Addressing the Challenge of Sample Size in Rare Disease: Expanding the Use of Health Plan Claims in Patients with Only Medical Coverage, Lacking Corresponding Prescription Insurance Coverage

Author(s)

Wade R1, Gorritz M2, He J2
1IQVIA, Crozet, VA, USA, 2IQVIA, Plymouth Meeting, PA, USA

OBJECTIVES:

Health plan claims databases can contain substantial numbers of patients with only medical coverage, that is, without corresponding prescription drug coverage. This may occur when prescription coverage is not purchased, or such coverage is acquired from another source such as with Medicare Part D programs. Health outcomes research on these patients is severely limited without prescription utilization information. This study examines the ability to conduct research on such patients by linking their medical claims to an open-source prescription claims database.

METHODS:

A retrospective cohort study using the PharMetrics Plus database (P+) identified patients >=18 years old with >=2 medical claims >=30 days apart for gastrointestinal (GI-NET) or pancreatic neuroendocrine tumors (P-NET) between 1/1/2013-7/31/2020. Continuous medical enrollment for 12 months prior and 1 month after the first such claim in P+ was required. Patients with other primary tumor types were excluded, the remaining were linked to the IQVIA open-source claims database (LRxDx). The number of patients eligible for study with combined medical/pharmacy coverage in P+ and those with medical coverage only were evaluated

RESULTS:

Of 33,388 patients meeting the GI-NET/P-NET requirement, 26,079 had continuous medical and pharmacy eligibility, and 6,838 of those met all eligibility requirements (GI-NET n=2,177, P-NET n=4,661). When considering patients with medical coverage only, an additional 3,372 met all eligibility requirements, an increase of 49% in the potential study population (n=10,210). The linkage rate to LRxDx was 80% (n=8,177) for a population increase of 19.6% (GI-NET n=2,623, P-NET n=5,554). In the final population, 92% (n=7,492) of the patients had at least one pharmacy claim.

CONCLUSIONS:

This study demonstrates that studies using health plan data having patients with medical coverage only can be expanded by merging with open source claims, perhaps most useful in rare diseases where sample size is critical.

Conference/Value in Health Info

2022-05, ISPOR 2022, Washington, DC, USA

Value in Health, Volume 25, Issue 6, S1 (June 2022)

Code

RWD19

Topic

Methodological & Statistical Research, Real World Data & Information Systems, Study Approaches

Topic Subcategory

Health & Insurance Records Systems, Missing Data

Disease

No Additional Disease & Conditions/Specialized Treatment Areas

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