Data Analysis and Analytics Research
There has been increased debate on the influence of health, financial and the public health over the years. For the years that have elapsed, the use of data has been viewed as important in making decisions within the health sectors. Clinical performances measurements are factors that have increased in demand of late in all the major sectors of the economy. Quantitative analysis has become a major factor in the decision-making models and as such, there has been increased input from various departments with the primary aim of ensuring that the analysis of data within an organization is efficient and as such, there is need to ensure that organizations implement the necessary data analytics within the various industries. This paper analyzes various concepts relating to the confidentiality of data within the workplace of employees (DeGaspari, 2015).
The concept of performance measurement has been emphasized from various quarters. As such, the delivery of healthcare has been quantified and a formula structure whereby the outcome of the entire process depends on structure and process (DeGaspari, 2015). According to the Joint Commission for Accreditation of Healthcare Organizations (JCAHO) there is increased the need to ensure that performance is improved (Devine et al., 2008). The structure, in this case, refers to the physical plants or the additional structure of the organizations. Additionally, processes are specific to patients and are initiated by health care professionals, and these include acute myocardial infarctions (AMI). The concept in this case requires that both the outcomes and the available structures ensure that the available information is only made available to the relevant authorities. Finally, the outcomes refer to the interactions between the patients and the medical professionals and as such should be considered as the essential parts of the data development. As such, to achieve the most desirable outcomes, it is appropriate to ensure that the most effective data protection strategies are effectively implemented (Devine et al., 2008).
Clinical data has been identified to have a major stake in the health sector. In the United States, such data has been identified to have a greater potential in transforming the health docket and achieving greater outcomes as desired by the health professionals (DeGaspari, 2015). There are various types of data that are being used by the both the private and the public entities: the health survey data, administrative data and the information regarding the general patterns of consumptions. The Nationwide Health Information Network (NHIN) and the National Committee on the Vital and Health Statistics (NCVHS) can be used for various reasons and thus ensuring that the available data is used to improve the quality of services as well as ensuring that the costs of operations are considerable reduced (Devine et al., 2008). Moreover, the available data should be analyzed to provide the most efficient platform through which the public relations, financial and the healthcare sectors are well catered for.
According to research, optimization is likely to occur during the entire process of implementing the EHR. However, to achieve this, there are a series of issues that have to be taken into consideration to ensure the success of the entire process. DeGaspari states that establishing and measuring the KPIs is one way through which the outcomes can be significantly improved (DeGaspari, 2015). As such, specific targets as well as benchmarks should be set to determine the various ways through which the progress of the process is to be evaluated. Additionally, for the optimization of the clinical, financial and public health care to be successful, there is to assess the people and the technology used as the improvement tools. Such tools include Six Sigma and Lean. Optimization is also necessary for the achievement of outcomes. In this instance, the best practices arising from EHR user groups should be used. Additionally, it is necessary to constantly monitor the results and establish the mechanisms through which they can be sustained. After that, a change occurs within the system; in this case, the transitioning ownership of the new process is integrated into the front-line operational leadership (Devine et al., 2008).
The influence of leadership on innovation is an important element in decision making. As such, it is necessary for organizations to develop mechanisms that are likely to facilitate the necessary change within an organization (Barsh, Capozzi & Davidson, 2015). To achieve the most desirable results from a combination of leadership and innovation, it is necessary to define the kind of innovation that enables growth and ensures that the strategic objectives of the health care sector are achieved. Additionally, innovation models should be integrated into the formal agenda of the organizations during the periodic meetings. Finally, it is necessary to set the metrics for measuring performances and the targets that the public health care system in a country desires to achieve within a specific time frame (Barsh, Capozzi & Davidson, 2015). The metrics that have been implemented within an organization must be able to highlight instances when the data confidentiality has been compromised or not. In instances where specific breaches have been identified, it becomes imperative that the individuals and systems in place are improved to a higher level to avoid misuse of medical data available.
Barsh, J., Capozzi, M. and Davidson, J. (2015). Leadership and innovation. Retrieved December 24, 2015, from http://www.mckinsey.com/insights/innovation/leadership_and_innovation
DeGaspari, J. (2015). Six Steps for Outcomes-Based Improvement | Healthcare Informatics Magazine | Health IT | Information Technology. Retrieved December 24, 2015, from http://www.healthcare-informatics.com/blogs/john-degaspari/six-steps-outcomes-based-improvement?page=2
Devine, S., Dagher, R., Weiss, K. and Santana, V. (2008). Good Clinical Practice and the Conduct of Clinical Studies in Pediatric Oncology. Pediatric Clinics of North America, 55(1), pp.187-209.
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