Public Health Informatics: Advancing Healthcare at the Patient and Population Level Público
Esser, Edward (Spring 2018)
Abstract
The increased adoption of electronic health record systems by health care providers offers an opportunity to improve public health on multiple levels. The access to quality data provided by the proposed system could improve decision making for each of these stakeholders: a patient could track and understand their latest health numbers, a physician could be alerted of a patient health condition that needs immediate attention, and health departments could design more effective interventions, thus enabling a holistic approach to public health. The deliverables within this document demonstrate how health informatics can advance public health at both the population level as well as the patient level.
The first set of deliverables address patient health. Health literacy is the ability to find, to understand, to use, and to communicate basic health information and services in order to make appropriate health decisions. Although government websites such as CDC.gov and Cancer.gov are highly reliable, they are not always the primary sources of health information for average internet users. There is a need to bridge the gap between the scientific and technical users of these federal agency websites and the average internet user. This need can be addressed through enhanced user engagement and user experiences that provide access to pertinent public health information.
The second set of deliverables address population health. The collection, analysis, and dissemination of disease surveillance data must be improved. Public health informaticians should strive to develop centrallized surveillance systems similar to a health information exchange in which surveillance data can be automatically captured and securely accessed amongst all participating stakeholders. As these surveillance systems mature, advanced predictive and prescriptive analytics will offer data scientists increased opportunities to aid in evidence-based preventive efforts. Advanced decision support from cognitive computing engines, cluster analysis, machine learning, natural language processing, and text analytics can help providers recognize diagnoses that might remain elusive otherwise, while population health management tools can highlight those most at risk of being readmitted to the hospital or developing costly diseases and infections.
Table of Contents
Introduction. 7
Informatics to Improve Health Literacy. 8
Background. 8
CDC Compass. 9
Overview.. 9
Features. 10
Information Architecture. 14
Cancer Care. 16
Overview.. 16
Development Plan. 18
Enterprise Architecture. 19
Discussion on Improving Health Literacy through Informatics. 21
Informatics to Improve Disease Surveillance. 23
Background. 23
National Health Safety Network Modernization Initiative. 24
Overview.. 24
Data Needs, Sources, and Uses. 26
Enterprise Architecture. 27
Ithaca 2.0 Chronic Disease Surveillance System.. 29
Overview.. 29
Features. 31
Enterprise Architecture. 32
Discussion on Informatics Improving Disease Surveillance. 34
Conclusion. 36
Reference
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