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October 31, 2017

Clinical Intelligence for Enhanced Patient Care

The prowess of big data analytics in translating complex healthcare data into actionable business intelligence can create a vital thread that reaches out to patients and makes an improvement in their lives. For IntrinsiQ Specialty Solutions, a specialty healthcare intelligence company, “It’s ensuring every patient has access to the most appropriate care in a timely and efficient manner,” says Susan Weidner, Sr. Vice President.
IntrinsiQ Specialty Solutions is an integrated patient care intelligence provider, partnering with pharmaceutical manufacturers and life sciences to help demonstrate drug utilization and potential implication to clinical and outcome research. With insights from their proprietary data sources, they also discovered that their customers involved in research were struggling to find participants for their studies. Early on, many of the solutions that IntrinsiQ Specialty Solutions had access to enabled practices in identifying and monitoring patients participating in a clinical trial. As a result, they have a very long history of data across patients who can be evaluated for various clinical outcomes after trial. These data can better inform practices and study sponsors about the long-term outcomes post research participation.


Essentially, IntrinsiQ Specialty Solutions is developing ways to leverage their existing solutions to help drive access to clinical research for patients that are seen by their customer base. And that customer base is impressive. Across their solutions, IntrinsiQ Specialty Solutions manages close to 16 million specialty patients annually. “We have developed over 500,000 business rules on standardizing and augmenting data, especially in the areas of lines of therapy, to allow for data aggregation,” says Weidner. The goals are both quantitative and qualitative, ensuring the data used into further analyses have no patient-level duplications and has met necessary completion levels for appropriate interpretation. By providing the analytics engine, they can offer researchers with a dataset that is of sufficient size and quality to yield better comparisons. A typical example in their ability to leverage the value of their datasets comes from a recent request from one of their existing customers. The customer was trying to sponsor a research study, but after many attempts, could not find the specific type of patients they needed for participation. With their aggregated data, they could quickly identify 12-15 provider sites that potentially had the right type of patients for the study.

According to Weidner, as the next step in their roadmap, they have established a new research network called AdvanceIQ Network. AdvanceIQ Network allows for data aggregation across multiple data sources informing their analytic solutions, which healthcare practices may utilize to identify appropriate patients for a specific sponsor’s study. The ability to identify potential participants across such breadth and depth of patient data results will reduce the time required to locate a potential participant, resulting in quicker patient access, faster to study completion and improved patient participation and outcomes.

Roadmap for AdvanceIQ Network includes a focus on new specialties and more integrated capabilities that leverage their ‘reach of clinical trials’. Whether it is clinical trial access and management, insights into drug markets or patient care intelligence— the future involves coming together to create an integrated approach for customers