Semantic Interoperability

After the release of ResearchKit, Medidata revealed an open- source connecter linking the Apple ResearchKit to the Medidata Clinical Cloud. This integration will further help to use the data that is collected through the ResearchKit to improve the study designs. “Medidata has developed a mechanism allowing study builders to map the data generated from ResearchKit apps to studies in Medidata Rave” (NASDAQ:MDSO, 2015). The connection of software will give birth to a new level of productivity; expanding the quality, study designs, management and reporting of the clinical trials. “With the use of semantic web technology, a researcher will be able to create a data file using tags that identified which data items identified the researchers, the inclusion criteria, the aim of the study, the baseline tests to be performed, the details of the treatments to be compared and so on. And such data can be analyzed

McDonald (1997) points out that health care data is siloed in multiple areas that are inaccessible to others. This kind of management of patient data does not serve the patient well. It is for this reason that SCEMS approached Providence and Swedish hospitals to propose implementation of HDE. Moreover, as stated in the McDonald article a feasible way to integrate data from disparate sources is through the use of interfaces such as the HDE. In addition, a problem that exists in the integration of these two data sources is the fact that the hospital system communicates via the standard HL7 language, while the pre-hospital system communicates via XML. Fortunately, the HDE structure accounts for this difference by translating back and forth between the two different languages.

A computerized clinical database consists of clinical data for storing, retrieving, analyzing, and reporting of information (McCartney, 2012).

NIH Public Access published an article about SNOMED CT 's RF2. SNOMED is complex and extensive computer information that allows common medical to be captured, shared, and aggregating health data. SNOMED was established in 2002 and was research up until 2010. During that time there were many problems that arise. Therefore, in 2010 the International Health Terminology Standards Development Organization (IHTSDO) that implemented a new format called RF2. At first glance, RF2 seems to be a cosmetic change; however, it holds great promise for the future because of its flexibility and to deal with a number of issues concerning the ontological underpinnings.

In 2013, the HIMSS Board of Directors defined interoperability in health care as having the ability to have different information technology systems and software applications communicate, exchange date, and then use the information that has been exchanged (HIMSS, 2015). Data exchange permits data accessibility between organizational boundaries, while interoperability means health systems have the ability to work together in order to advance the health status of the individuals and communities the system serves. For two systems to be interoperable, they must be able to exchange data that can be understood by a user (HIMSS, 2015). This is extremely important to the goals of HITECH and meaningful use because it aligns with the government standard

The information sharing document is often patient-centered. This means that the patient is in relation to each type of material in rotation. In fact, when a document having the patient’s information is going around in different health information systems, it is vital in guaranteeing that all the systems are referring to the patient in question. Therefore, this type of

Currently, the topic of interoperability is at the forefront of health data management. While lacking a standard definition of interoperability itself, the National Alliance for Health Information Technology defines it as “the ability of different information technology systems and software applications to communicate, to exchange data accurately, effectively, and consistently, and to use the information that has been exchanged.” Interoperability now stands at the center of health IT’s future, as the success of electronic health records (EHRs) relies upon the exchange of health information. In essence, health information is already interoperable, as providers can write down data on a

The passage of the American Recovery and Reinvestment Act encouraged and mandated the use of health information exchange (HIE) technology in the healthcare industry. The time had finally come to enter into the electronic age, and learn how to integrate electronic health records (EHRs) into their environment. Evolution and revolution are never easy, and several issues will arise during the transition. As EHR utilization spread through healthcare organizations, problems with interoperability became evident. How could healthcare organizations successfully achieve interoperability, and collect consistent patient data? A data dictionary may be the key to unlocking an accurate and efficient HIE.

Interoperability is the way information is shared across an organization. Sharing information across all avenues of health care is imperative to quality patient care. Coordination between all members of the health care team can occur through a congruent system, eliminating unnecessary phone calls and paper work that take away from patient care. The sharing of information electronically reduces the likelihood that files could be lost or stolen which creates a liability for all those involved in the care of the patient.

However, there are still some interface issues between Allscripts and Epic. Interfacing between two different EHR systems is vital for communication, accuracy, and efficiency. It requires customization of interoperability methodologies to overcome the constraints that prevent information flowing from one EHR to another.

As the implementation of electronic health records (EHR) progress nationwide, the concepts of interoperability and health information exchange (HIE) must be discussed. The Healthcare Information and Management Systems Society (2005, p. 2) define interoperability as “the ability of health information systems to work together within and across organizational boundaries in order to advance the effective delivery of healthcare for individuals and communities.” Interoperability is the enabling of two systems, including those that do not share

We can say it is true the interoperability and health information exchange are similar, it is a common mistake that interoperability means health information exchange (HIE).

When I first enrolled in BMI 5300: Introduction to Biomedical Informatics class, I was very eager and excited to learn the role of biomedical informatics in healthcare organizations and the importance of data capture and analysis in improving public health. One of the major misconceptions I had was that this course would not cover wide range of factors influencing the biomedical informatics field. Much to my surprise, the course provided a comprehensive analysis of factors related to biomedical informatics, including but not limited to EHR systems, interfaces, Health Information Exchanges, Meaningful Use (MU) requirements, and controlled medical vocabularies such as Logical Observation Identifiers Names and

In health care, patients’ lives are in the hands of the health care practitioners, health care organizations, insurance companies, and to some degree, even health care technology. The growth and future implications of evidence-based medicine (EBM) through improvement of technology in health care are important today, because health care practitioners and organizations want to ultimately decrease cost, improve quality of care, and increase access to health care (Glandon, Smaltz, & Slovensky, 2014, p. 28). One way to achieve these goals is through the implementation and improvement of EBM and interoperability which will enhance the efficiency of work production resulting in these positive outcomes. According to Glandon, Smaltz, and Slovensky (2014), EBM is an “information management and learning strategy that seeks to integrate clinical expertise with the best evidence available to make effective clinical decisions that will ultimately improve patient care,” (p. 6). “Interoperability is the ability of different information and communications technology systems and software applications to communicate, to exchange data accurately, effectively, and consistently, and to use information that has been exchanged,” (Iroju, Soriyan, Gambo, & Olaleke, 2013, para. 1). Without interoperability and EBM, fundamental data and information such as patient records cannot be easily shared across and within enterprises having a direct impact on the quality of care. It

The construction of ontologies requires content expertise and continuous accrual of new knowledge, which is challenging to incorporate in a timely manner. The comprehensiveness of ontology in a given domain is crucial for its usefulness. Thus, there is a need for systems that can effectively and efficiently provide an assessment of domain coverage and potential new content for inclusion. One of these mechanisms includes exploiting the information found in biomedical resources like published literature and EHRs. Electronic health records have several advantages for use in phenotyping such as cost efficiency and the availability of large amounts of clinical and temporal information (11). Although structured data, such as International Classification of Disease (ICD) codes, are useful controlled vocabularies, they are limited in detail as they are designed to facilitate medical billing. On the other hand, the unstructured clinical data (e.g. consult notes, history and physical notes, discharge summaries, and pathology reports) are rich in