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Celebrating G. Octo Barnett, MD

Celebrating G. Octo Barnett, MD In the eighth month of 2020, in which the COVID-19 (coronavirus disease 2019) pandemic remains a global health crisis and there is heightened awareness of structural racism in our society, I’ve chosen to step back from these critical issues and briefly reflect on the legacy of G. Octo Barnett, MD, medical informatics pioneer, who died at the end of June. I’m not forgetting about the issues. We have published innovative informatics solutions related to the pandemic over the last few months in Journal of the American Medical Informatics Association (JAMIA), and we will continue to do so. A recent Health Affairs blog called for a new standard of publishing on racial inequities, including recommendations for journals, reviewers, and authors.1 While we have made some efforts, such as a 2019 JAMIA double issue related to improving the reach and impact of health informatics to address health inequities including those related to race,2 there is no doubt that we can and must do more. However, JAMIA’s response to the recommendations requires reflection and discussion among our Associate Editors and Editorial Board as well as the American Medical Informatics Association’s Publications Committee. Once we have given this topic the careful deliberation it deserves, I will share our response with readers in a future editorial. In the JAMIA article summarizing the presentation of the Morris F. Collen Award to Octo, Bob Greenes describes not only Octo’s professional contributions, but also the significance of the 8. He writes that “Octo was named after his father. The possibly apocryphal story is that his father was the eighth son, born on the eighth day of the eighth month, in 1888.”3 For more information, the 2004 interview of Octo by Joan Ash and Dean Sittig entitled “From ‘Farm Boy’ to Director of the Laboratory of Computer Science” as part of the “Conversations with Medical Informatics Pioneers: An Oral History Collection” at the National Library of Medicine provides a fascinating view of Octo’s professional and personal life.4 There will be many opportunities to celebrate Octo’s legacy, but here I focus on the JAMIA perspective. Octo was the author of 6 JAMIA articles, the first in 1994 and the last in 2012, both coauthored with Henry Chueh.5–10 A 2006 sole-authored article was an extract of a report given by Octo to the National Institutes of Health 40 years earlier.9 Remarkably, among 7 areas of concern that he identified, 2 resonate more than 50 years later—the need for evolutionary approaches for computer-based systems and transferability among institutions. The discussion list of the American College of Medical Informatics has been filled with heartwarming stories about the influence of Octo on their careers and highlighted the multitude of progeny that can be traced back to him in some way. In celebration of Octo’s legacy, I selected the highlights for this issue based on the linkage of 1 of more authors in an article to him directly as a trainee or close collaborator in the Laboratory of Computer Science or from his academic descendants. As a remarkable measure of his influence, I had a least 7 to choose from in my queue of available articles for this issue. Appropriate to celebrating the co-developer of the COmputer-STored Ambulatory Record (COSTAR), one of the first electronic health records (EHRs) in the United States, I selected articles that focus on some aspect of the EHR, including policy aspects of adoption, quality and use of its contents for care and research, and its influence on clinicians. Adler-Milstein et al11 considered the question of whether U.S. hospitals have adopted EHR functions to support age-friendly care focusing on structured documentation of the 4Ms (What Matters, Medication, Mentation, and Mobility) and electronic health information exchange or communication with patients, caregivers, and long-term care providers. Using an online survey of 797 U.S. acute care hospitals in 2018-2019 with a 60.1% response rate, they found that only 41.5% had structured documentation of the 4Ms fully implemented across all units with medications the highest and mentation the lowest area. Less than 8% had implemented all exchange or communication functions across all units. Less than half of hospitals had an EHR portal for long-term care facilities to access hospital information or sent information electronically to long-term care facilities; about a third had training for adults or caregivers on the patient portal. The authors concluded that U.S. acute care hospital EHRs lack key functions that support age-friendly care and that additional policy efforts are needed to enhance EHR implementations to include such high-value functions. Everson et al13 also addressed the topic of hospital adoption of EHRs.12 They argued that a 2009 New England Journal of Medicine article that stated that only 9% of U.S. hospitals had adopted a basic EHR system became a memetic anchor point for EHR adoption at the dawn of the Health Information Technology for Economic and Clinical Health Act and that alternative approaches to treatment of the data may have led to a different sense of U.S. hospitals’ EHR adoption and, subsequently, a difference in public policy. To support this argument, they reanalyzed the 2008 American Heart Association Information Technology supplement and complementary sources to produce a range of estimates of EHR adoption and plotted an alternative definition of national progress toward hospital EHR adoption from 2008 to 2018. Their findings suggest that by 2008, the majority of hospitals had adopted at least 6 of the 10 functionalities of a basic system, and they estimated that 30%, rather than 9%, of hospitals had adopted a basic EHR. This larger estimate of basic EHR adoption could have resulted in different public policy. Wang and Wright14 characterized EHR problem list completeness and duplications through a retrospective analysis of EHR data from Partners HealthCare. They analyzed the problem lists of patients within 8 common chronic disease groups for completeness and duplications and examined associations with disease type, patient demographics, and disease severity. Among 327 695 unique patients with 383 404 problem list entries, completeness varied from 72.9% in hypertension to 93.5% in asthma, and duplications varied from 4.8% in hypertension to 28.2% in diabetes. There was a variable relationship between demographic factors and rates of completeness and duplications. However, disease severity was positively correlated with both completeness and duplications. The authors called for further research on user behaviors and organizational policies related to the problem list as the foundation for interventions to improve its utility for care. An article by Ahuja et al15 includes among its coauthors Octo’s long-time collaborator Shawn Murphy. The authors addressed a major bottleneck hindering utilization of EHR data for translational research—the lack of precise phenotype labels—by proposing a fully automated topic modeling algorithm to simultaneously annotate multiple phenotypes. The method, sureLDA (surrogate-guided ensemble latent Dirichlet allocation), is a label-free multidimensional phenotyping method that (1) uses the PheNorm algorithm to initialize probabilities based on 2 surrogate features for each target phenotype, (2) leverages these probabilities to constrain the latent Dirichlet allocation topic model to generate phenotype-specific topics, and (3) combines phenotype-feature counts with surrogates via clustering ensemble to yield final phenotype probabilities. Evaluation of sureLDA supports its high accuracy and precision across a range of simulated and real-world phenotypes as well as its suitability for large-scale EHR phenotyping for applications such as phenome-wide association studies. Co et al16 described the potential tradeoffs between safety and EHR-based alert fatigue using data from a natural survey of hospital medication–related clinical decision support. They analyzed data from 1599 hospitals that completed the Computerized Physician Order Entry Evaluation Tool in both 2017 and 2018 and examined overall performance on the evaluation tool as well as the percentages of appropriate fatal order alerts and inappropriate nuisance order alerts. Percentage of appropriate fatal order performance demonstrated a statistically significant increase from 78.8% to 83.0%, but there was no significant change in percentage of inappropriate nuisance order performance. Hospitals alerting on 1 or more nuisance orders had a 3-percentage-point increase in their overall score on the evaluation tool, raising the concern that some hospitals may be achieving higher scores at the cost of overalerting; this has the potential to negatively influence clinician burnout and worsen safety. Octo will be missed, but there is no doubt that his influence on our field will live on. CONFLICT OF INTEREST STATEMENT None declared. REFERENCES 1 Boyd RW , Lindo EG , Weeks LD , McLemore MR. On racism: a new standard for publishing on racial health inequities. https://www.healthaffairs.org/do/10.1377/hblog20200630.939347/full/ Accessed July 8, 2020. 2 Veinot TC , Ancker JS , Bakken S. Health informatics and health equity: improving our reach and impact . J Am Med Inform Assoc 2019 ; 26 ( 8–9 ): 689 – 95 . Google Scholar Crossref Search ADS PubMed WorldCat 3 Greenes RA. Presentation of the Morris F. Collen Award to G. Octo Barnett, MD, by Robert A. Greenes, MD, PhD . J Am Med Inform Assoc 1997 ; 4 ( 2 ): 155 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat 4 Barnett GO. From ‘Farm Boy’ to Director of the Laboratory of Computer Science: 2004 Interview of G. Octo Barnett. In: Goodwin RM , Ash JS , Sittig DF , eds. Conversations with Medical Informatics Pioneers: An Oral History Collection . Bethesda, MD : U.S. National Library of Medicine (NLM ); 2015 . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 5 Chueh HC , Barnett GO. Client-server, distributed database strategies in a health-care record system for a homeless population . J Am Med Inform Assoc 1994 ; 1 ( 2 ): 186 – 98 . Google Scholar Crossref Search ADS PubMed WorldCat 6 Barnett GO. Information technology and medical education . J Am Med Inform Assoc 1995 ; 2 ( 5 ): 285 – 91 . Google Scholar Crossref Search ADS PubMed WorldCat 7 Humphreys BL , Lindberg DA , Schoolman HM , Barnett GO. The Unified Medical Language System: an informatics research collaboration . J Am Med Inform Assoc 1998 ; 5 ( 1 ): 1 – 11 . Google Scholar Crossref Search ADS PubMed WorldCat 8 Ohno-Machado L , Gennari JH , Murphy SN , et al. The guideline interchange format: a model for representing guidelines . J Am Med Inform Assoc 1998 ; 5 ( 4 ): 357 – 72 . Google Scholar Crossref Search ADS PubMed WorldCat 9 Barnett GO. Report to the National Institutes of Health Division of Research Grants Computer Research Study Section on computer applications in medical communication and information retrieval systems as related to the improvement of patient care and the medical record–September 26, 1966 . J Am Med Inform Assoc 2006 ; 13 ( 2 ): 127 – 37 . Google Scholar Crossref Search ADS PubMed WorldCat 10 Feldman MJ , Hoffer EP , Barnett GO , Kim RJ , Famiglietti KT , Chueh H. Presence of key findings in the medical record prior to a documented high-risk diagnosis . J Am Med Inform Assoc 2012 ; 19 ( 4 ): 591 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat 11 Adler-Milstein J , Raphael K , Bonner A , Pelton L , Fulmer T. Hospital adoption of EHR functions to support age-friendly care: results from a national survey . J Am Med Inform Assoc 2020 ; 27 ( 8 ). 1205–1212. doi: 10.1093/jamia/ocaa129. OpenURL Placeholder Text WorldCat 12 Everson J , Rubin JC , Friedman CP. Reconsidering hospital EHR adoption at the dawn of HITECH: Implications of a reported 9% adoption of a “basic” EHR . J Am Med Inform Assoc 2020 ; 27 ( 8 ). 1197--1204. OpenURL Placeholder Text WorldCat 13 Jha AK , DesRoches CM , Campbell EG , et al. Use of electronic health records in US hospitals . N Engl J Med 2009 ; 360 ( 16 ): 1628 – 38 . Google Scholar Crossref Search ADS PubMed WorldCat 14 Wang EC , Wright A. Characterizing outpatient problem list completeness and duplications in the electronic health record . J Am Med Inform Assoc 2020 ; 27 ( 8 ). 1189--1196. OpenURL Placeholder Text WorldCat 15 Ahuja Y , Zhou D , Zeling H , et al. sureLDA: A multidisease automated phenotyping method for the electronic health record . J Am Med Inform Assoc 2020 ; 27 ( 8 ). 1235--1243. OpenURL Placeholder Text WorldCat 16 Co Z , Holmgren AJ , Classen DC , et al. The tradeoffs between safety and alert fatigue: Data from a national evaluation of hospital medication-related clinical decision support . J Am Med Inform Assoc 2020 ; 27 ( 8 ). 1252--1258. OpenURL Placeholder Text WorldCat © The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of the American Medical Informatics Association Oxford University Press

Celebrating G. Octo Barnett, MD

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Publisher
Oxford University Press
Copyright
© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com
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1067-5027
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Abstract

In the eighth month of 2020, in which the COVID-19 (coronavirus disease 2019) pandemic remains a global health crisis and there is heightened awareness of structural racism in our society, I’ve chosen to step back from these critical issues and briefly reflect on the legacy of G. Octo Barnett, MD, medical informatics pioneer, who died at the end of June. I’m not forgetting about the issues. We have published innovative informatics solutions related to the pandemic over the last few months in Journal of the American Medical Informatics Association (JAMIA), and we will continue to do so. A recent Health Affairs blog called for a new standard of publishing on racial inequities, including recommendations for journals, reviewers, and authors.1 While we have made some efforts, such as a 2019 JAMIA double issue related to improving the reach and impact of health informatics to address health inequities including those related to race,2 there is no doubt that we can and must do more. However, JAMIA’s response to the recommendations requires reflection and discussion among our Associate Editors and Editorial Board as well as the American Medical Informatics Association’s Publications Committee. Once we have given this topic the careful deliberation it deserves, I will share our response with readers in a future editorial. In the JAMIA article summarizing the presentation of the Morris F. Collen Award to Octo, Bob Greenes describes not only Octo’s professional contributions, but also the significance of the 8. He writes that “Octo was named after his father. The possibly apocryphal story is that his father was the eighth son, born on the eighth day of the eighth month, in 1888.”3 For more information, the 2004 interview of Octo by Joan Ash and Dean Sittig entitled “From ‘Farm Boy’ to Director of the Laboratory of Computer Science” as part of the “Conversations with Medical Informatics Pioneers: An Oral History Collection” at the National Library of Medicine provides a fascinating view of Octo’s professional and personal life.4 There will be many opportunities to celebrate Octo’s legacy, but here I focus on the JAMIA perspective. Octo was the author of 6 JAMIA articles, the first in 1994 and the last in 2012, both coauthored with Henry Chueh.5–10 A 2006 sole-authored article was an extract of a report given by Octo to the National Institutes of Health 40 years earlier.9 Remarkably, among 7 areas of concern that he identified, 2 resonate more than 50 years later—the need for evolutionary approaches for computer-based systems and transferability among institutions. The discussion list of the American College of Medical Informatics has been filled with heartwarming stories about the influence of Octo on their careers and highlighted the multitude of progeny that can be traced back to him in some way. In celebration of Octo’s legacy, I selected the highlights for this issue based on the linkage of 1 of more authors in an article to him directly as a trainee or close collaborator in the Laboratory of Computer Science or from his academic descendants. As a remarkable measure of his influence, I had a least 7 to choose from in my queue of available articles for this issue. Appropriate to celebrating the co-developer of the COmputer-STored Ambulatory Record (COSTAR), one of the first electronic health records (EHRs) in the United States, I selected articles that focus on some aspect of the EHR, including policy aspects of adoption, quality and use of its contents for care and research, and its influence on clinicians. Adler-Milstein et al11 considered the question of whether U.S. hospitals have adopted EHR functions to support age-friendly care focusing on structured documentation of the 4Ms (What Matters, Medication, Mentation, and Mobility) and electronic health information exchange or communication with patients, caregivers, and long-term care providers. Using an online survey of 797 U.S. acute care hospitals in 2018-2019 with a 60.1% response rate, they found that only 41.5% had structured documentation of the 4Ms fully implemented across all units with medications the highest and mentation the lowest area. Less than 8% had implemented all exchange or communication functions across all units. Less than half of hospitals had an EHR portal for long-term care facilities to access hospital information or sent information electronically to long-term care facilities; about a third had training for adults or caregivers on the patient portal. The authors concluded that U.S. acute care hospital EHRs lack key functions that support age-friendly care and that additional policy efforts are needed to enhance EHR implementations to include such high-value functions. Everson et al13 also addressed the topic of hospital adoption of EHRs.12 They argued that a 2009 New England Journal of Medicine article that stated that only 9% of U.S. hospitals had adopted a basic EHR system became a memetic anchor point for EHR adoption at the dawn of the Health Information Technology for Economic and Clinical Health Act and that alternative approaches to treatment of the data may have led to a different sense of U.S. hospitals’ EHR adoption and, subsequently, a difference in public policy. To support this argument, they reanalyzed the 2008 American Heart Association Information Technology supplement and complementary sources to produce a range of estimates of EHR adoption and plotted an alternative definition of national progress toward hospital EHR adoption from 2008 to 2018. Their findings suggest that by 2008, the majority of hospitals had adopted at least 6 of the 10 functionalities of a basic system, and they estimated that 30%, rather than 9%, of hospitals had adopted a basic EHR. This larger estimate of basic EHR adoption could have resulted in different public policy. Wang and Wright14 characterized EHR problem list completeness and duplications through a retrospective analysis of EHR data from Partners HealthCare. They analyzed the problem lists of patients within 8 common chronic disease groups for completeness and duplications and examined associations with disease type, patient demographics, and disease severity. Among 327 695 unique patients with 383 404 problem list entries, completeness varied from 72.9% in hypertension to 93.5% in asthma, and duplications varied from 4.8% in hypertension to 28.2% in diabetes. There was a variable relationship between demographic factors and rates of completeness and duplications. However, disease severity was positively correlated with both completeness and duplications. The authors called for further research on user behaviors and organizational policies related to the problem list as the foundation for interventions to improve its utility for care. An article by Ahuja et al15 includes among its coauthors Octo’s long-time collaborator Shawn Murphy. The authors addressed a major bottleneck hindering utilization of EHR data for translational research—the lack of precise phenotype labels—by proposing a fully automated topic modeling algorithm to simultaneously annotate multiple phenotypes. The method, sureLDA (surrogate-guided ensemble latent Dirichlet allocation), is a label-free multidimensional phenotyping method that (1) uses the PheNorm algorithm to initialize probabilities based on 2 surrogate features for each target phenotype, (2) leverages these probabilities to constrain the latent Dirichlet allocation topic model to generate phenotype-specific topics, and (3) combines phenotype-feature counts with surrogates via clustering ensemble to yield final phenotype probabilities. Evaluation of sureLDA supports its high accuracy and precision across a range of simulated and real-world phenotypes as well as its suitability for large-scale EHR phenotyping for applications such as phenome-wide association studies. Co et al16 described the potential tradeoffs between safety and EHR-based alert fatigue using data from a natural survey of hospital medication–related clinical decision support. They analyzed data from 1599 hospitals that completed the Computerized Physician Order Entry Evaluation Tool in both 2017 and 2018 and examined overall performance on the evaluation tool as well as the percentages of appropriate fatal order alerts and inappropriate nuisance order alerts. Percentage of appropriate fatal order performance demonstrated a statistically significant increase from 78.8% to 83.0%, but there was no significant change in percentage of inappropriate nuisance order performance. Hospitals alerting on 1 or more nuisance orders had a 3-percentage-point increase in their overall score on the evaluation tool, raising the concern that some hospitals may be achieving higher scores at the cost of overalerting; this has the potential to negatively influence clinician burnout and worsen safety. Octo will be missed, but there is no doubt that his influence on our field will live on. CONFLICT OF INTEREST STATEMENT None declared. REFERENCES 1 Boyd RW , Lindo EG , Weeks LD , McLemore MR. On racism: a new standard for publishing on racial health inequities. https://www.healthaffairs.org/do/10.1377/hblog20200630.939347/full/ Accessed July 8, 2020. 2 Veinot TC , Ancker JS , Bakken S. Health informatics and health equity: improving our reach and impact . J Am Med Inform Assoc 2019 ; 26 ( 8–9 ): 689 – 95 . Google Scholar Crossref Search ADS PubMed WorldCat 3 Greenes RA. Presentation of the Morris F. Collen Award to G. Octo Barnett, MD, by Robert A. Greenes, MD, PhD . J Am Med Inform Assoc 1997 ; 4 ( 2 ): 155 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat 4 Barnett GO. From ‘Farm Boy’ to Director of the Laboratory of Computer Science: 2004 Interview of G. Octo Barnett. In: Goodwin RM , Ash JS , Sittig DF , eds. Conversations with Medical Informatics Pioneers: An Oral History Collection . Bethesda, MD : U.S. National Library of Medicine (NLM ); 2015 . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 5 Chueh HC , Barnett GO. Client-server, distributed database strategies in a health-care record system for a homeless population . J Am Med Inform Assoc 1994 ; 1 ( 2 ): 186 – 98 . Google Scholar Crossref Search ADS PubMed WorldCat 6 Barnett GO. Information technology and medical education . J Am Med Inform Assoc 1995 ; 2 ( 5 ): 285 – 91 . Google Scholar Crossref Search ADS PubMed WorldCat 7 Humphreys BL , Lindberg DA , Schoolman HM , Barnett GO. The Unified Medical Language System: an informatics research collaboration . J Am Med Inform Assoc 1998 ; 5 ( 1 ): 1 – 11 . Google Scholar Crossref Search ADS PubMed WorldCat 8 Ohno-Machado L , Gennari JH , Murphy SN , et al. The guideline interchange format: a model for representing guidelines . J Am Med Inform Assoc 1998 ; 5 ( 4 ): 357 – 72 . Google Scholar Crossref Search ADS PubMed WorldCat 9 Barnett GO. Report to the National Institutes of Health Division of Research Grants Computer Research Study Section on computer applications in medical communication and information retrieval systems as related to the improvement of patient care and the medical record–September 26, 1966 . J Am Med Inform Assoc 2006 ; 13 ( 2 ): 127 – 37 . Google Scholar Crossref Search ADS PubMed WorldCat 10 Feldman MJ , Hoffer EP , Barnett GO , Kim RJ , Famiglietti KT , Chueh H. Presence of key findings in the medical record prior to a documented high-risk diagnosis . J Am Med Inform Assoc 2012 ; 19 ( 4 ): 591 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat 11 Adler-Milstein J , Raphael K , Bonner A , Pelton L , Fulmer T. Hospital adoption of EHR functions to support age-friendly care: results from a national survey . J Am Med Inform Assoc 2020 ; 27 ( 8 ). 1205–1212. doi: 10.1093/jamia/ocaa129. OpenURL Placeholder Text WorldCat 12 Everson J , Rubin JC , Friedman CP. Reconsidering hospital EHR adoption at the dawn of HITECH: Implications of a reported 9% adoption of a “basic” EHR . J Am Med Inform Assoc 2020 ; 27 ( 8 ). 1197--1204. OpenURL Placeholder Text WorldCat 13 Jha AK , DesRoches CM , Campbell EG , et al. Use of electronic health records in US hospitals . N Engl J Med 2009 ; 360 ( 16 ): 1628 – 38 . Google Scholar Crossref Search ADS PubMed WorldCat 14 Wang EC , Wright A. Characterizing outpatient problem list completeness and duplications in the electronic health record . J Am Med Inform Assoc 2020 ; 27 ( 8 ). 1189--1196. OpenURL Placeholder Text WorldCat 15 Ahuja Y , Zhou D , Zeling H , et al. sureLDA: A multidisease automated phenotyping method for the electronic health record . J Am Med Inform Assoc 2020 ; 27 ( 8 ). 1235--1243. OpenURL Placeholder Text WorldCat 16 Co Z , Holmgren AJ , Classen DC , et al. The tradeoffs between safety and alert fatigue: Data from a national evaluation of hospital medication-related clinical decision support . J Am Med Inform Assoc 2020 ; 27 ( 8 ). 1252--1258. OpenURL Placeholder Text WorldCat © The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Journal

Journal of the American Medical Informatics Association – Oxford University Press

Published: Aug 1, 2020

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