April 2007 • Volume 18 • Number 4 www.PMToday.com

Advancing theMarketing Plan:StrategicMarketing andBrandingRefinedInside

■ Engaging Physicians in OnlineContinuing Medical Education

■ Building the Business Case for Culturally CompetentCommunications in Health Care

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14 PRODUCT MANAGEMENT TODAY • April 2007

Industry Intelligence

Songwriter Neil Diamond observed, “When you’re on a merry-go-round, you miss a lot of the scenery.” Brand managerscaught up in the annual brand-planning cycle may experi-ence that same sensation as they attempt to identify freshopportunities within the market each year. However, to helpa product achieve its full potential over its lifecycle—alsoknown as “maximizing the molecule”—marketers mustpause each year, take a close look at market conditions, andrevise their strategy accordingly.

How do various patient segments respond to the prod-uct’s current positioning? Do treatment practices exist thatsuggest the need for further clinical investment? Has theproduct won new business, only to lose it through productswitching or poor patient persistence? Marketing profes-sionals must probe for the answers to such questions toidentify where they must fine tune their approaches for on-going market success.

Anonymized patient-level data can support brand teamsin this annual planning process by defining the needs of

various patient segments and identifying patterns in prod-uct use. Both types of analyses can uncover unrealized op-portunity in the market.

One source of this information, health plan claims data,can define the needs of patient segments. Tracked overtime, these data provide an evidence-based view of thetreatment context for millions of de-identified patients. It in-cludes details on patients’ pharmaceutical therapies, di-agnoses, testing, medical procedures, and hospitalizations,which lead to a complete picture of patients’ health careexperiences. Another patient-level data source, longitudi-nal prescription data, tracks dispensed prescriptions for mil-lions of de-identified patients over time and ties that infor-mation to prescriber-level details. This provides insight intothe use of drugs in real-world settings. Real-world obser-vations regarding the use and nonuse of therapeutics canhelp focus strategic thinking and enable more deliberatemarketing decisions over the life of a particular pharma-ceutical molecule.

Patient Segmentation CanSpot Pockets of Opportunity In the past, marketers conducted pri-mary research to segment patient pop-ulations according to their clinical char-acteristics. Today, companies can relyon actual behavioral data to profile thetypes and groups of patients who re-ceive specific treatments for a given dis-ease or condition.

This process often unearths oppor-tunities that may not otherwise havecome to light. For instance, a companymight learn that a meaningful subseg-ment of the patient population with a par-ticular comorbidity profile is more apt tobe prescribed a competing product. Thecompany could then assess the value ofconducting further clinical work to prove

Creating Brand Plans That“Maximize the Molecule”

By Jim Carroll and Matthew Guagenty

Anonymized patient-level data supports the annual brand-planning process by profilingpatient segments and outlining real-world treatment pathways. When brand teams knowwhat type of patients use a brand under what clinical conditions, they can create plans tomaximize a particular molecule.

Figure 1. Type 2 diabetes profile summaries: Patient targeting characteristics and messages. ACE = Angiotensin-converting enzyme.

Segment D—Well Managed WithoutComplications

Targeting Characteristics:• Older (48% between 55–64 yr; > 50% male)• Treated with combination therapies—oral

agents alone or oral agent plus insulin • Highest utilization of indicated Rx’s• Less sick• Use few services• Diagnosed with retinopathy• Treated by an endocrinologist or specialist

Potential Targeting Messages• Maintain control—moderate progression• Benefit from oral sensitizing and basal insulin • Improve adherence to cardioprotective therapies (statins and ACE inhibitors)

29%

Segment C26%

Segment B36%

Segment A 5%

the product’s degree of effi-cacy within this particularsubpopulation.

For example, a segmen-tation analysis of patientswho have been diagnosedwith type 2 diabetes showsfour patient types having distinctly different clinicalprofiles (Figure 1). One seg-ment, comprised of older pa-tients with well-managedconditions, received fre-quent combination-therapytreatment and tended to usecardioprotective therapies.This information suggestedto the brand team that, to in-crease utilization within thiscohort, they must:

• Reach this segment withDTC advertising that emphasizes the value ofmedication in maintaining control over diabetes

• View patients in this group as ideal candidates for therapies that combine new agents with older ones

• Consider opportunities for bundling or copromoting itsproducts with a statin or angiotensin-converting enzymeinhibitor

Patient-Flow Modeling Can Identify KeyPoints in the Treatment Pathway Patient-flow models, a tool used for pinpointing where pa-tients enter the health care system, also provide data abouthow their treatment progresses. When used to quantify thenumber of patients in each part of the pathway and revealpatterns in clinical practices, such models clarify wheremarketers must invest brand-building resources.

For example, if an unusually large number of patients re-ceive a diagnosis but remain untreated for a given condi-tion, a company may want to increase DTC education tostress the importance of therapy in managing the disease.If diagnostic hurdles hamper the administration of treatment,a company might support diagnostic innovations.

Patient-flow models can also highlight such issues ashow often physicians deviate from established treatmentguidelines, how often they switch patients off of a givenproduct, what they substitute as an alternative therapy, andat what point patient persistence drops off during the treat-ment progression. In each instance, such insight would

suggest how marketers might improve treatment rates.The conceptual patient-flow model in Figure 2 combines

anonymized patient-level data derived from health planclaims databases with that drawn from longitudinal pre-scription databases. Were this model populated with ac-tual patient counts for a chronic condition, it might reveala brand generally used as second-line therapy—an un-welcome finding if the FDA approved the product as a first-line treatment. Knowing this, the brand team could inves-tigate the cause and build corrective actions into themarketing plan to create a better match between the prod-uct’s indication and its actual use. Furthermore, the mod-el would provide significant insight into the type, timing, andlocale of dynamic treatment decisions made, giving theteam the ability to create tactical plans to address areasof concern.

ConclusionWhen brand managers pause and get off the hypotheticalmerry-go-round during the annual business planningprocess, they are often rewarded with a fresh set of op-portunities for their brands. Investing the time to better un-derstand the clinical profiles of patients and their stages inthe treatment pathway brings previously hidden opportu-nities into focus. Innovative marketing tactics directed atthese targets help fuel brand growth and maximize mole-cules’ lifecycles. �

Industry Intelligence

AUTHOR—Continued from page xx

PRODUCT MANAGEMENT TODAY • www.PMToday.com 15

Mr. Carroll is Director of Performance Management for IMS Health, and Mr. Guagenty is a Practice Leader within IMS Management Consulting. For more information about the anonymized patient-level offerings of IMS Health, please call (610) 834-5000 or E-mail jcarroll@us.imshealth.com or mguagenty@us.imshealth.com.

TotalDiagnosed Population

UntreatedWith Rx

Treatment Administration

Reasons forTreatmentDecision

Monotherapy

Combination Therapy

Treated With Rx

Prior RxTreatment

RxInitiation

TreatmentChange

Titration

Stop Therapy

Switch Therapy

Add Therapy

Health plan claims dataLongitudinal Rx data/Health plan claims dataPrimary research

Dynamic Market—“Patients in Play”

Figure 2. Patient-flow model: Treatment cohorts.

©2007 IMS Health Incorporated or its affiliates. All Rights Reserved.

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