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
Subject matter expertise is critical for real-world implementation in health and human services. Our team has decades of experience in data and technology specific to health and human services industries. 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 Strategy
Planning for the Future
Modernize your data capabilities, and develop HIPAA-compliant AI solutions to increase revenue and improve outcomes.
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.
Artificial Intelligence in Healthcare
We are actively deploying HIPAA-compliant AI solutions for healthcare organizations to automate operations, enrich data, and conduct research. As part of our healthcare data strategic services, we also provide AI workshops to healthcare organizations to better understand limitations and opportunities with AI-based solutions and to develop customized strategies to deploy future AI solutions. Get in touch at info@keywell.ai to learn more.
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.
We help our clients develop fully-managed AI solutions. Deliverables include:
- Project strategy and success criteria
- Cost and feasibility analysis
- Model recommendations
- Secure document repository or API feeds for model inputs
- Vector and relational databases
- Custom algorithms and prompt engineering as needed
- Web interfaces with secure login for user chat and outputs
- APIs for AI integration
- Ongoing oversight and model maintenance
- 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 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
MIPS Quality Reporting: Challenges and Solutions in Value-Based Care
The Merit-based Incentive Payment System (MIPs) is a key component of Medicare’s push towards value-based care. It aims to reward
Using the Keywell Relevance Score to Drive Clarity in Price Transparency Data
Since the enforcement of price transparency laws in July 2022, health plans have been required to publish negotiated contract rates
From Information Overload to Insight: Keywell’s AI Research Solution for Human Services
At Keywell, we recently partnered with a human services agency to address a significant challenge in the public sector: managing
Keywell Responds to OMB Guidance on Artificial Intelligence
The Evolving Regulatory Environment In the rapidly evolving landscape of artificial intelligence (AI), regulatory frameworks are emerging as essential tools
White House AI Executive Order – Healthcare Implications
On October 30th, 2023, President Biden issued an Executive Order on safe, secure, and trustworthy artificial intelligence
Here’s Why Medicaid Programs Have a Lot to Gain from Emerging AI Technologies
Here are a few examples of areas for AI disruption in Medicaid.