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Healthcare Operations Management - Essay Example

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"Healthcare Operations Management" is a perfect example of a paper on the health system. The process of descriptive analytics sets into meaningful information that assists the healthcare team to make decisions. Through statistics from descriptive analytics, the past performance is examined and summarized to discern data trends and patterns to be able to explain individual behavior…
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"Healthcare Operations Management" is a perfect example of a paper on the health system. The process of descriptive analytics sets into meaningful information that assists the healthcare team to make decisions. Through statistics from descriptive analytics, the past performance is examined and summarized to discern data trends and patterns to be able to explain individual behavior. The reporting mechanisms, such as quality measures, regulatory compliance, and financial results used in descriptive analytics.

Descriptive analytics can make up the largest analytics field, with the main feature as data visualization to be able to make data easily consumable by individuals (Daniel B, 2017). The healthcare operating issues that could benefit from descriptive analytics are the reports from business intelligence, dashboards with key performance indicators, descriptive statistics, and traditional data visualization techniques.B. Predictive.Predictive analytics can build models on a data basis that enable health practitioners to forecast the probabilities in the future.

The models are not correctly predicted in the future. Still, they can provide for the same individual's insights to be able to make decisions that are more effective in concern to the healthcare operating issues. Predictive analytics can use statistical techniques varieties ranging from regression models to machine learning to data mining. The activities will be able to make future events projections. Disease management and population health have enabled the use of predictive models in healthcare operating issues (Daniel B, 2017).C. PrescriptivePrescriptive analytics can provide the healthcare decision-makers with the necessary models that offer the right guidance to be able to give recommendations for the operating issues.

The presented models suggest a form of advice. The combination of predictive models includes optimization, mathematical models, and other techniques that enable individuals to generate prescriptive solutions (Daniel B, 2017). The rigid model solutions include the staffing models that will allow quality maximization through an outcome that minimizes costs. The capacity maximization in terms of models in operating rooms in the authoritarian model. The demonstration of strategic models that efficiently allocate the capital investments in the strict model and the risk of minimization of events concerning the adverse in health.

CHAPTER: 101. What are the drivers of the healthcare industry’s focus on patient satisfaction and effectively employing resources?The importance of patients’ satisfaction is an indicator for the provision of quality health care. Clinical outcomes, patient retention, and medical malpractice are indicators of patient satisfaction. The drivers of the healthcare industry’s focus are to enable the patients to receive the heat care services whenever needed and also to deliver the health care services that are considered as cost-effective and are able to meet the standards pre-established to provide quality services.

The drivers should be able to engage patients in the healthcare industry in services that are affordable to be able to maintain wellness to the patients’ health and resources. Therefore the drivers should focus on the patients’ easy access to the care needed for the patients to achieve optimal health outcomes (Daniel B, 2017). It is important to note the treatment delays can lead to irreversible progression of the disease and even the resources from the patients become exacerbated.

Therefore the drivers of the healthcare industry should be focused enough to promote satisfaction from the patients.2. What are the differences between Lean and Six Sigma? The similarities? Would you like to see both applied in your organization? Why or why not?The Lean production initially developed by Taiichi Ohno, Toyota's Chief output after World War 11. The Massachusetts institute researchers studied the Toyota Production System. The origin of the Lean system was from just-in-time production, which became adopted widely in the operations concerned with the manufacturing of the Lean system.

The Lean was able to spread fast into the healthcare organizations through waste removal from the system; therefore, this improved the clinical safety measures. The Six Sigma, total quality management, and continuous quality were able to create customer value improvement through the elimination of defects values. Six Sigma is also able to create a seamless flow to eliminating waste from the customers (Daniel B, 2017).CHAPTER: 112. Which process improvement tool can have the most powerful impact,and why?

The Lean, the improvement process projects can focus on waste elimination and therefore improve the flow in the system. Through the kaizen philosophy, the lean basis includes the specific value identified to provide for the perspective of the customers, the improvement in the value stream, and the map to determine the sequence of activities. To enable the flow, to allow the current to move quickly and smoothly, to allow the pull, to pull the products and services for the customer. Perfect, to enable the cycle to repeat on continuous improvement.

The importance of Lean is value stream mapping, which allows the process definition to determine the occurring waste (Daniel B, 2017).

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