Healthcare Leadership: Data-Driven Decision-Making and its Challenges

This report explores the significance of data-driven decision-making in healthcare leadership. It highlights the importance of using data to optimize processes, such as redesigning emergency rooms based on data analysis. The report identifies challenges like data quality, accessibility, and the need for skilled data analysts. It also emphasizes the importance of continuous data analysis to inform effective decision-making. The assignment provides an overview of the practical applications of data-driven decision-making and the obstacles that healthcare organizations may face in implementing these strategies. The report concludes by discussing the importance of integrating data analysis into the healthcare setting to improve patient care and operational efficiency.

Running head: LEADERSHIP IN HEALTHCARE
Leadership in Healthcare
Name of the Student:
Name of the University:
Author’s Note:

1LEADERSHIP IN HEALTHCARE
Vision: As a healthcare leader, the vision in support of data-driven decision-making includes
managing throughput and workforce optimization.
Example:
After evaluating the data from the healthcare organization, the decision was made to
redesign the emergency room of the future by optimizing the physical layout of the room. After
considering the data-driven by the healthcare, it has been seen that the emergency room needs to
be redesigned for convenience and comfort of the patients. The doctors, nurses and the staffs will
be provided with data ID badges that will make it easier to monitor the physical and digital world
of 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 to
disparate and manage large data, accessing the large data is sometimes an issue. This is
because accessing the data from the cloud is a major challenge for the healthcare
organization due to which the quality is hampered (Raghupathi & Raghupathi, 2014).
 Another issue with making data-driven decision-making is that people with exceptional
data analytics expertise are difficult to find. The healthcare organization is facing extreme
challenges 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 the
decision-making. However, analysing the data in the healthcare sector are often
hampered due to lack of experienced and skillful employees thereby, deriving
inappropriate data that hampers the decision-making.

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 Additionally, data-driven decision-making is challenging, as the employees might not be
able to understand and interpret the data for correct decision-making.

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References
Groves, P., Kayyali, B., Knott, D., & Kuiken, S. V. (2016). The'big data'revolution in healthcare:
Accelerating value and innovation.
Raghupathi, W., & Raghupathi, V. (2014). Big data analytics in healthcare: promise and
potential. Health information science and systems, 2(1), 3.