Enabling High-Value Provider Performance Through Tailored Healthcare Analytics
With roughly 30% of all health spend being of low-value, it’s a trillion-dollar problem and growing.
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Info
55 Court St. Second Floor
Boston, MA 02203
(617) 221-7190
info@healthcorum.com
Identifying Wasteful Spending
Benchmark and score providers relative to their peers using cost, quality, and efficiency metrics
HealthCorum has developed proprietary technology and methodologies to analyze various healthcare data, including
Create New Networks
Expedite the research process and be better prepared for contracting discussions
Optimize Existing Networks
Compare providers to one another in a fair and meaningful way in order to assess areas that need improvement
Expand Existing Networks
View data on all available providers, including proprietary scores that indicate the relative cost efficiency of each provider
Educate Providers
Share data-driven benchmarks to facilitate conversations with providers and improve performance
Gain Competitive Advantage
Opportunities to execute various cost-saving strategies
Quantify Low-Value Care
Instantly analyze claims data to identify low-value care with our AI-driven process
Detect And Analyze Referral Patterns
Surface provider referral patterns and work to eliminate inefficiencies
Surface Competitive Intelligence
Aggregate data on all providers in each selected network to deliver a greater understanding of network strengths and weaknesses
Markets we serve
Payers
Low-value care detection
Tracking and quantifying low-value care services has been difficult and labor intensive -until now. HealthCorum has developed a first-of-its kind AI technology called the HealthCorum Neural Network (HNN) which learns from existing clinical guidelines and formulates an unbiased logic to recognize instances of low-value care in health claims data. This proprietary breakthrough allows us to quickly analyze millions of lines of data with fewer resources and greater accuracy than existing methods.
Referral pattern identification and optimization
Referrals are an important part of tracking patient flow and communication between primary care and specialty providers, yet these relationships are not always apparent. Physicians decide to refer patients to other physicians for many reasons, ranging from the need for specialization to addressing problems of overcrowding. A physician’s decision to refer (or not refer) a patient is essential in determining cost and quality of care. We have developed an algorithm based on preferential attachment methodology that can analyze claims data and identify referral patterns.
Potential conflict of interest recognition
Network leakage analysis
For payors and health systems, it is crucial that patients stay in-network or visit preferred providers as often as possible. Patients may visit out-of-network providers for a host of reasons – many of which can be avoided with the right information. HealthCorum leverages referral identification technology to deliver insights into patient journeys and report on individual physician capture rates, primary care to specialist leakage, and overall network integrity.
Take complexity out of provider network optimization with a holistic view of provider efficiency and value-driven referral patterns.
We work collaboratively to accomplish your goals, achieve better outcomes and reduce the delivery of low-value care.
FAQ
What is HealthCorum's definition of a 'low-value' care (treatment)?
A. The treatment is medically unnecessary.
B. The benefits are short-term.
C. A lower-cost alternative is available.
Can HealthCorum use our internal data?
Absolutely! HealthCorum platform is equipped to analyze claims and create scores based on client data. There are some basic guidelines and minimal required fields that any dataset should contain. HealthCorum’s scores are designed to harness the richness and homogeneity of CMS data covering significant portions of the physician’s patient’s panel. However, we understand the value and fit-for-purpose use of our partners’ own data, which is reflective of the physician patterns through the lens of their own populations. While CMS-based scores establish a good foundation for understanding physician groups’ relative appropriateness for value-based arrangements, we recommend fine-tuning interventions/strategies based on scores derived from your own population.