Not to be confused with computational biology or bioinformatics, health informatics involves the integration and management of a person’s health record data to support healthcare.
In the past, physicians used paper-based medical records, creating a highly fragmented healthcare system. Diagnoses and treatment decisions were often based on the narrow perspective offered by how a patient presented during an office visit, the information contained in their chart and generally-understood population data.
Today, the use of electronic medical records (EMRs) in physician offices (clinical informatics) is becoming more commonplace. But to properly manage patients with chronic diseases or complex conditions, a patient’s complete medical history should be readily accessible—wherever that patient may be—and the disparate facts within a patient’s history need to be easily distilled and interpreted.
In the future, an individual’s electronic health records (EHRs)—going back to birth—will be available anytime and anywhere. Using mathematical models, we will be able to see trends over the course of a person’s life, allowing us to provide truly personalized medicine that is predictive, pervasive, pre-emptive, participatory and preventative.
Recognizing the benefit of EMRs and EHRs, a variety of solutions, such as Microsoft’s HealthVault, are being marketed directly to consumers and providers. But these patient snapshots are captured with varying—and subjective—lenses.
Making a patient’s complete medical records both accessible and meaningful requires a multidisciplinary effort that involves health data acquisition, management, processing, visualization, data mining, modeling and simulation; knowledge extraction and decision support; and human-computer interaction interfaces.
Health informatics enables the integration and interpretation of multi-scale data about a person’s entire body—right down to their DNA. This data is collected through a variety of means and from an array of technologies. The results of a lifetime of EKGs, ECGs, lab tests, MRIs, CT and PET scans, X-rays and other imaging can be combined to paint a picture far more detailed and precise than the notes captured during an office exam or entered by a patient on a Web site.
The development and adoption of standards provide a common language that allows healthcare providers, engineers, IT personnel, mathematicians, public health specialists and social and behavioral scientists to work seamlessly.
Medical coding is one area of standards that has gotten a lot of attention. While the US begins migrating from ICD-9 to ICD-10—with its 155,000 codes used largely for billing purposes, the far more comprehensive SNOMED CT (Systematized Nomenclature Of MEDicine—Clinical Terms) offers over a million medical concepts to provide a unified medical terminology system for the consistent exchange of clinical information between and among healthcare providers across specialties and institutions.
SNOMED CT is one of several standards for the electronic exchange of medical information designated by the US Federal Government and other member countries of the International Health Terminology Standards Development Organization (IHTSDO). Free automatic coding tools and services are available to help healthcare professionals navigate the standardized clinical terms.
While billing for payment necessitates the adoption of uniform medical coding, the broader adoption of EHRs is being detained by both political and privacy concerns (nobody has a problem with the doc keeping records—EMRs). Currently, the US is significantly behind northern European countries in this area. By integrating data from both healthy individuals and patients with various diseases, when fully adopted, EHRs will provide a systems-based approach to the management of patients and healthcare costs.
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