For Providers & ACOs
Limited Private Beta

Stop leaving revenue on the table

The average primary care practice undercodes by 10–15%. Medicare beneficiaries see seven providers a year, but your EHR only knows what happens in your four walls. Sguardo pulls every record together, normalizes it to a research-grade standard, and gives you the analytics to recover missed HCC codes, close care gaps, and negotiate payer contracts from a position of data.

Runs on your infrastructure (on-prem or cloud). HIPAA audit trails built in. Your data never leaves your control.

Sguardo is currently in limited private beta. Request an invite and we'll get you set up personally.

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Sguardo Care Gaps dashboard showing open quality gaps
Privacy & Safety First
Purpose-built local AI. No third-party data sharing. No PHI leaves your servers.
Sguardo uses small, purpose-built language models that run locally on your infrastructure , not third-party LLMs. You control the de-identification level and have full transparency into exactly what data is transferred. Every algorithm is auditable.
Vocabulary lookups use a local DuckDB parquet file (no external API calls with your patient data
HCC scoring, care gap logic, and reference ranges are embedded math. Language understanding uses local models, not third-party AI
The ETL pipeline, OMOP mappings, and quality measure logic are fully inspectable by your team
Clinical knowledge search powered by Predicato: answers from a local knowledge graph, not an external LLM
10–15%
avg. undercoding rate
in primary care
7
providers the avg. Medicare
beneficiary sees per year
CMS Partner
registered Data at the
Point of Care vendor
500+
reference ranges for
lab interpretation

Why practices stay stuck

You can't improve what you can't measure , and right now, most practices can't measure much at all.

Your EHR sees one room

Claims data arrives weeks late. External records come by fax. A typical Medicare beneficiary sees seven providers a year , and you're making clinical and financial decisions with a fraction of the picture. Sguardo aggregates what every other system misses.

Quality reporting is a scramble

When your data lives in silos with inconsistent coding (SNOMED in one system, ICD-10 in another, free text in a third), computing accurate HEDIS scores or identifying care gaps requires heroic manual effort every reporting season. Sguardo runs those computations continuously, not annually.

Missed codes cost real money

Undercoding costs the average primary care practice 10–15% of potential revenue. HCC codes get missed because they require complete clinical context (which no single system has). Contracted rates drift below market without anyone noticing. Without data, you negotiate blind.

For fee-for-service practices

You don't need to be in a VBC contract to benefit from Sguardo. Most practices leave money on the table in FFS. We help you find it.

Understand your practice economics

Sguardo breaks down your revenue by procedure, payer, and provider, showing you exactly where your FFS income comes from. See which services are profitable, which payers reimburse below market, and where coding improvements would increase revenue without changing how you practice.

Identify underpaid services

Compare your contracted rates against the Medicare Physician Fee Schedule and regional commercial benchmarks. Sguardo flags specific CPT codes where your reimbursement is below the 25th percentile , and generates the supporting data you need to request a rate increase at your next payer contract renewal.

Optimize coding accuracy

Undercoding costs real money. Sguardo analyzes your claims history to identify patterns of consistent downcoding: procedures billed at lower complexity than clinical documentation supports , and gives your coders specific, actionable feedback.

Benchmark against peers

Compare your reimbursement rates against regional and national benchmarks using CMS fee schedules and publicly available transparency data. Know where you stand , and where renegotiation will have the highest revenue impact.

Your pathway from FFS to value-based care

The transition doesn't have to be all-or-nothing. Sguardo helps you move at your pace, starting with low-risk steps that improve your FFS practice and building toward full VBC readiness.

1

Optimize FFS

Start by understanding your current economics. Fix undercoding, identify underpaid services, and negotiate better rates. This generates immediate revenue (no contract changes needed.

2

Enroll in CMS DPC

DPC gives you Medicare claims data for your attributed patients, the foundation for population health analytics. Sound Prediction helps with enrollment and handles the technical integration.

3

Build quality metrics

With DPC data flowing, Sguardo computes your HEDIS scores, identifies care gaps, and tracks HCC coding accuracy. You'll have 6-12 months of quality data before signing any VBC contract.

4

Enter VBC with confidence

Model contract terms against your actual panel data. Know your projected savings before you sign. Sguardo continues to track performance, flag risks, and generate the reports you need for payer negotiations and renewals.

For value-based care practices

With clean, normalized data in place, Sguardo delivers the analytics that drive VBC performance.

Care Gap Identification

Sguardo identifies patients who are due or overdue for evidence-based interventions across HEDIS measures: HbA1c testing and control, blood pressure control, statin therapy for cardiovascular disease, and cancer screenings. Each gap surfaces as an actionable item with patient context and clinical rationale.

HCC Risk Adjustment Coding

Sguardo identifies Hierarchical Condition Category codes from your clinical and claims data, surfacing coding opportunities that reflect true patient acuity. Accurate HCC coding directly impacts risk-adjusted capitation payments and ensures your patient population's severity is properly represented.

Population Health Dashboard

View your patient panel stratified by risk level, chronic conditions, and care gaps. See where to focus resources: which patients need outreach, which cohorts are trending poorly, and where your quality scores stand.

Total Cost of Care (TCOC)

Track your attributed population's total cost of care with IBNR adjustments for claims lag. Identify high-cost patients and rising-risk cohorts, project shared savings before reconciliation, and get early warning alerts when you're trending above target spend.

Quality Measures

Sguardo computes eCQMs and HEDIS measures directly from OMOP CDM data. Numerator/denominator logic runs on normalized, deduplicated records rather than whatever your EHR happens to capture. More accurate measurement, fewer surprises at reporting time.

Reference Range Evaluation

Every lab result is automatically evaluated against 500+ reference ranges, stratified by age, sex, fasting status, pregnancy, and specimen type. Your team sees which values are borderline and which are critical, in context for each patient's clinical profile.

Population Health dashboard with risk stratification

Population Health — Risk stratification, utilization metrics, and action items at a glance

Data infrastructure

Every feature in Sguardo depends on the same thing: clean, normalized, complete data. Here's how we produce it.

SMART on FHIR EHR Integration

Sguardo supports EHR-initiated SMART on FHIR launch: clinicians open Sguardo directly from Epic, Cerner, or any SMART-compliant EHR without a separate login. FHIR R4 resources (Patient, Observation, Condition, MedicationRequest, Procedure) sync into OMOP CDM in the background.

CMS DPC & Blue Button

Sguardo manages the entire DPC lifecycle: organization registration, practitioner attribution, patient roster sync, and automatic conversion of claims into OMOP CDM records. Blue Button 2.0 roster management tracks authorization status across your Medicare panel with proactive re-consent alerts. Sound Prediction helps practices onboard into the CMS DPC program.

OMOP CDM Standardization

Every data source (EHR exports, claims feeds, legacy databases, FHIR bundles) is normalized to the OMOP Common Data Model. Full Athena vocabulary integration: SNOMED CT, RxNorm, LOINC, ICD-10, HCPCS, and CPT. CDM versions 4.0 through 6.0, including Oncology extensions.

Schema Discovery

Sguardo's schema discovery engine (inspired by OHDSI's WhiteRabbit methodology) connects to any source (PostgreSQL, MySQL, SQL Server, Oracle, CSV, Parquet) and inventories every table and column, profiles value distributions, and measures completeness. The scan runs without extracting PHI, safe for production databases.

Visual ETL Mapping

Drag source tables to OMOP CDM targets in a visual editor. Sguardo auto-generates field mappings with confidence scores using deterministic concept matching and stem table architecture. The output is executable DuckDB SQL, reproducible and auditable.

DuckDB Analytics Engine

Vocabulary queries and analytics run on DuckDB (no separate import step, no heavyweight database. 2.4 million OMOP concepts queryable in milliseconds. Vocabulary-aware SQL generation resolves source codes to standard concepts automatically.

ETL Mappings interface

ETL Mappings — Epic FHIR, Cerner, Athena and more mapped to OMOP CDM

Financial decision support

Whether you're in fee-for-service, transitioning, or already in a VBC contract, Sguardo gives you the data to optimize revenue and negotiate from strength.

Payer Negotiation Reports

Generate data-backed negotiation packages ready to present to payers. Sguardo compiles your quality metrics, cost savings, patient outcomes, and benchmark comparisons into structured reports, giving you leverage whether you're negotiating FFS rates, shared savings terms, or capitation arrangements.

Reimbursement Benchmarking

Compare your reimbursement rates against regional and national benchmarks using CMS fee schedules and publicly available transparency data. Surface where you're being underpaid and identify the specific CPT codes and payers where renegotiation will have the highest revenue impact.

VBC Contract Modeling

Model the financial impact of value-based care contracts before you sign them. Project revenue under different shared savings arrangements, capitation rates, and quality bonus structures using your actual patient panel data and historical utilization patterns.

VBC Readiness scorecard

VBC Readiness — Quality, cost, risk coding, access, and data completeness scores

Why not just use your EHR's built-in tools?

Typical EHR Analytics

  • Siloed to data entered within that single EHR
  • Missing claims history and external encounters
  • Limited vocabulary mapping across coding systems
  • Vendor-proprietary data formats
  • Analytics modules at additional licensing cost
  • No financial modeling or payer negotiation tools
  • Cloud-only . Your data on someone else's servers

Sguardo

  • Aggregates data from all connected sources into OMOP CDM
  • Full CMS claims + clinical data picture per patient
  • Automated terminology normalization (ICD, SNOMED, RxNorm, LOINC)
  • Open standards from the ground up: FHIR R4, US Core, USCDI
  • Quality measures, HCC coding, care gaps, and population health included
  • FFS rate analysis, VBC contract modeling, reimbursement benchmarking
  • On-prem or private cloud: data stays under your control with HIPAA audit trails

Security and compliance, built in

On-Prem or Cloud

Sguardo deploys within your own infrastructure — on-prem behind your firewall or in your own cloud tenant. No data leaves your environment.

HIPAA Audit Trails

Every PHI access is logged with structured metadata. Request bodies are deliberately excluded to prevent PHI from appearing in logs.

Zero-Trust Auth

OAuth2 with PKCE, HTTP-only SameSite=Strict cookies, CSRF protection, and role-based access control. SMART on FHIR launch context for EHR integration.

Encrypted at Rest

Credentials encrypted in storage. OAuth tokens with automatic expiration. TLS enforced for all connections.

Visual ETL mapping (no code required

Drag source tables to OMOP CDM targets. Sguardo auto-generates field mappings with confidence scores, then produces executable DuckDB SQL.

sguardo.local:5005/mapping

Source Tables

patients
1,000 rows · 12 fields
encounters
5,400 rows · 18 fields
lab_results
32,100 rows · 9 fields
medications
8,700 rows · 14 fields
diagnoses
15,300 rows · 7 fields

Active Mappings

patients person
12 field mappings · ✓ validated
encounters visit_occurrence
15 field mappings · ✓ validated
lab_results measurement
9 field mappings · 2 warnings
diagnoses condition_occurrence
7 field mappings · ✓ validated

OMOP CDM 5.4

person
visit_occurrence
condition_occurrence
drug_exposure
measurement
observation
procedure_occurrence

Sguardo ETL Mapping Interface — Rabbit-in-a-Hat style visual mapping from source schema to OMOP CDM

Ready to see the full picture?

Sguardo is in limited private beta. Request an invite and we'll walk through it with your actual workflows — care gaps, HCC coding, financial benchmarks, or OMOP ETL setup. Bring your hardest data problems.

Request Limited Private Beta Invite

Or email us directly at info@mederrata.com — we respond within one business day.