Blog
Leveraging Real World Data to Uncover True Cost of Cancer Care
Chi-Chang Chen, MsPharm PhD, Principal, Medical and Scientific Services, Real World Evidence Solutions, IQVIA
Feb 12, 2021

In 2020, spending on cancer care in the U.S. alone reached $157 billion, with much of that cost spent on new cancer drugs. The average annual cost of new cancer medicines continues to trend upward, with the cost per product ranging from $90,000 to over $300,000, according to IQVIA Institute’s 2019 Global Oncology Trends report. These innovative, life-saving drugs might have a limited market due to the rare nature of many cancers. The top 38 drugs accounted for 80 percent of total spending in 2019, and competition is fierce.

The number of oncology clinical trials initiated in 2018 increased 27 percent over the previous year, and the pipeline of oncology drugs in late-stage development expanded 19 percent. This late stage category included 711 companies, many of which are emerging biopharma companies, that now account for a larger proportion of the development pipeline than ever before.

Relieving cost analysis pressures

This is welcome news for healthcare providers and cancer patients who have growing access to treatments that can slow down disease progression, and improve their survival rates and quality of life. However, the intense competition and scrutiny from payers means pharmaceutical companies are under increased pressure to better quantify the real world outcomes and values for all decision makers – including payers, providers, and patients.

To do so, the various stakeholders require accurate and detailed real world data (RWD) about the cancer treatment journey, cost of care, and resulting outcomes, along with comparative data to prove their treatment delivers better results. This kind of analysis is best performed using advanced analytics and multiple large healthcare data sets that enable a broad exploration of the healthcare landscape, as well as tracking the patient journey across different, disparate settings. These RWD sets include health insurance claims, electronic medical records (EMRs), hospital records, laboratory results, and many others.

When drug developers can demonstrate a thorough and accurate analysis of the economic and clinical burden related to a specific cancer treatment journey, they can make a stronger case to for the value proposition of using new treatments.

Quantifying chemotherapy

IQVIA works with pharmaceutical companies from across the globe to help them clarify the health outcomes and cost benefits of new treatments by analyzing diverse healthcare RWD sets to provide a detailed picture of the true impact on patient care.

Pharma companies use these studies to estimate the true cost of treatment and current burden of disease, identify value drivers among patients and physicians, and to conduct comparative effectiveness analyses.

In one example, IQVIA recently worked with a global pharmaceutical company to conduct a retrospective analysis of the economic burden of specific hematologic cancer episodes of care in the U.S. Claims data alone does not provide detailed information about hospital resource use due to the way global payment systems function. This often results in an overestimation of hospitalization burden related to chemotherapy and resulting adverse events in oncology patients. By incorporating additional hospital-based data sources and analytic methods, a more accurate estimate of cost was obtained.

IQVIA’s real world evidence experts identified patients with the cancer of interest by using IQVIA’s Charge Data Master (CDM) database. This database features data from roughly 400 short-term, general non-federal hospitals (STGNF), and tracks patients from all pay types to provide a greater level of detail about what happens during hospital visits, from administration through discharge.

The CDM database identified thousands of patients with the hematologic malignancy of interest to predict the percentage of hospital charges directly related to chemotherapy, utilizing advanced predictive analytic methods.

Then the estimated chemotherapy attributable proportions were applied to chemotherapy hospitalizations observed in IQVIA’s PharMetrics® Plus database, which features RWD on commercially insured patients across the U.S. dating back to 2006. This database provides details about every healthcare event that occurred during that time, and because all the claims are adjudicated, the cost data is more precise, presenting a more accurate picture of health resource utilization. Linking both databases, IQVIA researchers were able to derive the adjusted costs associated with chemotherapy for each chemotherapy hospitalization.

The combination of the patient-level detail from the CDM data and the vastness of the PharMetrics Plus database, made it possible for IQVIA’s research team to carefully analyze in-patient items attributable to chemotherapy, and more accurately project the real hospitalization costs related to these hematologic malignancy episodes in the U.S.

The study determined that the adjusted cost per hospitalization was approximately 40% less than the cost that had been projected using claims data alone. An accurate description of healthcare costs is imperative to accurately evaluate the economic impact of therapy. The same approach may be used in future studies to model the impact of chemotherapy on hospital related costs.

Demonstrating value

A study like this offers the opportunity to obtain a more accurate estimate of burden of illness, and in turn, demonstrate the value proposition for a pharmaceutical company’s drug to their key stakeholders in an even more precise and credible manner.

Pharmaceutical companies often rely simply on claims data to estimate burden of illness, but these studies frequently over-estimate specific disease treatment costs. When companies can combine these projects with an analysis of line-item details from the hospital, they can confidently describe these numbers, and provide more accurate cost projections to payers and to providers.

Such insights will help the industry better manage the cost of cancer care and make data-based decisions about which treatments offer the best quality and cost outcomes for the patient community.

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