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Arvisais-Anhalt S, Lehmann CU, Bishop JA, Balani J, Boutte L, Morales M, Park JY, Araj E. Searching Full-Text Anatomic Pathology Reports Using Business Intelligence Software. J Pathol Inform 2022; 13:100014. [PMID: 35251753 PMCID: PMC8892022 DOI: 10.1016/j.jpi.2022.100014] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/07/2021] [Indexed: 01/24/2023] Open
Abstract
Although the laboratory information system has largely solved the problem of storing anatomic pathology reports and disseminating their contents across the healthcare system, the retrospective query of anatomic pathology reports remains an area for improvement across laboratory information system vendors. Our institution desired the ability to query our repository of anatomic pathology reports for clinical, operational, research, and educational purposes. To address this need, we developed a full-text anatomic pathology search tool using the business intelligence software, Tableau. Our search tool allows users to query the 333,685 anatomic pathology reports from our institutional clinical relational database using the business intelligence tool's built-in regular expression functionality. Users securely access the search tool using any web browser, thereby avoiding the cost of installing or maintaining software on users' computers. This tool is laboratory information system vendor agnostic and as many institutions already subscribe to business intelligence software, we believe this solution could be easily reproduced at other institutions and in other clinical departments.
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Affiliation(s)
- Simone Arvisais-Anhalt
- Department of Hospital Medicine and Department of Laboratory Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Christoph U. Lehmann
- Clinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Justin A. Bishop
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jyoti Balani
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Laurie Boutte
- Health System Quality & Operational Excellence, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Marjorie Morales
- Health System Quality & Operational Excellence, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Jason Y. Park
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Ellen Araj
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA,Corresponding author at: Department of Pathology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas, TX 75390-9072, USA.
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Musselman RP, Rothwell D, Auer RC, Moloo H, Boushey RP, van Walraven C. Can Text-Search Methods of Pathology Reports Accurately Identify Patients with Rectal Cancer in Large Administrative Databases? J Pathol Inform 2018; 9:18. [PMID: 29862128 PMCID: PMC5952547 DOI: 10.4103/jpi.jpi_71_17] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Accepted: 02/26/2018] [Indexed: 01/05/2023] Open
Abstract
Background: The aim of this study is to derive and to validate a cohort of rectal cancer surgical patients within administrative datasets using text-search analysis of pathology reports. Materials and Methods: A text-search algorithm was developed and validated on pathology reports from 694 known rectal cancers, 1000 known colon cancers, and 1000 noncolorectal specimens. The algorithm was applied to all pathology reports available within the Ottawa Hospital Data Warehouse from 1996 to 2010. Identified pathology reports were validated as rectal cancer specimens through manual chart review. Sensitivity, specificity, and positive predictive value (PPV) of the text-search methodology were calculated. Results: In the derivation cohort of pathology reports (n = 2694), the text-search algorithm had a sensitivity and specificity of 100% and 98.6%, respectively. When this algorithm was applied to all pathology reports from 1996 to 2010 (n = 284,032), 5588 pathology reports were identified as consistent with rectal cancer. Medical record review determined that 4550 patients did not have rectal cancer, leaving a final cohort of 1038 rectal cancer patients. Sensitivity and specificity of the text-search algorithm were 100% and 98.4%, respectively. PPV of the algorithm was 18.6%. Conclusions: Text-search methodology is a feasible way to identify all rectal cancer surgery patients through administrative datasets with high sensitivity and specificity. However, in the presence of a low pretest probability, text-search methods must be combined with a validation method, such as manual chart review, to be a viable approach.
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Affiliation(s)
| | - Deanna Rothwell
- Department Epidemiology and Community Medicine, Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Rebecca C Auer
- Division of General Surgery, University of Ottawa, Ottawa, ON, Canada
| | - Husein Moloo
- Division of General Surgery, University of Ottawa, Ottawa, ON, Canada
| | - Robin P Boushey
- Division of General Surgery, University of Ottawa, Ottawa, ON, Canada
| | - Carl van Walraven
- Department Epidemiology and Community Medicine, Ottawa Hospital Research Institute, Ottawa, ON, Canada
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Kennell TI, Willig JH, Cimino JJ. Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record. Appl Clin Inform 2017; 8:1159-1172. [PMID: 29270955 DOI: 10.4338/aci-2017-06-r-0101] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
OBJECTIVE Clinical informatics researchers depend on the availability of high-quality data from the electronic health record (EHR) to design and implement new methods and systems for clinical practice and research. However, these data are frequently unavailable or present in a format that requires substantial revision. This article reports the results of a review of informatics literature published from 2010 to 2016 that addresses these issues by identifying categories of data content that might be included or revised in the EHR. MATERIALS AND METHODS We used an iterative review process on 1,215 biomedical informatics research articles. We placed them into generic categories, reviewed and refined the categories, and then assigned additional articles, for a total of three iterations. RESULTS Our process identified eight categories of data content issues: Adverse Events, Clinician Cognitive Processes, Data Standards Creation and Data Communication, Genomics, Medication List Data Capture, Patient Preferences, Patient-reported Data, and Phenotyping. DISCUSSION These categories summarize discussions in biomedical informatics literature that concern data content issues restricting clinical informatics research. These barriers to research result from data that are either absent from the EHR or are inadequate (e.g., in narrative text form) for the downstream applications of the data. In light of these categories, we discuss changes to EHR data storage that should be considered in the redesign of EHRs, to promote continued innovation in clinical informatics. CONCLUSION Based on published literature of clinical informaticians' reuse of EHR data, we characterize eight types of data content that, if included in the next generation of EHRs, would find immediate application in advanced informatics tools and techniques.
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Affiliation(s)
- Timothy I Kennell
- Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - James H Willig
- Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States.,Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - James J Cimino
- Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States.,Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
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Onega T, Weaver DL, Frederick PD, Allison KH, Tosteson ANA, Carney PA, Geller BM, Longton GM, Nelson HD, Oster NV, Pepe MS, Elmore JG. The diagnostic challenge of low-grade ductal carcinoma in situ. Eur J Cancer 2017; 80:39-47. [PMID: 28535496 DOI: 10.1016/j.ejca.2017.04.013] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Revised: 03/30/2017] [Accepted: 04/05/2017] [Indexed: 12/14/2022]
Abstract
BACKGROUND Diagnostic agreement among pathologists is 84% for ductal carcinoma in situ (DCIS). Studies of interpretive variation according to grade are limited. METHODS A national sample of 115 pathologists interpreted 240 breast pathology test set cases in the Breast Pathology Study and their interpretations were compared to expert consensus interpretations. We assessed agreement of pathologists' interpretations with a consensus reference diagnosis of DCIS dichotomised into low- and high-grade lesions. Generalised estimating equations were used in logistic regression models of rates of under- and over-interpretation of DCIS by grade. RESULTS We evaluated 2097 independent interpretations of DCIS (512 low-grade DCIS and 1585 high-grade DCIS). Agreement with reference diagnoses was 46% (95% confidence interval [CI] 42-51) for low-grade DCIS and 83% (95% CI 81-86) for high-grade DCIS. The proportion of reference low-grade DCIS interpretations over-interpreted by pathologists (i.e. categorised as either high-grade DCIS or invasive cancer) was 23% (95% CI 19-28); 30% (95% CI 26-34) were interpreted as a lower diagnostic category (atypia or benign proliferative). Reference high-grade DCIS was under-interpreted in 14% (95% CI 12-16) of observations and only over-interpreted 3% (95% CI 2-4). CONCLUSION Grade is a major factor when examining pathologists' variability in diagnosing DCIS, with much lower agreement for low-grade DCIS cases compared to high-grade. These findings support the hypothesis that low-grade DCIS poses a greater interpretive challenge than high-grade DCIS, which should be considered when developing DCIS management strategies.
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Affiliation(s)
- Tracy Onega
- Department of Biomedical Data Science, Department of Epidemiology, The Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
| | - Donald L Weaver
- Department of Pathology, University of Vermont and UVM Cancer Center, Burlington, VT, USA
| | - Paul D Frederick
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Kimberly H Allison
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Anna N A Tosteson
- Department of Medicine, The Dartmouth Institute for Health Policy and Clinical Practice and Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
| | - Patricia A Carney
- Department of Family Medicine, Oregon Health and Science University, Portland, OR, USA
| | - Berta M Geller
- Department of Family Medicine, University of Vermont, Burlington, VT 05401, USA
| | - Gary M Longton
- Department of Biostatistics, University of Washington, Seattle, WA 98101, USA
| | - Heidi D Nelson
- Providence Cancer Center, Providence Health and Services Oregon, and Department of Medical Informatics and Clinical Epidemiology and Department of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Natalia V Oster
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Margaret S Pepe
- Department of Biostatistics, University of Washington, Seattle, WA 98101, USA
| | - Joann G Elmore
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
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Allison KH, Rendi MH, Peacock S, Morgan T, Elmore JG, Weaver DL. Histological features associated with diagnostic agreement in atypical ductal hyperplasia of the breast: illustrative cases from the B-Path study. Histopathology 2016; 69:1028-1046. [PMID: 27398812 DOI: 10.1111/his.13035] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Accepted: 07/08/2016] [Indexed: 01/26/2023]
Abstract
AIMS This study examined the case-specific characteristics associated with interobserver diagnostic agreement in atypical ductal hyperplasia (ADH) of the breast. METHODS AND RESULTS Seventy-two test set cases with a consensus diagnosis of ADH from the B-Path study were evaluated. Cases were scored for 17 histological features, which were then correlated with the participant agreement with the consensus ADH diagnosis. Participating pathologists' perceptions of case difficulty, borderline features or whether they would obtain a second opinion were also examined for associations with agreement. Of the 2070 participant interpretations of the 72 consensus ADH cases, 48% were scored by participants as difficult and 45% as borderline between two diagnoses; the presence of both of these features was significantly associated with increased agreement (P < 0.001). A second opinion would have been obtained in 80% of interpretations, and this was associated with increased agreement (P < 0.001). Diagnostic agreement ranged from 10% to 89% on a case-by-case basis. Cases with papillary lesions, cribriform architecture and obvious cytological monotony were associated with higher agreement. Lower agreement rates were associated with solid or micropapillary architecture, borderline cytological monotony, or cases without a diagnostic area that was obvious on low power. CONCLUSIONS The results of this study suggest that pathologists frequently recognize the challenge of ADH cases, with some cases being more prone to diagnostic variability. In addition, there are specific histological features associated with diagnostic agreement on ADH cases. Multiple example images from cases in this test set are provided to serve as educational illustrations of these challenges.
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Affiliation(s)
- Kimberly H Allison
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Mara H Rendi
- Department of Pathology, University of Washington School of Medicine, Seattle, WA, USA
| | - Sue Peacock
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Tom Morgan
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Joann G Elmore
- Department of Medicine, University of Washington School of Medicine, Seattle, WA, USA
| | - Donald L Weaver
- Department of Pathology and University of Vermont Cancer Center, University of Vermont, Burlington, VT, USA
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Mammography Screening in a Large Health System Following the U.S. Preventive Services Task Force Recommendations and the Affordable Care Act. PLoS One 2015; 10:e0131903. [PMID: 26121485 PMCID: PMC4487998 DOI: 10.1371/journal.pone.0131903] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2015] [Accepted: 06/08/2015] [Indexed: 11/19/2022] Open
Abstract
Background Practice recommendations for mammography screening were issued by the U.S. Preventive Services Task Force in 2009 and expansion of insurance coverage was provided under the Patient Protection and Affordable Care Act soon thereafter, yet the influence of these changes on screening practices in the United States is not known. Methods To determine changes in mammography screening and their associations with new practice recommendations and the Affordable Care Act, we examined patient-level data from 249,803 screening mammograms from January 1, 2008 through December 31, 2012 in a large community-based health system in the northwestern United States. Associations were determined by an intervention analysis of time-series data method. Results Among women screened, 64% were age 50-74 years; 84% self-identified as white race; 62% had commercial insurance; and 70% were seen in facilities located in metropolitan areas. Practice recommendations were associated with decreased screening volumes among women age <40 (-37.4 mammograms/month; -39.4% change; P<0.001), 40-49 (-106.0 mammograms/month; -11.2% change; P<0.001), and ≥75 (-54.7 mammograms/month; -10.0% change; P<0.001), but not women age 50-74. Implementation of the Affordable Care Act was associated with increased screening among women age 50-74 (+184.3 mammograms/month; +7.2% change; P=0.001), but not women <40 or ≥75; increases for age 40-49 were of borderline statistical significance (+56.9 mammograms/month; +6% change; P=0.06). Practice recommendations were also associated with decreased screening for women with commercial insurance, while the Affordable Care Act was associated with increased screening for women with Medicare, Medicaid, or other noncommercial sources of payment. Conclusions Mammography screening volumes in a large community health system decreased among women age <50 and ≥75 in association with new U.S. Preventive Services Task Force practice recommendations, while insurance coverage changes under the Affordable Care Act were associated with increased screening volumes among women age 50-74.
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