Translational Medicine Is a New Term Paper

Pages: 15 (4711 words)  ·  Bibliography Sources: ≈ 29  ·  File: .docx  ·  Level: Master's  ·  Topic: Medicine

BI's ability should be managed towards exploring information on human medicine as its ultimate pursuit. Bioinformatics methods are meant to identify molecular and cellular areas or aspects for specific clinical interventions and better insights into the profile of the disease. Imaging informatics are designed to understand pathogenesis and identification of treatment from the molecular, cellular, tissue or organ level. Innovations are aimed at improving patient care by providing relevant information at the bedside. And public health informatics solutions address population-based needs. These needs may be the tracking of emergent infectious diseases, the development of resources as response; and the evaluation of the latest clinical interventions affecting the population (Sarkar).

Information Needs and Principles of Information Retrieval

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Lancaster and Warner (1993 as qtd in Mendonca et al. 2001) identified three basic types of information needs. These are the need to solve a certain problem or arrive at a decision; the need for background information; and the need for updated information on a particular subject. Studies showed that physician information needs center mostly on patients' problems, categorized as diagnosis or treatment. These most often occur in primary care and practice-related rather than generalized. Most frequent questions were on the causes of symptoms, drug dosage and treatment. Nurses' information needs, on the other hand, were mostly patient-specific. These referred to general nursing care, medication administration, and laboratory reports. Their other information needs were for institution-specific and domain knowledge. Other studies revealed that the regular use of computers was only a few times a month by practitioners in hospital units, ambulatory clinics, office-based practices and a clinical pharmacy group (Mendonca et al.).

Term Paper on Translational Medicine Is a New Assignment

Evidence-based practice is defined as the responsible, open and proper use of the current and best evidence in making decisions on care (Mendonca et al. 2001). It focuses on diagnosis, etiology, prognosis, therapy, prevention, and other clinical and health care matters. It needs to access, summarize and apply information for daily operations and clinical situations. Doing so involves a process, consisting of four basic steps. These are rephrasing their information needs into clear questions; effectively locating the best evidence to answer the questions; critically validating the evidence and its clinical usefulness; and evaluating its outcome in clinical application (Mendonca et al.).

Information Retrieval

Information retrieval systems are used to organize and obtain relevant information from databases (Landers 2010). This is done when a request is made to the computer system to retrieve the information from the databases. The most popular information retrieval tool in the field of biomedical informatics is the PubMed Interface to the MEDLINE citation database. It not only contains substantial information in biomedicine but is also quite effective in Bioinformatics. These systems can be drawn from existing as well as developing approaches within the biomedical information community, such as the contemporary semantic web technologies. That capability to efficiently identify relevant data is crucial in building the knowledge that will cross the translational barriers. This ability has been demonstrated by GenBank and MEDLINE (Landers).

Electronic Health Records

A patient's encounters with the health care system are inputted into medical charts in addition to the data taken down by direct care providers (Landers 2010). These medical charts are now evolved and computerized as electronic health records or EHRs from paper-based medical documents. These are data from ancillary services, like radiology, laboratory and pharmacy. They have become available across health care. EHRs can include varied information constructed by clinicians from the patient's bedside. They can also have electronic interfaces to individual services, such as administrative, laboratory, radiology and pharmacy. Many of these can be used and inputted into the computerized provider order entry or CPOE. Through CPOE, clinicians can electronically order services and tap real-time clinical decision support features. One such feature is a warning about an order that may have adverse effects (Landers).

Overwhelming large amounts of available electronic health data can have significant impact on translational medicine (Landers 2010). Personal health projects, like Google Health and consumer services, can generate more genotype and phenotype data for analysis and support for community-based studies. Massive data proceeding from consumer-driven grassroots effort may produce the next breakthroughs. These and core biomedical informatics retrieval techniques can be used with HER-based data in crossing translational barriers (Landers).

The Biomedical Informatician in the Translational Medicine Team

He has a unique education, with expertise in at least one area (Landers 2010). That

expertise is meant to enable trans-disciplinary team science and needed by translational medicine to succeed. The biomedical informatician is able to interact with key stakeholders across the translational medicine realm. This may consist of biologists, clinicians, clinical researchers, epidemiologists and health service researchers. The biomedical informatician's role is so important that his addition into the team will more than determine its success. That success also depends on the team's understanding of biomedical informatics. With this view in mind, the importance of a biomedical informatics is a key consideration in the entire field of translational medicine. The biomedical informatics expertise infused into the team should also complement the requisite domain expertise. Hence, the biomedical informatician's synergistic relationship with the other team members has become a major challenge in the pursuit of breakthroughs in translational medicine (Landers).

A Model IR Technology

A model was presented to demonstrate these functions. It integrates a querying module, which uses evidence-based principles, with an electronic medical record in a digital library (Mendonca et al. 2001). Its major components are display, data, and processing. It facilitates search, presentation, and summarization of medical information obtained online. It automatically produces queries about the specific characteristics of individual patients. It uses patient information to guide clinicians in the search for evidence for use in patient care. Examples are when a patient is not compliant with his medication and when a comparison is made between two or more medications as to better compliance. There are, however, certain questions arise in the process, such as generalizability of the methods and the model. The authors say it can be generalized according to the quality of medical records/knowledge base, or KB, and the technical aspects of integration. Integration concerns can be settled if resources develops agree on standards, such as set of elements, controlled vocabularies or classification of data elements (Mendonca et al.).


Medical informatics, or MI, has been defined as the use of information science and information technology on the problems confronted by the theory and practice of biomedical research, clinical practice and medical education (Morris 2002). It is the point where biomedicine makes use of products and services evolved by information science and technology. According to MI-related data searches for 1995-1999 on frequently used indexing, information science or technology perspective centers on diagnostic technologies and techniques and data analysis and management. The information science or information technology -- IS or IT -- relates to a service provider, while the biomedical aspect is consumer-oriented. MI, on the other hand, is the marketplace. The market consists of biomedicine's research applications within MI. This covers areas, such as diagnostic imaging, decision support systems and artificial intelligence, biophysics and biomechanics and the design and use of medical computing systems. More specifically, evidence-based medicine, biotechnology, genomics, picture archiving and communication systems, and healthcare administration and management are IS/IT-dependent for its principles, theories and techniques for advancement. Furthermore, biomedicine needs to draw from the knowledge discovery and knowledge management aspects within MI (Morris).

In summary, MI is the meeting point between biomedicine and information science and information technology (Morris 2002). Biomedicine needs tools to achieve its goals. IS/IT provides these tools in addition to principles and theories to market biomedicine. IS/IT products are applied specifically on evidence-based medicine, the center of MI (Morris).

Other Uses of Informatics in the Health-Related Areas

The expanding application of medical or clinical informatics can go beyond bioinformatics, imaging informatics, specific health care disciplines -- such as nursing and dentistry -, research and public health (Hersh 2009). It can extend to consumer health informatics or informatics from a consumer's point-of-view. It is also now creating an entire health information management system. Health information management or HIM is a discipline, which focuses on the management of medical records. This comes as a consequence of medical records' becoming electronic. HIM differs from informatics in that HIM is used for education while informatics is used by clinicians (Hersh).


Computerized individual health records were first referred to electronic medical records or EMR (Hersh 2009). It has been replaced by electronic health records, which comprise a broader and more varied collection of patient information. The personal health records or PHR format is also evolving. This is the patient-controlled aspect of health records in which the patient can interact with his clinician securely. Through these, the patient can access the clinician's working records and become part of the care team. He does this by suggesting revisions on his data and keeping tab of his own progress with the clinician (Hersh).


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