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This entry is out of date, and will not be updated, June 2017
Clinical informatics is a scientific and information-based discipline that focuses on implementing knowledge management systems to prevent disease, deliver efficient and safe patient care, increase translational research, and improve biomedical knowledge systems. According to Gardner (2009), "...clinical informaticians transform health care by analyzing, designing, implementing, and evaluating information and communication systems that enhance individual and population health outcomes, improve patient care, and strengthen the clinician-patient relationship". Further, informaticians use their knowledge of patient care combined with their understanding of informatics concepts, methods, and health informatics tools to:
A focus of clinical informatics is the electronic health record (EHR). Informatics is an intensely data-driven discipline but most of the information in the discipline is paper-based. Important health information about individuals is scattered across many systems that do not, and cannot, communicate with each other; clinical informatics seeks to resolve some of these issues. The Health Level Seven International. Introduction to HL7 Standards is a good starting point to learn about standards in communicating patient data across systems, jurisdictions and national boundaries.
Clinical data management
As a subset of clinical informatics, clinical data management may involve one or more of the following areas & functions:
Moreover, clinical data management (CDM) consists of various activities involving the handling of data or information outlined in a study protocol. A wide range of computer software and hardware have been successful in making clinical data management an important information discipline. Clinical data management systems (CDMSs) are based on centralized data management and electronic data capture, and place data queries at the point of collection in the clinic. These systems have helped to eliminate problems with multiple data entry and reducing query costs.
One of the benefits of implementing a CDM system is the ability to mine data from it. Large datasets from patient records can inform the way that doctors make decisions in treating their patients.
Various CDM systems available
Oracle Clinical is an integrated trial management system with specialized modules integrated via the Oracle database management system. Oracle has assembled its suite from various clinical products and companies that it has acquired; now with the acquisition of Phase Forward it will be performing additional major integration. The EDC module is called Oracle RDC (Remote Data Capture).
Open source software is software that does not have its program code hidden, and therefore can be modified by any programmer and redistributed. Other examples of open-source software in widespread use are the Linux operating system and Firefox web browser. According to a presentation by Cal Collins at the 2009 Association of Clinical Research Professionals conference, eClinica has 200 adopters and 6000 “community members” worldwide, the latter being people who use, critique, and/or modify eClinica modules. A no-cost Internet-hosted open-source set of applications created by a consortium of volunteer software developers, managed centrally by (currently 3-person) eClinica in Belgium (which is a consulting services company).
Role for librarians in big data
A future role for librarians is to help locate and utilize data from clinical trials. When speaking of this patient-driven data, we are referring to information that results from conducting experiments and clinical trials in biomedicine in formats such as datasets, microarray, numerical data, clinical trial data, textual records, images and multimedia. This data (Big data)is critical to researchers as they do their work and validates findings, observations and hypotheses. By making data open you encourage efficient knowledge production - which is recognized as critical to solving society's most pressing problems.
Government investment in information technologies in Canada has increased the rate of adoption of electronic health record systems, with a concomitant rise in the collection of patient data (i.e. "Big Data"). Information systems in data management aim for quality and performance improvements using analytics - or, the systematic use of data combined with quantitative as well as qualitative analysis to make decisions. Informatics-analytics have been utilized in health including risk assessment, decision support, home health monitoring, and resource allocation. Visual analytics is an example of analytics. Big data and analytics have created demand for clinical informatics professionals who can navigate the gap between the medical and information sciences.