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Sigma Computing

Turn healthcare data into coordinated action

Explore clinical, claims, and operational data in your warehouse. Build apps that help teams investigate issues and coordinate follow-up.

  • Investigate on governed data

    PHI stays in your warehouse, under the access policies already set there.

  • Coordinate the follow-up

    Assign reviews, work denials, and log outreach as records with an owner and a status.

  • AI that shows its work

    Summaries link to the rows behind them, and a person approves before anything is saved.

Readmissions review

Clinical quality · 30-day readmissions

Cardiology readmissions

Unplanned readmissions within 30 days of discharge

Service lineCardiology
PeriodQ3 2026
Compare toQ3 2025

Readmission rate, Q3 2026

15.6%

+3.3 ptsvs Q3 2025

Readmissions, Q3 2026

62

of 398 discharges

Readmissions, Q3 2025

50

of 405 discharges

Largest unit change

4 West

+8.9 ptsvs Q3 2025

By segment

30-day rate. Select a row to filter.

SegmentQ3 2025Q3 2026Change
All Cardiology12.3%15.6%+3.3 pts
4 Westunit11.6%20.5%+8.9 pts
CVICUunit12.8%15.5%+2.7 pts
5 Eastunit12.7%12.1%−0.6 pts
Medicarepayer13.4%17.8%+4.4 pts
Medicaidpayer15.4%18.8%+3.4 pts
Commercialpayer8.3%8.7%+0.4 pts

Cohort: Cardiology, Q3 2026

Assign review

398 encounters · 62 readmitted

EncounterDischargedUnitPayerReadmitted
E-31207Sep 30 Wed5 EastCommercialN
E-31198Sep 29 TueCVICUMedicareN
E-31188Sep 27 Sun4 WestMedicareYin 6 days
E-31174Sep 26 Sat4 WestMedicaidYin 11 days
E-31160Sep 25 Fri5 EastMedicareN
E-31142Sep 24 Thu4 WestMedicareN
E-31131Sep 23 WedCVICUCommercialYin 17 days

Review queue

Separate from clinical source records

TaskCohortOwnerDueReview noteStatus
RV-1041Orthopedics · 3 North · Q2 2026Marcus BellOct 30Compare PT start times by unitIn review
RV-1038Pulmonary · 6 West · Q2 2026Renee CallowayOct 9Inhaler teaching at dischargeClosed

Quality Analyst

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I summarize changes in readmissions from the data on this page. I flag associations; I don't establish causes.

Ask anything

AI can make mistakes. Please double-check responses.

Trusted by healthcare teams

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Issues to resolution

Finding the issue is the easy part

Teams can see the trend. The follow-up, who owns it, what was decided, and whether it closed, happens in email and spreadsheets.

TodayWith Sigma
PHI extracted to spreadsheets to work a listPHI stays in the warehouse under its access policies
Review assignments tracked in emailReviews saved to the warehouse with an owner and a due date
Provider mappings and reference data corrected in spreadsheetsCorrections saved to the warehouse with the editor’s name
Denial follow-up split across billing exports and notesDenials worked from one queue on live billing data
Providers and clients get static screens and slide decksEach provider and client drills into only their own data
No record of what was decided or by whomEvery decision recorded with who made it and when

From the trend to the follow-up

Analytics finds the issue, an app captures the team’s response, an agent assembles the context, and writeback records the decision and its owner.

Constraints owned

Investigate capacity constraints

Find where beds, staffing, and throughput fall short, unit by unit, on live data. Managers assign the response, like a staffing change, with an owner and due date in the warehouse.

  • Occupancy, boarding, and staffing gaps by unit
  • Staffing changes assigned with an owner and due date
  • Agents draft the huddle summary for approval

Denials resolved

Coordinate denial follow-up

Track denials and balances across facilities on live billing data. Revenue cycle teams assign claims, log notes, and record decisions, so follow-up doesn’t stall in a spreadsheet.

  • Denials by payer, reason, and facility
  • Assignments and notes saved to the warehouse
  • Provider and staff mappings kept in one place
Denials Queue

Ask what’s behind the CO-16 denials.

Denials Analyst

New chat

I summarize new denials and prepare follow-up. I never contact payers or change claims.

AI can make mistakes. Please double-check responses.

Synthetic data · work assignments only

Denials Queue

New denials

37

+8vs last week

At risk

$117.5K

3 payer reasons

Unassigned

22

CO-16

New denials this week

PayerReasonClaimsAt riskStatus
Ashcombe Health PlanCO-16 missing info22$61,400Open
Wexcombe CareCO-197 no auth9$38,200Assigned
Ashcombe Health PlanCO-50 not necessary6$17,900Assigned

Denial assignments

PayerClaimsOwnerDue
1Ashcombe Health Plan6Clinical reviewOct 30
2Wexcombe Care9Auth teamOct 29
+

At risk by reason

Ashcombe Health Plan$61,400Wexcombe Care$38,200Ashcombe Health Plan$17,900

Gaps closed

Manage outreach queues

Work HEDIS and Stars care gaps from a shared queue. Care teams record outreach outcomes against the member list, and managers see what’s closed.

  • Care gaps by measure and member
  • Outreach outcomes saved as records
  • Agents prepare the day’s queue for review

Cohorts explored

Support research cohort exploration

Researchers explore curated data in a spreadsheet interface and save cohort definitions and notes, without exporting CSVs or waiting on a data engineer.

  • Cohorts built by pivoting, not by ticket
  • Definitions and notes saved for the team
  • Access governed by warehouse roles

Clients self-serve

Deliver reporting inside your product

Health tech teams embed interactive, white-labeled reporting in their own applications, with each customer’s data isolated by Sigma Tenants.

  • White-labeled embedded apps
  • One tenant per customer
  • No separate data pipeline to run

Codes validated

Validate suspect conditions at scale

Health plans review HCC suspect conditions across millions of members, manage exceptions, and record each status, without exporting member records.

  • Suspect conditions by plan and member
  • Exception workflows with an owner
  • Status changes recorded with an audit trail

Agents with a reviewable role

Agents prepare the work so people can decide

Agents summarize the evidence, find exceptions, and prepare work for a person to approve. Records save to your warehouse, never to clinical source systems.

  1. 1Summarize the evidenceAn agent summarizes this week’s new denials and links each point to the claims behind it.
  2. 2Separate what’s knownIt marks what it observed apart from what still needs review, such as a payer’s portal change.
  3. 3Prepare for approvalIt drafts the follow-up assignments. A manager approves them, and nothing goes to the payer or the billing system.

Explore healthcare apps built in Sigma

Working examples from the App Library. Open one to see how it works.

Browse the App Library

Built for PHI

Meet strict compliance requirements without moving patient records out of your warehouse.

Visit the Trust Center
  • Writeback kept separate

    Review tasks and outreach outcomes save to their own tables, never to clinical source records.

  • Per-user OAuth

    Connect with OAuth so queries run with each person’s own warehouse role.

  • Row- and column-level security

    Reads and writes both inherit your table policies.

  • Audit trail

    Audit logs record user activity, AI conversations, and input table edits, so you can see who changed what.

  • Your data stays put

    Sigma queries your warehouse in place and never copies the data out.

  • Certified

    SOC 1, SOC 2, SOC 3, HIPAA, GDPR, CCPA, and ISO 27001.

Healthcare FAQs

  • How do we analyze patient data without compromising HIPAA compliance?

    Sigma queries PHI in place in your cloud data warehouse, under its access policies, so there are no extracts to secure.

  • How do we coordinate claim denial follow-up?

    Revenue cycle teams work denials from one queue on live billing data, drill to the claim line, and record assignments, notes, and decisions as they go.

  • How do we close HEDIS and Stars care gaps?

    Care teams work gaps from a shared queue and record outreach outcomes against the member list, so managers see what’s closed and what’s next.

Bring the trend your quality team is chasing

We’ll show the investigation, the summary, and the review assigned and tracked, on synthetic data first.