From Data, to Knowledge to Action: Leveraging Clinical Analytics to Impact Patient Outcomes

Thomas Van Gilder
Thomas Van Gilder

Guest post by Thomas J. Van Gilder, MD, JD, MPH.

Electronic health record (EHR) technology has become truly transformative for the healthcare industry; prepared or not, healthcare teams are increasingly relying on new information technologies to improve the delivery and management of care. EHRs have enabled faster and easier access to patient information, and hold the promises of improved workflows, efficient sharing of information across communities and reduced costs for many physicians and hospitals.

But now that nearly 80 percent of physician practices in the U.S. today have EHR systems in place and the Centers for Medicare & Medicaid Services’ (CMS) meaningful use program is well underway, it is time to look to the next stage of health care technology and innovation. Health care teams must now move beyond the first step of digitizing patient records to transforming this valuable data into meaningful and actionable knowledge that will help care teams make more informed decisions at the point of care and ultimately, improve outcomes.

For this impact to take place at both the individual level and at the population level, care teams need to leverage clinical analytics that will provide visibility into important clinical trends across the entire population. For example, being able to review trends in diabetes care or readmission rates across a population represents an opportunity for specific, meaningful change to improve care delivery and outcomes.

For a practicing clinician, “population health management” means being able to see where an individual patient is within the clinician’s or clinic’s population (e.g., whether the individual’s chronic condition is above or below population benchmarks) and to take action at the point of care, as well as being able to refer to relevant population health metrics.

For a patient, clinical analytics presumes trust, not only in the competency and care of the physician, but also in the security of his or her information. Population health management and analytics tools must ensure that patient information can be gathered, stored, and used in a way that is demonstrably secure.

Care teams should consider four key elements when exploring clinical analytics tools for population health management:

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