• Scaling down clinical variation – Seen as a hallmark cause for defects in quality and a driver for increasing costs of care across all patient types, geographies and socio-economic environments, clinical variation is a challenge many healthcare organizations are struggling with across the country today. Data is beginning to play a more prominent role in helping to better ensure quality across systems, reducing clinical variation, and improving cost and quality outcomes.

By identifying and visualizing trends that lead to deterioration using data from electronic health records (EHRs) through real-time clinical analytics, providers are given a standardized way to identify deteriorating patients, intervene earlier, and reduce unplanned transfers.
• Improving transitions of care – With an aging population and shifting value-based reimbursement models, it is becoming more important for acute and post-acute care organizations to work more collaboratively during transitions. Similar to standardizing interventions for patient deterioration, clinical analytics can help to standardize the transitions of care to improve the outcomes of the patient and workflow, as well as reduce readmissions.

Determining the appropriate level of post-acute care that is customized to a specific community is key, and is a challenge that data can help ease. Using clinical analytics to visualize a holistic picture of a patient's condition, care providers will be able to better understand their condition at the time of discharge, enabling them to improve communication and ensure the patient will receive the right level of care.

As the transition to value-based care continues to be a top industry priority and powers the emerging role of real-time clinical analytics, these solutions can provide needed improvement to many key areas of patient care, transforming healthcare as we know it.

About the Author: Carolyn Scott, RN, M.Ed., MHA, is the senior vice president and chief customer officer at PeraHealth

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