Abstract
The transformation of healthcare has and will continue to require a meaningful integration of data into bedside care, population health models, and sophisticated strategies to translate analytics into better outcomes. However, the ability to readily access, properly analyze, and effectively use data to drive improvement is still a challenge for many healthcare organizations. Harnessing the power of data for quality improvement requires a cultural change within many institutions and practices. Healthcare systems benefit when health informatics is applied and data is converted to useable information with timely delivery; this transformation requires both technology and expertise. Organizations must support cross-functional teams comprised of clinical, operational, and financial expertise with a data governance structure to support their functions. With the shift in healthcare payment models from fee-for-service to value-based payment (lower costs for better outcomes), there is an increasing need to measure both outcomes and costs with more accuracy and precision. This chapter explores key strategic elements needed to advance analytics in healthcare and how analytics can be applied to clinical decision support, population health strategies, and measuring the value of care.
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Macias, C.G., Carberry, K.E. (2021). Data Analytics for the Improvement of Healthcare Quality. In: Giardino, A., Riesenberg, L., Varkey, P. (eds) Medical Quality Management. Springer, Cham. https://doi.org/10.1007/978-3-030-48080-6_6
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