A PRODUÇÃO CENTÍFICA SOBRE COVID-19: ESTUDO EXPLORATÓRIO

Analisa a produção científica no campo da Ciência da Informação acerca da temática do coronavírus ou COVID-19. Tem como objetivo geral analisar as iniciativas e as publicações feitas sobre o tema coronavírus no campo da informação, especialmente nas áreas de Biblioteconomia e Ciência da Informação. Tem como objetivos específicos: mapear os principais periódicos utilizados para comunicação das pesquisas; identificar os programas ou instituições mais atuantes e reconhecer autores em destaque na temática. Utiliza de metodologia exploratória, com abordagem quantitativa. Busca suporte teórico na bibliometria e na cientometria. Constata a alta produção do campo acerca da temática. Detecta os primeiros resultados datando do ano de 2005, relacionados à síndrome respiratória aguda grave (SARS). Nota a explosão da produção do campo acerca da temática a partir do ano de 2020. Percebe o destaque dos periódicos Journal of the American Medical Informatics Association, dos Estados Unidos, e do Profesional de la Información, da Espanha, com 49 e 47 resultados, respectivamente. Observa a alta produtividade dos autores americanos, apresentando mais que o dobro de resultados em relação aos autores espanhóis, que figuram no segundo lugar em número de resultados. Evidencia a maior aparição de agências financiadoras americanas em relação a outras nacionalidades. Percebe o destaque em produtividade, entre as instituições, dos pesquisadores da University of London, da Inglaterra. Revela o destaque dos autores CONBOY, K.; DA CUNHA, M. B.; DWIVEDI, Y. K.; PAN, S. L.; PARKER, R. M. e WANG, H., com três resultados cada. Evidencia, entre os autores brasileiros, a predominância de publicações feitas no periódico AtoZ Novas Práticas em Informação e Conhecimento e a maior vinculação a instituições brasileiras em comparação a instituições estrangeiras.

Gender representation in U.S. biomedical informatics leadership and recognition

Objective This study sought to describe gender representation in leadership and recognition within the U.S. biomedical informatics community. Materials and Methods Data were collected from public websites or provided by American Medical Informatics Association (AMIA) personnel from 2017 to 2019, including gender of membership, directors of academic informatics programs, clinical informatics subspecialty fellowships, AMIA leadership (2014-2019), and AMIA awardees (1993-2019). Differences in gender proportions were calculated using chi-square tests. Results Men were more often in leadership positions and award recipients (P < .01). Men led 74.7% (n = 71 of 95) of academic informatics programs and 83.3% (n = 35 of 42) of clinical informatics fellowships. Within AMIA, men held 56.8% (n = 1086 of 1913) of leadership roles and received 64.1% (n = 59 of 92) of awards. Discussion As in other STEM fields, leadership and recognition in biomedical informatics is lower for women. Conclusions Quantifying gender inequity should inform data-driven strategies to foster diversity and inclusion. Standardized collection and surveillance of demographic data within biomedical informatics is necessary.

Measuring success: perspectives from three optimization programs on assessing impact in the age of burnout

Electronic health record (EHR) optimization has been identified as a best practice to reduce burnout and improve user satisfaction; however, measuring success can be challenging. The goal of this manuscript is to describe the limitations of measuring optimizations and opportunities to combine assessments for a more comprehensive evaluation of optimization outcomes. The authors review lessons from 3 U.S. healthcare institutions that presented their experiences and recommendations at the American Medical Informatics Association 2020 Clinical Informatics conference, describing uses and limitations of vendor time-based reports and surveys utilized in optimization programs. Compiling optimization outcomes supports a multi-faceted approach that can produce assessments even as time-based reports and technology change. The authors recommend that objective measures of optimization must be combined with provider and clinician-defined value to provide long term improvements in user satisfaction and reduce EHR-related burnout.

Recommendations for patient similarity classes: results of the AMIA 2019 workshop on defining patient similarity

Defining patient-to-patient similarity is essential for the development of precision medicine in clinical care and research. Conceptually, the identification of similar patient cohorts appears straightforward; however, universally accepted definitions remain elusive. Simultaneously, an explosion of vendors and published algorithms have emerged and all provide varied levels of functionality in identifying patient similarity categories. To provide clarity and a common framework for patient similarity, a workshop at the American Medical Informatics Association 2019 Annual Meeting was convened. This workshop included invited discussants from academics, the biotechnology industry, the FDA, and private practice oncology groups. Drawing from a broad range of backgrounds, workshop participants were able to coalesce around 4 major patient similarity classes: (1) feature, (2) outcome, (3) exposure, and (4) mixed-class. This perspective expands into these 4 subtypes more critically and offers the medical informatics community a means of communicating their work on this important topic.

P52 A baseline review of the activity of the PICU pharmacists using electronically captured data

AimTo date there are no metrics for the clinical pharmacist service to PICU. It is accepted that use of a Clinical Information Management System (CIMS) has a role in medication safety,1 however there are few studies that review the information potential of a CIMS for collecting pharmacist activity.2MethodAdditional fields and custom reports were configured in the CIMS to enable PICU pharmacists to record their activity in the following areas:Medicines reconciliation within 72 hours of admission to PICUDischarge kardex reviewAnalgesia and sedation (A&S) reviewClinical pharmacy reviewOther interventions & medication error reporting continued as per normal practice. Data was analysed using Microsoft Excel®.ResultsComplete data was available from July 2017 to end of 2018.There were 1274 medicines reconciliations by a pharmacist within 72 hours of admission (78% admissions). 14% of discharge kardexes had been reviewed prior to discharge to the ward. There was an average of 190 pharmacy reviews per 100 bed days. A total of 780 Pharmacist A&S Plans were documented by the clinical pharmacists – an average of 2 per working day, and 48% of admissions.Comparisons between each six month period showed a significant increase in the number of pharmacists medicines reconciliations (p<0.001). No other differences were found.ConclusionThis study has shown that electronic tracking of pharmacist ward activity is possible. It has the potential to demonstrate compliance with external or internal standards and audits. This data continues to be collected, and therefore these results will be used as a baseline to compare future activity. The findings of this study may encourage other units to replicate, providing data that can be used for comparison. Further configuration of the CIMS to capture other metrics such as TDM, and document discrepancies in medicines reconciliation is planned.ReferencesForni A, Chu H, Fanikos J. Technology Utilization to Prevent Medication Errors. Current Drug Safety. 2010;5:13–18.Nelson S, Poikonen J, Reese T, El Halta D, Weir C. The pharmacist and the EHR. Journal of the American Medical Informatics Association. 2016;24:193–197.Health and Information Quality Authority. Guidance for health and social care providers; Principles of good practice in medication reconciliation. Dublin: HIQA; 2014

Data Migration: A Thorny Issue in Electronic Health Record Transitions—Case Studies and Review of the Literature

Objective To review the existing literature regarding data migration during electronic health record (EHR)-to-EHR transitions and add two case studies on this topic. Methods Very few publications exist that detail the processes and potential pitfalls of data migration during EHR transitions. One of the authors participated in a panel discussion at the American Medical Informatics Association symposium in 2015; at the time, only five empiric or experiential research articles on any aspect of EHR transitions were available. Of those, only two mentioned their experiences with data migration or conversions. A detailed PubMed and CINAHL (Cumulative Index to Nursing and Allied Health Literature) search in March 2019 yielded only one more article giving details about data migration. Results The two new case studies contrast starkly: one relied on manual abstraction and data entry, whereas the other leveraged several electronic tools. The literature reflects this diversity of approach: no two sites have reported the same approaches. The authors identify nine domains of potential consequences of the currently available techniques and offer mitigating strategies. Discussion Very little empiric information exists in the peer-reviewed literature regarding data migrations during EHR-to-EHR transitions; yet the case studies reflect that much remains suitable for a prospective study. Conclusion This report adds two new case studies to the six already reported in the literature. There is a wide disparity in techniques of data migration, each with its own set of pros and cons, which sites must consider during an EHR-to-EHR transition. Such transitions would benefit from prospective research on evaluation and knowledge discovery.

Reducing Alert Burden in Electronic Health Records: State of the Art Recommendations from Four Health Systems

Background Electronic health record (EHR) alert fatigue, while widely recognized as a concern nationally, lacks a corresponding comprehensive mitigation plan. Objectives The goal of this manuscript is to provide practical guidance to clinical informaticists and other health care leaders who are considering creating a program to manage EHR alerts. Methods This manuscript synthesizes several approaches and recommendations for better alert management derived from four U.S. health care institutions that presented their experiences and recommendations at the American Medical Informatics Association 2019 Clinical Informatics Conference in Atlanta, Georgia, United States. The assembled health care institution leaders represent academic, pediatric, community, and specialized care domains. We describe governance and management, structural concepts and components, and human–computer interactions with alerts, and make recommendations regarding these domains based on our experience supplemented with literature review. This paper focuses on alerts that impact bedside clinicians. Results The manuscript addresses the range of considerations relevant to alert management including a summary of the background literature about alerts, alert governance, alert metrics, starting an alert management program, approaches to evaluating alerts prior to deployment, and optimization of existing alerts. The manuscript includes examples of alert optimization successes at two of the represented institutions. In addition, we review limitations on the ability to evaluate alerts in the current state and identify opportunities for further scholarship. Conclusion Ultimately, alert management programs must strive to meet common goals of improving patient care, while at the same time decreasing the alert burden on clinicians. In so doing, organizations have an opportunity to promote the wellness of patients, clinicians, and EHRs themselves.

Health informatics and health equity: improving our reach and impact

Health informatics studies the use of information technology to improve human health. As informaticists, we seek to reduce the gaps between current healthcare practices and our societal goals for better health and healthcare quality, safety, or cost. It is time to recognize health equity as one of these societal goals—a point underscored by this Journal of the American Medical Informatics Association Special Focus Issue, “Health Informatics and Health Equity: Improving our Reach and Impact.” This Special Issue highlights health informatics research that focuses on marginalized and underserved groups, health disparities, and health equity. In particular, this Special Issue intentionally showcases high-quality research and professional experiences that encompass a broad range of subdisciplines, methods, marginalized populations, and approaches to disparities. Building on this variety of submissions and other recent developments, we highlight contents of the Special Issue and offer an assessment of the state of research at the intersection of health informatics and health equity.

La Informática Médica en la formación de profesionales de la salud.

La solución de problemas en medicina requiere algunos elementos fundamentales como la representación de datos, almacenamiento y recuperación de información, procesamiento de señales e imágenes, sistemas expertos en medicina, estándares de comunicación, expedientes e historias clínicas del paciente y múltiples áreas de aplicación de la Informática Médica, que tienen repercusión directa en la calidad de atención al paciente. Por ende, no se trata solamente del uso de computadoras, smartphones u otros dispositivos en la práctica de medicina, sino como lo sugiere la American Medical Informatics Association (AMIA), “Es el campo científico interdisciplinario que estudia y persigue el uso efectivo de datos, información y conocimientos biomédicos, para la indagación científica, la solución de problemas y la toma de decisiones, motivada por los esfuerzos para mejorar la salud humana”.