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Data-Driven Decision Making in Healthcare

   

Added on  2020-04-15

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Running head: LEADERSHIP IN HEALTHCARELeadership in HealthcareName of the Student:Name of the University:Author’s Note:
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1LEADERSHIP IN HEALTHCAREVision: As a healthcare leader, the vision in support of data-driven decision-making includesmanaging throughput and workforce optimization. Example:After evaluating the data from the healthcare organization, the decision was made toredesign the emergency room of the future by optimizing the physical layout of the room. Afterconsidering the data-driven by the healthcare, it has been seen that the emergency room needs tobe redesigned for convenience and comfort of the patients. The doctors, nurses and the staffs willbe provided with data ID badges that will make it easier to monitor the physical and digital worldof the emergency room. The challenges in supporting data-driven decision-making include:The quality of data that is considered for decision-making. Though technology is used todisparate and manage large data, accessing the large data is sometimes an issue. This isbecause accessing the data from the cloud is a major challenge for the healthcareorganization due to which the quality is hampered (Raghupathi & Raghupathi, 2014). Another issue with making data-driven decision-making is that people with exceptionaldata analytics expertise are difficult to find. The healthcare organization is facing extremechallenges to find the right person for analysing the data for improved decision-making(Groves et al., 2016). The analysis of data needs to be a continuous process that needs to influence thedecision-making. However, analysing the data in the healthcare sector are oftenhampered due to lack of experienced and skillful employees thereby, derivinginappropriate data that hampers the decision-making.
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