Informatics as Science.

The evolution of the informatics field, now with a well-accepted and crucial role in modern biomedicine and health care delivery, is the result of creative research over seven decades. The success is due in part to recognition that, throughout the process, investigators have documented not only what they have done but what they have learned, stimulating and guiding the next generation of projects. Such iterative experimentation, learning, sharing, and progressing is typical of all scientific disciplines. Yet progress depends on identifying key lessons, insights, and methods so that others can use them. This paper addresses the nature of scientific progress in informatics, recognizing that while the field is motivated by applications that can improve biomedicine and health, the scientific underpinnings must be identified and shared with others if the field is to progress optimally.

Donald A.B. Lindberg and the U.S. National Library of Medicine transformed biomedical and health informatics.

This overview summary of the Informatics Section of the book Transforming biomedical informatics and health information access: Don Lindberg and the U.S. National Library of Medicine illustrates how the NLM revolutionized the field of biomedical and health informatics during Lindberg's term as NLM Director. Authors present a before-and-after perspective of what changed, how it changed, and the impact of those changes.

Donald A.B. Lindberg, pioneer in biomedical and health informatics: His involvement in creating professional organizations.

Among the many contributions of Donald A.B. Lindberg was his work on behalf of a variety or professional organizations in the field of biomedical and health informatics. These began during his early days at the University of Missouri and continued throughout his 30 years at the National Library of Medicine. This chapter summarizes that work, which occurred both through his personal efforts and through the impact of the NLM under his leadership. Examples include his role in the development of organizations themselves (e.g., the International Medical Informatics Association, the American College of Medical Informatics, and the American Medical Informatics Association) and also his contributions to the professional scientific meetings that have advanced the field (e.g., the Symposium on Computer Applications in Medical Care, MEDINFO, and the AMIA Annual Symposium).

A tribute to Karen Greenwood and her contributions to the American Medical Informatics Association.

After 25 years of service to the American Medical Informatics Association (AMIA), Ms Karen Greenwood, the Executive Vice President and Chief Operating Officer, is leaving the organization. In this perspective, we reflect on her accomplishments and her effect on the organization and the field of informatics nationally and globally. We also express our appreciation and gratitude for Ms Greenwood's role at AMIA.

Donald A.B. Lindberg and the U.S. National Library of Medicine Transformed Biomedical and Health Informatics.

This overview summary of the Informatics Section of the book Transforming biomedical informatics and health information access: Don Lindberg and the U.S. National Library of Medicine illustrates how the NLM revolutionized the field of biomedical and health informatics during Lindberg's term as NLM Director. Authors present a before-and-after perspective of what changed, how it changed, and the impact of those changes.

Donald A.B. Lindberg, Pioneer in Biomedical and Health Informatics: His Involvement in Creating Professional Organizations.

Among the many contributions of Donald A.B. Lindberg was his work on behalf of a variety or professional organizations in the field of biomedical and health informatics. These began during his early days at the University of Missouri and continued throughout his 30 years at the National Library of Medicine. This chapter summarizes that work, which occurred both through his personal efforts and through the impact of the NLM under his leadership. Examples include his role in the development of organizations themselves (e.g., the International Medical Informatics Association, the American College of Medical Informatics, and the American Medical Informatics Association) and also his contributions to the professional scientific meetings that have advanced the field (e.g., the Symposium on Computer Applications in Medical Care, MEDINFO, and the AMIA Annual Symposium).

The roles of the US National Library of Medicine and Donald A.B. Lindberg in revolutionizing biomedical and health informatics.

Over a 31-year span as Director of the US National Library of Medicine (NLM), Donald A.B. Lindberg, MD, and his extraordinary NLM colleagues fundamentally changed the field of biomedical and health informatics-with a resulting impact on biomedicine that is much broader than its influence on any single subfield. This article provides substance to bolster that claim. The review is based in part on the informatics section of a new book, "Transforming biomedical informatics and health information access: Don Lindberg and the US National Library of Medicine" (IOS Press, forthcoming 2021). After providing insights into selected aspects of the book's informatics-related contents, the authors discuss the broader context in which Dr. Lindberg and the NLM accomplished their transformative work.

DISCARDED MEDICATIONS IN VIALS ARE A SYMPTOM OF OUR HEALTH CARE SYSTEM: A CALL TO ACTION.

DISCLOSURES: No funding was received for the writing of this letter. All authors were members of the National Academies study committee to which this letter refers, with Shortliffe as the chair. All committee members who contributed to the report were themselves vetted for potential conflicts of interest, as is described in the recently published version of the report. Lieu is an employee of Kaiser Permanente and the content does not represent the official views of Kaiser Permanente. The other authors have nothing to disclose.

Comparison of an oncology clinical decision-support system's recommendations with actual treatment decisions.

OBJECTIVE: IBM(R) Watson for Oncology (WfO) is a clinical decision-support system (CDSS) that provides evidence-informed therapeutic options to cancer-treating clinicians. A panel of experienced oncologists compared CDSS treatment options to treatment decisions made by clinicians to characterize the quality of CDSS therapeutic options and decisions made in practice. METHODS: This study included patients treated between 1/2017 and 7/2018 for breast, colon, lung, and rectal cancers at Bumrungrad International Hospital (BIH), Thailand. Treatments selected by clinicians were paired with therapeutic options presented by the CDSS and coded to mask the origin of options presented. The panel rated the acceptability of each treatment in the pair by consensus, with acceptability defined as compliant with BIH's institutional practices. Descriptive statistics characterized the study population and treatment-decision evaluations by cancer type and stage. RESULTS: Nearly 60% (187) of 313 treatment pairs for breast, lung, colon, and rectal cancers were identical or equally acceptable, with 70% (219) of WfO therapeutic options identical to, or acceptable alternatives to, BIH therapy. In 30% of cases (94), 1 or both treatment options were rated as unacceptable. Of 32 cases where both WfO and BIH options were acceptable, WfO was preferred in 18 cases and BIH in 14 cases. Colorectal cancers exhibited the highest proportion of identical or equally acceptable treatments; stage IV cancers demonstrated the lowest. CONCLUSION: This study demonstrates that a system designed in the US to support, rather than replace, cancer-treating clinicians provides therapeutic options which are generally consistent with recommendations from oncologists outside the US.

Effect of an Artificial Intelligence Clinical Decision Support System on Treatment Decisions for Complex Breast Cancer.

PURPOSE: To examine the impact of a clinical decision support system (CDSS) on breast cancer treatment decisions and adherence to National Comprehensive Cancer Center (NCCN) guidelines. PATIENTS AND METHODS: A cross-sectional observational study was conducted involving 1,977 patients at high risk for recurrent or metastatic breast cancer from the Chinese Society of Clinical Oncology. Ten oncologists provided blinded treatment recommendations for an average of 198 patients before and after viewing therapeutic options offered by the CDSS. Univariable and bivariable analyses of treatment changes were performed, and multivariable logistic regressions were estimated to examine the effects of physician experience (years), patient age, and receptor subtype/TNM stage. RESULTS: Treatment decisions changed in 105 (5%) of 1,977 patients and were concentrated in those with hormone receptor (HR)-positive disease or stage IV disease in the first-line therapy setting (73% and 58%, respectively). Logistic regressions showed that decision changes were more likely in those with HR-positive cancer (odds ratio [OR], 1.58; P < .05) and less likely in those with stage IIA (OR, 0.29; P < .05) or IIIA cancer (OR, 0.08; P < .01). Reasons cited for changes included consideration of the CDSS therapeutic options (63% of patients), patient factors highlighted by the tool (23%), and the decision logic of the tool (13%). Patient age and oncologist experience were not associated with decision changes. Adherence to NCCN treatment guidelines increased slightly after using the CDSS (0.5%; P = .003). CONCLUSION: Use of an artificial intelligence-based CDSS had a significant impact on treatment decisions and NCCN guideline adherence in HR-positive breast cancers. Although cases of stage IV disease in the first-line therapy setting were also more likely to be changed, the effect was not statistically significant (P = .22). Additional research on decision impact, patient-physician communication, learning, and clinical outcomes is needed to establish the overall value of the technology.

Artificial Intelligence Treatment Decision Support For Complex Breast Cancer Among Oncologists With Varying Expertise.

PURPOSE: The aim of the current study was to assess treatment concordance and adherence to National Comprehensive Cancer Network breast cancer treatment guidelines between oncologists and an artificial intelligence advisory tool. PATIENTS AND METHODS: Study cases of patients (N = 1,977) who were at high risk for recurrence or who had metastatic disease and cell types for which the advisory tool was trained were obtained from the Chinese Society for Clinical Oncology cancer database (2012 to 2017). A cross-sectional observational study was performed to examine treatment concordance and guideline adherence among an artificial intelligence advisory tool and 10 oncologists with varying expertise-three fellows, four attending physicians, and three chief physicians. In a blinded fashion, each oncologist provided treatment advice on an average of 198 cases and the advisory tool on all cases (N = 1,977). Results are reported as rates and logistic regression odds ratios. RESULTS: Concordance for the recommended treatment was 0.56 for all physicians and higher for fellows compared with chief and attending physicians (0.68 v 0.54; 0.49; P = .001). Concordance differed by hormone receptor subtype-TNM stage, with the lowest for hormone receptor-positive human epidermal growth factor receptor 2/neu-positive cancers (0.48) and highest for triple-negative breast cancers (0.71) across most TNM stages. Adherence to National Comprehensive Cancer Network guidelines was higher for oncologists compared with the advisory tool (0.96 v 0.82; P < .003) and lower for fellows compared with attending physicians (0.93 v 0.98; 0.96; P = .04). CONCLUSION: Study findings reflect a complex breast cancer case mix, the limits of medical knowledge regarding optimum treatment, clinician practice patterns, and use of a tool that reflects expertise from one cancer center. Additional research in different practice settings is needed to understand the tool's scalability and its impact on treatment decisions and clinical and health services outcomes.