Data expertise for a transforming healthcare industry
We provide strategic data science and analytics services to help healthcare organizations improve outcomes and impact lives. Our industry-focused capabilities and deep domain knowledge will accelerate your mission-critical initiatives and keep you ahead of the analytics modernization curve.
We help you keep pace with healthcare technology innovations and industry trends
Healthcare data is complex and heavily influenced by the changing healthcare policy landscape and industry data standards. In the new value-based payment environment, timely data must be in the hands of in the hands of clinicians, case managers, and leadership to achieve quality goals and pursue clinical interventions. Innovations such as natural language processing and artificial intelligence have moved beyond the hypothetical and present opportunities to reduce administrative burden and costs while improving care.
Meanwhile, increased interoperability means that patient data is flowing, for the first time, across traditionally impenetrable data silos. Modern cloud and analytics standards underpin new capabilities to securely integrate disparate healthcare data streams. At Keywell, we’re excited to stay on the cutting edge and partner with you in your analytics and innovation journey.
Domain Expertise
We’re a small team of healthcare data professionals with decades of experience in healthcare technology. With previous roles at industry-leading organizations such as Optum, Mayo Clinic, and Johns Hopkins, we bring cross-industry perspectives and knowledge to our engagements.
We know and work with common healthcare data sources, healthcare-specific analytics vendors, and industry standards. We’re also well-versed in HIPAA compliance and are committed to protecting patient information.
Our Technology and Advising Solutions
Analytics projects often struggle to return real value from significant investments. We help ensure that your analytics strategy is sound and aligns with your organizational priorities. Our services include healthcare data strategy, medical price transparency (LEARN MORE ABOUT OUR PRICE TRANSPARENCY SOLUTIONS), value-based purchasing analytics, data pipeline development and normalization for claims and electronic health record (EHR) data.

Healthcare Data Normalization
Normalization for Analysis
Normalization of claims, EHR, and secondary healthcare datasets for analysis.

Value-Based Payment Analytics
VBP Models and Metrics
Models to identify and monitor shared savings opportunities as well as patient interventions.

Medical Price Transparency
Negotiated Payer-Provider Prices
Unique dataset and analysis capabilities for nationwide healthcare negotiated rates.

Healthcare Data Strategy
Planning for the Future
Strategic roadmap, build vs buy analysis, and change management to quickly achieve analytics goals.

AI and Advanced Analytics
Advanced Analytics
Explore and implement emerging AI technologies and generative models to transform healthcare
Deliverables for Project Success
We work with clients at various stages of analytics maturity. Some organizations have already developed well-conceived data warehouses and want to incorporate advanced analytics or new algorithms. Others are at earlier stages of data maturity and need help navigating the journey from current state to future vision. As an illustration, the tangible work that we do to help our clients often falls into strategy, dashboard, dataset, or algorithm deliverables.
- Gap analysis – summary of current state vs future vision and current vs future technical architecture
- Use case assessment – definitions of users and use cases and map to analytics capabilities
- Build vs buy assessments – analysis of strategic and cost impact of various options
- Policy and compliance review – review of federal and state reporting requirements
- Organizational resource assessment and planning – assessment of technical and business resources required for proposed solutions
- Timeline and implementation planning – recommendations for implementation sequencing and cadence
- KPIs and metrics – well-formed healthcare KPIs and metrics that provide actionable knowledge to users
- Dashboard user experience – dashboard designs that are intuitive and visually-appealing
- Reporting data architecture – optimized structures of underlying data sources appropriate to the analytics tool and user need
- BI tool recommendation – assessment of options and client-specific recommendation
- User access and security – recommendations for ensuring secure access to data and structuring reporting data marts to ensure protection of PHI
We help develop data pipelines and curated datasets to help organizations get more value of their key data assets. Our data integration work includes:
- Data acquisition – data acquisition and data profiling for net new data sources
- Data integration – development of data pipelines through stream or data warehousing for normalized and curated datasets; integration of vendor solutions, especially healthcare-specific tools, to accelerate commoditized data normalization of claims, EHR, administrative, and reference data
- Data maintenance – processes to maintain updated and relevant data (client data and healthcare-specific datasets and ontologies such as diagnosis code definitions often change over time)
- Data governance – supplemental data documentation and data visibility and compliance with organizational governance standards
We help develop and deploy data science capabilities such as predictive models and data labeling for healthcare applications. We address particular challenges in deploying healthcare models such as the need to develop clinically-comprehensible “explainable” models as well as known risk in reinforcement of bias from underlying data. How we can help:
- Model prototyping and feasibility assessment – assessment of whether an AI model can effectively solve a particular problem
- Risk stratification models – development (or deployment of vendor solutions that implement) risk stratification, prediction, revenue cycle, and NLP models
- Model maintenance – management of model performance shift and deployment
- Model integration into existing operations – integration of model outputs into existing workflows such as case management outreach

We Work With
Our focus is on the success of our clients. We solve for common strategic data challenges shared across health and human service organizations.
- Payers
- Health Systems
- Provider Organizations
- Digital Health and Technology Platforms
- Health IT Agencies
- Managed Care Organizations
- Social Care Platforms
- Medicaid Programs
- Human Services Agencies
- Data Aggregators (including RWE)
- Strategy Consulting Firms
Meet our Clients









Technologies we know well
We have experience implementing and working with common platforms and business intelligence systems that enable analytics capabilities, including healthcare-specific technologies that may accelerate client data needs.







What our Clients Say


Frequently Asked Questions
Our team has deep expertise in claims data (medical, facility, pharmacy), electronic health record data, and industry value sets such as NPPES provider data that are often used in conjunction with these datasets. We can help normalize with healthcare ontologies and build in groupers, metrics, and enrichments to prepare data for analysis.
Our experience also includes Social Determinants of Health (SDoH) data and social services resource ontologies for available providers and services in the healthcare and human services domain. In the course of our engagements we often work with these datasets and customer datasets such as digital health app data.
Yes, we bring data science and AI trends to our client engagements where it is practical and expected to provide meaningful value. AI will bring transformation to the healthcare industry and presents opportunities to reduce costs and improve care.
Our team has worked with the largest healthcare claims datasets and have experience working with big-data cluster computing technologies that often have a different workflow than analytics with smaller datasets.
Yes, we have experience working with data from multiple EHR vendors and are familiar with common normalization challenges and solutions. We can help you get more value out of EHR data analysis through normalization and enrichment (including labeling data using natural language processing).
We have experience working on both the payer and provider side of payment model implementation. Analytics are crucial to assessing VBP opportunity, implementing programs that reduce cost and improve quality for targeted patient populations, and accurately monitoring shared savings for payment.
All of our team members are trained in management of protected health information – it’s in our professional DNA. We typically sign a Business Associate Agreement but primarily work inside the virtual walls of our healthcare clients, keeping all data within client systems. If hosting is required, we will jointly ensure that an approved, HIPAA-compliant hosting solution is implemented.
News and Insights

Cost information is live on payer websites – but is it helpful?
Find out how insurers comply with the No Surprises Act by comparing online prices for a routine colonoscopy across three of the largest health insurance companies. Learn what we found in this price comparison research and get key insights.

5 Takeaways from Datapalooza 2023
Now that the transparency data is available, the Federal IDR Process should be revised to incorporate this data, creating a more equitable process and enabling the certified IDR entities to make more informed payment determinations.

How the Health Plan Price Transparency Data Can Improve the Federal IDR Process
Now that the transparency data is available, the Federal IDR Process should be revised to incorporate this data, creating a more equitable process and enabling the certified IDR entities to make more informed payment determinations.

An AI model to predict kidney damage, trained on data from veterans, works less well in women
Healthcare data plays a key role in improving patient outcomes by identifying patients most at risk, improving care coordination, monitoring

Health Plan Price Transparency: What’s in the Data?
The Centers for Medicare and Medicaid Services (CMS) is responsible for issuing new regulations requiring health plans (e.g., health insurance

4 Questions to Ask When Evaluating Business Intelligence Tools for Healthcare
Healthcare data plays a key role in improving patient outcomes by identifying patients most at risk, improving care coordination, monitoring