HQS 640 DQ 15 Paper
HQS640 DQ 15 Paper
Organizations, including those in healthcare, are leveraging data to help them identify challenges, capitalize on opportunities, make timely decisions that impact their overall operations, quality of care and services, and overall patient outcomes (Yeng et al., 2020). Data driven decision making (DDDM) is a process of using data to make informed and verified decisions to improve quality care in healthcare organizations. Individuals, especially organizational leaders, managers, and nurses use modern analytics tools like interactive dashboards to overcome biased and attain the best choices and managerial rulings that align with quality improvement and increase the attainment of their business goals (Stobierski, 2019). Therefore, data-driven decision making allows healthcare organizations and their manager to guard against biases, define their quality improvement objective, collect relevant data, and organize it effectively to arrive at informed decisions and choices to benefit care process.
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Through data, leaders and manager find trends and patterns so that they make decisions that are based on facts. For instance, in healthcare settings, the implementation of innovative care models, like value-based purchasing, use of artificial intelligence, and deployment of evidence-based practice (EBP) interventions all depend on effective analysis of data and getting trends and patterns that support such approaches (Shah, A.2019). Using dashboard offers a powerful tool to analyzing key performance indicators (KPI) in healthcare and enhancing patient care and management of facilities. Healthcare dashboards offer a visually balanced information hub that is designed to streamline patient care and reduce operational costs. Improving quality implies that healthcare leaders and organizations reduce inefficiencies and errors that could mark the difference between life and death. Therefore, making informed decisions allows providers like nurses to improve quality of care by minimizing and preventing infections like hospital acquired infections and implementing interventions that offer better patient outcomes
References
Stobierski, T. (2019). The Advantages of Data-Driven Decision-Making.
https://online.hbs.edu/blog/post/data-driven-decision-making
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Shah, A. (2019). Using data for improvement. BMJ, 364. doi: https://doi.org/10.1136/bmj.l189
Yeng, P. K., Nweke, L. O., Woldaregay, A. Z., Yang, B., & Snekkenes, E. A. (2020, September).
Data-driven and artificial intelligence (AI) approach for modelling and analyzing healthcare security practice: a systematic review. In Proceedings of SAI Intelligent Systems Conference (pp. 1-18). Springer, Cham.
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How does data-driven decision-making affect quality improvement? Provide at least one example when you have seen this used in your professional life.