Health Data Management Review

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    1. QUESTION

     There are two discussion board question.

     


    Topic: Health Data Management Review

    Choose ONE of the question sets below to research and post a thorough answer to the questions.  

    1. Why is it important for data from various sources to be defined in a standardized or uniform way?  How do a data set and core data elements make it possible to standardized data in healthcare organizations?
    2. What is the reason for creating a unique identification number for every healthcare consumer?  What could be some issues caused if this is not done?
    3. What is a data dictionary?  What is its importance in ensuring data quality?  What type of information would be listed in a data dictionary?

    What is data integrity?  How is data integrity

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Subject Nursing Pages 3 Style APA
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Answer

Week 2 Discussion

Topic: Health Data Management Review

            This paper provides definitions of data integrity and data security. Besides, the differences and similarities between data integrity and data security is also provided in this paper. Data integrity is defined as the accuracy and validity of data (Al-Saiyd & Sail, 2013). Data integrity can also be defined as the consistency and accuracy of data. Data integrity is the outcome of data security.

            Data security is the shielding of data against corruption and unauthorized access. Data security is one of the means of ensuring data integrity. Data security can include three functions, namely, securing of communications, access control, and protection of private data. Data security protects data from unauthorized manipulation, modification, observation, and/or interference (Al-Saiyd & Sail, 2013). Data integrity is judged based various variables such physical integrity and logical integrity. The physical integrity of data can be defined by aspects such as data validity, accuracy, and completeness. Logical integrity may be compromised if the retrieval or storage is irrational or incorrect in some way (Syncsort Editors, 2019). Compromise of data of data in interpreted as a breach in data security (Saxena & Dey, 2016).

Data security approaches for protecting data integrity include duplication of data and data backup. In addition, data integrity can be protected through use of input validation to help prevent entry of invalid data, improve detection of errors, and data encryption (Prakash & Agarwal, 2019).  Data security include use of a large spectrum of controls including control of stored functions or database applications, links to the network, database systems, data, and data servers (Mariuta, 2014). Data integrity can be a process as well as a state.  As a process, data integrity refers of measures that are used to ensure accuracy and validity of all data or a data set in a given construct or a database. On the other hand, data integrity is a state of accuracy and validity of data (Lagoze, 2014).

Data integrity is important since it guarantees the searchability, recoverability, connectivity, and traceability of data. In addition, data accuracy and validity ensures that the performance, stability, maintainability, and reusability of data are maintained (Prakash & Agarwal, 2019).  Maintenance of data validity and accuracy through effective data security measures will ensure that the decision making process that is informed by data is not faulty on itself leading to wrong decisions (Mariuta, 2014).

In conclusion, data integrity and data security are interrelated terms. Data integrity refers to the accuracy, validity, and consistency of data; whereas, data security is the protection of data from unauthorized access and corruption. Data security is necessary so as to achieve data integrity both as a state and well as a process. Data security ensures that data integrity is maintained as all time. Valid and correct data is necessary for making of informed decisions. 

Topic: Case Study: Preparing for a Joint Commission Survey Visit

            As the team leader of the Mock Joint Commission Survey Team, the following are areas and items, which should be surveyed in the Health Information Services Department. These include storage of data, analysis of data, transmission of information, and retrieval procedures. In addition, the completeness, security, and integrity of health information should also be including in the survey (University of Virginia, 2019).  On the other hand, different types of documentation standards should be surveyed include classification standards, terminology standards, informatics standards, records management standards, health information practice standards, accreditation standards, and data standards (American Health Information Management Association (AHIMA), 2019).  The source and areas and items to be surveyed were outsourced from the University of Virginia (2019); whereas, the documentation standards were retrieved from the AHIMA (2019) website.

 

 

 

 

 

References

AHIMA. (2019). AHIMA’S long-term care health information practice and documentation guidelines. Author. Retrieved on Mar 31, 2019 from, http://bok.ahima.org/Pages/Long%20Term%20Care%20Guidelines%20TOC/Legal%20Documentation%20Standards

Al-Saiyd, N.L., & Sail, N. (2013). Data integrity in cloud computing security. Journal of Theoretical and Applied Information Technology,   58(3), 570-581.

Lagoze, C. (2014). Big data, data integrity, and the fracturing of the control zone. Big Data & Society, 1(2). https://doi.org/10.1177%2F2053951714558281

Mariuta, S. (2014). Principles of security and integrity of databases. Procedia Economics and Finance, 15, 401-405. https://doi.org/10.1016/S2212-5671(14)00465-1

Prakash, A., & Agarwal, D.P. (2019). Data security and wireless systems. London: IGI Global.

Saxena, R., & Dey, S. (2016). Cloud audit: A data integrity verification approach for cloud computing. Procedia Computer Science, 89, 142-151.

Syncsort Editors. (2019). Data integrity vs. data quality: How are they different? Syncsort. Retrieved on Mar 30, 2019 from, https://blog.syncsort.com/2019/01/data-quality/data-integrity-vs-data-quality-different/

University of Virginia. (2019). Health Information Services. Retrieved on Mar 31, 2019 from, https://hit.healthsystem.virginia.edu/index.cfm/departments/health-information-services/

 

 

 

 

 

 

 

 

 

 

Appendix

Appendix A:

Communication Plan for an Inpatient Unit to Evaluate the Impact of Transformational Leadership Style Compared to Other Leader Styles such as Bureaucratic and Laissez-Faire Leadership in Nurse Engagement, Retention, and Team Member Satisfaction Over the Course of One Year

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