Digital Analytics Strategies for the Healthcare Payer Industry

Transform your healthcare payer business and innovate for the future.

Transform your healthcare payer business and innovate for the future.

Healthcare payer, health plan, and reimbursement organizations need to address the changing circumstances of the healthcare ecosystem, uncover new business models to enhance productivity, improve care quality and deliver new services.    With skyrocketing costs of healthcare (The U.S. spends more than $3 trillion, heading to 20% of GDP according to the WSJ) and the push to value-based care, healthcare payers to find innovative ways to optimize healthcare reimbursement.  Multiple changes are happening all at once. Payers are dealing with emerging payment and care models, M&A consolidation, care incentive realignments, unprecedented advances in new digital technologies just to name a few. Healthcare insurance carriers, third-party payers, or health plan sponsors that adapt to change will need to transform their business models and processes to meet the evolving requirements of healthcare industry.  

Dealing with challenges around member risks, outcomes and regulations

Payers need to strengthen existing and create new processes to better engage plan members, optimize quality and health risk adjustments, boost network and provider efficiency,  prevent waste, and fraudulent abuse and manage administrative costs. In order to be profitable, healthcare payer plans will have to bring together disparate data sources and truly partner or work together with providers to open the door for member-centered delivery models.  This also means investing technology platforms and solutions to align and drive with the accountable care pay for performance programs.  Some of the other challenges include risk stratification (high, low, and rising risk group identification) population health management, and the plan performance regulations surrounding Healthcare Effectiveness Data and Information Set HEDIS and Medicare STAR ratings.  National Committee for Quality Assurance NCQA recently released new Health Plan Accreditation standards.  Aculyst specializes in data-driven insights to help healthcare payers drive clinical value chain improvements.  Payers and commercial health plans have the opportunity to differentiate themselves through not just traditional transactional support, but analytic offerings supporting care systems that measures health outcome values across multiple conditions, providers, and interventions.          

Payers need to maximize reimbursements: value-based purchasing and pay-for-performance health plan programs.     
Our healthcare consulting focuses on data strategy, data governance, operational analysis, regulatory compliance, quality programs, technical infrastructure evaluation and project management. We leverage our strong health plan network expertise on core claims processing systems, provider data management systems and care / medical management systems.

Healthcare Payers need:

Data Integration and Interoperability  

  • Integrating structured and unstructured healthcare data
  • Payer-provider data integrations (claims, pharmacy, provider, EHR)
  • Custom interfaces, adapters and parsers
  • Expertise across (X12, CCFL, FHIR, QRDA, CCDA, HL7) terminologies (ICD, CPD, LOINC)  

Data Management (EDW & Big Data)  

  • Aggregate large healthcare data – EDW & big Data
  • Expertise in EDW and data modeling
  • Expertise in Hadoop, other big data streaming platforms
  • Solid frameworks for data quality and data governance
  • Healthcare data management platforms

Performance Management (BI/Analytics)

  • Drive value-based performance across the population
  • Hedis performance
  • Configurable apps for wellness management, gaps in-care, financial risk assessment

Data Science & machine Learning

  • Mine and leverage healthcare data for actionable insights
  • Machine learning & AI for advanced business use cases
  • Predict Population Health Risk by identifying future patterns of clinical and cost outcomes.
  • Proficiencies in using data science and machine learning tools such as R, Python, SAS, Tensorflow
  • data profiling, model development, reporting and integrating analytics results with enterprise systems    

Our Areas of Expertise

  • Big data
  • Data strategy
  • Modern data architecture
  • Advanced Analytics
  • Data science & ML
  • Data governance
  • Data Warehouse/ Data Lake Implementations
  • Enterprise data management
  • Cloud Migration & Cloud Re-engineering
  • Business intelligence
  • Data visualization

Technologies

Storage
(Hadoop, In Memory Data Grid, Relational)
Data Integration Tools
(Flume, Hive, Impalla, Informatica, Kafka, PigScoop, Spark, Talend)
Cloud
(AWS, MS Azure, Google Cloud, Private Cloud)
Analytical Tools
(Aster, Business Objects, Cognos, Excel, MicroStrategy,R, SAS, Spotfire, Tableau, Qlik View)
Types of Data
Structured/Relational/XML/JSON/CSV Unstructured/Text/Video/Sound/Graphics/Undefined

Aculyst’s deep healthcare and data science expertise allow our consultants to apply the most advanced analytics, technologies and process improvement methodologies to make our clients more successful in closing gaps in care and delivering high-quality healthcare at an appropriate cost.

Schedule a 30-minute healthcare discovery call.

In this complimentary call, we’ll explore your goals and challenges and discuss how Aculyst can help you extract value from data and improve patient outcomes.