Quality management frequently uses statistical methods to identify the existence of a quality problem and to analyze the root cause of the problem. Statistical methods require the collection of numerical data related to a process under investigation. The data can then be used to identify trends that can affect quality such as the rate of variance in the outcomes of a production process. The descriptive or inferential analysis of the statistical methods can also provide information about the most likely causes of the problem. Statistical methods also have predictive value because they can identify potential problems before they have a significant impact on quality (Ryan, 3).
Some of the statistical tools include descriptive statistics data such as frequency distributions, histograms, and inferential statistics analysis approaches such as regression analysis and analysis of variance (ANOVA). Each tool has advantages and disadvantages to their use. As a result, the use of the statistical tool often depends on the specific quality problem under investigation.
Descriptive Statistics Tools and Histograms
Descriptive statists provide a description of the the central properties of data obtained from observations. In quality management, the central properties can provide basic information concerning the amount of variance from a desired norm, which is a major advantage of using descriptive statistics. For example, descriptive statistics can provide information about the frequency of variance in desired tolerance that is greater than 10%, with less than 10% as the desired norm. In quality management, the descriptive statistical data that is of greatest interest is the central tendency, the dispersion, and the frequency (Madan, 268). In ad...
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...pes of information. At the same time, the disadvantages of the various statistical processes suggest that quality managers should use several approaches to analyzing data to ensure that their interpretation of the data is correct.
Works Cited
Christensen, Eldon, Christine Coombes-Betz, and Marilyn Stein. The Certified Quality Process Analyst Handbook. Milwaukee WI: Quality Press, 2007.
Lighter, Donald and Douglas Fair. Principles and Methods of Quality Management in Healthcare. Gaithersburg MD: Aspen Publishing, 2000.
Madan, Pankaj. Total Quality Management. Delhi: Krishna House, 2006.
Ryan, Thomas. Statistical Methods for Quality Improvement. Hoboken NJ: John Wiley and Sons, 2011.
Tari, Juan and Vincente Sabater. "Quality Tools And Techniques: Are They Necessary for Quality Management? International Journal of Production Economics, 92.3 (December 2004): 267-270.
After reading this book, I am touched by the underlying philosophy of statistics. Various theories and models are introduced in this book. During the progress of the development, controversies and confits among these theories are largely attributable to diversity of ideology and doctrine from their establishers. In future, the statistics might evolve into a new era and the vogue methods, like p-value or confidence interval, might be discarded. I am looking forward to witness how statistics make our lives
Furthermore, the methods applied convey “the techniques or procedures used to gather and analyze data that is
Evaluate the appropriateness and thoroughness of the data analysis procedures, and clarity of the results presentation. Do not become overly concerned about technical statistical aspects of the analysis.
To understand the strategies being adopted in various healthcare facilities in order to improve their scores on quality measures and if these strategies have proved helpful in improving the over quality of care.
Methods for quality improvement offer numerous benefits and there are many models to use for quality improvement. These models and features have traits in the up to date version of total quality management practise models and are of numerous benefits, with the likes of six sigma and kaizen model using these traits (Royal Charter, 2011)
Descriptive statistics is a procedure of organizing sample data. This procedure allows readers to be able to understand and describe the data’s importance. Descriptive statistics allows an individual to quickly understand the data and make predict an individual score; however, descriptive statistics does not describe all data in the sample. Inferential statistics is a process that determines whether sample data accurately represented the relationship to the population. In other words, one uses inferential statistics to determine if the sample data is believable.
Statistics was primely developed in 17th century. It was initially used in collecting population and recourses information of United States. But now, statistics is widely applied in various fields after hundred years of progress. Today, few professional activities are untouched by statistical thinking. However, only statistics itself cannot give any conclusions and findings. It is significant when complied with other subjects or studies resulted in numerous of different independent disciplines were developed, for example Environmental Health Statistics, Biostatistics and Economics Statistics, etc.
Introduction to healthcare quality management (2nd ed.). Chicago, IL: Health Administration Press. Young, G. J., Charns, M. P., & Barbour, G. L. (1997). Quality improvement for the US Veterans Health Administration. International Journal of Quality Health Care, 9(3), 183-188.
The Deming Application Prize, established in honor of Dr. W. Edward Deming, is awarded to companies that continually apply Company-Wide Quality Control and have achieved a certain quality standard (ibid.). The focus of this award is quality achievement of Deming's 14 points, which are verified through the use of statistical methods. The judging criteria consist of 10 major categories (ibid.): (1) policy and objectives, (2) organiza...
TQM was developed and utilized in other industries prior to adoption in health care (Shi & Singh, 2015, p.493-494). TQM has since modernized administration, reduced hospital stays, improved clinical outcomes, and improved patient satisfaction (Shi & Singh, 2015, p.493-494). Examples of utilization of the total quality management include improvement of patient safety through prevention of medical error incidences and as a positive influence for organizational learning and improvement. “Using total quality management approach to improve patient safety by preventing medication error incidences” is a study conducted at General Government Hospital to review current medication practices, implement a six sigma method through utilization of a five-step DMAIC procedure to find out the root cause for the errors, and establish solutions to avoid medication error occurrences throughout the hospital (Yousef & Yousef, 2017). The results demonstrated that the root cause was related to mistakes during prescribing due to poor handwriting (Yousef & Yousef, 2017). To decrease these errors, Guideline Recommendations to be followed by all physicians were published (Yousef & Yousef, 2017). This method is useful in decreasing errors during the prescribing phase and prevent the wrong medications from being administered. “Impact of Total Quality Management on Organizational Performance: Exploring the Contingent Effects of Organizational Learning and Innovation” is another article that discusses the importance of total quality management (Proceedings for the Northeast Region Decision Sciences Institute (NEDSI), 2017). This article examines the effect that total quality management can have on organizational learning and improvement. This has become an important concept for health care organizations specifically because of globalization and the pressure from insurers, accreditation agencies,
Understanding quality measurement is essential in improving quality. Teams need to be able to understand whether the changes being made are actually leading to improved care and improved outcomes. For data to have an impact on an improvement initiative, providers and staff must understand it, trust it, and use it. Health care organization must understand the measurement of quality provided by the Institute of Medicine (patient outcomes, patient satisfaction, compliance, efficiency, safe, timely, patient centered, and equitable. An organization cannot improve its performance if it does not know how it is performing. Measuring quality improvements is essential as it reflects the quality of care given by the providers and that by comparing performance
Product designing, in this stage for continuous quality improvement the parameters of the design gets changed and the level of tolerance gets altered. This is very difficult for the manufacturing companies in implementation stage.
Shepard, M. (2009, August). Improving quality and value in the u.s. health care system. Retrieved from http://www.brookings.edu/research/reports/2009/08/21-bpc-qualityreport
However, not all of these effects are foreign to accountants. A good example of this is that Total Quality Management focuses on fact based decision making and Cost and Managerial Accountants use this decision making process on a daily bases (Chartered Quality Institute, 2016; American Society for Quality, 2016). Realizing that total quality management does not just effect the decisions and policies of an organization is necessary for successful implantation. Since total quality management focuses on eliminating waste in all aspects of an organization, this includes how we collect and use production data, and internal controls on accounting
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