimen reception, based on specimen and/or pathology test type.[1][2] Examples of pathology-driven reflex testing in use today include testing for additional biomarkers for non-small-cell lung carcinoma (NSCLC) adenocarcinoma[3], HPV testing in addition to cervical cytology examination[4][5] (discussed further in "adjunctive testing"), and additional automatic testing based off routine coagulation assays at hemostasis labs.[6]
  • adjunctive testing: Adjunctive testing is testing "that provides information that adds to or helps interpret the results of other tests, and provides information useful for risk assessment."[7] A common adjunctive test performed in cytopathology is HPV testing.[4][5] The FDA described this as such in 2003, specifically in regards to expanding the use of the Digene HC2 assay as an adjunct to cytology[4]:

In women 30 years and older, the HC2 High-Risk HPV DNA test can be used with Pap to adjunctively screen to assess the presence or absence of high-risk HPV types. This information, together with the physician’s assessment of cytology history, other risk factors, and professional guidelines, may be used to guide patient management.

Some PIMS vendors allow users to manually add an adjunctive test to a primary pathology test, or in some cases this may be enabled as part of an automated reflex testing process.[8] However, ensure that any such solution is capable of feeding any adjunctive test results into the final report (see the subsection on this topic).
  • demand management: Similar to test optimization or clinical decision support, demand management mechanisms help laboratories reduce the amount of unnecessary and duplicate testing they perform. The idea of using demand management to reduce unnecessary pathology testing has been around since at least the beginning of the twenty-first century, if not well before, in the form of decision support systems and order request menus of informatics systems.[9] Lang described what the process of demand management would look like in a system like a laboratory information management system (LIMS) in 2013[10]:

When implementing a demand management tool it is important that the system used to manage a laboratory workload can correctly identify the patient and match requests with the patient’s medical record. Ideally there should be one unique identifier used (e.g., NHS number in the UK), which will allow the LIMS to interrogate the patient’s previous pathology result to allow identification of duplicate or inappropriate requests. If a subsequent request is blocked, then it is also important that there is real-time notification of a potential redundant test so that the requestor can make an informed choice on the clinical need of the test and if it is required to override the rule. It is important that there is a facility whereby the laboratory or requestor can record the reason for blocking a request or overriding the rule.

Today, some PIMS are designed to allow configurable rules and parameters to check for duplicate and unnecessary tests at various levels (e.g., by test ID or catalog type, activity type, or some other order level).[11][12]
  • consent management: In clinical medicine, patients typically must sign a form indicating informed consent to medical treatment.[13] Biobanking facilities, which store biospecimens, also must collect consent forms regarding how a patient's biospecimens may be used.[14] In all cases, these consent documents drive how and when certain actions take place. Though not common, some LIMS like LabVantage Pathology by Software Point[15] provide consent management mechanisms within their PIMS, giving pathologists the ability to quickly verify consent details electronically. In biobanking solutions, this consent management process may be more rigorous to ensure biospecimen donors' preferences and regulatory requirements are being carefully followed. For example, the system may need to be able to prevent further use of a biospecimen and trigger sample and data deletion protocols when a donor withraws their consent to use.[16]
  • case management and review: Most PIMS provide a means for managing pathology cases, recorded instances of disease and its attendant circumstances.[17] This includes the management of case history, a collection of data concerning an individual, their family, their environment, their medical history, and other other information valuable for analyzing, diagnosing, reviewing, or otherwise instructing others on the case.[18] Having an information system to better manage data entry, data analysis, case tracking, and case storage may aid in secondary and internal case reviews before final report, which have been shown to improve diagnostic accuracies and overall experiential knowledge of pathologists.[19] Aspects of case manamagement and review that a PIMS may handle include automatic case creation, automatic and priority case assignment, and automatic case tracking, as well as limit case acces based on user permissions, and send alerts for clinical history follow-ups and other case statuses.[20][21][22] Note that a handful of vendors such as Leica Biosystems provide stand-alone case management solutions that can be integrated with instruments and other LIS systems.[22]
  • workflow management: The tools for workflow management have become increasingly common in PIMS and other laboratory informatics applications over the years, with the idea of using automation to improves efficiencies and accuracies in the lab. However, workflows and protocols can differ—sometimes significantly—from one pathology lab to another. Being able to configure workflow pathways in the PIMS to be compliant with required testing protocols is vital. This is especially important with the gradual transition to more digital pathology methods, where digitally sharing cases and automatically scanned slide images has great value.[23] As such, vendors such as Orchard Software and XIFIN provide solutions with configurable workflows to help labs translate their workflows into the system.[24][25]
  • speech recognition and transcription management: Like other medical fields, pathologists may utilize dictation and transcription services within their workflow. This has traditionally involved the pathologist speaking while a transcriptionist manually records the words to paper, or the pathologist scribbling notes in shorthand, with the transcriptionist "translating" the notes to usable clinical documentation. This could include anything from specimen descriptions and diagnoses to pathology obsevations and procedure notes. PIMS vendors have over the years added more automated methods to such tasks in their solutions, however, such as speech recognition modules and transcription management tools that, for example, automatically assign recordings to a transcriber's pending work list.[1][15][26][21]
It's important to note, however, though PIMS vendors may market the speech recognition component of their solution at being 99 percent effective, past studies have shown 88.9 to 96 percent accuracy, though with tiny annual gains as the technology matures.[27][28] If speech recognition is being used in lieu of a hired transcriptionist, it's especially vital to add manual editing and review before reporting.[28][29]
  • storage and tissue bank management: Biorepositories and pathology laboratories go hand-in-hand. A significant example can be found with the relationship medical school biorepositories have with their pathology labs and departments, as with, for example, Duke University[30], University of Illinois Chicago[31], and the Icahn School of Medicine at Mount Sinai.[32] However, even small pathology laboratories must also responsibly store and track their specimens, blocks, and slides, as well as the storage variables affecting them. Any reputable laboratory informatics solution will be able to track the location of such items through barcode or RFID support, as well as allowing for the creation of named storage locations in the system. However, some informatics solutions like AgileBio's LabCollector go a step further, providing data logging modules that are capable of connecting to data logger hardware and other sensors that capture environmental storage information such as temperature, humidity, light level, carbon dioxide level, and pressure. When a variable is out of range, an alert can be sent and logged.[33] And full-fledged biorepository management LIMS may have all the bells and whistles, including randomized biospecimen location auditing.[34]
  • task management: Task management is a typical feature of a laboratory informatics solution, giving laboratorians the ability to assign tasks to individuals or groups of individuals, including analyses, results review, and more. In pathology labs, additional task and even management may include, for example, case assignment, slide or block assignment, grossing, staining, or some other pathology task. Additionally, some may incorporate this task management and tracking into a dashboard, to facility timely access to short-term status individual cases and specimens, and long-term aggregate data about cases, workflow, and workloads.[35]
  • billing management with code support: Instead of turning to a separate billing solution, pathology labs can often turn to PIMS for billing management. Vendors of LIS and LIMS have recognized not only the value of adding billing management to their solutions but also the many benefits that come with tying in diagnosis and billing code support. For example, a pathologist scanning a specimen into the system can not only have a case automatically generated but also auto-generate diagnosis codes based on the specimen or slide's code. Additionally, as has been witnessed during the COVID-19 pandemic, billing rules may change rapidly during extraordinary events, requiring rapid used-defined billing rule changes.[36] As such, support for CPT, ICD-10, SNOMED CT, and other types of autocoding are somewhat common in today's PIMS.[1][20][21][26]
  • reflex and adjunctive test reporting: Ensure that a PIMS is capable of feeding any adjunctive test results into the final report, along with the results from the primary tests. Using adjunctive HPV test results as an example, the report should optimally include details such as assay name, manufacturer, the HPV types it covers, results, and any applicable educational notes and suggestions.[5] Be careful with simple color-coding of results for interpretation, as they can be easily misinterpreted, including by the colorblind. A combination of symbol with color will help limit such misinterpretation.[3]
  • structured data entry: The concept of structured data entry (SDE) is relatively simple, but it may still get taken for granted. At its core, SDE is all about ensuring that entered data is based on a set of predefined conditions or rules, usually implemented through standardized forms with pre-determined drop-down and auto-populated fields.[37] This typically confers numerous advantages, including easier data entry, easier and more standardized reporting, decrease costs, improve translational research, and ensure better compatibility and integration across different information systems.[37][38] As such, some PIMS vendors like NovoPath and Orchard Software describe their solutions as having SDE elements such as enabling intelligent auto-loading of diagnosis and billing codes during case loading, allowing input fields to be required, and synoptic reporting support.[39][24]
  • synoptic reporting: Synoptic reporting involves a structured, pre-formatted "checklist" of clinically and morphologically relevant data elements that help make pathology reporting more efficient, uniform, and relevant to internal and external stakeholders. Another way to put this is that synoptic reporting is SDE applied to the pathology report, often based upon specific reporting protocols by professional or standards organizations like the College of American Pathologists (CAP).[20][39] Support for synoptic reporting methods is typical within PIMS solutions, including support for configurable templates that can be adapted to changing and custom reporting protocols.
  • correlative and consultive reporting: In the late 1930s, the concept of correlating pathology results with clinical observations (and pathology) was beginning to be addressed in student textbooks.[40] Today, the concept remains integral in medical practice and toxicologic study reporting.[41][42][43] On the clinical side, a pathologist may include the phrase "clinical correlation is recommended" and additional comments. And in some cases, a third-party pathology consultation, with their own respective comments, is involved with specimen analysis.[44] These correlative and consultive comments or reports play an important part in the overall final pathology report and should not be omitted, particularly if differing opinions are involved. Vendors such as Orchard Software, LigoLab, and Aspyra tout their solutions' ability to tie together multiple reports and comments across pathology disciplines and consultants into one concise report.[24][20][26]
  • CAP Cancer Reporting Protocol support: Previously mentioned was CAP and its reporting protocols. In particular, CAP has its Cancer Reporting Protocols, which the CAP describe as providing "guidelines for collecting the essential data elements for complete reporting of malignant tumors and optimal patient care."[45] In conjunction with its electronic Cancer Checklists (eCCs)[46], pathologists are able to integrate CAP cancer reporting protocols of tumors, resections, and select biopsies into their PIMS' workflow and ensure proper reporting outcomes. Some PIMS vendors (e.g., Orchard Software, LigoLab[24][20]) explicitly indicate their solution integrates CAP's eCC templates and reporting protocols into their solution.
  • annotated organ mapping: In the world of PIMS, organ mapping refers to the concept of placing location-specific diagnostic information from specimen analyses into an anatomical diagram, typically during reporting, to more clearly communicate the results of those analyses. PIMS vendor WebPathLab, Inc. demonstrates this concept well with its Auto Organ Map Module, which not only shows an organ map in the rport but also simplifies data entry for the pathologist using SDE.[47][48] They use the prostate as an example, and explain that "selecting the predetermined number of quadrants in the prostate [diagram], the system autopopulates the specimen description to each corresponding quadrant, and autofills the text for the Gross Description field, leaving only the dimension of each core to be entered by the grosser." NovoPath and Psyche Systems Corporation are additional examples of vendors incorporating organ mapping into their PIMS.[2][39]
  • stain panel and unstained/control slide support: A positive control slide is typically used to qualitatively assess how well a non-hematoxylin-eosin (non-H&E) or "special" stain performs against a gold standard like H&E, and the positive control is usually included with manufactured unstained slides (e.g., see Newcomer Supply's control slide catalog). These slides may be used in histopathology (gauging the manifestation of disease in a tissue) and immunopathology (gauging immune response through visualization of an antibody-antigen interaction in a tissue). In particular, immunopathology and its associated immunohistochemistry may turn to special stain panels, which utilize multiple immunochemical stains to visualize the presence of more than one biomarker expression at the same time.[49][50][51] Vendors like NovoPath and Integrated Business Solutions Group explicitly state their solution supports the management of these types of slides and stain panels.[39][52]
  • grossing support: In medical terms, the adjective "gross" means "visible without the aid of a microscope."[53] By extension, gross examination (i.e., grossing) involves a macroscopic visual assessment of a biospecimen before preparation for microscopy, in order to gleen diagnostic information. Grossing remains a valuable skill used in modern pathology.[54][55] Some PIMS provide a grossing menu for pathologists to scan in and include commentary about a gross examination of a specimen.[20]
  • high-risk patient follow-up: A 2015 study published in Annals of Family Medicine showed evidence that "patients with high clinical complexity and high risk of readmission" benefited from early outpatient follow-up.[56][57] The authors concluded : "Follow-up within seven days was associated with meaningful reductions in readmission risk for patients with multiple chronic conditions and a greater than 20% baseline risk of readmission, a group that represented 24% of discharged patients." Presumably some health care systems are synthesizing that information into their patient workflows, likely through some sort of scheduled event and alert in their primary informatics system, e.g., an electronic health record (EHR) system.[58] Though not common, at least one PIMS vendor—LigoLab, LLC—indicates their solution helps address high-risk patient follow-up, though it's not clear how.[20]
  • research animal support: Non-clinical pathology and toxicology laboratories assisting with research and evaluation studies may be handling non-human specimens or even live research animals. Additional data about these animals, animal groups, and animal tissues may need to be carefully documented as part of a study. As such, some solutions such as Instem's Provantis preclinical pathology solution are designed to record specific animal and group identifiers, animal cross-reference information, organ weight ratios, palpable mass diagnoses, and other attributes for reporting.[59]


References

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  2. ↑ 2.0 2.1 "WindoPath Ē.ssential". Psychē Systems Corporation. https://psychesystems.com/enterprise-laboratory-information-software/windopath/. Retrieved 05 September 2020. 
  3. ↑ 3.0 3.1 Sundin, T. (2019). "Pathology-Driven Reflex Testing of Biomarkers". Medical Lab Management 8 (11): 6. https://www.medlabmag.com/article/1619. 
  4. ↑ 4.0 4.1 4.2 U.S. Food and Drug Administration (8 March 2019). "New Approaches in the Evaluation for High-Risk Human Papillomavirus Nucleic Acid Detection Devices". U.S. Food and Drug Administration. https://www.fda.gov/media/122799/download. Retrieved 05 September 2020. 
  5. ↑ 5.0 5.1 5.2 Stoler, M.H.; Raab, S.S.; Wilbur, D.C. (2015). "Chapter 9: Adjunctive Testing". In Nayar, R.; Wilbur, D.. The Bethesda System for Reporting Cervical Cytology. Springer. pp. 287–94. doi:10.1007/978-3-319-11074-5_9. ISBN 9783319110745. 
  6. ↑ Mohammed, S.; Priebbenow, V.U.; Pasalic, L. et al. (2019). "Development and implementation of an expert rule set for automated reflex testing and validation of routine coagulation tests in a large pathology network". International Journal of Laboratory Hematology 41 (5): 642–49. doi:10.1111/ijlh.13078. PMID 31271498. 
  7. ↑ "adjunct test". Segen's Medical Dictionary. 2011. https://medical-dictionary.thefreedictionary.com/adjunct+test. Retrieved 05 September 2020. 
  8. ↑ "TD HistoCyto Livextens". Technidata SAS. https://www.technidata-web.com/solutions-services/disciplines/anatomic-pathology. Retrieved 05 September 2020. 
  9. ↑ Rao, G.G.; Crook, M.; Tillyer, M.L. (2003). "Pathology tests: is the time for demand management ripe at last?". Journal of Clinical Pathology 56 (4): 243–48. doi:10.1136/jcp.56.4.243. PMC PMC1769923. PMID 12663633. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1769923. 
  10. ↑ Lang, T. (2013). "Laboratory demand management of repetitive testing – time for harmonisation and an evidenced based approach". Clinical Chemistry and Laboratory Medicine 51 (6): 1139–40. doi:10.1515/cclm-2013-0063. PMID 23420284. 
  11. ↑ Morris, T.F.; Ellison, T.L.; Mutabbagani, M. et al. (2018). "Demand management and optimization of clinical laboratory services in a tertiary referral center in Saudi Arabia". Annals of Saudi Medicine 38 (4): 299–304. doi:10.5144/0256-4947.2018.299. PMC PMC6086671. PMID 30078029. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6086671. 
  12. ↑ "DXC Laboratory Information Management (LIMS)". DXC Technology Services, LLC. https://www.dxc.technology/healthcare/offerings/139499/139776-dxc_laboratory_information_management_lims. Retrieved 05 September 2020. 
  13. ↑ "Informed Consent". Code of Medical Ethics. American Medical Association. https://www.ama-assn.org/delivering-care/ethics/informed-consent. Retrieved 22 September 2020. 
  14. ↑ Avery, D. (16 July 2018). "Biobanking Consent: Informing Human Subjects of the Possibilities". Biobanking.com. https://www.biobanking.com/biobanking-consent-informing-human-subjects-of-the-possibilities/. Retrieved 22 September 2020. 
  15. ↑ 15.0 15.1 "LabVantage Pathology". Software Point Oy. https://softwarepoint.com/solutions/product/labvantage-pathology. Retrieved 22 September 2020. 
  16. ↑ SANBI; Bika Lab Systems (20 November 2015). "NCB-H3A Cape Town Biobank Management System - Functional Requirements Overview & Phase I Objectives" (PDF). Bika Lab Systems. https://www.bikalims.org/downloads/bika-open-source-biobank-management-system/at_download/file. Retrieved 22 September 2020. 
  17. ↑ "case". Farlex Partner Medical Dictionary. 2012. https://medical-dictionary.thefreedictionary.com/case. Retrieved 25 September 2020. 
  18. ↑ "case". Miller-Keane Encyclopedia and Dictionary of Medicine, Nursing, and Allied Health, Seventh Edition. 2003. https://medical-dictionary.thefreedictionary.com/case. Retrieved 25 September 2020. 
  19. ↑ Huck, A.; Nosé, V. (2015). "Chapter 7: Knowledge, Training, and Experience". In Nakhleh, R.E.. Error Reduction and Prevention in Surgical Pathology. Springer. pp. 103–114. ISBN 9781493923397. https://books.google.com/books?id=HXAKBwAAQBAJ&pg=PA103. 
  20. ↑ 20.0 20.1 20.2 20.3 20.4 20.5 20.6 "Anatomic Pathology Solutions". LigoLab, LLC. https://www.ligolab.com/solutions/anatomic-pathology-solution. Retrieved 23 September 2020. 
  21. ↑ 21.0 21.1 21.2 "PathX Laboratory Information System" (PDF). Physicians Independent Management Services. http://pathxlis.com/downloads/PDFs/PathX%20-%20Capabilities%20Brochure.pdf. Retrieved 25 September 2020. 
  22. ↑ 22.0 22.1 "Aperio Path DX - Case Management Software". Leica Biosystems Nussloch GmbH. https://www.leicabiosystems.com/digital-pathology/manage/aperio-path-dx/. Retrieved 25 September 2020. 
  23. ↑ "Is Your Lab Ready for an AI Digital Pathology Workflow?". XIFIN, Inc. 3 January 2020. https://www.xifin.com/resources/blog/201912/your-lab-ready-ai-digital-pathology-workflow. Retrieved 25 September 2020. 
  24. ↑ 24.0 24.1 24.2 24.3 "Orchard Pathology". Orchard Software Corporation. https://www.orchardsoft.com/orchard-pathology.html. Retrieved 22 September 2020. 
  25. ↑ "Laboratory Information System". XIFIN, Inc. https://www.xifin.com/products/laboratory-information-system. Retrieved 25 September 2020. 
  26. ↑ 26.0 26.1 26.2 "Anatomic Pathology". Aspyra, LLC. http://aspyra.com/anatomic-pathology/. Retrieved 23 September 2020. 
  27. ↑ Hodgson, T.; Coiera, E. (2016). "Risks and benefits of speech recognition for clinical documentation: A systematic review". JAMIA 23 (e1): e169–79. doi:10.1093/jamia/ocv152. PMC PMC4954615. PMID 26578226. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4954615. 
  28. ↑ 28.0 28.1 Zhou, L.; Blackley, S.V.; Kowalski, L. et al. (2018). "Analysis of Errors in Dictated Clinical Documents Assisted by Speech Recognition Software and Professional Transcriptionists". JAMA Network Open 1 (3): e180530. doi:10.1001/jamanetworkopen.2018.0530. PMC PMC6203313. PMID 30370424. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6203313. 
  29. ↑ Matthews, K. (20 December 2019). "Why Medical Dictation Is Still Better Than Voice Recognition ... For Now". Health IT Outcomes. https://www.healthitoutcomes.com/doc/why-medical-dictation-is-still-better-than-voice-recognition-for-now-0001. Retrieved 25 September 2020. 
  30. ↑ "Biorepository & Precision Pathology Center". Duke University School of Medicine. https://pathology.duke.edu/core-facilities-services/biorepository-precision-pathology-center. Retrieved 22 September 2020. 
  31. ↑ "UI Health Biorepository". University of Illinois Chicago. https://rrc.uic.edu/cores/rsd/biorepository/. Retrieved 22 September 2020. 
  32. ↑ "Biorepository and Pathology". Icahn School of Medicine at Mount Sinai. https://icahn.mssm.edu/research/portal/resources/deans-cores/biorepository-and-pathology. Retrieved 22 September 2020. 
  33. ↑ "Data Logger". AgileBio. https://www.labcollector.com/labcollector-lims/add-ons/data-logger/. Retrieved 22 September 2020. 
  34. ↑ "Biobank Management LIMS". Autoscribe Informatics, Inc. 22 September 2020. https://www.autoscribeinformatics.com/industries/biobank-management-systems. 
  35. ↑ Halwani, F.; Li, W.C.; Banerjee, D. et al. (2016). "A real-time dashboard for managing pathology processes". Journal of Pathology Informatics 7: 24. doi:10.4103/2153-3539.181768. PMC PMC4872478. PMID 27217974. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4872478. 
  36. ↑ Ferrante, T.B.; Goodman, R.B.; Wein, E.H. (3 April 2020). "COVID-19: CMS Issues Monumental Changes to Medicare Telehealth: What You Need to Know". Insights, a Foley & Lardner LLP Blog. https://www.foley.com/en/insights/publications/2020/04/covid19-cms-monumental-changes-medicare-telehealth. Retrieved 25 September 2020. 
  37. ↑ 37.0 37.1 Public Health Informatics Institute. "Analyzing Clinical Data and Workflows - 4. Understanding Clinical Data and Workflow" (DOCX). EHR Toolkit. https://www.phii.org/sites/default/files/resource/files/Understanding%20Clinical%20Data%20and%20Workflow%20Guide.docx. Retrieved 22 September 2020. 
  38. ↑ "Using structured data entry systems in the electronic medical record to collect clinical data for quality and research: Can we efficiently serve multiple needs for complex patients with spina bifida?". Journal of Pediatric Rehabilitative Medicine 11 (4): 303–09. 2018. doi:10.3233/PRM-170525. PMC PMC6491202. PMID 30507591. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6491202. 
  39. ↑ 39.0 39.1 39.2 39.3 "NovoPath - Software Advancing Patient Diagnostics" (PDF). NovoPath, Inc. 2013. https://www.novopath.com/content/pdf/novopathbrochure.pdf. Retrieved 22 September 2020. 
  40. ↑ "Textbook of Pathology. A Correlation of Clinical Observations and Pathological Findings". JAMA 114 (2): 184. 1940. doi:10.1001/jama.1940.02810020088032. 
  41. ↑ Smith, S.M.; Yearsley, M. (2016). "Constructing Comments in a Pathology Report: Advice for the Pathology Resident". Archives of Pathology & Laboratory Medicine 140 (10): 1023–24. doi:10.5858/arpa.2016-0220-ED. PMID 27684971. 
  42. ↑ Ramaiah, L.; Hinrichs, M.J.; Skuba, E.V. et al. (2017). "Interpreting and Integrating Clinical and Anatomic Pathology Results: Pulling It All Together". Toxicologic Pathology 45 (1): 223–37. doi:10.1177/0192623316677068. PMID 27879439. 
  43. ↑ Aulbach, A.; Vitsky, A.; Arndt, T. et al. (2019). "Overview and considerations for the reporting of clinical pathology interpretations in nonclinical toxicology studies". Veterinary Clinical Pathology 48 (3): 389–99. doi:10.1111/vcp.12772. PMID 31556157. 
  44. ↑ Kaplan, K. (19 June 2014). "What is a Pathology Consultation? When is it Used?". Corista Digital Pathology Blog. https://blog.corista.com/corista-digital-pathology-blog/bid/389513/What-is-a-Pathology-Consultation-When-is-it-Used. Retrieved 23 September 2020. 
  45. ↑ "Cancer Protocol Templates". College of American Pathologists. April 2020. https://www.cap.org/protocols-and-guidelines/cancer-reporting-tools/cancer-protocol-templates. Retrieved 23 September 2020. 
  46. ↑ "CAP eCC". College of American Pathologists. https://www.cap.org/laboratory-improvement/proficiency-testing/cap-ecc. Retrieved 23 September 2020. 
  47. ↑ WebPathLab, Inc (22 April 2019). "AutoProstateMap". YouTube. https://www.youtube.com/watch?v=NLr5_pLgYpg. Retrieved 23 September 2020. 
  48. ↑ "GU Auto Organ Map Module". WebPathLab, Inc. http://webpathlab.com/solutions/gu-auto-organ-map/. Retrieved 23 September 2020. 
  49. ↑ Shield, P.W.; Perkins, G.; Wright, R.G. (1996). "Immunocytochemical staining of cytologic specimens. How helpful is it?". American Journal of Clinical Pathology 105 (2): 157–62. doi:10.1093/ajcp/105.2.157. PMID 8607438. 
  50. ↑ Martin, B.A.; Kerner, J.A.; Hazard, F.K. et al. (2014). "Evaluation of intestinal biopsies for pediatric enteropathy: A proposed immunohistochemical panel approach". American Journal of Surgical Pathology 38 (10): 1387–95. doi:10.1097/PAS.0000000000000314. PMID 25188866. 
  51. ↑ Torbenson, M.S. (24 November 2019). "Chapter 4. Immunohistochemistry and Special Stains in Liver Pathology". Abdominalkey. https://abdominalkey.com/immunohistochemistry-and-special-stains-in-liver-pathology/. Retrieved 23 September 2020. 
  52. ↑ "LABLION Software Suite". Integrated Business Solutions Group, LLC. https://www.lablion.com/lablion-lis-laboratory-information-system. Retrieved 23 September 2020. 
  53. ↑ "Gross". Merriam-Webster.com Dictionary. Merriam-Webster. https://www.merriam-webster.com/dictionary/gross. Retrieved 23 September 2020. 
  54. ↑ Ruthushree, T.; Harsha, M.; Amberkar, V.S. (2018). "Grossing of tissue specimens in oral pathology - Elemental guidelines". International Journal of Oral Health Sciences 8 (2): 63–7. doi:10.4103/ijohs.ijohs_32_18. 
  55. ↑ Schubert, M.; Nashm C; McCoy, J. (26 November 2019). "The Art of Grossing: Gross examination underpins all diagnoses based on tissue samples – but is this vital skill given the credit it deserves?". The Pathologist. https://thepathologist.com/inside-the-lab/the-art-of-grossing. Retrieved 23 September 2020. 
  56. ↑ Joszt, L. (20 April 2015). "High-Risk Patients Benefit Significantly From Early Follow-up Post Hospital Discharge". The American Journal of Managed Care. https://www.ajmc.com/view/high-risk-patients-benefit-significantly-from-early-follow-up-post-hospital-discharge. Retrieved 23 September 2020. 
  57. ↑ Jackson, C.; Shahsahebi, M.; Wedlake, T. et al. (2015). "Timeliness of Outpatient Follow-up: An Evidence-Based Approach for Planning After Hospital Discharge". Annals of Family Medicine 13 (2): 115–22. doi:10.1370/afm.1753. 
  58. ↑ Futrell, K. (18 April 2018). "Health information technology can support population health management". Medical Laboratory Observer. https://www.mlo-online.com/information-technology/lis/article/13009479/health-information-technology-can-support-population-health-management. Retrieved 23 September 2020. 
  59. ↑ "Provantis: Integrated preclinical software". Instem LSS Limited. https://www.instem.com/solutions/provantis/index.php#2. Retrieved 23 September 2020. 
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