Virtually all healthcare organizations are repositories of huge and perpetually growing amounts of data. Some data is collected as part of mandated programs such as the Consumer Assessment of Healthcare Providers and Systems (CAHPS) surveys. Some data is collected as part of federal, state and local regulatory requirements and some is collected by the organization to insure that the organization will meet its own organizational goals and objectives. Regardless of the source of the data, it can ultimately be a difficult to impossible task to insure that the data is being synthesized in such a way as to make it meaningful and truly useful to the organization.
Clinical analytics helps healthcare leaders use medical data (in real-time or not) to generate insights, make decisions, improve revenues, reduce costs, reduce medical errors and improve patient outcomes. Clinical analytics can aggregate the large amounts of disparate data that all healthcare organizations have to improve decision making and identify opportunities for improvements in quality and efficiency.
Focus on clinical analytics has been increasing over time perhaps because of the move towards accountable care and value-based reimbursement. Accountable Care Organizations (ACOs) are groups of doctors, hospitals and other providers who deliver high-quality, coordinated care to their Medicare patients. Coordinated care that delivers the right care at the right time is higher quality care and can also reduce healthcare spending, but it depends on having actionable data that will help drive treatment decisions and reduce errors. Another key driver in the emergence of healthcare analytics is the prevalence of electronic health records or (EHR). EHR puts health information in the hands of providers instantly and can also be mined for analytical purposes. Of course, while EHR contributes to the collection of data, it does not aggregate or report the data in such a way as to make that data meaningful on a more global level.
The Institute of Medicine (IOM) identifies six key components of quality:
EHR can provide organizations with data that will provide performance data on each of these six metrics. It can end there unless there is a coordinated effort between health data scientists, technology and quality experts and providers. Clinical analytics can turn this data into actionable information that providers can use to drive towards safer and more effective and efficient care. It can also be foundational to improving individual provider competence.
Once your organization has tapped into the power of clinical analytics the next step is using that analysis to optimize the appropriate support through training. HealthStream's suite of competency products can help you connect the dots between what your organization has learned from its' clinical analytics and what your team needs to build competency.
Clinical and workforce data can be used to reduce errors, provide safer, more effective care and build a culture of patient and family-centered care. It can also help build engagement, retention and satisfaction by providing training that supports growth and career development.
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