Applications and AnalysisStart Free Course
This class is offered as CS6440 at Georgia Tech where it is a part of the Online Masters Degree (OMS). Taking this course here will not earn credit towards the OMS degree.
This is a survey course designed to provide a broad, forward-facing overview of contemporary health informatics, a specialized field of computing that seeks to improve the quality and efficiency of healthcare delivery. To understand health informatics (HIT) you also need to have at least a basic understanding of the complex and highly regulated US healthcare industry. The course is designed for students from diverse backgrounds and who have not been previously exposed to HIT. It is divided into three sections:
The US healthcare delivery and the key role of the federal government in promoting HIT adoption
The core technologies that drive all contemporary HIT systems and tools
The real world applications of HIT from electronic medical and personal health records to exploiting digital data aggregated from them for research and other purposes
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This lesson will discuss unique and the complex nature of the US healthcare system: its key problems, the specific challenges presented by chronic disease, the major disconnect between the health system’s capabilities and the demands of chronic disease management, and the hope that a combination of new incentives, health IT adoption, and new models of care can bridge this disconnect leading to a more efficient, effective, safer and more patient-centered US system of care.
This lesson will focus on the important details of the specific programs that the federal government has put into place to spur health IT adoption by eligible providers and hospitals as well as the role played by financial incentives that reward performance, rather than the quantity of procedures.
This lesson will focus on the rationale for and the major challenges of health information exchange (HIE). We will discuss the various ways of classifying HIE, how to differentiate the various HIE architectures, and the Indiana Health Information Exchange as a premier example including descriptions of its key services. We will discuss new approaches and technologies with a particular emphasis on Direct HIE, a new technology based on secure email and encrypted attachments.
This lesson focuses on the keys issues of privacy, security, and trust in a world of digital records and health information exchange. Students will understand the key role that patient engagement plays in chronic disease prevention and management and the concerns patients have about sharing their health data. They will also explore the various privacy consent models. Data segmentation will be discussed as a key challenge for obtaining patient consent under what may be the most acceptable model. The concept of public key infrastructure (PKI) including the roles of the public key, private key, registration authority and certificate authority will be covered.
We divide the discussion of standards into those for health data and those for achieving its sharing by fostering interoperability. This lesson focuses on data standards after reviewing the rationale for standards and the evolutions that have been taking place in their use, technology and structure. Students will be able to recognize the difference between a classification and an ontology. They will be familiar with the key data standards (including ICD, CPT, LOINC and SNOMED). They will also gain an overview of the differences between standards based on EDI/X12 and XML.
This lesson builds on Lesson 5A on data standards to show how these data are transmitted within messages using HL7 and packaged into CCDA-based clinical documents for sharing via HIE. We’ll briefly introduce even more advanced standards with a particular emphasis on clinical decision support (CDS, an important technology for the future) and the key elements of and remaining challenges with standards to support CDS. We’ll also discuss more facile next generation approaches based on web technologies and approaches.
Students should understand the key roles that data plays in medical practice and the root causes of common data quality issues in general and the specific root causes of data quality issues with respect to electronic health records. They should understand the high level challenges of efficiently and accurately collecting high quality, comprehensive clinical data from physicians and of visualizing digital health data in a way that supports the provider’s mental model. They should understand the key roles that information technology plays in the future vision of healthcare.
Students should understand the key role that support for patients can play so they can achieve behavior change, adhere to their prescribed treatments and generate data to help their providers more continuously manage their chronic diseases. They should understand patient interests. They should understand the key information technology tools now available to patients including patient health records, portals, social networking, in home technologies and mobile devices and sensors. They should have a detailed functional understanding of personal health records and their potential as app platforms. They should understand the potential role of social networking in patient education and care management. They should understand the various telemedicine modalities being developed and offered for use by patients at home.
Students should understand the difference between individual patient management, population management and public health. They should understand the technologies for aggregating data, the kinds of data that are collected and the kinds of reports that are required for population and public health management.
Students should understand the challenges of data query and aggregation in an environment where care providers are using disparate and non-interoperable EHRs. They should be familiar with and understand the differences among the distributed query technologies. They should be familiar with the distributed query standards and the various open source query frameworks reviewed in this lesson.
Students should understand the concept of “big data”; the common technical approaches to modeling and simulation and the common applications of each. They should be familiar with the specific case studies of analytic applications to healthcare problems as diverse as improved clinical decision support, understanding clinical processes, modeling care spaces and providing optimal patient-specific treatments.
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Healthcare is the largest industry in the US. Spurred by new federal programs and incentives, the adoption of health IT is growing very rapidly, leading to many new career and entrepreneurial opportunities. The increasing use of modern web, mobile and sensor technologies in health informatics is also growing rapidly and is leading to many new and innovative approaches. Students who are trained and well-qualified in this field are in great demand.
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