Effective of the Model of Standardizing Image Qualities

Over the years there has been a focus on the maintenance and enforcement of image standards. The Joint Commission of Implementation has been using various models in achieving the alternative to that is known as the at-home recovery. This essay evaluates the effectiveness of this model through an analysis of a summary of an article from a peer review journal and followed by the proper analysis on the study of the effectiveness of the Medical Improvement for Patients and Providers Act model. 

Article Summary

Analytics involves the study of historical data in projection the potential trends to improvement. It is multidimensional and timesaving. The rise in new Information technology firms has revolutionized the healthcare industries as data increasingly becomes a product and a service itself. The advantage is not absolute as the data may be able to ignore emerging changes in medical practice (Reine, 2013).

The historical medical data has been instrumental in the conduct of CT scans as it boosts the protocol of scans and optimizes the quality of images and reduces radiation thus improving the results of the tests through the creation of best practices. Presently, the image quality is affected by many factors among them the varying and fast-changing technology and increase the utility of the image services. The lack of a direct effect of quality on the monetary returns has a dampening effect on the motivation to improve image quality.  The limitation of the image quality is furthered by the delegation of the obligation to service providers who are more subjective. The Pay for performance and MIPPA models can be quality-centric solutions.

Standardization of the standards is also a concern that if settled enables comparison of results across areas and over time and analysis of relationship with a complexity of examination. This is exemplified by the deficiency of MQSA and BI-RAIDS methodologies. A qualitative model that takes into account the exam complexity and various variables such as parental, technology, data and examination profiles can settle this concern. This means that the image quality and the consideration of exam complexity go in hand to result in a composite quality of images. Additionally, the analyses should include the context analyses since the decision of a good a radiologist is subjective on the viewer after all.

The workflow and efficiency can also be improved by applications for decision support for use by the radiologists and the consumers. They include protocol optimization that utilizes the parameters of acquisition and image processing. The other is the dose optimization which ensures that the reduction n in the dose does not compromise the image quality.

Analysis and Opinion

Data analytics has permeated all the areas of business. But to state that the potential in the health care remains untapped is misleading.  This is because the article grapples with the models used in the provision of CT scans. Further, there is a remarkable entry of Companies such as IBM, Google and Microsoft exemplify how there are of healthcare data analytics have been tapped. The proper premise would be that the data analytics implementation models are inadequate and thus insufficient, concerning ensuring image quality.

The Article decries the subjective nature of the analyses of the quality of images. The article also notes the commercialization of imaging services. This is undoubtedly true. However, it is possible that that the solution to this problem may not be way above control. This is because the medical and clinical practices are professional practices governed by professional standards and ethics. As a profession, therefore, the promise of return ought not to override the quality of the services to the public. Therefore, the profession should be keen on standards that apply to all persons in practice.

Additionally, there is a lack of standardization format for recording and analysis of clinical data. Through there are some of the standards used, they are not consistent. In my opinion, this does not pose an immediate problem as rarely would a patient be faced with a situation where a choice has to be made between two or more radiologists. However, given the rising need for consumer protection, this is a concern worth settling in the long term.

The projected approach by MIPPA for an elimination of at-home recovery and introduction of new standards is thus unrealizable due to its inflexibility (Bloink, 2013). The Supreme Court decision in Olmstead case favored the existing bias for health-care services in nursing homes. From the analysis of the article, standardizing the formats of data analyses involve multidimensional approach and considerations to certain variables that easily change with time. It would, therefore, be safe to state that the current standards such as MQSA and the BI-IRADS in the breast imaging are a fair representation of the best practices so far.


In conclusion, it is evident that the strategies of standardization of image quality introduced by MIPPA are geared towards development and achievement of certain goals. However, there seems to be more effective and wholesome means of approaching the change and given the long-standing bias in the nursing homes, the strategies would be largely ineffective.