What changed
Why is LOS increasing?
Separate case mix shift from discharge bottlenecks, physician variation, campus-specific workflows, and post-acute friction before leaders overreact to the headline trend.
Operating intelligence for hospital leadership
Turn fragmented hospital data into executive-ready operating intelligence
SanaLytics unifies hospital data ingestion, maps it into a trusted operating model, isolates the drivers behind change, and supports executive decisions with AI-assisted investigation. Leadership teams can see where LOS, margin, case mix, documentation, and physician variation are moving, then decide what deserves attention next.
Unified ingestion
Bring operations, finance, documentation, case mix, and physician data into one trusted operating layer.
Driver isolation
Separate mix shift, throughput drag, documentation lift, and performance variation before leadership takes action.
Executive support
Move from analysis to operating reviews, decision support, and AI-assisted investigation without losing rigor.
Early pilot and design-partner conversations
Built for hospitals and health systems that want a credible operating intelligence layer, not generic BI plus generic AI.
workspace.sana-lytics.com/executive-review
Enterprise workspace
March executive review
Systemwide performance drivers
One operating layer for unified data ingestion, driver-level analysis, AI-assisted investigation, and executive reporting.
Example hospital dataset
Updated 08:30 PT
Unified model
Driver views
AI assist
Memo ready
Case mix shift
+0.18
Higher-acuity cardiovascular and surgical volumes are lifting the enterprise profile.
Length-of-stay
+0.6d
Discharge coordination and post-acute placement remain the primary throughput drag.
Documentation lift
$1.2M
Open CC/MCC follow-up and query backlog still represent recoverable value.
Margin at risk
-1.8 pts
Mix gains are being diluted by throughput friction and downgrade pressure.
Performance drivers
Mix, throughput, and capture trend together
MixThroughputCapture
Oct
Nov
Dec
Jan
Feb
Mar
Variation watchlist
Campus NorthLOS +0.8d
Case management handoff
Campus SouthCapture +2.4 pts
Improved query close rate
Dr. PatelCMI +0.11
Higher-acuity cardiology mix
Dr. LewisLOS +0.5d
Observation to admit delay
AI summary layer
Executive memo draft ready
AI-assisted synthesis from approved filters, metrics, and comparison views.
Case mix improved, but throughput drag is still eroding margin conversion.
LOS pressure is concentrated in two campuses and one orthopedic workflow.
Documentation completion remains a near-term financial lever worth pursuing.
Why SanaLytics
A more credible operating layer for hospital performance
SanaLytics is designed as the connective layer between raw hospital data, driver-level analytics, AI-assisted investigation, and executive action.
A unified operating layer for hospital data
Unify operational, financial, documentation, case mix, physician, and facility datasets in one executive-facing system instead of managing fragmented reporting tracks.
Driver-level performance intelligence
Separate movement caused by mix shift, throughput, documentation lift, physician variation, facility variation, or margin pressure before leadership acts on a headline KPI.
Executive-ready reporting and decision support
Move from dashboard review into operating memos, leadership reviews, and board-ready decision support without rebuilding the narrative by hand each month.
AI built to think like an operations consultant
Use AI to investigate, synthesize, and recommend better next questions in support of operators and analysts, not as a theatrical chatbot or autonomous clinical system.
How it works
Ingest, structure, analyze, investigate, support the decision
The workflow is simple by design: unify hospital data, normalize it into a trusted operating model, isolate what changed and why, then help leadership move into action with stronger reporting.
01
Ingest disparate hospital datasets
Pull source files and extracts across case mix, throughput, documentation, physician, facility, and financial reporting.
02
Normalize the operating model
Clean, map, and organize the data into a consistent structure leaders and analysts can use repeatedly.
03
Surface trends and performance drivers
Show where movement sits across LOS, DRGs, CMI, capture opportunity, physician variation, facility variation, and margin.
04
Investigate with AI-assisted workflows
Use an analyst-style copilot to summarize changes, suggest follow-up cuts, and frame the next questions worth asking.
05
Produce executive-ready reporting
Turn validated analysis into leadership dashboards, operating memos, and decision-ready review materials.
Platform capabilities
Purpose-built for hospital operations intelligence
The platform is designed to support the full path from unified source data and driver analytics to AI-assisted investigation and executive-ready output.
Unified data ingestion
Ingest disparate hospital datasets across encounters, throughput, documentation, service lines, finance, and reporting workflows.
Normalized operating model
Structure messy source data into a decision-ready model for LOS, GLOS, DRGs, CMI, capture opportunity, physician variation, facility variation, and margin review.
Driver-level performance analytics
Show what is changing, where it is changing, and which operational or financial drivers explain the movement.
Physician and facility performance visibility
Compare performance across physicians, facilities, and service lines with enough context to support real operating conversations responsibly.
AI-assisted investigation
Layer in AI-assisted analysis to trace likely drivers, summarize shifts, and help teams ask better follow-up questions.
Executive decision support
Move approved metrics and filter states into polished summaries, memo drafts, and leadership-ready operating narratives.
Auditability and trust
Keep source freshness, validation checks, and logic transparency close to the measures executives rely on.
Product story
Enter the operating review instead of scanning another thumbnail.
SanaLytics is built to move hospital teams from fragmented source data into a disciplined operating narrative: what changed, why it changed, where to investigate next, and how to turn that readout into executive-ready action.
Ingest data
Structure it
Analyze drivers
Investigate with AI
Generate executive output
workspace.sana-lytics.com/executive-review
Enterprise workspace
March executive review
Systemwide performance drivers
One operating layer for unified data ingestion, driver-level analysis, AI-assisted investigation, and executive reporting.
Example hospital dataset
Updated 08:30 PT
Unified model
Driver views
AI assist
Memo ready
Case mix shift
+0.18
Higher-acuity cardiovascular and surgical volumes are lifting the enterprise profile.
Length-of-stay
+0.6d
Discharge coordination and post-acute placement remain the primary throughput drag.
Documentation lift
$1.2M
Open CC/MCC follow-up and query backlog still represent recoverable value.
Margin at risk
-1.8 pts
Mix gains are being diluted by throughput friction and downgrade pressure.
Performance drivers
Mix, throughput, and capture trend together
MixThroughputCapture
Oct
Nov
Dec
Jan
Feb
Mar
Variation watchlist
Campus NorthLOS +0.8d
Case management handoff
Campus SouthCapture +2.4 pts
Improved query close rate
Dr. PatelCMI +0.11
Higher-acuity cardiology mix
Dr. LewisLOS +0.5d
Observation to admit delay
AI summary layer
Executive memo draft ready
AI-assisted synthesis from approved filters, metrics, and comparison views.
Case mix improved, but throughput drag is still eroding margin conversion.
LOS pressure is concentrated in two campuses and one orthopedic workflow.
Documentation completion remains a near-term financial lever worth pursuing.
Where value leaks
Where is margin leaking?
Trace financial pressure back to throughput drag, downgrade risk, documentation loss, and service-line mix movement inside the same operating review surface.
Variation watch
Which physicians are driving variation?
Surface the cohorts, facilities, and specialties shaping divergence without flattening the story into a simplistic leaderboard.
Signal quality
Is case mix shifting or documentation improving?
Differentiate genuine acuity movement from capture lift so leadership does not confuse documentation performance with operational improvement.
AI-assisted investigation
What should we investigate next?
Ask SanaLytics to move from what changed into the highest-value follow-up cuts, the most credible explanation path, and a memo-ready executive summary.
Ask SanaLytics: “What should we investigate next?”
Key drivers
Financial impact
Executive summary
AI copilot
AI-assisted investigation with the posture of an operations consultant
This is not a consumer chatbot and not a clinical AI product. The AI layer is meant to help hospital leaders and analysts investigate variance, synthesize drivers, and move faster toward better questions and clearer reporting.
Investigate root causes with discipline
The AI layer is designed to trace likely drivers behind performance movement and summarize what changed between periods without rushing past the evidence.
Recommend stronger next questions
Instead of jumping to confident answers, the copilot can suggest which cohorts, facilities, physicians, or workflows deserve follow-up next.
Draft executive-ready decision support
Validated analysis can roll forward into leadership-ready memo language, operating-review summaries, and decision support materials.
Leadership outcome
What the platform helps leaders do better
The goal is not more dashboard volume. It is sharper operating context, faster investigation, and stronger follow-through.
Understand what is changing
Track movement across LOS, GLOS, DRGs, CMI, documentation, facility performance, physician performance, and margin in one coherent operating view.
Explain why it is changing
Break results down into mix, throughput, capture, service line, physician, and facility drivers rather than stopping at summary KPIs.
Know where to investigate next
Prioritize the facilities, service lines, physicians, and workflows most likely driving risk or opportunity.
Communicate with confidence
Carry the analysis forward into executive memos, operating reviews, and aligned leadership follow-through.
Who it’s for
Made for the teams accountable for hospital performance
SanaLytics is aimed at the leadership, finance, operations, physician, and analytics teams that need a credible shared operating picture.
Health system executives
A sharper operating lens for CEOs, COOs, and leadership teams accountable for enterprise performance.
Finance and margin leaders
Clearer visibility into case mix, LOS pressure, documentation opportunity, and the operational drivers affecting financial performance.
Hospital operations leaders
A reliable system for throughput review, service line performance, and recurring operating meetings that need shared definitions.
Physician leadership
Comparative views that help frame discussions around physician variation, documentation, and service line opportunity without flattening context.
Performance improvement teams
A clearer way to trace where performance is leaking, which questions to ask next, and how to move from signal to action.
Analytics and data teams
A presentation layer and workflow surface that respects rigorous data modeling, traceability, and reusable analytic logic.
FAQ
Common questions from hospital and health system teams
The messaging is intentionally disciplined: unified data ingestion, driver-level intelligence, executive decision support, and AI that supports analysis without hype.
What kind of hospital data is SanaLytics built around?
SanaLytics is built for hospital operational and financial intelligence. That includes case mix and DRG reporting, LOS and GLOS review, physician and facility variation, documentation and capture opportunity, and executive reporting workflows.
Is SanaLytics trying to replace a data warehouse or enterprise BI stack?
No. The platform is designed as an operational intelligence and decision-support layer that can sit on top of existing hospital data infrastructure while making the output more usable for leadership teams.
How does the platform handle DRGs and case mix reporting?
The product is built to preserve clear analytic logic, keep DRG frameworks interpretable, and support case mix analysis without turning distinct systems into one opaque score.
What role does AI play in the product?
AI is positioned as an investigation and reporting assistant. It helps summarize movement, suggest follow-up questions, and accelerate memo creation, while final judgment stays with operators and analysts.
Who is the platform meant for first?
The immediate audience is hospital and health system leadership, finance and operations teams, physician leaders, and analytics groups that need better executive-facing operational intelligence.
What does an early engagement look like?
Most conversations start with a working demo around current reporting pain points, the datasets already available, and where an early pilot or design-partner engagement could create leverage first.
Next step
See how SanaLytics could support your hospital or health system
Book a demo to walk through the platform, discuss your current reporting stack, and explore whether an early pilot or design-partner engagement makes sense.