Healthcare data and AI.
From strategy to working systems.
Signal Forward helps health systems, physician groups, MSOs, and other healthcare organizations, and their counsel, trust the numbers behind their decisions. We build Signal Forward Insights, our analytics product, and bring senior analytics and operations experience to financial, clinical, and data challenges.
AI you can audit. Models you can defend.
Signal Forward Insights
Our analytics product for health systems, physician groups, and MSOs. Each leader opens to the measures they own and what needs attention, every measure defined once and traced to source. When a measure raises a question, AI answers from the same definitions.
From the question to the work
All case studies →Physician Compensation Across Multiple Divisions
A configurable calculation system validated across six divisions and multiple accounting periods, with source reconciliation and a review interface.
Read the studyEvaluating Clinical AI Coding Performance
Recurring analysis of coding performance, error patterns, and financial value using audited cases and claims.
Read the studyAssessing Hospital Opportunity from Medicare Claims
Claims-based applications for assessing hospital opportunity, care-pathway economics, and prospective partnerships.
Read the studyWork grounded in healthcare
We connect analytical methods with financial, clinical, and operating needs. The work can begin with data strategy or a focused assessment and continue through implementation.
Revenue Cycle & Coding Analytics
Assess coding performance, investigate denial patterns, and estimate the financial implications of proposed changes.
Accounting & Close Automation
Build configurable compensation calculations, reconcile results, and improve finance reporting.
Operational Performance Improvement
Work with Marianna Heacock on labor planning, productivity, patient flow, and implementation.
Value-Based Care & Risk Economics
Model episode costs and care pathways to assess payment-model opportunity and prospective partners.
AI Evaluation & Enablement
Evaluate model performance, assess data readiness, and plan implementation with your review teams.
Healthcare Fraud, Abuse & Litigation Analytics
Examine billing and service patterns, reconstruct populations, and test explanations for healthcare investigations.
Open the calculation. Follow the evidence.
Your team can inspect the assumptions, follow the calculations, and review the checks behind a result. We call this a glass-box approach.
- Methods selected and evaluated for the question at hand.
- Documented assumptions, source mappings, and validation.
- Clear limitations and identified points for human review.
- Senior people do the work, with a credentialed core team and a vetted specialist network.
See how the work is reviewed.
Insights is our analytics product, implemented on your data by our team. Provenance is a review capability we include where it helps. The screens below are working demos using synthetic data.
View full-size image (new tab) Provenance
The audit surface
A review interface for automated workflows: inspect recorded stages, checks, and the source evidence behind a result.
View full-size image (new tab) Signal Forward Insights
Our analytics product
Each leader in a health system, physician group, or MSO opens to the measures they own and what needs attention, each defined once and traced to source. Ask and connected AI tools answer from the same definitions.
Signal Forward Groundwork
The data foundation
Connect source records, establish shared definitions, and prepare the tables behind reporting and AI. We assess your existing estate and build the data foundation in your cloud.
Data preparation, useful reporting, and a record of the work support each other. See how they compose →
Three ways in
Advisory Services
Data strategy, model and data assessment, fractional leadership, and implementation planning.
Delivery Services
Build analytical systems, validate them with the client team, and prepare for operation and handoff.
AI Governance & Readiness
Evaluation requirements, data-handling controls, policies, and workflows for responsible use.
New to AI and not sure where to start? Our fixed-scope AI Strategy Workshop assesses potential use cases, data readiness, and priorities for further work.
From the question to implementation
Frame
Understand the question, the available data, and the people involved.
Build
Develop the analysis, model, or system the work requires.
Validate
Test the method, reconcile the results, and document limitations.
Transfer
Document the work, train the team, and agree ongoing responsibilities.
We review results and limitations with your team throughout the work. Documentation, training, and the agreed handoff are part of delivery.
Trusted by
Selected consulting clients
About Daniel Heacock
Daniel leads Signal Forward’s analytics and data work, combining healthcare experience with financial modeling, model evaluation, and hands-on implementation.
Before Signal Forward, Daniel led analytics at Optum and worked in HCA Healthcare’s Clinical Services Group. Earlier economic-consulting work at LECG included antitrust and DOJ matters.
He works alongside Marianna Heacock, who leads operations and performance improvement, and specialists engaged for the needs of the work.
“Better data, better decisions, better outcomes. Everything else is just noise.”
What do you need to decide, improve, or build?
Tell us about the question and the available data. We will discuss a practical first scope.
Advisory, delivery, AI governance, or a fixed-scope AI Strategy Workshop, tailored to your stage and goals.