Hard-to-obtain insights are now available, including granular visibility into settings of care, service type, and units-of-service completeness

Proving a therapy’s value is a two-part equation. First, how does it impact quality of life and health outcomes; and second, how does it reduce healthcare resource utilization (HCRU) and costs? 

Answering these two questions is crucial to increasing market access and driving therapy adoption. Yet, a 2023 industry survey reveals that 50% or more of HEOR experts struggle to obtain reliable insights on HCRU and costs.

What’s Behind the Challenge
There are numerous reasons why insights on HCRU and cost by care setting are challenging to obtain: 

• Many datasets provide only a snapshot in time vs. comprehensive view of the patient journey. The latter tracks interactions across HCPs, HCOs, care settings, and payers and captures switches in patient insurance.
• There is a lack of visibility into each setting of care and services rendered for a given patient visit as well as completeness of utilization data across datasets. 
• Payer cost information is often redacted in claims data. 
• Because cost data is dispersed among different insurers, providers, and pharmacies, it can be complex and time-consuming to consolidate and aggregate.
• Lack of standardization for Mx and Rx claims across healthcare systems and payers creates additional challenges in harmonizing and integrating data. 
• Payer cost has a variety of components, including reimbursements, out-of-pocket costs, etc., making it challenging to extract and analyze specific cost components.
• Some datasets don’t include all payers or include all payers but not health plan type (e.g., PPO vs. high deductible; Medicare FFS vs. Medicare Advantage).

The Power of a Customized Data Schema
Komodo’s fit-for-purpose data schema, the Komodo Research Dataset, solves these challenges. It encompasses all the data sources commonly needed for these analyses and comprehensive HEOR studies. Notably, this data schema:

•  Enables HEOR teams to obtain granular insights not previously possible, such as:
  • Services rendered within each care setting, including utilization categories (inpatient events, outpatient events, etc.), units, and granular dispensing information (fill/refill # and days’ supply)
  • Utilization and cost by care setting
• Leverages an imputed cost model built on a sample size that is three to five times larger than any other industry source (4.4 billion healthcare claims), ensuring a level of accuracy and representativeness that can’t be found elsewhere

Example: An HCRU & Cost Analysis 
A poster presentation at ISPOR 2023 revealed what’s possible. Using the Komodo Research Dataset, researchers assessed the real-world economic burden pre- and post-progression to metastatic castration-resistant prostate cancer (mCRPC) following first-line therapy initiation. This more severe form of prostate cancer, which affects roughly 20% of prostate cancer patients nationwide, has been associated with significantly greater treatment costs and higher mortality rates. But zeroing in on the detailed composition of these costs and where those costs start to mount along the patient journey have historically been a challenge.

Researchers found that prior to first-line therapy initiation, prostate cancer–related total costs post-progression to mCRPC were two times higher than pre-progression and four times higher once first-line mCRPC therapy is initiated. 

Given the incremental costs associated with prostate cancer disease progression reported in this study, clinical interventions aiming to delay progression — and ultimately lower total costs — are warranted. 

Get Granular Insights Faster
Using a data schema that’s purpose-built for HEOR studies and HCRU/cost analyses enables researchers to generate richer, more accurate insights — faster. 

View our Publications Database to see the types of studies Komodo supports, and learn more about how we partner with HEOR teams.

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