Outcomes Research
MTPPI's core mission is to help healthcare organizations use real-world data to improve patient outcomes. Our research is aimed at analyzing the effectiveness of medical interventions, whether they be medications, devices, procedures, or care delivery protocols. We also help organizations implement strategies to make their investigative trials more representative of racial and ethnic minority population groups. By identifying enrollment shortcomings in advance of trial initiation, sponsors can mitigate disparities and decrease the risk that their trial results are not generalizable to the US population.
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retrospective studies
Many clinical research questions have not been investigated by randomized assessments. Rigorously performed retrospective analyses can compare the effectiveness of two or more interventions or treatment protocols by statistically evaluating their risks and benefits. MTPPI helps healthcare stakeholders use retrospective studies to investigate interventions aimed at preventing disease, slowing disease progression, improved screening, treatment innovations, and management of comorbid conditions.
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real-world evidence platforms
MTPPI can help your organization build a real-world evidence (RWE) platform that can be used to improve outcomes for your patients. Pharmaceutical companies can use RWE to supplement investigative data gathered in RCTs. Payers can use RWE platforms to design and evaluate the effectiveness of value-based contracting arrangements while ensuring regulatory compliance with federal anti-kickback statutes. We are always looking to collaborate with providers on the creation of innovative registries. EHRs can provide valuable lab results, clinical notes and diagnosis information that help drive new clinical guidelines derived from RWE.
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unstructured data
MTPPI's proprietary NOWledge Graph engine can take your unstructured medical data and model connections between variables in order to build a meaningful semantic layer that sits on top of your data lake. NOWledge Graph is source agnostic and can relate internal and external data together, giving you a enriched model of your organization's data that is informed with the full metadata from all sources.