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Population health analytics key to value-based care

As healthcare moves to value-based reimbursement, analytics is becoming increasingly important for the efficient practice of population health management.

Craigan Gray, M.D., is chief medical officer at New York-based Salient Management Company, a management software and consulting company with a healthcare practice among its other industry concentrations. Gray, who also holds law and business degrees, formerly was director of North Carolina's Medicaid program. He talks with SearchHealthIT about population health analytics and its applications in value-based care.

This is the first part of a two-part Q&A. In part two, Gray talks more about value-based care and his experience with North Carolina's Medicaid program.

How critical is population health analytics to value-based care?

Craigan Gray: It is very important to understand the population you have under your care as a physician, to understand how you can bring value to that care. Because keep in mind that the population is made up of individual patients, individual people, each having a unique medical profile that needs attention. So in the important stuff, the individual encounter, the conversation between the nurse and the patient, the doctor and the patient, other caregivers with the patient, there's a key to success in the management of population health.

When you're talking about analytics within the objective of managing care, it becomes very important.
Craigan Gray, M.D.chief medical officer, Salient Management Company

When you're using population health analytics for value-based care, how important are benchmarking and tracking metrics and how do you use them?
Gray: When you're talking about analytics within the objective of managing care, it becomes very important. Because what it will do, whether it's on the population; micro-population; or macro-population, say state-wide, level, it puts together all the elements that will measure for success within managing that population, both financially and clinically.

For example, you want to look at emergency room utilization -- one of the least appropriate venues for managing the individual care, unless there's a true, life-threatening emergency that needs to be managed then and there. Look at emergency room trends. Who is using the emergency room, how frequently and for what purposes? Are they using the emergency room inappropriately? Are they using it for their primary care or for drug-seeking or for mental health issues, which are best managed in another venue?

Craigan Gray, M.D., chief medical officer, Salient Management CompanyCraigan Gray

How can analytics pinpoint gaps in care? And once you do identify the gaps, how do you use population health analytics to bridge them?
Gray: There are multiple gaps in the care that analytics help to reveal by looking at trends within that particular population, looking at those individuals that are utilizing healthcare inappropriately.

One of the most common ones is the gap in care of mental health, and then one of the reasons why those particular patients move to an emergency room for care. The gap in care may be [that] there should be an intermediary stop for mental health, a mental health urgent care facility to receive those patients who usually would go to the emergency room. They might best go to a mental health urgent care where their immediate mental health problems could be cared for at a 24/7 facility.

Another gap in care on the micro-population level is at the physician's office. The office could be closed on Friday, and they have a gap in care. Patients call the office, and they say, "If you have an emergency, call 911; otherwise, the office will be open on Monday morning." So where do those patients go? They go to the emergency room.

There are other gaps in care with the management of most operative patients, such as the transitions between hospital and the primary care physician after they're discharged from the hospital.
How is population health analytics not just a tool for providing value-based care and better outcomes, but also for helping physicians learn?
Gray: An analytical tool can help the physician see his or her population in the aggregate on a disease basis. For example, analytics can help a doctor see all of his diabetic patients in the aggregate with names and hemoglobin levels. They can then see that portion of their patient population, their micro-population, that is having particular problems or [is] at risk for increased problems because of the high level in sustained hemoglobin A1c.
Or they could look at that same population and see who is not getting frequent eye examinations on a regular basis or that same population that is not getting an annual wellness visit, so then they can map out care for the following year. Or if they have a population that has chronic obstructive pulmonary disease, those [are] patients that are particularly susceptible to pulmonary and similar infections.

So analytics would then reveal to that physician all of this diagnosis, all of the patients with the diagnosis of COPD. That's not on the basis of claims data, but of the clinical data. Out of that population, which ones have received the [pneumococcal] vaccine or which ones have received their flu shot for the year or which ones haven't, and more importantly, that gap in care can be remedied by calling those patients in to receive those particular immunizations.

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