Clinical Informatics Sub-Specialty Board Certification

Lehmann, Christoph U.; Shorte, Vanessa; Gundlapalli, Adi V.

doi:10.1542/pir.34-11-525

Cited by 15 publications

(14 citation statements)

References 14 publications

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“…The objectives are to describe the history, pathways, and motivations for certification in nursing informatics and compare and contrast those with board certification in clinical informatics for physicians recently addressed elsewhere [20][21][22][23].…”

Section: Discussionmentioning

confidence: 99%

“…Nursing and physician certification processes share similarities with regard to skills and competencies required to demonstrate eligibility for and maintain certification in their fields. The motivation and need for obtaining formal [20], [22], [39], [40], [42] Informatics competencies as listed on the outline for board certification: leading and managing change, health information systems, fundamentals of informatics, clinical decision making and care process improvement, legal, ethical, and regulatory issues Eligibility is limited to physicians with MD or DO degree; current, unrestricted medical license in the U.S.; current American board certification in primary clinical discipline or pathology Continuing education needs for maintenance of certification; requires examination once every 10 years certification may be driven by prospects for positions in the field. However, this remains to be seen with respect to physicians, who at present do not need formal board certification in clinical informatics to take operational, teaching, research, or leadership positions such as chief health or medical informatics officers or directors of clinical informatics.…”

Section: Discussionmentioning

confidence: 99%

“…A recent position paper by the American Medical Informatics Association (AMIA) addresses the emerging role of Chief Clinical Informatics Officer (CCIO), a role that combines the Chief Medical/Nursing/Dental/ Pharmacy Informatics Officer roles [15]. For physicians, Clinical Informatics was recognized in 2011 as a medical subspecialty in the U.S. [20,22]. This was the culmination of a 6-year effort by the American Medical Informatics Association (AMIA) [38].…”

Section: Comparison Of Informatics Certification Processes For Nursesmentioning

confidence: 99%

“…One of the motivations for the U.S. subspecialty certification was the recognition that informatics is now considered an essential component to the practice, education, and research aspects of all medical specialties and subspecialties [22,42]. In the short-term, it is anticipated that the ability to show competency and expertise in this new field will act as a catalyst for the training and recruitment of experts to advance clinical informatics in hospitals and practices.…”

Section: Comparison Of Informatics Certification Processes For Nursesmentioning

confidence: 99%

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Transforming Data into Knowledge: How to Improve the Efficiency of Clinical Care?

Séroussi¹,

Soualmia²,

Holmes³

2017

Yearb Med Inform

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Summary Objectives: To provide an introduction to the 2017 IMIA Yearbook of Medical Informatics by the editors. Methods: We present a brief overview of the 2017 special topic “Learning from experience: Secondary use of patient data”. We review our choice of special topic section editors, present the new section “Health Information Management”, and discuss transitions in the editorial team. Results: In this edition of the Yearbook, we focused on one of the most important issues for the medical informatics community: The secondary use of clinical data. With the ubiquitous adoption of electronic health records (EHRs) and the increasing availability of genomic and environmental data, as well as the accessibility of unstructured data in social media, issues related to data integration, storage, and management, as well as the need for novel analytic approaches are clear challenges. The paradigm of Learning Health Systems (LHSs) is presented in the keynote paper and survey papers review the significant developments in allied fields such as clinical research, clinical systems, translational informatics, and public health over the past two years. IMIA Working Groups also contributed to this topic. Conclusion: The 2017 issue of the IMIA yearbook focuses on the secondary use of patient data and presents the difficulties that still need to be solved before witnessing the actual development of LHSs.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Comparison Of Informatics Certification Processes For Nursesmentioning

confidence: 99%

Section: Comparison Of Informatics Certification Processes For Nursesmentioning

confidence: 99%

See 2 more Smart Citations

Transforming Data into Knowledge: How to Improve the Efficiency of Clinical Care?

Séroussi¹,

Soualmia²,

Holmes³

2017

Yearb Med Inform

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“…In addition, there has been signifi cant innovation in the United States in Pathology Informatics in the last three decades including the pathology informatics role in bioinformatics [ 4 ], imaging informatics including whole slide imaging [ 51 , 72 ], molecular pathology informatics [ 28 ], telepathology [ 72 ], tissue banking informatics [ 4 ] as well as many of the more modern innovations to the LIS that have occurred since the pioneering work described by Dr. Collen For an in depth look at the current innovations going on in Pathology Informatics see the Journal of Pathology Informatics ( http://www.jpathinformatics.org ). An important example of this is Pathology Informatics' instrumental role and also the American Board of Pathology's joint sponsorship with the American Board of Preventative Medicine for the new Clinical Informatics board certifi cation under the American Board of Medical Specialties [ 43 ]. The future of Pathology Informatics is extremely bright and we are grateful to Dr. Collen for so accurately refl ecting its early history and foundations in biomedical informatics.…”

Section: Summary and Commentarymentioning

confidence: 99%

Anatomic Pathology Information Laboratory Information Systems and Natural Language Processing: Early History

Carter

Becich

Collen³

2015

Health Informatics

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Anatomic Pathology laboratories began to encode and retrieve diagnoses from paper reports using punched cards in the 1960s. When Anatomic Pathology Laboratory Information systems (APLIS) began to be used in the 1970s, pathology departments found that searching free text for diagnoses was hindered by the variability of terms for the same concept and by the amount of computer resources required. Consequently, system developers began to engineer natural language processing (NLP) algorithms to translate computationally ambiguous written language into coded concepts. At the same time, pathologists began to develop the Systemized Nomenclature of Pathologists (SNOP), which eventually developed into the internationally utilized ontology called the Systematized Nomenclature of Medicine Clinical Terms (SNOMED-CT). Systems in the 1970s used keywords based on concepts to encode reports and the development of query languages to retrieve them. By the 1980s, the user was guided through decision trees to the best matching concept code from data dictionaries that linked pathology systems with medical record systems, and linguistic analysis that converted natural language into a structured database. At that time, some advanced NLP systems had knowledge bases that indicated how experts would interpret the meaning of words in particular contexts, but most query languages were still based on the search and retrieval of encoded terms. Much has occurred since then, including the recognition of Pathology Informatics as a discipline and the use of many NLP algorithms as well as algorithms to scrub identifi ers from free text reports for research purposes.

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A Review of Analytics and Clinical Informatics in Health Care

et al. 2014

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Federal investment in health information technology has incentivized the adoption of electronic health record systems by physicians and health care organizations; the result has been a massive rise in the collection of patient data in electronic form (i.e. "Big Data"). Health care systems have leveraged Big Data for quality and performance improvements using analytics-the systematic use of data combined with quantitative as well as qualitative analysis to make decisions. Analytics have been utilized in various aspects of health care including predictive risk assessment, clinical decision support, home health monitoring, finance, and resource allocation. Visual analytics is one example of an analytics technique with an array of health care and research applications that are well described in the literature. The proliferation of Big Data and analytics in health care has spawned a growing demand for clinical informatics professionals who can bridge the gap between the medical and information sciences.

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Clinical Informatics Sub-Specialty Board Certification

Cited by 15 publications

References 14 publications

Transforming Data into Knowledge: How to Improve the Efficiency of Clinical Care?

Transforming Data into Knowledge: How to Improve the Efficiency of Clinical Care?

Anatomic Pathology Information Laboratory Information Systems and Natural Language Processing: Early History

A Review of Analytics and Clinical Informatics in Health Care

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