When is data better than money? When you’re a healthcare company trying to disrupt the system, and the data comes from about 19 billion health insurance claims.

The five finalists in the BlueCross BlueShield Data Innovation Challenge will have two months to dig in to information about doctor visits, hospital stays, and prescriptions from more than 27 million BlueCross BlueShield members. The entire Blue Health Intelligence data warehouse includes more than 10 years of history and represents every three-digit ZIP code in the United States.

The BlueCross BlueShield Association (BCBSA) and Blue Health Intelligence (BHI) announced the finalists this week. The companies will have access to a subset of the BCBS data for two months. The idea is to use real-world data as a reality check against solutions the companies are developing. The winner will have access to a subset of the data for six months as well as mentoring from BCBSA.

The finalists are working on healthcare problems ranging from diabetes to cancer to drug addiction.

Meet the finalists


Livongo helps people living with health issues that need daily management like diabetes and high blood pressure. Livongo sells its products to big companies with the goal of reducing healthcare costs among employees.

The company launched with a management program for people with diabetes, which provided a connected glucose monitor, unlimited test strips, personalized health suggestions, digital tools, and coaching. Livongo went public earlier this year.
Livongo plans to leverage the BHI dataset to identify, predict, and prioritize health plan members who don’t take prescriptions as directed. The company describes its analysis approach as: AI+AI: Aggregate, Interpret, Apply, and Iterate (Figure A).

Figure A: Livongo’s Applied Health Signals Engine uses data analysis to improve healthcare for people with chronic health conditions.
Source: Livongo


This company provides a healthcare navigator to help people get the right care at the right time, whether that means a conversation with a nurse, a trip to the ER, or a doctor visit. Pager’s goals are to reduce ER visits, improve call center efficiency, and increase the use of single point solutions. Pager plans to use BHI’s dataset in combination with their own data sources to simplify the process of receiving appropriate healthcare quickly (Figure B).

Figure B: Pager’s navigators help individuals find the right healthcare at the right time.
Source: Pager

Thrive Earlier Detection

This startup is developing CancerSEEK, a blood test designed to detect cancer at earlier stages of the disease. If the test comes back positive, Thrive will offer guidance for additional clinical care, as appropriate. One of Thrive’s priorities is to make the test affordable for all patients and to ensure it is covered by health insurance. Thrive plans to leverage the BHI dataset to quantify the economic impact of earlier cancer detection.

Wildflower Health

Wildflower’s founder started the company after her own high-risk pregnancy. She found “silos within silos” of information and had difficulty navigating the available resources. Wildflower has an app and other digital services to help families navigate healthcare resources for pregnant women, infants, and young children. Wildflower Health plans to use BHI’s dataset in combination with their own data sources to improve their existing risk-stratification model to allow appropriate and timely intervention for pregnant people (Figure C).

Figure C: Wildflower Health helps pregnant women find the right care.
Source: Wildflower Health

Workit Health

Workit Health provides online opioid addiction treatment for individuals and a digital wellness program for employers. The company will study the BHI dataset to find ways to measure the success of addiction treatments. The team also wants to figure out how to provide real-time interventions for people with substance use disorders.

These new solutions must address one of these use cases:

  • Identify, predict, and prioritize members and providers for real-time interventions
  • Use data to address barriers to care
  • Manage the dynamic individual process of care

At the end of two months, each finalist will pitch to BCBSA and BHI leadership. The health insurer wants to use machine learning and algorithms to predict the future of a person’s health. To do that, they need to integrate different data sources– everything from genomic data to financial data to EHR information; find new ways to incorporate real-time data into the analysis; and get better at pattern recognition.

The BHI data warehouse includes claims data from 195 million members including more than 984.6 million facility claims, 13.6 billion professional claims, and 4.6 billion Rx claims.

SEE: Digital transformation road map (free PDF)

Blue Health Intelligence manages a healthcare database of integrated medical and pharmacy claims. All data used for BHI analytics undergoes four levels of certification, including an independent third-party actuarial review, to ensure the strongest foundation of statistically reliable data. Member and pricing data are de-identified to protect patient and partner privacy.