Knowing the key stakeholders and users of analytics tools allows IT executives to discover the ways these people apply analytics to meet clinical quality and performance goals. In healthcare organizations, analytics affects almost all decision making, so effective data management and reporting enhances a wide array of roles.
Operational, clinical quality, and performance objectives help define why an organization embarks on quality improvement and business improvement initiatives that will be supported by analytics.
Accurate, relevant, and readily available data form the backbone of all analytics used for decision making. In the age of big data, it is important to understand which data sources are available, the quality of the sources, and how the data can be reported to provide insight into the many workflows and processes that are part of healthcare delivery.
It is also crucial to understand how this data can gauge related factors, including elements such as patient satisfaction expressed via social media.
From business intelligence and reporting to predictive analytics and simulations, there’s a range of analytical tools available to answer pressing business and clinical questions. Selecting the appropriate “tools that fit” ensures that the analytics are the right kind to address user needs and the healthcare organization’s business, clinical quality, and performance challenges.
People are a critical consideration when developing or expanding an analytics plan within a healthcare organization. If your culture supports collaborative analysis and decisions, you won’t feel pressed to bend your data to special interests.
The current, short-term, and long-term analytics needs of a healthcare organization need to be addressed early and often—before it acquires analytics-related capabilities and as it grows into using its big data.
An analytics strategy needs to evolve as analytics demands and capabilities evolve. It must be adjusted as technology becomes better or less expensive. Because of the rapidly changing landscape of healthcare analytics, a healthcare organization leadership team needs to revisit its plan frequently. IT teams also need to regularly check that the plan is up to date and that its execution helps the organization achieve its analytical potential.
Plan. Get your data in shape. Decide. Execute. Measure. Rinse and repeat, always improving.
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