Prior to beginning work on this discussion forum, review the Domain 3: Data Analytics review questions in your  Registered Health Information Administrator (RHIA) Exam Preparation textbook, and review Chapters 15 through 19 from your  Health Information Management: Concepts, Principles, and Practice Every week you are reviewing different RHIA domains. During the weekly discussion, you will be expected to review the RHIA practice questions for the respective domain being covered. The weekly discussions will provide an opportunity for you to ask questions about the practice questions, concepts, definitions, or review of the weekly domain.

Domain 3: Data Analytics and Informatics makes up 24% of the RHIA exam. The following knowledge is covered in this week’s domain review:

· Develop productivity reports.

· Prepare to support end user in EHR applications.

· Apply knowledge necessary to create visual representation of data for decision-making.

· Provide summary reports based on trends.

· Apply the knowledge necessary to optimize health information technology to improve workflow.

· Support health information exchange solutions.

· Examine clinical, administrative, and specialty service applications.

· Validate healthcare statistics for organizational stakeholders.

After completing the review questions, include four questions regarding this week’s domains or practice questions. Include information you researched to assist in answering the questions, feedback from the RHIA practice exam, and external resources that supported your knowledge of the content. This is a great dialogue to include concepts in which you would like to strengthen your skills and knowledge.

Respy 1

Hi,

 

How can productivity reports be utilized to improve healthcare operations and decision-making?

Reports on productivity measure the efficacy and efficient of healthcare operations, proving valuable insight into those operations (Tung et al., 2011). The results can help businesses streamline processes, better manage resources, and make educated decisions. They are helpful resources for improving healthcare efficiency and effectiveness.

What are the key considerations when creating visual representations of healthcare data for decision-making purposes?

When creating visual representations of healthcare data for decision-making, several key considerations should be taken into account (Thokala et al., 2016). First, consider the audience and their level of understanding to ensure the visualization is appropriate and easily comprehensible. Second, choose the most suitable visualization technique that effectively conveys the intended message, such as charts, graphs, or dashboards. Third, ensure the visuals are clear, concise, and accurately represent the underlying data to prevent misinterpretation. Finally, incorporate proper labeling, titles, and legends to provide context and aid the interpretation of the visualizations.

How can health information technology be optimized to improve workflow in healthcare settings?

Health information technology (HIT) can be optimized to improve workflow in healthcare settings through various strategies. First, workflow analysis can identify inefficiencies and bottlenecks, allowing for targeted improvements. Second, customization of HIT systems to align with specific organizational needs can streamline processes and enhance user experience. Third, integrating different HIT systems promotes seamless data exchange and eliminates manual data entry redundancies. Lastly, leveraging decision support tools and automation features within HIT systems can enhance clinical decision-making and reduce manual workload, leading to improved workflow efficiency.

Why is validating healthcare statistics vital for organizational stakeholders?

Validating healthcare statistics is essential for organizational stakeholders because it ensures the accuracy and reliability of the data used for decision-making. Validated statistics provide confidence in the analyzed information, enabling stakeholders to make informed judgments and strategic decisions (Wang & Byrd, 2017). By validating healthcare statistics, stakeholders can assess the quality of the data, identify any inconsistencies or errors, and take corrective actions if necessary. Validated statistics also promote trust and credibility among stakeholders, enhancing the overall effectiveness of data-driven decision-making processes within the organization.

Reply 2

Good evening,

 

220.HIE Governance is concerned with the establishment of a set of behaviors and standards that enable health information exchanges among HIEs participants. 

 

Clearly defined processes help to create a HIE governance structure within an organization, which should have a clearly defined set of rules and standards for how and when the HIE is used, and protects the confidentiality, integrity and accessibility of the patient's information. Press, A. (n.d.).

 

235. What type of interoperability addresses medical words, phrases, and terms used in healthcare and their definitions so that there is a clear and consistent usage among all EHR systems?  Semantic

 

IT Blog Demigos describes Semantic Interoperability as “covers data handling and usage. Semantic interoperability healthcare systems leverage data in a standardized way as they break down and share information. For example, two systems can now recognize terminology, medication symbols, and other nuances while exchanging data automatically, without human intervention.” -Demigos 2021

247. What type of data tool is used to show frequency of continuous variables such as length of stay?

A Histogram. According to   a Histogram is also known as a frequency distribution chart. The histogram graphically demonstrates the frequency with which various values of a particular variable occur in a set of data. The height of the bar indicates the frequency of occurrence. The site goes on to explain the uses are to quickly and easily demonstrate a data sets distribution and to compare two time periods, looking for change.  Histograms can be constructed utilizing most spreadsheet software, 

312. A quality coding review that is based on specific problems identified on the initial audit inside the hospital is called a focused review. 

 

AHIMA states “Focused Reviews focus on areas that cause the most risk, New coders – 100% for at least 3 months, High risk MS-DRGs, POA/HAC conditions, RAC initiatives, High volume/high cost outpatient procedures. ( AHIMA 2008)