HealthcareOperations

Revenue cycle gaps and capacity constraints compound when clinical and operational data stay siloed.

We build HIPAA-aligned data infrastructure connecting your EHR, scheduling, billing, and HR systems, so administrators and clinical leaders see throughput, utilization, and revenue risk together.

30%
faster revenue cycle

Improve throughput and revenue cycle performance with live dashboards on bed utilization, AR days, denial rates, and staff scheduling efficiency.

The Challenge

The operational reality of healthcare

01

Revenue cycle bottlenecks invisible until cash slips

AR ages, denials accumulate, and collections slow before anyone in finance sees the pattern. By the time the report lands, the damage to cash flow is already done.

02

Bed and resource utilization tracked after the fact

Bed management decisions happen with yesterday's data or with a phone call to the charge nurse. Real-time visibility does not exist.

03

Staffing decisions run on outdated data

Scheduling decisions are made on yesterday's census. Overstaffing and understaffing cost money daily but the feedback loop is too slow to act on.

04

Denials and write-offs eat margin invisibly

Claims denials are tracked in aggregate but not by payer, category, or provider. The same denial reasons recur because root cause is never surfaced.

Key Metrics

The KPIs we surface for healthcare operators

Revenue cycle days
Denial rate
Bed utilization
Average length of stay
Patient throughput
Staff utilization and overtime
Clean claim rate
Cost per encounter
Readmission rate
No-show rate
Capabilities

How we help healthcare operations

01

HIPAA-aligned data warehouse and pipelines

Data infrastructure built to HIPAA standards from architecture through access controls. PHI handling, BAA coverage, and audit logging included.

02

Revenue cycle analytics with denial root cause

Track AR aging, denial rates by payer and category, and clean claim rates in real time. Surface root causes before patterns become habits.

03

Real-time bed and resource dashboards

Live bed availability, patient flow, and resource utilization across every unit and site. Charge nurses and operations directors see the same real-time picture.

04

Staffing optimization models

Census-based staffing models that adjust recommendations in real time based on patient volume, acuity, and shift patterns.

05

AI document intelligence for claims and auth

Automated extraction from prior authorization requests, claim forms, and clinical documentation. Reduce manual review time and submission errors.

06

Patient flow forecasting

Demand forecasting for patient volume by unit, day of week, and seasonal pattern. Help operations plan capacity before demand peaks arrive.

Integrations

Some of the systems we connect with

These are some of the platforms we connect. We integrate with almost any system. If you run it, we can likely work with it.

Epic
Cerner
Meditech
Athenahealth
NextGen
Allscripts
Kronos
UKG
ADP
Workday
Epic
Cerner
Meditech
Athenahealth
NextGen
Allscripts
Kronos
UKG
ADP
Workday
Use Cases

Where this applies

01

Multi-site clinic: revenue cycle transparency

A multi-site outpatient clinic group had denial rates of 12 to 18% at different sites but could not identify which payers, providers, or denial codes were responsible. Monthly reports were not granular enough to act on.

Outcome

We built a revenue cycle dashboard connected to the practice management system. Denial rates by payer and denial code became visible in real time. Targeted corrective action reduced denial rates to 7% within 90 days.

02

Health system: real-time bed and throughput visibility

A regional health system had no real-time view of bed availability, patient flow, or discharge readiness. Bed management decisions relied on floor-by-floor phone calls that took 20 minutes to complete.

Outcome

We connected the EHR to a Sigma dashboard. Bed availability, patient acuity, and discharge status are now visible across all units in real time. Average bed wait time decreased by 22%.

03

Hospital: staffing optimization by census

A hospital was experiencing both mandatory overtime and scheduled overstaffing within the same month. Scheduling was done 2 weeks in advance without real-time census data feeding the process.

Outcome

We built a census-based staffing model that adjusts scheduling recommendations daily based on projected patient volume. Overtime cost decreased by 18% in the first quarter.

Results

Outcomes you can expect

30%
Faster revenue cycle
18%
Reduction in denials
22%
Improvement in bed utilization
Real-time
Visibility across multi-site operations
FAQ

Frequently asked questions

Get Started

Revenue cycle and operations visibility in real time.

Book a free call and we will show you what healthcare analytics can deliver in 60 days.