Stakeholder demands can be daunting. HealthCore provides guidance and support throughout the research process. We construct and validate our automated data and we understand how to navigate the complexities of real-world studies to generate timely answers that are high-quality, reliable, and cost-effective. We know the intricacies of real-world data which we effectively leverage for uncovering insights into safety and effectiveness. Our multidisciplinary team brings a broad range of scientific expertise and operational experience to safety and risk management studies in the pre- and post-marketing setting.
We design and manage safety studies as the coordinating center for multi-database, multi-year studies and single database studies requiring more rapid completion. As an original partner in the FDA Sentinel Initiative, our commitment to realizing the potential of electronic real-world data allows us to fulfill industry needs and exceed regulatory requirements.
Our researchers validate clinical endpoints by linking administrative claims data to medical records, cancer registries, the National Death Index, and other data sources. We use machine learning methods to develop predictive models that target health conditions of interest with greater accuracy and improve the validity of epidemiologic research.
Machine learning combines advanced statistical methods with the results from validation studies to construct new case-identifying algorithms. We have found these methods to offer marked improvement in the accuracy with which we can identify patients of interest. These methods not only reduce bias from misclassification, which translates into more valid research, but we have also been able to identify patients with conditions for which there are no diagnosis codes in claims, such as cancer stage or biomarker status.
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