You are a quality analyst in a health information management (HIM) department appointed to lead a project team. Your team must assess the problem with the documentation of the patient’s discharge disposition status in the health record and present your findings in a meeting to the department.
An increasing number of errors have been reported, and frustration among the coders has risen. These coders claim that conflicting information is often present in the record, requiring them to spend an inordinate amount of time trying to obtain verification. Coding productivity has been affected. Explain how you would assess the problem, strategies that you may develop to resolve the problem, and a way to study the effectiveness of your strategies. Give examples of tools you would use to present your findings in the meeting.
Your research paper should be 3 pages long (excluding the cover page and reference page), supported by the readings from Week 4 and at least two additional scholarly sources (not Wikipedia etc.) Please adhere the writing rubric and let me know if you have any questions. This paper should be in proper APA format, which includes a title page, reference page, and APA-formatted references.
Lesson Reading: Examine legal and ethical aspects of health information management.
Because of their capacity to provide objectivity, data are a crucial element used to measure the quality of patient care. Data have been used to study the quality of patient care for over a century, leading in part to the development of accrediting organizations that concentrate on advancing patient care. Data collected from the patient’s healthcare record are a vital part of any quality initiative in the healthcare field, including those at the federal level. Private efforts to advance patient care have measured the performance of care and service through data collected at the healthcare provider level, with the HEDIS data set serving as a prototype for managed care plans. The use of quality monitoring cycles, benchmarking processes, and quality indicator reports has expanded vastly over the last few decades, assisting those within the healthcare field to improve the delivery of patient care and those outside the field to evaluate care given.
Two areas that depend greatly on data quality are performance improvement and risk management, with performance improvement concentrating on the review of clinical processes as a means to improve the quality of patient care and risk management focusing on the review of nonclinical processes as a means to reduce medical, financial, and legal risk to an organization. Both areas have gotten a lot of attention because of their potential to affect both the administration and delivery of patient care.
By contrast, utilization management emphasizes the appropriateness and planned use of resources as an effort to govern healthcare costs. This concentration has become essential to the delivery of patient care, as both accrediting and licensing standards require healthcare organizations to comply with utilization management requirements.
We will also review the historical development of healthcare quality including a review of the important pioneers and the tools they developed. Their work has been deliberated, polished, and broadly used in a variety of applications related to performance-improvement activities. We will also analyze risk management, with emphasis on the significance of coordination with quality activities. This is followed by is a discussion of the evolution of utilization management, with a focus on its relationship to quality management.
Numbers and mathematical theories have played a role in society for millennia. The past few centuries have seen the growth of healthcare statistics, ranging from the elementary level to the complex level. These statistics are characterized by category, with descriptive statistics playing the largest role in healthcare. Measures of central tendency appear regularly in the healthcare field like research studies, as well as in mainstream fields like press releases and articles. How data are gathered, utilized in calculations and formulae, and presented are essential to the practice of statistics in any field, including healthcare.
Relationships among data variables are the emphasis of regression analysis, an advanced statistical tool used in the emergent fields of clinical and applied informatics. Regression analysis is an important element of grouper programs. Health information management statistics concentrate on the use of statistical formulae on a routine basis. HIM managers count on productivity measures to determine how effectively the organization is being managed. Statistical instruments such as control charts, trend charts, and process capability analysis are used to address process problems, increase productivity, and contribute to the organization’s financial well-being.
Green, M., & Bowie, M. (2011). Essentials of health information management: Principles and practices
(2nd ed.). Clifton Park, NY: Cengage.
LaTour, K. (2013). Health information management: Concepts, principles, and practice (4th ed.). Chicago,
McWay, D. (2014). Today’s health information management: An integrated approach (2nd ed.). Clifton Park,
NY: Cengage Learning.
Sayles, N. (n.d.). Health information management technology: An applied approach (4th ed.). Chicago, IL:
Required Reading
McWay, D. (2014). Today’s health information management: An integrated approach (2nd ed.). Clifton Park,
NY: Cengage Learning.
◦ Chapter 7 & 8

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