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One of our recent posts, “Prescribing Intelligence: The Role of Data Analytics in Combatting the Opioid Epidemic,” focused on the usefulness of data within clinical decision support tools to help clinicians at the patient bedside. In that article, we made the key point that “analyzing and accurately indexing data” is a critical hurdle that must be crossed if big data is going to be useful for clinical care delivery. That challenge—the ability to rack, sort, and access the most important information at the right time—is perhaps the biggest challenge that electronic health records face among the clinician community. But there is also a second side to that problem as well—how can clinical leaders and administrators use the insights developed from platforms, including AffirmHealth’s Shield, to drive meaningful change across their organizations? How do we take the thousands of individual encounters that we shape at the bedside, and turn them into meaningful behavior change on a much larger scale? We believe that’s the question we have to answer to keep making progress against the opioid epidemic.
The First Wave: Automation & Efficiency
Over the last several years, we’ve seen a number of companies working in the opioid space, including our own, integrate morphine equivalency dosage calculators and PDMP automation tools into electronic health records. Some of these platforms have gone an additional step and help facilitate interstate data sharing of PDMP data. There’s no doubt that having that information has been instrumental in helping to change unsafe opioid prescribing behavior and minimize duplicate opiate prescriptions.
The limitation with this type of information, though, is that unless you can look across macroscopic trends in the organization at local, state, and interstate geographic areas, then you’re left to intervene at only a small scale. We believe that for large health systems, being able to best serve their patients means looking at what’s happening across the organization, and then using that data to target interventions where they’re needed most.
The Second Generation: Data Analytics
For a practice administrator or healthcare leader, whose critical interests not only include the best clinical care delivery, but also efficiency, compliance, and cost management, the next generation of opioid risk management tools must be able to deliver customized information that connects multiple inputs. For example, the savvy administrator may not only want to know how many patients are receiving concurrent opioid-benzodiazepine prescriptions -- but also how many patients are receiving those scripts sorted by prescriber, specialty, and geographic location plotted against patient satisfaction scores and retention by month. Or, they may want to know what the most common opioid prescriptions are within their organization and how those scripts vary by diagnostic code and geographic location. We’ve previously discussed how the opioid epidemic is heavily influenced by provider populations and geographic location. As such, the macroscopic prescribing data becomes even more critical -- without it, it's likely that efforts within the clinical community will stall into isolated pockets of success and failure.
Health Tech Affecting Opioid Crisis: Critical Components
In his Healthcare IT News article, “How Leading Health Systems Customize EHRs, Leverage Analytics to Improve Opioid Prescribing,” Mike Miliard writes about how “clinical buy-in and engagement” as well as “IT leadership” are two critical components necessary if big data is going to be effectively leveraged against the opioid epidemic. In our experience at AffirmHealth, we’ve absolutely found that to be true—the leading organizations we work with have both clinical champions and IT leaders that are dedicated to building systems that deliver the second-generation tool discussed above. We have been intentional to architect a platform that supports clinicians at the point of care while providing clinical leaders and administrators actionable data intelligence.
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