Identifying applicants Riskstratification using pharmaceutical data, in combination withbehavioral insights, can identify that plan member before atraditional condition-based program can. (Photo: Shutte

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Self-insured employers seeking to squeeze costs out of theirhealth plans have taken savvy steps to target specific membersub-segments for supplemental care. The rise of programs specificto cancer, diabetes and heart disease, and musculoskeletalconditions like arthritis, attests to the recognition that reducingthe costs of a few high users can have faster, greater impact onboth overall costs and individuals' health outcomes than addressinga broader population.

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These population health efforts almost always focus on aspecific condition or disease. It's a solid step, and the effortshave made an impact–but self-insured employers are leavingcost-saving and member care opportunities on the table.

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Related: 5 tips for self-insurers to up their populationhealth management game

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Targeting people for intervention based on their having achronic condition means they must already bevery sick, and very expensive. And focusing on high-cost conditionsbased on typical industry trends means a natural exclusion of otherutilization that could not only have a higher short-term spendcomponent, but also be based on individual patient variables thatcould drive up higher costs in the future.

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When pharmacy data is considered in risk stratification, though,employers can identify "red flags" that drive costs up and thatpredict future costs, at an individual member level, withoutrelying on a diagnosis of a specific condition.

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Take, for example, a plan member who is morbidly obese. Theyhave a prescription for a rescue inhaler, are taking a statin tolower cholesterol, and they're on a blood thinner, related toplacement of a stent to unblock a clogged artery.

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A pharmacist can see this combination of drugs. They can seethat populations on such a drug combination statistically progressto higher costs, further health deterioration, and higherabsenteeism at work.

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Risk stratification using pharmaceutical data, in combinationwith behavioral insights and analysis of proprietary morbiditystatistics, can identify that plan memberbefore a traditional condition-basedprogram can. Pharmacy-based population health management can flagthat individual for nutritional counseling and other medical andbehavioral interventions, so that person receives disruptive carethat can prevent future costs. And as data integration acrosshealth care specialties progresses, pharmacists will also be ableto see lab results and social determinant data that, when combined,can provide more effective, more comprehensive and less biased riskstratification.

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The cost implications of population health management via thepharmacy benefit are huge: Pharmacy spending is at greater than $300 billion, and prescriptiondrug costs make up 25 percent of an average employer'shealth care expense.

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To examine whether their clients' pharmacy benefit plan isproviding enough resources for a plan sponsor to disrupt potentialfuture pharmacy and medical costs, advisers and brokers toself-insured employers can consider whether the pharmacy benefitprovides:

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Risk stratification based on longitudinal analysis ofmember clinical and financial cost. This approach iscondition-neutral and outcome-sensitive. Multiple data inputsshould include not just prescription claims, but also prescriptionprior authorizations, medical and behavioral health claims. If thedata is available, even lab results and social determinants can beintegrated into pharmacy-based population health management.

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Examination of prescriber profiles provides an additional layerof analysis for this total cost of care view. Such a portraitallows for deeper prescription case management and alignment withthe medical plan.

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Targeted interventions. Daily claims reviewshould support self-insured employers' efforts to identify anddeploy additional care resources to members. And since members arerisk-stratified based on a combination of variables rather than aspecific condition, interventions should be defined on a case bycase basis. The additional legwork required here demands personal,human attention, informed by a data-driven risk stratificationengine. Interventions work only if they incorporate individualbehavior, both that of the prescribing physician and of thepatient.

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In this manner, you move from identifying one diagnosis for caremanagement, to selecting members with a variety of conditions thathave the highest risks and largest opportunity to effect change.Our pharmacists flagged a cancer patient who was taking three 20mgpills of Cabometyx per day, at a cost of $45,192 per month. But a60mg pill costs the same as a 20mg pill. Following a consultationwith our pharmacist, the physician changed the prescription to asingle 60mg pill per day, reducing the number of pills the patienthad to manage and resulting in an annual cost savings of $361,536on that single drug.

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In another example of pharmacy data offering a morecomprehensive view, a patient with psoriatic arthritis wasprescribed a 90mg dose of Stelara every 12 weeks. That's aclinically appropriate treatment for the diagnosis … but when ourpharmacist reviewed the patient's biometric variables, they flaggedthat the dose was too high for the patient's weight. Reducing to a45mg dose saved the plan $40,986.68 per year and resolved thepatient overmedication issue.

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Physician engagement. Out with the fax machine.Pharmacist-physician collaboration should capitalize on thepeer-to-peer relationship and offer physicians a supportive,reachable, know-them-by-name partner in member care decisions. Ourpharmacists engage with 88 percent of the prescribing physicians onour members' plans, usually by phone and never by impersonal formletters. When our pharmacists recommend an alternative therapy,physicians make the switch 64 percent of the time. The result is a93.5 percent prescription adherence rate and a 2.3 percent permember, per month pharmacy cost trend across a quarter of a millionmanaged lives.

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Population health management is a valuable approach todisrupting the paths of plan members who will cost more infuture, but the key to doing so is to catch them beforethey hit a point where they already have a high-cost diagnosis.Amplifying medical benefit population health efforts byincorporating insights from the pharmacy benefit is the way forself-insured employers to more comprehensively identify and disruptfuture cost drivers.

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Karthik Ganesh is president of EmpiRx Health, aboutique value-based PBM specializing in pharmacy cost containmentwith a risk-bearing model that includes population healthmanagement, differentiated physician engagement and a high-touchservice experience.

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