Shining the Spotlight on Health Informatics

This blog explores health informatics—a collaborative activity connecting people, process, and technologies to produce trusted data for better decision-making.


By Dawn Paulson, MJ, RHIA

 

Welcome to the first post of the new Journal of AHIMA blog Illuminating Informatics! We are pleased to this monthly blog, which will focus on the topic of health informatics. Previously, the Journal of AHIMA blog Data Revolution discussed both informatics and analytics, but will be shifting focus solely to analytics-related content in the future. So… why are each of these topics getting the star treatment now? To answer that, let’s take a closer look at the definition of each:

  • Health Informatics is a collaborative activity that involves people, processes, and technologies to produce and use trusted data for better decision-making, according to AHIMA. Health information management professionals who are working in IT departments or in a system support role are working in informatics, according to this definition.
  • Data Analytics is the science of examining raw data with the purpose of drawing conclusions about that information. It includes data mining, machine language, development of models, and statistical measurements. Analytics can be descriptive, predictive, or prescriptive.

In other words, Analytics involves the actual analysis of the data, and Informatics is the design, management, support, and application of that information. As displayed in the infographic below, Analytics activities occur AFTER all systems are set up and tools are functioning properly to collect the data.

Let’s dig even deeper into the roles and responsibilities of an informatics professional:

  • Project Management: Ensure that projects are executed as defined in the Project Charter. Projects should be delivered within scope, delivered on time and at or under budget, and meet the intended needs.
  • Workflow: Establish, understand, and define the scope of workflows to ensure collection/entry of needed data aligns with those established workflows.
  • Clinical Support: Understand and ensure that all clinical needs are met through data definition, data collection, and reporting. Work closely with clinicians to better understand needs and enhance user functionality experience.
  • System Design: Plan data collection needs, processes, and tools that are needed to ensure accurate and complete documentation, as well as ensure that the result is complete and accurate data reporting.
  • System Development: Create the tools used to collect data within the electronic health record. Ensure standards are met across the enterprise for consistent data collection/reporting.
  • Interface: Monitor flow of data between multiple systems to eliminate redundant data entry, ensure consistent information across all systems, which supports accurate and complete reporting.
  • Integration: Ensure that all elements and platforms in an information system communicate and act as a uniform entity.
  • Decision Support: Utilize tools that process information to help users make a clinical decision. Some provide active support by triggering an alert or reminder, while others are more passive by integrating clinical practice guidelines, protocols, or care pathways.
  • Business Intelligence: Complex analysis on a large set of data from multiple sources retained in either a multidimensional or relational database.
  • System Implementation: Process of going live with a change, a system update, or an entire upgrade in the information system. This only occurs after all testing and training has been completed.
  • System Support: Assistance provided during and after system changes. This is an ongoing activity.
  • Portal and Consumer Support: Management of tools where electronic protected health information can be viewed, transmitted, or downloaded by an individual via secured access. Individual user access assistance is provided on an ongoing basis.

In our next Illuminating Informatics post, we will focus on the importance of obtaining the CPHI credential (Certified Professional in Health Informatics), how the above roles and responsibilities align with the domains of the credentialing exam, and what resources are available to assist those interested in pursuing the CPHI credential.

References

AHIMA. Pocket Glossary of Health Information Management and Technology, Fifth Edition. Chicago: AHIMA Press, 2017.

Clack, Lesley; Houser, Shannon H.; Kadlec, Lesley; Mikaelian, Raymound; Tabisula, Braden; Zeglen, Margie. “Data Analytics and Informatics are Two Separate Disciplines (And Why This Matters to HIM).” Journal of AHIMA 88, no.10 (October 2017): 20-24.

Biedermann, Sue and Diane Dolezel. Introduction to Healthcare Informatics, Second Edition. Chicago: AHIMA Press, 2017.

Amatayakul, Margret K. Health IT and EHRs: Principals and Practices, Sixth Edition. Chicago: AHIMA Press, 2017.

 

If you’re interested in learning more about opportunities to write a guest post for Illuminating Informatics, contact Dawn Paulson at dawn.paulson@ahima.org.

 

Dawn Paulson (dawn.paulson@ahima.org) is director of informatics at AHIMA.

1 Comment

  1. Thanks for the great post! Health care analytics allows for the examination of patterns in various healthcare data in order to determine how clinical care can be improved while limiting excessive spending.

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