Information Technology for the Practicing Physician (Health Informatics)
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Rebecca B. Staff Liaison: Brooke Rockwern, brockwern acponline. Board of Regents Charge Advise the Board of Regents, committees and councils on medical informatics and health information technology HIT , including HIT education, adoption, incorporation in practice, and use to improve the quality, safety and affordability of patient care.
Healthcare Informatics | HIMSS
This can be done through different types of data collections, such as hospital surveys, or electronic surveys submitted to the organization such as the CDC. Before the advent of the internet, public health data in the United States, like other healthcare and business data, were collected on paper forms and stored centrally at the relevant public health agency. If the data were to be computerized they required a distinct data entry process, were stored in the various file formats of the day and analyzed by mainframe computers using standard batch processing.
The second category is to find ways to improve the efficiency of different public health systems. This is done through various collections methods, storage of data and how the data is used to improve current health problems. In order to keep everything standardized, vocabulary and word usage needs to be consistent throughout all systems. Finding new ways to link together and share new data with current systems is important to keep everything up to date. Storage of public health data shares the same data management issues as other industries.
And like other industries, the details of how these issues play out are affected by the nature of the data being managed. Due to the complexity and variability of public health data, like health care data generally, the issue of data modeling presents a particular challenge.
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While a generation ago flat data sets for statistical analysis were the norm, today's requirements of interoperability and integrated sets of data across the public health enterprise require more sophistication. The relational database is increasingly the norm in public health informatics. Designers and implementers of the many sets of data required for various public health purposes must find a workable balance between very complex and abstract data models such as HL7 's Reference Information Model RIM or CDC's Public Health Logical Data Model , and simplistic, ad hoc models that untrained public health practitioners come up with and feel capable of working with.
Due to the variability of the incoming data to public health jurisdictions, data quality assurance is also a major issue. Finding new algorithms that will sort through large quantities of data quickly and effectively is necessary as well.
Such analyses usually require methods that appropriately secure the privacy of the health data. One approach is to separate the individually identifiable variables of the data from the rest . There are a few organizations out there that provide useful information for those professionals that want to be more involved in public health informatics.
AMIA is for professions that are involved in health care, informatics research, biomedical research, including physicians, scientists, researchers, and students. They hold annual conferences, online classes and webinars, which are free to their members. This use of informatics in healthcare management can entail a comprehensive enough approach to be labeled a data science strategy, beginning with the establishment of a well-organized central data repository and utilizing analytical tools to integrate data from disparate sources into it.
But what is health informatics useful for if not for enabling thoughtful, long-term planning for the future of the field?
The most directly observable way in which health informatics can aid in a planning capacity is through the generation of robust, sortable health record databases. Collections of patient data, from history, background and symptoms to treatment and outcomes, can be analyzed to generate best practices guidelines that target predictably positive results in future cases. And in the even longer term, health information technology and data analysis can be used to inform the research that is crucial for improving the strategic application of healthcare delivery into the future.
Thus far, we have exclusively discussed health informatics defined in terms of its use by professionals working in the field. But what is health informatics for the average patient or consumer? The next wave of health informatics may involve the creation of standardized databases derived from information collected actively or passively from patients that can be used to rank care options according to various criteria. These rankings—in categories that could include cost, quality of care, safety, efficiency or customer satisfaction—could then be visualized in a dashboard interface to help patients wade through the often dizzying array of healthcare options available to them.
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