Decisions in healthcare deserve better than a stitched-together spreadsheet

Healthcare data lives in fragments. Clinical events sit in the EHR. Financial activity sits in claims, remittance, and authorization feeds. Operational signal — scheduling, staffing, throughput — lives in another set of systems entirely. The questions that matter to a CFO, a CMO, or a service-line leader almost always cross those boundaries, and the answers usually arrive too late, with too many caveats, to drive action.

Canopy Analytic builds the analytics layer that sits between those systems and the people making decisions. We model clinical, operational, and financial data into a shared, governed structure, and we deliver it through reporting and applications that reflect how the work actually happens — not how a textbook says it should.

Operational analytics for clinical workflows

Throughput, length of stay, and capacity utilization look simple in a slide deck and are anything but in practice. Definitions drift between departments. Edge cases pile up. Reports that started as a single number end up surrounded by footnotes nobody reads.

We take the time to nail down the metric definitions with the clinical and operational owners, encode them once, and version them. The result is a small number of trusted measures that hold up across service lines and survive turnover.

Payer-provider data integration

Reimbursement and care delivery are managed by different teams looking at different feeds. We bring authorization, eligibility, claims, and remittance data into the same analytics environment as clinical activity, so denial trends, payer mix, and net-revenue movement can be traced back to the encounters that generated them. Finance stops arguing with operations about whose number is right.

Patient cohort analytics

Most analytics requests in healthcare resolve to “show me this for these patients.” Without a cohort layer, every request is a one-off SQL exercise. We build cohort definitions as first-class, versioned assets — quality program denominators, outcomes-research populations, risk segments — so subsequent requests reuse the work instead of redoing it.

Regulatory and claims reporting

Regulatory submissions and payer reporting reward consistency and reproducibility. We deliver pipelines whose outputs are explainable end to end: where each row came from, which transformations applied, when the data was last refreshed. When auditors or reviewers ask, the trail is already there.

Where we work

We deliver primarily through Power BI, Microsoft Fabric, and Azure, and we plug into whichever EHR, claims platform, or warehouse you already operate. Engagements typically combine strategy work to align stakeholders, execution to build the pipelines and reporting, and training so internal teams can extend the work after we step back.