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FHIR (Fast Healthcare Interoperability Resources) is an open source standard, which facilitates data integration, reduces interoperability costs and fosters innovation. FHIR is an effective online protocol that connects systems and improves the app-based approach to interoperability (“Four basics to know about the role of FHIR in interoperability,” 2016).

With electronic health records replacing paper forms, the practice has proven that exchanging information electronically benefits research, clinical trials, and audits. Therefore, FHIR is a vital tool in healthcare. FHIR has been established as a new data exchange HL7 standard, which benefits data implementation, information integrity, data exchange between applications, and cooperation between institutions (“What is FHIR (and why should I care?),” 2013). To be more precise, FHIR Specification facilitates data exchange and interoperability, making electronic forms accessible, clear, and transparent.

Although FHIR has been designed mainly for programmers, the Specification can be found online and can be accessed at all times. Patients, developers, clinicians, and providers can only benefit from high-quality electronic records. Clinicians will be able to manage medical data easily, providers will reduce interoperability costs, patients will have access to numerous apps, and by using FHIR, developers will overcome all tech barriers of integrating abundant and complex data.

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FHIR Observation, in particular, is a crucial aspect in the Clinical – Diagnostics module of the FHIR Specification (“FHIR,” 2017). Observations contain basic and vital clinical content, such as medical conditions and care plans. Observations are needed to help experts draw research conclusions, support clinical diagnoses, monitor study results and consider individual characteristics. In addition, Observations can provide information for research, practice, and investigation.

Even if you are not an IT developer, FHIR Observation can help you visualize how clinical data is presented in a structured way via codes – all with the purpose to improve data exchange and interoperability. Content is fully hyperlinked, and as FHIR is an open source standard, access is clear and at no cost (“FHIR (Fast Healthcare Interoperability Resources),” 2017).

Note that all content that can be exchanged is called a Resource. For example, Resources can be a patient, a condition or a clinician. Often Resources are being combined to provide a clearer scientific picture (“FHIR,” 2017). Thus, one can extract a single piece of information not only a whole document, with which FHIR moves from a document-centered approach to a data-level access.

FHIR Observation includes all measurements, assertions, and tests that might be needed about a subject. From providers and devices to medications and diagnostics, there’s plenty of data researchers can use. To be more precise, FHIR Observation contains:

  • Vital signs, such as body temperature
  • Lab data, such as blood glucose
  • Imaging data, such as fetal measurements
  • Device measurements, such as EKG
  • Clinical assessment, such as APGAR
  • Personal traits, such as eye color
  • Social history, such as drug abuse
  • Core characteristics, such as pregnancy status.

In addition, Observations can help researchers manage and share actual data. Note that each Observation contains a status, a category code of vital signs, a “magic value” (LOINC) to tell what’s being measured, a patient, a time of measurement, a numeric result value, and a standard Unified Code for Units of Measure (UCUM) unit. Thus, one can find the subject of observations, the particular observation of interest, and the period of observations and analyses.The FHIR Vital Signs is one of the core profile sets in the FHIR Observation. Experts can record, search and exchange vital signs (such as blood pressure), which may be associated with a subject. Note that vital signs need a global and consistent vocabulary to support semantic interoperability. The wide variety of wearables, for instance, bombards experts with a huge abundance of data. Due to its complexity, consistent codes are required (“FHIR and the future of interoperability,” 2015).

With FHIR, experts can access data easily and analyze it systematically. Consequently, researchers can search for vital signs by category, category code and date, and by one or more codes. For example, one can search for all heart rates and respiratory observations for a patient. In the case of body temperature, FHIR can show if it’s taken orally, for example.

Some of the vital signs are heart rate, respiratory rate, body weight, body length (mainly for infants), body height, body temperature, head circumference, oxygen saturation, body mass index, and blood pressure (systolic and diastolic).The FHIR Lab Data section is another crucial set included in FHIR Observation. Usually, data collection and management require staff training. To speed up the process, increase its effectiveness and erase discrepancies, FHIR will help experts find information, break down big sets, and increase readability.

On top of that, FHIR guarantees successful exchange between lab information systems and electronic health records, which improves practice (Wilkerson et al., 2015). For instance, if practitioners in ERs had access to data, such as blood glucose, they’d know what medications to give based on the patient’s history. FHIR Lab Data also shows who performed the lab tests, interpretations, and comments. Thus, FHIR makes data accessible, updated, and vital.

FHIR Laboratory Data can include medical indicators and tests, such as blood glucose and estimated GFR.Just like Vital Signs and Lab Data, FHIR Imaging Results can improve healthcare practice. FHIR has implemented a user-friendly application programming interface (API), which makes the collection of data, availability of information, and exchange of electronic health records effective. Any system can read FHIR resources and all resources have human-readable text representation via HTML; which means that experts do not need fax or mail to exchange information.

In addition, FHIR Observation – Imagining Results can save healthcare providers time and money. There’s no need to perform numerous scans if, for example, experts can access fetal measurements online promptly (“The big picture: Interoperable medical image exchange,” 2015).

Fetal measurements and bone density are only a couple of the FHIR Imagining Results included in the FHIR platform.Retrieving information, such as Devices Measurement, is important. FHIR improves the exchange of information and electronic health records. In fact, data can be linked from the resource of a device to the data type of that device (“FHIR,” 2017). Additionally, having clear specifications facilitates further audits and investigation.

Measuring physiological and anatomical parameters is crucial for patients’ well-being. The increase of wearables that track biological changes challenges data collection. However, FHIR brings apps, cloud communications, and providers together.

With FHIR Observation, experts can access and share Devices Measurement data, such as EKG data and Pulse Oximetry data with interpretations for non-numeric results.Not only physiological parameters are needed in research and practice. Researchers have created a wide variety of assessment tools, questionnaires, and interview techniques. Not surprisingly, standardized qualitative methods support healthcare practices (“FHIR,” 2017).

From psychologists to investigators, experts can benefit from data integration and healthcare solutions regarding various clinical assessment tools. FHIR can help practitioners access crucial information from clinical assessment tools. In addition, if a measurement cannot be performed, the Observation status changes and observations can be canceled or aborted.

Examples of clinical assessment tools are APGAR and Glasgow Coma Score.Patients’ personal characteristics may also become a focus of observations. Although they’re not vital signs, they are factors to consider. As patients have become active participants in healthcare, the data included in electronic health records (EHRs) is abundant.

FHIR can help experts to mine data for analytics and share information (“FHIR,” 2017). On top of that, FHIR helps developers build apps faster and retrieve information from them.

Let’s focus on the personal characteristic eye color. FHIR displays text boxes that can show experts data, such as the subject and the value, which in this case is the particular color.Patients’ social history can reveal a lot about one’s health status, medical condition and attitude towards treatment. With the rise in chronic diseases, environmental factors and social history matter.

With FHIR Social History, experts can collect, analyze and share information, such as tobacco use, family support, and cognitive status.

Note that although FHIR facilitates sharing of information and individual’s health data (with a focus on mobile platforms) – data security is not breached (“FHIR,” 2017). Confidentiality and safety are considered.As an interoperability standard for electronic exchange of healthcare information, FHIR facilitates sharing, integration, and retrieval of core characteristics.

Core characteristics can be factors, such as pregnancy status or death assertion.

Note that data is structured and even based on codes and values – the system allows comments to be added. Thus, one can retrieve an isolated resource or a combination of complex documents without getting lost in data sets.FHIR makes data exchange and app development easy and effective. It also gives researchers a unique chance to perform multiple statistical analyses (“FHIR,” 2017). For instance, stats operation performs calculations based on clinical measurements, such as blood pressure (BP). One can get the average, min, max and count of a series of BP measurements for a patient and even determine percentiles over time. Other possible metrics are median, sum, variance, skew and kurtosis.

Note that if successful, the Observation resource for each code will appear along with the results of the statistical calculations (the component code that is displayed is the statistical code). In case the operation is unsuccessful, the FHIR system will send Operation Outcome with an error message (displayed on screen).

In addition, to support better graphical presentations, experts can include and specify parameters and limits.

To sum up, FHIR is an effective tool that can be used as an open-source standard for data exchange, which can facilitate app development, interoperability, and statistical analyses. Having accessible data online can benefit practitioners, investigators, providers, and patients. FHIR is becoming an inseparable part of healthcare technology, which can reduce costs and erase discrepancies. The data can improve people’s well-being and enlighten the future of medicine.Interoperability – According to the Healthcare Information and Management Systems Society (HIMSS), “In healthcare, interoperability is the ability of different information technology systems and software applications to communicate, exchange data, and use the information that has been exchanged. Data exchange schema and standards should permit data to be shared across clinicians, lab, hospital, pharmacy, and patient regardless of the application or application vendor.”

HL7 – Health Level Seven International is accepted as the main organization involved in the development of international healthcare informatics interoperability standards.

Resource – FHIR resources are defined as information elements that can be shared. Resources can be described 1) in a hierarchical table that presents a logical view of the content; 2) a UML diagram that summarizes the content graphically; 3) a pseudo-XML syntax that provides a visual sense of what the end resource instances will look like in XML; 4) a pseudo-JSON syntax that provides a visual sense of what the end resource instances will look like in JSON; 5) a pseudo-Turtle syntax that provides a visual sense of what the end resource instances will look like in Turtle.

Magic value – Magic values tell experts what’s being measured. In FHIR, LOINC – which is the universal standard for identifying health elements – is used to describe all magic values.

UCUM – Unified Code for Units of Measure (UCUM) is a code system that includes all units of measures, which is used to facilitate electronic communication of quantities and their units.

GFR – The glomerular filtration rate (GFR) is the best test to measure one’s kidney functions.

API – Application Programming Interface (API) is a set of protocols and tools used to build an application software.

EKG – EKG stands for electrocardiography, which records the electrical activity of the heart.

Pulse Oxymetry – It’s a non-invasive technology to measure the oxygen levels in the blood and the heart.

Glasgow Coma Score – A popular and effective scale that measures brain injury based on motor, eye, and verbal criteria.

Skew – Skewness in statistics shows the asymmetry of the probability distribution of a real-valued random variable about its mean.

Kurtosis – Kurtosis is defined as a measure of the “tailedness” (specific distribution) of the probability distribution of a real-valued random variable.FHIR (Fast Healthcare Interoperability Resources) (October 30, 2017). Retrieved from http://searchhealthit.techtarget.com/definition/FHIR-Fast-Healthcare-Interoperability-Resources

FHIR and the future of interoperability (January 6, 2015). Retrieved from http://www.healthcareitnews.com/news/fhir-and-future-interoperability

Four basics to know about the role of FHIR in interoperability (March 22, 2016). Retrieved from https://healthitanalytics.com/news/4-basics-to-know-about-the-role-of-fhir-in-interoperability

The big picture: Interoperable medical image exchange (October 2, 2015). Retrieved from https://www.beckershospitalreview.com/healthcare-information-technology/the-big-picture-interoperable-medical-image-exchange.html

What is FHIR (and why should I care?) (October 14, 2013). Retrieved from https://fhirblog.com/2013/10/14/what-is-fhir-and-why-should-i-care/comment-page-1/#comment-30881

Wilkerson, M., Henricks, W., Castellani, W., Whitsitt, M., & Sinard, J. (2015). Management of laboratory data and information exchange in the electronic health record. Achieves of Pathology and Laboratory Medicine.

FHIR. Retrieved from http://hl7.org/fhir/

FHIR. Retrieved from http://wiki.hl7.org/index.php?title=FHIR