Competency F

Conduct informatics analysis and visualization applied to different real-world fields, such as health science and privacy.

Introduction and PLO Discussion

Health Informatics

            As technologies continue to advance at an alarmingly rapid rate, many industries will undoubtedly experience a surge in their growth and expansion including the healthcare sector. Within healthcare, health informatics is one specific field that is bound to undergo boundless, transformative growth. Informatics is described as “the science of how to use data, information, and knowledge to improve human health and the delivery of health care services (American Medical Informatics Association, n.d.).” By leveraging real-time clinical data insights, health informatics positively impacts the health, well-being, and quality of life of patients and the workflows of clinicians and other ancillary staff. Areas that involve the ever-evolving realm of health informatics include: Electronic Health Records (EHRS) and interoperability, telehealth and remote monitoring, big data and analytics, AI and machine learning, mobile health (mHealth) and apps, and ethical, legal, and security considerations.

Propelled by the Health Information Technology for Economic and Clinical Health (HITECH) ACT, the adoption of EHRs continues at an ever-growing pace. Enhancing and advocating for interoperability is valuable to ensure that patients’ pertinent health information can be shared among their various providers regardless of the EHR system a particular healthcare system utilizes. Due to their virtual nature, telehealth and remote monitoring continues to benefit from the advances made in health informatics. The utilization of big data and analytics allows information science professionals to partner with clinicians to derive valuable insights from immense datasets. Some of the latest health information technologies (HITs) used within health informatics harness the latest in AI and machine learning. With millions of individuals around the world constantly on-the-go and favoring more portable technologies, there will likely continue to be an uptick in the creation and adoption of mobile health and apps. Lastly but inarguably most importantly, considerations of an ethical, legal, and security-related nature must be prioritized and upheld through the transparency of data usage and continuous maintenance of privacy and confidentiality of sensitive information.

Health Data Analytics

            Akin to and working in tandem with health informatics is the distinct field of health data analytics. The International Organization for Standardization (ISO) (n.d.) refers to health data analytics as “the uncovering of patterns and insights from raw healthcare data like patient histories, bloodwork, and genetic trackers to help healthcare providers determine the best course of treatment.” Healthcare data analytics is categorized into the following four types of healthcare data analytics with each one going a little deeper when it comes to generating keen insights: 1) Descriptive analytics, 2) Diagnostic analytics, 3) Predictive analytics, and 4) Prescriptive analytics (ISO, n.d.). As the initial phase, descriptive analytics is comprised of a historical account of healthcare events (ISO, n.d.). Next, diagnostic analytics goes a bit further by identifying trends and explaining them (ISO, n.d.). Utilizing past and current data, predictive analytics forecasts upcoming events (ISO, n.d.). Finally, the final stage of prescriptive analytics suggests actions in response to the predictions made (ISO, n.d.).

Relevant Coursework, Professional Experience, & Future Goals

            Since I pursued the Health Informatics Career Pathway, I was able to easily designate assignments completed from the following courses in order to fulfill Competency F: INFM 210: Health Informatics, INFM 213: Epidemiological Methods, and INFM 214: Health Data Analytics.  While I do not have professional experience in health informatics per se, I utilized various Electronic Health Records (EHRs) as a former Registered Nurse including those from EPIC, Cerner eTenet, MEDITECH, and HCS. My future career aspirations involve working towards becoming either an Electronic Health Record Analyst or User Experience Designer for a healthcare organization.

Evidence #1: INFM 210 (Presentation & Resource Website)

As my primary piece of evidence, I selected the presentation and resource website my group worked on for the INFM 210: Health Informatics course. After deciding upon our topic of maternal healthcare in the US, my group mates and I divided up the workload and each contributed by assuming the following roles: 1st Member: Technology Specialist and Presentation Designer, 2nd Member: Researcher and Content Developer, and 3rd Member: Policy Analyst and Resource Curator.   The aim of our tri-fold project entitled M.O.M. (Mind on Maternity) – composed of a presentation, resource website, and individual report – was to demonstrate our knowledge acquired through our combined research efforts, particularly related to relevant healthcare policies and emerging technologies. Our resource website is divided into the following subject areas: Background of Mental Health Care, Healthcare Policies, Health Information Technologies, and Recommended Resources.

Evidence #3: INFM 214 (Final Presentation)

My final piece of evidence that fulfills Competency F is the PowerPoint presentation I developed for the INFM 214: Health Data Analytics course. The aim of this presentation was to identify and expound upon a specific use case in a setting the student considers pursuing. For my particular use case, I chose to do my presentation on Promoting Mental Health in Adults with Major Depressive Disorder and Generalized Anxiety Disorder. I selected this particular topic as it involves the dual diagnosis of a specific depression and anxiety disorder, one of the most common mental health dual diagnosis occurrences found among American adults. The significance of this particular topic involves demonstrating how effective and efficacious programming is for the mental health services provided for this population. By including a value statement, declaring preconditions/assumptions, delineating a staffing plan, illustrating the data flow, and defining the desired post condition, I delivered a thoughtful presentation regarding a topic that concerns millions of people in our nation who desire to endeavor towards achieving enhanced overall mental and emotional health, well-being, and an improved quality of life.

References

For my second piece of evidence, I am including this group presentation created for the INFM 213: Epidemiological Methods course. With this particular project, my classmates and I were challenged with the task of developing a video presentation based on the topic of descriptive epidemiology for a disease process or health outbreak of our group’s choosing. Descriptive epidemiology refers to time, place, and person (National Center for State, Tribal, Local, and Territorial Public Health Infrastructure and Workforce, Division of Workforce Development, 2012).  In our case, we chose to do our project on the descriptive epidemiology of Influenza A in the US. We first defined Influenza A and its global impact. After delving into this significant contextual information, we provided multiple visuals, detailing positive influenza tests and flu vaccinations administered for a few distinct populations. We next broached the question, “Who is at higher risk to be hospitalized for Influenza A?” Finally, we included information regarding when “flu season” typically occurs and referenced various historical flu pandemics.

Conclusion

Evidence #2: INFM 213 (Project #1: Presentation)

As healthcare is one of the real-life fields that is referred to in Competency E, I included evidence from the 3 electives I chose in pursuing the Health Informatics Career Pathway: INFM 210: Health Informatics, INFM 213: Epidemiological Methods, and INFM 214: Health Data Analytics. Despite being in different areas of healthcare, the evidence utilized from these courses included solid examples of informatics analysis and accompanying visual aids. As emerging technologies begin to experience rapid, transformative growth, health informatics is a key industry that will certainly benefit from such technological advancements.         

American Medical Informatics Association (AMIA). (n.d.). Informatics: Research and practice. AMIA. https://amia.org/about-amia/why-informatics/informatics-research-and-practice

International Organization for Standardization (ISO). (n.d.). An easy guide to understanding healthcare data analytics. ISO. https://www.iso.org/healthcare/data-analytics

National Center for State, Tribal, Local, and Territorial Public Health Infrastructure and Workforce, Division of Workforce Development. (2012, May 18). National Center for State, Tribal, Local, and Territorial Public Health Infrastructure and Workforce, Division of Workforce Development. https://archive.cdc.gov/www_cdc_gov/csels/dsepd/ss1978/lesson1/section6.html