1
|
Berbís MA, McClintock DS, Bychkov A, Van der Laak J, Pantanowitz L, Lennerz JK, Cheng JY, Delahunt B, Egevad L, Eloy C, Farris AB, Fraggetta F, García del Moral R, Hartman DJ, Herrmann MD, Hollemans E, Iczkowski KA, Karsan A, Kriegsmann M, Salama ME, Sinard JH, Tuthill JM, Williams B, Casado-Sánchez C, Sánchez-Turrión V, Luna A, Aneiros-Fernández J, Shen J. Computational pathology in 2030: a Delphi study forecasting the role of AI in pathology within the next decade. EBioMedicine 2023; 88:104427. [PMID: 36603288 PMCID: PMC9823157 DOI: 10.1016/j.ebiom.2022.104427] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 12/06/2022] [Accepted: 12/13/2022] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND Artificial intelligence (AI) is rapidly fuelling a fundamental transformation in the practice of pathology. However, clinical integration remains challenging, with no AI algorithms to date in routine adoption within typical anatomic pathology (AP) laboratories. This survey gathered current expert perspectives and expectations regarding the role of AI in AP from those with first-hand computational pathology and AI experience. METHODS Perspectives were solicited using the Delphi method from 24 subject matter experts between December 2020 and February 2021 regarding the anticipated role of AI in pathology by the year 2030. The study consisted of three consecutive rounds: 1) an open-ended, free response questionnaire generating a list of survey items; 2) a Likert-scale survey scored by experts and analysed for consensus; and 3) a repeat survey of items not reaching consensus to obtain further expert consensus. FINDINGS Consensus opinions were reached on 141 of 180 survey items (78.3%). Experts agreed that AI would be routinely and impactfully used within AP laboratory and pathologist clinical workflows by 2030. High consensus was reached on 100 items across nine categories encompassing the impact of AI on (1) pathology key performance indicators (KPIs) and (2) the pathology workforce and specific tasks performed by (3) pathologists and (4) AP lab technicians, as well as (5) specific AI applications and their likelihood of routine use by 2030, (6) AI's role in integrated diagnostics, (7) pathology tasks likely to be fully automated using AI, and (8) regulatory/legal and (9) ethical aspects of AI integration in pathology. INTERPRETATION This systematic consensus study details the expected short-to-mid-term impact of AI on pathology practice. These findings provide timely and relevant information regarding future care delivery in pathology and raise key practical, ethical, and legal challenges that must be addressed prior to AI's successful clinical implementation. FUNDING No specific funding was provided for this study.
Collapse
Affiliation(s)
- M. Alvaro Berbís
- Department of R&D, HT Médica, San Juan de Dios Hospital, Córdoba, Spain,Faculty of Medicine, Autonomous University of Madrid, Madrid, Spain,Corresponding author. Department of R&D, HT Médica, San Juan de Dios Hospital, Córdoba, 14011, Spain.
| | - David S. McClintock
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Andrey Bychkov
- Department of Pathology, Kameda Medical Center, Kamogawa, Chiba, Japan
| | - Jeroen Van der Laak
- Department of Pathology, Radboud University Medical Center, Nijmegen, the Netherlands
| | | | - Jochen K. Lennerz
- Department of Pathology, Center for Integrated Diagnostics, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Jerome Y. Cheng
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Brett Delahunt
- Wellington School of Medicine and Health Sciences, University of Otago, Wellington, New Zealand
| | - Lars Egevad
- Department of Oncology-Pathology, Karolinska Institute, Stockholm, Sweden
| | - Catarina Eloy
- Pathology Laboratory, Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal
| | - Alton B. Farris
- Department of Pathology and Laboratory Medicine, Emory University, Atlanta, GA, USA
| | - Filippo Fraggetta
- Pathology Unit, Azienda Sanitaria Provinciale Catania, Gravina Hospital, Caltagirone, Italy
| | | | - Douglas J. Hartman
- Department of Anatomic Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Markus D. Herrmann
- Department of Pathology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Eva Hollemans
- Department of Pathology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | | | - Aly Karsan
- Department of Pathology & Laboratory Medicine, University of British Columbia, Michael Smith Genome Sciences Centre, Vancouver, Canada
| | - Mark Kriegsmann
- Institute of Pathology, University Hospital Heidelberg, Heidelberg, Germany
| | | | - John H. Sinard
- Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
| | - J. Mark Tuthill
- Department of Pathology, Henry Ford Hospital, Detroit, MI, USA
| | - Bethany Williams
- Department of Histopathology, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - César Casado-Sánchez
- Department of Plastic and Reconstructive Surgery, La Paz University Hospital, Madrid, Spain
| | - Víctor Sánchez-Turrión
- Department of General Surgery and Digestive Tract, Puerta de Hierro-Majadahonda University Hospital, Madrid, Spain
| | - Antonio Luna
- Department of Integrated Diagnostics, HT Médica, Clínica Las Nieves, Jaén, Spain
| | - José Aneiros-Fernández
- Department of R&D, HT Médica, San Juan de Dios Hospital, Córdoba, Spain,Pathology Unit, Azienda Sanitaria Provinciale Catania, Gravina Hospital, Caltagirone, Italy
| | - Jeanne Shen
- Department of Pathology and Center for Artificial Intelligence in Medicine & Imaging, Stanford University School of Medicine, Stanford, CA, USA.
| |
Collapse
|
2
|
Wheeler SE, Block DR, Bunch DR, Gramz J, Leung EKY, McClintock DS, Tuthill JM. Clinical Laboratory Informatics and Analytics: Challenges and Opportunities. Clin Chem 2022; 68:1361-1367. [PMID: 36264683 DOI: 10.1093/clinchem/hvac157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 09/01/2022] [Indexed: 11/12/2022]
Affiliation(s)
- Sarah E Wheeler
- Associate Professor of Pathology, University of Pittsburgh School of Medicine; Medical Director of UPMC Mercy and UPMC Children's Hospital Automated Testing Laboratories, Associate Director of UPMC Presbyterian Clinical Immunopathology Laboratory, Pittsburgh, PA, USA
| | - Darci R Block
- Assistant Professor of Laboratory Medicine and Pathology, Mayo Clinic Rochester, MN. Co-director of Central Processing and Central Clinical Laboratory, Vice Chair of Informatics for Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Dustin R Bunch
- Assistant Director Clinical Chemistry and Co-Director Laboratory Informatics, Nationwide Children's Hospital, Assistant Professor - Clinical, College of Medicine, The Ohio State University, Columbus, OH, USA
| | - Jamie Gramz
- Head of Digital Applications for Laboratory Diagnostics, Siemens Healthineers, Tarrytown, NY, USA
| | - Edward Ki Yun Leung
- Director, Core Laboratory, Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles. Assistant Professor of Clinical Pathology, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - David S McClintock
- Senior Associate Consultant, Division of Computational Pathology and Artificial Intelligence, Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - J Mark Tuthill
- Division Head, Department of Pathology and Laboratory Medicine, Henry Ford Health System, K-6 Pathology, Detroit, MI, USA
| |
Collapse
|
3
|
Mishra A, Tuthill JM. Implementation of Whole-Slide Imaging as a Pathology Teaching Tool and for Institutional Tumor Boards: A Resident’s Experience. Am J Clin Pathol 2019. [DOI: 10.1093/ajcp/aqz123.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Objectives
This presentation will describe our experience implementing and utilizing whole-slide imaging (WSI) as a teaching tool for the pathology residents in Henry Ford Hospital, Detroit, as well as our initial efforts to use WSI at institutional tumor boards.
Methods
Glass slides were scanned for practice over several weeks to determine basic operation, system performance, and workflow processes. Experience quickly showed that the scanner could be used to improvement quality and efficiency of weekly unknown slide conference. Informatics lecture and luncheon meeting topics as well as a grand-rounds presentation on novel ways to use WSI were shared with residents and other members of the department. This resulted in marked increased interest. Soon interest grew from attending physicians to use WSI for a subset of tumor boards. The same processes and procedures used for scanning slides for unknown conference were applied.
Results
In October 2016, an unknown slide conference was presented using WSI. The reaction to the quality of the histopathology system usage was excellent: nuclear contours and nucleoli were clear; navigation was easy; response time was excellent, with no screen lag. Residents and attending loved the new format. Since then, the unknown conference has been presented monthly using WSI. In November 2016, we started presenting cases on WSI in the GYN tumor board. Some had no idea that this was even technically possible. All GYN weekly tumor boards are now presented using WSI.
Conclusion
Whole-slide imaging is a useful tool for teaching and presentation purposes. It can be easily implemented and integrated into our day-to-day pathology practice and resident training. The reluctance to use WSI is initially high among pathologists, but enthusiasm increases once implemented into regular practice. WSI provides for efficiencies and ease of collaboration in both educational and clinical case review settings such as institutional tumor boards.
Collapse
|
4
|
Abstract
To achieve effective laboratory automation, analytical capabilities must be developed to support data analysis. This allows for effective development and deployment of decision support strategies within the automated laboratory. Practically, these take the form of dashboards, static and real time; workflow processes, such as autoverification; reflex protocols; and testing cascades, which reduce errors of omission and commission. This requires data from the LIS and middleware that enable sophisticated laboratory automation lines. This article addresses the historical, current, and future state of laboratory analytics using examples and offering a framework to organize thinking around analytical capabilities.
Collapse
Affiliation(s)
- J Mark Tuthill
- Henry Ford Health System, 2799 W. Grand Boulevard, K-6 Pathology, Detroit, MI 48202, USA.
| |
Collapse
|
5
|
Fraggetta F, Yagi Y, Garcia-Rojo M, Evans AJ, Tuthill JM, Baidoshvili A, Hartman DJ, Fukuoka J, Pantanowitz L. The Importance of eSlide Macro Images for Primary Diagnosis with Whole Slide Imaging. J Pathol Inform 2018; 9:46. [PMID: 30662792 PMCID: PMC6319037 DOI: 10.4103/jpi.jpi_70_18] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Accepted: 10/31/2018] [Indexed: 11/25/2022] Open
Abstract
Introduction: A whole slide image (WSI) is typically comprised of a macro image (low-power snapshot of the entire glass slide) and stacked tiles in a pyramid structure (with the lowest resolution thumbnail at the top). The macro image shows the label and all pieces of tissue on the slide. Many whole slide scanner vendors do not readily show the macro overview to pathologists. We demonstrate that failure to do so may result in a serious misdiagnosis. Materials and Methods: Various examples of errors were accumulated that occurred during the digitization of glass slides where the virtual slide differed from the macro image of the original glass slide. Such examples were retrieved from pathology laboratories using different types of scanners in the USA, Canada, Europe, and Asia. Results: The reasons for image errors were categorized into technical problems (e.g., automatic tissue finder failure, image mismatches, and poor scan coverage) and human operator mistakes (e.g., improper manual region of interest selection). These errors were all detected because they were highlighted in the macro image. Conclusion: Our experience indicates that WSI can be subject to inadvertent errors related to glitches in scanning slides, corrupt images, or mistakes made by humans when scanning slides. Displaying the macro image that accompanies WSIs is critical from a quality control perspective in digital pathology practice as this can help detect these serious image-related problems and avoid compromised diagnoses.
Collapse
Affiliation(s)
| | - Yukako Yagi
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, USA
| | - Marcial Garcia-Rojo
- Department of Pathology, Hospital Universitario Puerta del Mar, Cádiz, Spain
| | - Andrew J Evans
- Department of Pathology, University Health Network, Toronto, Canada
| | - J Mark Tuthill
- Department of Pathology, Henry Ford Health System, Detroit, Michigan, USA
| | | | - Douglas J Hartman
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Junya Fukuoka
- Department of Pathology, Nagasaki University Hospital, Nagasaki, Japan
| | - Liron Pantanowitz
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| |
Collapse
|
6
|
Rudolf JW, Garcia CA, Hanna MG, Williams CL, Balis UG, Pantanowitz L, Tuthill JM, Gilbertson JR. Career Paths of Pathology Informatics Fellowship Alumni. J Pathol Inform 2018; 9:14. [PMID: 29721362 PMCID: PMC5907454 DOI: 10.4103/jpi.jpi_66_17] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2017] [Accepted: 01/03/2018] [Indexed: 11/15/2022] Open
Abstract
Background: The alumni of today's Pathology Informatics and Clinical Informatics fellowships fill diverse roles in academia, large health systems, and industry. The evolving training tracks and curriculum of Pathology Informatics fellowships have been well documented. However, less attention has been given to the posttraining experiences of graduates from informatics training programs. Here, we examine the career paths of subspecialty fellowship-trained pathology informaticians. Methods: Alumni from four Pathology Informatics fellowship training programs were contacted for their voluntary participation in the study. We analyzed various components of training, and the subsequent career paths of Pathology Informatics fellowship alumni using data extracted from alumni provided curriculum vitae. Results: Twenty-three out of twenty-seven alumni contacted contributed to the study. A majority had completed undergraduate study in science, technology, engineering, and math fields and combined track training in anatomic and clinical pathology. Approximately 30% (7/23) completed residency in a program with an in-house Pathology Informatics fellowship. Most completed additional fellowships (15/23) and many also completed advanced degrees (10/23). Common primary posttraining appointments included chief medical informatics officer (3/23), director of Pathology Informatics (10/23), informatics program director (2/23), and various roles in industry (3/23). Many alumni also provide clinical care in addition to their informatics roles (14/23). Pathology Informatics alumni serve on a variety of institutional committees, participate in national informatics organizations, contribute widely to scientific literature, and more than half (13/23) have obtained subspecialty certification in Clinical Informatics to date. Conclusions: Our analysis highlights several interesting phenomena related to the training and career trajectory of Pathology Informatics fellowship alumni. We note the long training track alumni complete in preparation for their careers. We believe flexible training pathways combining informatics and clinical training may help to alleviate the burden. We highlight the importance of in-house Pathology Informatics fellowships in promoting interest in informatics among residents. We also observe the many important leadership roles in academia, large community health systems, and industry available to early career alumni and believe this reflects a strong market for formally trained informaticians. We hope this analysis will be useful as we continue to develop the informatics fellowships to meet the future needs of our trainees and discipline.
Collapse
Affiliation(s)
- Joseph W Rudolf
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | | | - Matthew G Hanna
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Christopher L Williams
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Ulysses G Balis
- Department of Pathology, University of Michigan, Ann Arbor, MI, USA
| | - Liron Pantanowitz
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - J Mark Tuthill
- Department of Pathology and Laboratory Medicine, Henry Ford Health System, Detroit, MI, USA
| | - John R Gilbertson
- Department of Pathology, Massachusetts General Hospital, Boston, MA, USA
| | | |
Collapse
|
7
|
Pantanowitz L, Dickinson K, Evans AJ, Hassell LA, Henricks WH, Lennerz JK, Lowe A, Parwani AV, Riben M, Smith CD, Tuthill JM, Weinstein RS, Wilbur DC, Krupinski EA, Bernard J. ATA clinical guidelines for telepathology. Telemed J E Health 2016; 20:1049-56. [PMID: 25384254 DOI: 10.1089/tmj.2014.9976] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- Liron Pantanowitz
- 1 Department of Pathology, University of Pittsburgh Medical Center , Pittsburgh, Pennsylvania
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
8
|
Pantanowitz L, Dickinson K, Evans AJ, Hassell LA, Henricks WH, Lennerz JK, Lowe A, Parwani AV, Riben M, Smith CD, Tuthill JM, Weinstein RS, Wilbur DC, Krupinski EA, Bernard J. American Telemedicine Association clinical guidelines for telepathology. J Pathol Inform 2014. [PMID: 25379345 DOI: 10.4103/2153–3539.143329] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Affiliation(s)
- Liron Pantanowitz
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Kim Dickinson
- Integrated Oncology, LabCorp and Digital Pathology Association, Irvine, CA, USA
| | - Andrew J Evans
- Department of Pathology, University Health Network Toronto General Hospital, Toronto, Canada
| | - Lewis A Hassell
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Walter H Henricks
- Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jochen K Lennerz
- Department of Pathology, University Ulm, Albert-Einstein-Allee, Ulm, Germany
| | | | - Anil V Parwani
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Michael Riben
- Department of Pathology, Anatomic Pathology Informatics, MD Anderson, Houston, TX, USA
| | - Col Daniel Smith
- Department of Pathology, Keesler Medical Center, Biloxi, MS, USA
| | - J Mark Tuthill
- Department of Pathology, Pathology Informatics, Henry Ford Health System, Detroit, MI, USA
| | | | - David C Wilbur
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | | |
Collapse
|
9
|
Pantanowitz L, Dickinson K, Evans AJ, Hassell LA, Henricks WH, Lennerz JK, Lowe A, Parwani AV, Riben M, Smith CD, Tuthill JM, Weinstein RS, Wilbur DC, Krupinski EA, Bernard J. American Telemedicine Association clinical guidelines for telepathology. J Pathol Inform 2014; 5:39. [PMID: 25379345 PMCID: PMC4221880 DOI: 10.4103/2153-3539.143329] [Citation(s) in RCA: 63] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2014] [Accepted: 09/15/2014] [Indexed: 11/16/2022] Open
Affiliation(s)
- Liron Pantanowitz
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Kim Dickinson
- Integrated Oncology, LabCorp and Digital Pathology Association, Irvine, CA, USA
| | - Andrew J Evans
- Department of Pathology, University Health Network Toronto General Hospital, Toronto, Canada
| | - Lewis A Hassell
- Department of Pathology, University of Oklahoma Health Sciences Center, Oklahoma City, Oklahoma, USA
| | - Walter H Henricks
- Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jochen K Lennerz
- Department of Pathology, University Ulm, Albert-Einstein-Allee, Ulm, Germany
| | | | - Anil V Parwani
- Department of Pathology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Michael Riben
- Department of Pathology, Anatomic Pathology Informatics, MD Anderson, Houston, TX, USA
| | - Col Daniel Smith
- Department of Pathology, Keesler Medical Center, Biloxi, MS, USA
| | - J Mark Tuthill
- Department of Pathology, Pathology Informatics, Henry Ford Health System, Detroit, MI, USA
| | | | - David C Wilbur
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | | | | |
Collapse
|
10
|
Tuthill JM, Friedman BA, Balis UJ, Splitz A. The laboratory information system functionality assessment tool: Ensuring optimal software support for your laboratory. J Pathol Inform 2014; 5:7. [PMID: 24741466 PMCID: PMC3986538 DOI: 10.4103/2153-3539.127819] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2013] [Accepted: 01/15/2014] [Indexed: 11/14/2022] Open
Affiliation(s)
- J Mark Tuthill
- Department of Pathology Informatics, Henry Ford Health System, Detroit, Michigan, USA
| | - Bruce A Friedman
- Division of Pathology Informatics, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Ulysses J Balis
- Division of Pathology Informatics, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Andrew Splitz
- President/CEO, S and P Consultants, Inc, West Bridgewater, Massachusetts, USA
| |
Collapse
|
11
|
Eide MJ, Tuthill JM, Krajenta RJ, Jacobsen GR, Levine M, Johnson CC. Validation of claims data algorithms to identify nonmelanoma skin cancer. J Invest Dermatol 2012; 132:2005-9. [PMID: 22475754 PMCID: PMC3393824 DOI: 10.1038/jid.2012.98] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Health maintenance organization (HMO) administrative databases have been used as sampling frames for ascertaining nonmelanoma skin cancer (NMSC). However, because of the lack of tumor registry information on these cancers, these ascertainment methods have not been previously validated. NMSC cases arising from patients served by a staff model medical group and diagnosed between 1 January 2007 and 31 December 2008 were identified from claims data using three ascertainment strategies. These claims data cases were then compared with NMSC identified using natural language processing (NLP) of electronic pathology reports (EPRs), and sensitivity, specificity, positive and negative predictive values were calculated. Comparison of claims data-ascertained cases with the NLP demonstrated sensitivities ranging from 48 to 65% and specificities from 85 to 98%, with ICD-9-CM ascertainment demonstrating the highest case sensitivity, although the lowest specificity. HMO health plan claims data had a higher specificity than all-payer claims data. A comparison of EPR and clinic log registry cases showed a sensitivity of 98% and a specificity of 99%. Validation of administrative data to ascertain NMSC demonstrates respectable sensitivity and specificity, although NLP ascertainment was superior. There is a substantial difference in cases identified by NLP compared with claims data, suggesting that formal surveillance efforts should be considered.
Collapse
Affiliation(s)
- Melody J Eide
- Department of Dermatology, Henry Ford Hospital, Detroit, Michigan 48202, USA.
| | | | | | | | | | | |
Collapse
|
12
|
Zarbo RJ, Tuthill JM, D’Angelo R, Varney R, Mahar B, Neuman C, Ormsby A. The Henry Ford Production System: reduction of surgical pathology in-process misidentification defects by bar code-specified work process standardization. Am J Clin Pathol 2009; 131:468-77. [PMID: 19289582 DOI: 10.1309/ajcpptj3xjy6zxdb] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
Abstract
Misidentification defects are a potential patient safety issue in medicine, including in the surgical pathology laboratory. In addressing the Joint Commission's national patient safety goal of accurate patient and specimen identification, we focused our lens internally on our own laboratory processes, with measurement tools designed to identify potential misidentification defects and their root causes. Based on this knowledge, aligned with our lean work culture in the Henry Ford Production System, we redesigned our surgical pathology laboratory workflow with simplified connections and pathways reinforced by a bar code technology innovation to specify and standardize work processes. We also adopted just-in-time prestain slide labeling with solvent-impervious, bar-coded slide labels at the microtome station, eliminating the loop-back pathway of poststain, batch slide matching, and labeling with adhesive paper labels. These changes have enabled us to dramatically reduce the overall misidentification case rate by approximately 62% with an approximate 95% reduction in the more common histologic slide misidentification defects while increasing technical throughput at the histology microtomy station by 125%.
Collapse
|
13
|
Mammen JJ, Tuthill JM. Structuring data in pathology reports: overcoming challenges with new tools. AMIA Annu Symp Proc 2008:1041. [PMID: 18998852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Received: 03/13/2008] [Revised: 07/14/2008] [Indexed: 05/27/2023]
Abstract
Traditional pathology reports have been textual with a high degree of variability. Checklist based structured pathology reports contribute significantly towards standardization and error reduction. As implemented, most of these are text templates making data retrieval dependent on natural language search. We describe a toolset that has been used to construct Laboratory Information System (LIS)-integrated checklists with forward chaining inference capabilities and contextual decision support. Data is saved directly into the LIS database facilitating queries and reporting.
Collapse
|
14
|
Henricks WH, Boyer PJ, Harrison JH, Tuthill JM, Healy JC. Informatics training in pathology residency programs: proposed learning objectives and skill sets for the new millennium. Arch Pathol Lab Med 2003; 127:1009-18. [PMID: 12873177 DOI: 10.5858/2003-127-1009-itiprp] [Citation(s) in RCA: 40] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
CONTEXT To be successful in tomorrow's health care environment, to make the most appropriate decisions for their laboratories, to optimize training and continuing medical education opportunities, and to advance pathology as a professional specialty, pathologists must possess basic informatics knowledge and proficiency. Traditional areas of anatomic and clinical pathology residency training employ learning objectives, knowledge expectations, and skill sets, but such items have not been as well developed or widely implemented for pathology informatics training. OBJECTIVE We present a proposal that defines a standard and specific set of learning (knowledge) objectives and skill set (proficiency) expectations for resident training in pathology informatics. DESIGN The proposal includes a comprehensive and detailed set of knowledge applications and proficiencies that will assist residency programs in developing basic pathology informatics training for residents. The content of the proposal is based on and compiled from existing successful pathology informatics training programs. Learning objectives include those related to general and enterprise computing as well as objectives related specifically to pathology informatics. Skill set expectations include the ability to use software that facilitates and adds value to the work of pathologists, including the use of a laboratory information system and of productivity software and other tools. Other topics include guidelines for evaluating residents' informatics competency, suggestions regarding curriculum structure and implementation, and recommendations for residents' computing infrastructure. CONCLUSION This proposal provides a foundation for building effective and standard curricula for residency training in pathology informatics. These curricula will be able to meet increasing expectations and needs for pathologists to contribute to clinical information management.
Collapse
Affiliation(s)
- Walter H Henricks
- Division of Pathology and Laboratory Medicine, Cleveland Clinic Foundation, Cleveland, Ohio 44195, USA.
| | | | | | | | | |
Collapse
|
15
|
Tuthill JM, Klatt EC. Information Technology in the Laboratory. Lab Med 2001. [DOI: 10.1309/463v-ht08-u81a-xftd] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022] Open
Affiliation(s)
- J. Mark Tuthill
- J. Mark Tuthill, MD, is assistant professor at the Department of Pathology, University of Vermont College of Medicine, Fletcher Allen Health Care, in Burlington, VT
| | - Edward C. Klatt
- Edward C. Klatt, MD, FASCP, is professor of pathology at the University of Utah, Salt Lake City, UT
| |
Collapse
|