Clinical Informatics Resources

In the age of increasingly complex laboratory information systems, electronic health records, big data, personalized health care, and artificial intelligence, pathologists hold a unique position in patient care. Information produced by pathologists is communicated primarily through healthcare information systems, is among the most reliable data in those systems, and is critical for clinical decision-making. Through clinical informatics‚ the application of information management to health care‚ pathologists ensure that the output of the laboratory is timely, accurate, and informative, and that laboratory data promotes safe, efficient, effective, personalized, and responsive care. When properly applied, clinical informatics can benefit individuals, institutions, communities, and whole populations.

Clinical Informatics and Pathology

Clinical informatics as applied to pathology is often called “Pathology Informatics.” Exciting developments in pathology informatics have occurred in recent years that are likely to transform the field. These advances include digital imaging in pathology, application of artificial intelligence and machine learning tools in anatomic pathology and laboratory testing, improvements in the interoperability of laboratory results through development of data standards, and cohort/population analytics that improve the understanding of disease and healthcare operations.

Pathologists who are familiar with clinical informatics have access to powerful tools for health data aggregation, analysis, and interpretation. Effective use of these tools can optimize pathology laboratory processes and clarify interpretation of diagnostic testing, adding value for patients, clinicians, and healthcare organizations. Training in pathology and clinical informatics is available through residency programs that emphasize this domain, and clinical informatics fellowships that emphasize pathology are available.

In response to these advancements and to support pathology informatics innovation, the CAP created the Council on Pathology Informatics and Innovation (CIPI) with committees focused on domains within informatics that are critical to pathology:

• Informatics Committee
• Artificial Intelligence Committee
• Digital and Computational Pathology Committee (DCPC)
• Pathology Electronic Reporting Committee (PERT)
• Cancer Committee

These committees provide publications, educational offerings, and electronic cancer reporting standards that empower pathologists to be recognized leaders in clinical informatics.

Are you interested in pathology informatics? Consider applying to join one of the CIPI committees as a regular or junior member, as appropriate. Just click the committee links above and then click “Apply Now” under “Interested in Joining this Committee?” on the right side of the committee page.

Webinars

• “Pathology Report Data Life Cycle” discusses the incorporation of pathology report data into population-scale databases to answer pathology-related research questions.
• “Transforming Cancer Registry Data” explores the use of the CAP Cancer Protocols to enhance the communication to and content of cancer registries.
• “SNOMED CT and eCP Binding and Data Navigation” introduces the use of SNOMED CT with pathology data for research, clinical care, and quality improvement, and presents new developments in SNOMED for use with the CAP electronic Cancer Protocols.
• "Real Intelligence About Artificial Intelligence" introduces various AI and ML models used to analyze clinical data, and the qualifications and training necessary to use these tools effectively. Case discussions highlight the use, validation, challenges, and pitfalls in evaluation of these products.

Educational Opportunities from the CAP

The CAP offers educational resources to build your knowledge and skills in critical clinical informatics topics. Log in anytime, anywhere to access CAP’s case-based educational modules in informatics (CME available) and other educational resources in informatics. Review the Informatics Competency Model For Pathologists to compare your knowledge and skills against those demonstrating proficiency in this discipline. The CAP also provides a useful glossary of clinical informatics-related terms and acronyms.

Pathology Informatics Essentials for Residents (PIER) Curriculum

PIER is a free informatics graduate medical education curriculum and resource toolkit for pathology residency programs developed by the Association of Pathology Chairs (APC), the Association for Pathology Informatics (API), and the CAP. PIER presents training topics, knowledge and skill statements, educational strategies, and learning resource options for program directors and faculty to effectively provide informatics training to their residents which meet Accreditation Council for Graduate Medical Education informatics milestone requirements. A published article on the initial version of PIER is available (Henricks et al. Arch Pathol Lab Med, 2016).

Lecture slide sets and term lists from the Association for Pathology Informatics (API)

A set of 10 slide decks with accompanying term lists covering a complete curriculum in pathology informatics are available from the API. These are designed to support an informatics training module in a residency program but can also be used for individual study.

Cancer Reporting Tools

• Cancer Reporting Tools help pathologists create the highest quality cancer reports to ensure excellent patient care.
• The CAP electronic Cancer Checklists (eCC) enable pathologists to better manage their cancer patient data through standardized electronic reporting, which integrates with their anatomic pathology-laboratory information systems workflow.

Published Materials

1. Harrison J. Management of pathology information systems, Chapter 6. In: Laboratory Administration for Pathologists. 2nd ed. CAP Press; 2019:286. Chapter available from the PIER Web site.
2. Henricks WH, Wilkerson ML, Castellani WJ, Whitsitt MS, Sinard JH. Pathologists as stewards of laboratory information. Arch Pathol Lab Med. 2015;139(3):332-337. doi:10.5858/arpa.2013-0714-SO
3. Henricks WH. Laboratory Information Systems. Clin Lab Med. 2016;36(1):1-11. doi:10.1016/j.cll.2015.09.002
4. Wilkerson ML, Henricks WH, Castellani WJ, Whitsitt MS, Sinard JH. Management of laboratory data and information exchange in the electronic health record. Arch Pathol Lab Med. 2015;139(3):319-327. doi:10.5858/arpa.2013-0712-SO
5. Cucoranu IC. Laboratory information systems management and operations. Surg Pathol Clin. 2015;8(2):153-157. doi:10.1016/j.path.2015.02.002
6. Michels C. Biocomputing for biobanks: Workflow and information management systems for biobanks. In: Hainaut P, Vaught J, Zatloukal K, Pasterk M, eds. Biobanking of Human Biospecimens: Lessons from 25 Years of Biobanking Experience. Springer International Publishing; 2021:45-64. doi:10.1007/978-3-030-55901-4_3
7. Im K, Gui D, Yong WH. An introduction to hardware, software, and other information technology needs of biomedical biobanks. Methods Mol Biol. 2019;1897:17-29. doi:10.1007/978-1-4939-8935-5_3
8. Bietenbeck A, Streichert T. Preparing laboratories for interconnected health care. Diagnostics. 2021;11(8):1487. doi:10.3390/diagnostics11081487
9. Stram M, Gigliotti T, Hartman D, et al. Logical Observation Identifiers Names and Codes for laboratorians: potential solutions and challenges for interoperability. Arch Pathol Lab Med. 2020;144(2):229-239. doi:10.5858/arpa.2018-0477-RA
10. Koné CJ, Babri M, Rodrigues JM. SNOMED CT: A clinical terminology but also a formal ontology. J Biosci Med. 2023;11(11):326-333. doi:10.4236/jbm.2023.1111027
11. Rossander A, Lindsköld L, Ranerup A, Karlsson D. A state-of-the art review of SNOMED CT terminology binding and recommendations for practice and research. Methods Inf Med. 2021;60(S 02):e76-e88. doi:10.1055/s-0041-1735167
12. Torous VF, Allan RW, Balani J, et al. Exploring the College of American Pathologists electronic Cancer Checklists: What they are and what they can do for you. Arch Pathol Lab Med. 2021;145(4):392-398. doi:10.5858/arpa.2020-0239-ED
13. Hanna MG, Ardon O, Reuter VE, et al. Integrating digital pathology into clinical practice. Mod Pathol. 2022;35(2):152-164. doi:10.1038/s41379-021-00929-0
14. Dash RC, Jones N, Merrick R, et al. Integrating the health-care enterprise pathology and laboratory medicine guideline for digital pathology interoperability. J Pathol Inform. 2021;12(1):16. doi:10.4103/jpi.jpi_98_20
15. Evans H, Hero E, Minhas F, et al. Standardized clinical annotation of digital histopathology slides at the point of diagnosis. Mod Pathol. 2023;36(11):100297. doi:10.1016/j.modpat.2023.100297
16. Harrison JH, Gilbertson JR, Hanna MG, et al. Introduction to artificial intelligence and machine learning for pathology. Arch Pathol Lab Med. 2021;145(10):1228-1254. doi:10.5858/arpa.2020-0541-cp
17. Zarella MD, McClintock DS, Batra H, et al. Artificial intelligence and digital pathology: clinical promise and deployment considerations. J Med Imaging. 2023;10(5):051802. doi:10.1117/1.JMI.10.5.051802
18. Hughes AEO, Jackups R. Clinical decision support for laboratory testing. Clin Chem. 2022;68(3):402-412. doi:10.1093/clinchem/hvab201
19. Patel AU, Williams CL, Hart SN, et al. Cybersecurity and information assurance for the clinical laboratory. J Appl Lab Med. 2023;8(1):145-161. doi:10.1093/jalm/jfac119