Dean F. Sittig | |
---|---|
Born | Bellefonte, Pennsylvania, United States | March 2, 1961
Education | Pennsylvania State University (B.S., M.S.) University of Utah School of Medicine (Ph.D.) |
Employer | University of Texas Health Science Center at Houston |
Known for | Clinical informatics |
Spouse | JoAnn Kaalaas-Sittig |
Children | 1 |
Website | circleinformatics |
Dean Forrest Sittig (born March 2, 1961) is an American biomedical informatician specializing in clinical informatics. He is a professor in Biomedical Informatics at the University of Texas Health Science Center at Houston [1] and Executive Director of the Clinical Informatics Research Collaborative (CIRCLE). [2] Sittig was elected as a fellow of the American College of Medical Informatics in 1992, [3] the Healthcare Information and Management Systems Society in 2011, and was a founding member of the International Academy of Health Sciences Informatics in 2017. [4] Since 2004, he has worked with Joan S. Ash, a professor at Oregon Health & Science University to interview several Pioneers in Medical Informatics, [5] including G. Octo Barnett, MD, [6] Morris F. Collen, MD, [7] Donald E. Detmer, MD, [8] Donald A. B. Lindberg, MD, [9] Nina W. Matheson, ML, DSc, [10] Clement J. McDonald, MD, [11] and Homer R. Warner, MD, PhD. [12]
Sittig earned a bachelor's degree in science and a master's degree in biomedical engineering before he trained in medical informatics at the University of Utah School of Medicine and the LDS Hospital under Reed M. Gardner and Homer R. Warner. [13] His dissertation was entitled, “COMPAS: A Computerized Patient Advice System to Direct Ventilatory Care." [14] He won the 1987 Martin Epstein Award [15] at the Annual Symposium on Computer Applications in Medical Care (now the American Medical Informatics Association) for this work.
His research focuses on understanding the sociotechnical risks of, and solutions to address, unintended consequences associated with design, development, implementation, and use of various health information technologies (HIT), [16] including computer-based provider order entry, clinical decision support within electronic health records (EHRs), and most recently in EHR-related patient safety. Along with Hardeep Singh, he developed an “8-dimension socio-technical model for safe and effective HIT implementation and use”. [17] A modification of the model was used by the National Academy of Medicine (NAM), [18] in a sentinel event report from the Joint Commission, [19] and the National Quality Forum to describe the socio-technical challenges associated with measuring HIT safety. [20] This model has also been used in a variety of HIT-related research studies including: identification of keys to implementing novel clinical prediction algorithms, [21] exploring barriers to implementation of clinical information systems in nursing homes, [22] development of a childhood cancer passport for care, [23] and development of a questionnaire regarding EHR-related safety concerns. [24]
Sittig has published over 600 scientific articles [25] and 6 books. [26] (h-index = 82 [27] ).
In 1992 he was elected a Fellow of the American College of Medical Informatics (ACMI). [28] In 2017 he was elected an Inaugural Fellow of the International Academy of Health Sciences Informatics (IAHSI). [29] In 2019 he was elected a Fellow of the American Medical Informatics Association (AMIA). [30] In 2023 he won the American Medical Informatics Association (AMIA) Donald Eugene Detmer Award for Health Policy Contributions in Informatics. [31]
Dean F. Sittig is married to Joann Kaalaas-Sittig. [32]
Health informatics is the study and implementation of computer structures and algorithms to improve communication, understanding, and management of medical information. It can be viewed as a branch of engineering and applied science.
An electronic health record (EHR) is the systematized collection of patient and population electronically stored health information in a digital format. These records can be shared across different health care settings. Records are shared through network-connected, enterprise-wide information systems or other information networks and exchanges. EHRs may include a range of data, including demographics, medical history, medication and allergies, immunization status, laboratory test results, radiology images, vital signs, personal statistics like age and weight, and billing information.
A clinical decision support system (CDSS) is a health information technology that provides clinicians, staff, patients, and other individuals with knowledge and person-specific information to help health and health care. CDSS encompasses a variety of tools to enhance decision-making in the clinical workflow. These tools include computerized alerts and reminders to care providers and patients, clinical guidelines, condition-specific order sets, focused patient data reports and summaries, documentation templates, diagnostic support, and contextually relevant reference information, among other tools. CDSSs constitute a major topic in artificial intelligence in medicine.
A personal health record (PHR) is a health record where health data and other information related to the care of a patient is maintained by the patient. This stands in contrast to the more widely used electronic medical record, which is operated by institutions and contains data entered by clinicians to support insurance claims. The intention of a PHR is to provide a complete and accurate summary of an individual's medical history which is accessible online. The health data on a PHR might include patient-reported outcome data, lab results, and data from devices such as wireless electronic weighing scales or from a smartphone.
Biomedical text mining refers to the methods and study of how text mining may be applied to texts and literature of the biomedical domain. As a field of research, biomedical text mining incorporates ideas from natural language processing, bioinformatics, medical informatics and computational linguistics. The strategies in this field have been applied to the biomedical literature available through services such as PubMed.
SNOMED CT or SNOMED Clinical Terms is a systematically organized computer-processable collection of medical terms providing codes, terms, synonyms and definitions used in clinical documentation and reporting. SNOMED CT is considered to be the most comprehensive, multilingual clinical healthcare terminology in the world. The primary purpose of SNOMED CT is to encode the meanings that are used in health information and to support the effective clinical recording of data with the aim of improving patient care. SNOMED CT provides the core general terminology for electronic health records. SNOMED CT comprehensive coverage includes: clinical findings, symptoms, diagnoses, procedures, body structures, organisms and other etiologies, substances, pharmaceuticals, devices and specimens.
Edward ("Ted") Hance Shortliffe is a Canadian-born American biomedical informatician, physician, and computer scientist. Shortliffe is a pioneer in the use of artificial intelligence in medicine. He was the principal developer of the clinical expert system MYCIN, one of the first rule-based artificial intelligence expert systems, which obtained clinical data interactively from a physician user and was used to diagnose and recommend treatment for severe infections. While never used in practice, its performance was shown to be comparable to and sometimes more accurate than that of Stanford infectious disease faculty. This spurred the development of a wide range of activity in the development of rule-based expert systems, knowledge representation, belief nets and other areas, and its design greatly influenced the subsequent development of computing in medicine.
The American Association for Medical Systems and Informatics (AAMSI) was an organization created to encourage improvements in the state of medical care by encouraging the development of computer systems for that field.
Homer Richards Warner was an American cardiologist who was an early proponent of medical informatics who pioneered many aspects of computer applications to medicine. Author of the book, Computer-Assisted Medical Decision-Making, published in 1979, he served as CIO for the University of Utah Health Sciences Center, as president of the American College of Medical Informatics, and was actively involved with the National Institutes of Health. He was first chair of the Department of Medical Informatics at the University of Utah School of Medicine, the first American medical program to formally offer a degree in medical informatics.
The Continuity of Care Document (CCD) specification is an XML-based markup standard intended to specify the encoding, structure, and semantics of a patient summary clinical document for exchange.
Health information technology (HIT) is health technology, particularly information technology, applied to health and health care. It supports health information management across computerized systems and the secure exchange of health information between consumers, providers, payers, and quality monitors. Based on a 2008 report on a small series of studies conducted at four sites that provide ambulatory care – three U.S. medical centers and one in the Netherlands, the use of electronic health records (EHRs) was viewed as the most promising tool for improving the overall quality, safety and efficiency of the health delivery system.
Clinical point of care (POC) is the point in time when clinicians deliver healthcare products and services to patients at the time of care.
E-referrals or electronic referrals or electronic consultation is an electronic platform that enables the seamless transfer of patient information from a primary to a secondary treating practitioner's client management system. E-referrals have fast become the best replacement of paper-based referrals, and hold great potential toward the ultimate goal of seamless communication and information sharing between practitioners.
Lawrence Leonard Weed was an American physician, researcher, educator, entrepreneur and author, who is best known for creating the problem-oriented medical record as well as one of the first electronic health records.
In 2005 the National Health Service (NHS) in the United Kingdom began deployment of electronic health record systems in NHS Trusts. The goal was to have all patients with a centralized electronic health record by 2010. Lorenzo patient record systems were adopted in a number of NHS trusts. While many hospitals acquired electronic patient records systems in this process, there was no national healthcare information exchange. Ultimately, the program was dismantled after a cost to the UK taxpayer was over $24 billion, and is considered one of the most expensive healthcare IT failures.
Morris Frank Collen was founder of the Kaiser Permanente Division of Research and an original member of the Permanente Medical Group, pioneering developer of Automated Multiphasic Health Testing (AMHT) systems, and Electronic Health Records (EHRs) for Public Health and Clinical Screening, serving as a model for pre-paid healthcare at the national level. Collen was a Founder of the American College of Medical Informatics (ACMI) in 1984, and the American Medical Informatics Association (AMIA) in 1989. The Morris F. Collen Award of Excellence was established in his honor by ACMI in 1993. In 1971 Collen was elected a member of the Institute of Medicine of the National Academy of Sciences.
Daniel Richard Masys is an American biotechnologist and academic. He is an Affiliate Professor of Biomedical and Health Informatics at the University of Washington.
Charles Safran is an American-born physician, biomedical informatician, and professor, who is known for his work regarding the use of health information technology (HIT) to improve the delivery and quality of healthcare, in particular clinical information systems.
Allison Beck McCoy is an American biomedical informatician focused on clinical informatics/health informatics. She is an associate professor of biomedical informatics and director of the clinical informatics core at the Vanderbilt University School of Medicine. She was elected a fellow of the American Medical Informatics Association and American College of Medical Informatics in 2018 and 2023 respectively.
Nigam Shah is a scientist, educator, and entrepreneur. His research is focused on the application of machine learning, knowledge representation, and artificial intelligence for the analysis of multiple types of health data. He is a professor of Medicine and Biomedical Data Science at Stanford University and the Chief Data Scientist at Stanford Health Care.