Healthcare analytics consulting, built around better care
This work is personal. I have lived experience with mental health and substance use challenges, as do people close to me. Insight Datalytics works with healthcare teams, researchers, and mission-driven organizations to provide the data-backed analyses and optimized workflows that let clinicians and researchers focus on what actually matters—the people they're trying to help.
Background
Insight Datalytics was founded to help teams save time and reduce errors by optimizing workflows and modernizing analytics, using automation and responsible AI to replace manual reporting and recurring tasks with clear, reliable, sustainable systems.
My approach is informed by Lean management principles, including formal training in Toyota’s Lean Foundations, with an emphasis on standard work, performance metrics, and continuous improvement.
The practice is informed by deep experience in data science, biostatistics, and applied AI within complex, regulated environments—particularly healthcare, behavioral health, and life sciences. This includes leading large-scale analytics and reporting efforts for federally funded programs, designing automated and audit-ready data pipelines, and supporting research and quality improvement initiatives where accuracy, transparency, and reproducibility are critical.
Alongside consulting work, I currently serve in a senior biostatistician and project management role within a large safety-net healthcare system, where I lead analytics for multi-million-dollar federal grants, develop executive-level reporting and dashboards, and ensure compliance with evolving regulatory requirements. My background also includes academic research and teaching in bioengineering and bioinformatics, with a strong foundation in statistical analysis, experimental design, and translating complex data into actionable insights.
Across projects, the emphasis is always the same: thoughtful analysis, well-designed workflows, and solutions that teams can understand, trust, and maintain over time.
How I approach data, analytics & automation
Good analytics consulting and data strategy should reduce friction, not create it.
The focus is on clarity, reproducibility, and solutions that teams can understand, maintain, and trust.
This approach is especially important in complex or regulated environments, where trust, consistency, and documentation matter.
Clarity over complexity
Metrics and dashboards should be easy to interpret and grounded in shared definitions.
Reproducibility over quick fixes
Workflows are designed to be consistent, auditable, and maintainable over time.
Practical solutions
Tools and techniques are chosen based on real-world constraints and long-term usefulness, not trends.
How I approach work
My work follows a clear but flexible four-step progression. The steps are sequential, but the process is responsive to what each engagement requires.
Discover is the foundation, and typically receives the most time and attention. This phase focuses on deeply understanding your goals, constraints, data, workflows, stakeholders, and operating context. The aim is not to jump to solutions, but to ensure the right questions are being asked and success is clearly defined from the outset.
Design translates what I've learned into a clear analytical and delivery plan. Depending on the work, this may include analytical approaches, automation strategies, workflow redesigns, or technical architecture, always tailored to your context, priorities, and regulatory environment.
Build develops solutions iteratively, with regular check-ins, shared progress, and early results. This often includes preliminary analyses, draft dashboards or reports, workflow diagrams, and feedback-driven refinement. When assumptions don't hold or early results miss the mark, the work adjusts until it does. This applies equally to analytical work, workflow design, automation, and applied AI solutions.
Handoff focuses on delivering durable, well-documented outputs with knowledge transfer as needed. Whether the deliverable is a custom data application, an automated workflow, a statistical analysis, or a regulatory report, the goal is the same: your team should understand what was built, how it works, and how to maintain or extend it over time.
Who I work with
Insight Datalytics works with small teams, departments, and organizations doing meaningful work, particularly those without dedicated data engineering or analytics capacity in place.
Common engagements include work with:
Healthcare and behavioral health teams navigating complex data, population-level reporting, and regulatory requirements.
Clinical and translational researchers including those working in psychedelics, life sciences, and behavioral health, who need rigorous analysis and reproducible workflows.
Non-profit organizations working in health, human services, or community-based care, where data capacity is often limited but the stakes are high.
Operations and reporting groups responsible for recurring metrics, dashboards, compliance reporting, and data strategy.
Organizations modernizing analytics workflows to reduce manual effort, improve consistency, and free staff to focus on higher-value work.
What you can expect
Clear communication and well-scoped work from the outset.
Respect for data sensitivity, privacy, and governance.
Thorough documentation and knowledge transfer.
Solutions designed to be owned and maintained by your team.
Let’s talk
If you’re exploring analytics, automation, or AI support, a short conversation can help clarify whether Insight Datalytics is a good fit.