This year’s ISPOR theme – “The future of HEOR in patient-driven digital healthcare systems” – echoes what we believe at Ontada: that the patient should be at the center of all that we do.
The COVID-19 pandemic has shifted how we operate in many facets of our lives, including healthcare. We’ve seen a rise in the delivery of healthcare via digital mediums, including patient-provider interactions via telehealth and within electronic health tools. This has given patients greater access to their data and created an ecosystem in which patients play a critical and active part.
This has also meant that real-world data and evidence are playing more important roles than ever, as we support the patient voice being heard in the research studies that are informing the future of cancer care. It’s a particularly rewarding time to be involved in real-world research and this was a sentiment I felt throughout the sessions I attended at this year’s ISPOR conference.
I’m proud to share that Ontada had a record seven presentations included at this year’s conference, covering topics that are core to what we do: the power of real-world data, innovations in precision oncology and improving health equity with social determinants of health (SDOH) insights. Below, you’ll find a summary of and link to each abstract.
I’m looking forward to continuing to work together with our partners – and with patients at the center of the fight against cancer – to advance cancer care.
ISPOR 2022 | Ontada abstracts
The power of real-world data
Feasibility of Using Oncology Specific Electronic Health Records (EHR) Data to Emulate Clinical Trial Inclusion and Exclusion Criteria
This study examines elements of recent oncology clinical trials to assess the degree to which real-world data (RWD) (both structured and unstructured) can be reasonably used to retrospectively replicate the inclusion and exclusion criteria needed in trials.
A Proposed Framework for Evaluating Continuity of Data Coverage in Electronic Health Record and Administrative Claims Data in Real-World Evidence (RWE) Studies
This poster provides a high-level framework to help analyze whether the candidate real-world data (RWD) source (an electronic health record or administrative claims data), has the requisite coverage and comprehensiveness over time to be utilized for regulatory-grade studies.
Integrating Data from Disparate Sources to Create a Comprehensive Patient Journey: A Case Study in Prostate Cancer
Understanding the patient journey helps to maximize the potential of novel therapies or services. This study aims to highlight the challenges of integrating different data sources and identify best practices to capture a more holistic view of the patient journey, focusing specifically on patients with prostate cancer.
Application of Medication History for Comorbidity Assessment in Cancer Patients
Cancer patients often have other comorbidities that affect care and outcomes. In the study, the team looked at the instruments that have been developed using real-world data to quantify comorbid conditions and their impact on costs and clinical outcomes.
Innovations in precision oncology
HER2 and Other Biomarker Testing Patterns Among Patients with Advanced Gastric Cancer (GC) or Gastric Esophageal Junction Cancer (GEJC)
Biomarker testing is recommended for advanced gastric cancer/gastric esophageal junction cancer (aGC/GEJC) patients to inform treatment decisions. This study aims to examine biomarker testing patterns among these patients by analyzing structured data with the iKnowMed electronic health record database of the US Oncology Network.
Frequency of and Testing Patterns for Microsatellite Instability High (MSI-H) and Deficient Mismatch Repair (dMMR) Among Solid Tumors in a US Community Oncology Setting
Microsatellite Instability High (MSI-H)/Deficient Mismatch Repair (DMMR) is an actionable biomarker in the treatment of several tumors. This study assesses the frequency of and testing patterns for MSI-H/dMMR across various solid tumors.
Improving health research through methodological insights
Lack of Standardization in Quantitative Evaluations of the Efficacy-Effectiveness Gap (EEG) for Cancer Therapies: A Targeted Literature Review (TLR)
The Efficacy-Effectiveness Gap (EEG) is a term for the difference between the outcomes observed within randomized controlled trials and those observed in real-word clinical practice. The objective of this study is to quantitatively evaluate the magnitude of this gap for different cancer therapeutics and to use this information to help inform future research.
Additional information about our presence at ISPOR can be found here.