The same data, keyed into system after system
Patient and encounter details are re-entered between the EHR, billing, scheduling, and registries — by staff who have better things to do.
Use case · Healthcare
One encounter. Five systems. One number you can trust.
A patient visit closes today. Scroll, and follow that encounter from the point of care, through the five systems that hold your operation today, to the quality committee's dashboard — and watch what changes when it's only captured once, with PHI protected throughout.
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Why healthcare
Healthcare doesn’t have a data shortage. It has a distance problem.
Every encounter, order, and claim is data. The gap is the distance between the point of care where numbers are born and the reports leadership and committees steer by.
Reporting runs a committee cycle behind
Quality measures and utilization are compiled by hand. Leaders steer by last month’s picture.
Revenue leaks surface as denials
Documentation and coding gaps are discovered weeks later as denied claims — then reworked by hand.
Know-how lives in a few heads
Protocols, referral workflows, and payer quirks belong to experienced staff — and leave with them.
The journey
Seven steps. One number.
The health of the organization lives in encounters, coding, and utilization — born at the point of care, steered by in committees, protected under HIPAA. The seven steps below walk one encounter along that route, each removing a place where the number breaks today. Follow the line.
Data FoundationBusiness IntelligenceAI & Automation
EHRBilling / revenue cycleSchedulingLab & pharmacyHR / workforce
Where the encounter is scattered today
One central platformMicrosoft Fabric
This is where the number's journey changes. Instead of being re-keyed into billing, scheduling, and registries separately, it lands once — here — and flows everywhere it's needed, with PHI governed by design. Five versions of the record become one.
Step 01 · Data Capture & Quality
01The number is born
A clinic visit closes. Today the coding and documentation happen in after-hours chart catch-up, and gaps surface weeks later as denied claims — whether the data can ever be trusted is decided right here, at the point of care.
Our approach
We help define what each encounter must capture — demographics, coding, consent, outcome measures — and build quality checks into the workflow, so the record is right at the source.
Who feels it
CliniciansDocumentation checks at the visit — less after-hours chart cleanup.
Coding & billingClaims go out clean the first time; denial rework drops.
Quality teamRegistry and measure data complete without chart-chasing.
The payoff — Denials and rework drop, and clinical data becomes trustworthy enough to steer by — not just to bill from.
Step 02 · System Integration
02It stops being re-keyed
That encounter used to be re-keyed between the EHR, billing, scheduling, and registries — by staff who have better things to do.
Our approach
We help map how patient and operational data should flow and implement the integrations — so one completed encounter feeds billing, capacity planning, and quality measures on its own.
Who feels it
Admin staffDuplicate entry between EHR, billing, and scheduling disappears.
OperationsUtilization, throughput, and staffing on one consistent picture.
ITGoverned integrations on one platform — not a web of point-to-point interfaces.
The payoff — Re-keying and reconciliation shrink, and “clinical says one thing, billing says another” stops being normal.
Step 03 · Business Intelligence Roadmap
03It reaches the report by itself
Quality measures and utilization are still compiled by hand for committees — so leaders steer by last month's picture, long after the schedule could have used it.
Our approach
We help automate the reports you already produce and stand up self-serve capacity and quality views — refreshed automatically, while the schedule can still change.
Who feels it
ExecutiveCost, quality, and capacity visible together, on demand.
Clinic managersSelf-serve utilization and no-show views, by site and provider.
Quality teamMeasure reporting drops from weeks of compiling to a refresh.
The payoff — Capacity and quality problems surface while the schedule can still change — answers in minutes instead of committee cycles.
Step 04 · Data as a Product
04Everyone agrees what it means
“Readmission rate” and “panel size” are calculated differently by every department — and comparing sites means arguing about definitions first.
Our approach
We help the organization settle on one definition per measure and publish each with an owner and a source — findable by anyone, from front desk to boardroom.
Who feels it
New hiresRamp on the numbers in days, not months.
AnalystsFewer “can you pull this for me” requests.
LeadershipSite-to-site comparisons on one agreed definition per measure.
The payoff — Self-service that’s actually self-serve — the measure library becomes the shared language across clinical and administrative teams.
Step 05 · AI & Automation Governance
05It stays safe around AI
Staff are already pasting clinical text into AI tools — protected health information demands guardrails before that spreads, and HIPAA leaves no room for “we didn’t know”.
Our approach
We help classify data by sensitivity and set up a governed, minimum-necessary AI environment — a documentation assistant works on access-controlled data that never leaves it, with every use logged.
Who feels it
ExecutiveAI adoption with a defensible HIPAA compliance story.
Privacy officerPHI ring-fenced from external tools, with an audit trail.
EveryoneA clear answer to “am I allowed to use AI for this?”
The payoff — AI gets adopted broadly and safely — on governed data, with an audit trail built for a privacy review.
Step 06 · Data Culture & Engagement
06Clinicians shape what’s built next
Clinicians and front-desk staff know exactly what’s broken about the data work they’re asked to do — but frustration becomes workarounds and burnout.
Our approach
We help put a visible request channel in place, from idea to shipped — respecting clinical time — so the people at the point of care keep shaping how the data is captured and used.
Who feels it
CliniciansTheir input visibly shapes the tools — so they keep giving it.
LeadershipFriction surfaces early, with context, instead of festering.
The orgAdoption compounds — each shipped request builds trust in the next.
The payoff — The organization keeps getting more data-driven after the engagement ends — improvement becomes routine, and visible.
Step 07 · Centralized Knowledge Base
07It becomes know-how
Care protocols, referral workflows, and payer quirks live in a few experienced heads — and walk out the door with each departure.
Our approach
We help stand up a central knowledge base with AI-assisted capture — so a veteran specialist’s payer rules inform the next denied claim, not a departure loss.
Who feels it
Clinical staffCurrent protocols and workflows at hand, not on a shared drive.
New staffOnboarding from a knowledge base, not from shadowing alone.
AI toolsThe context they need to be accurate about your organization.
The payoff — Onboarding and AI both get faster and more accurate — institutional know-how stops walking out the door.
The same number, everywherePoint of care to boardroom
Quality & ops dashboardsMeasure portalGoverned AIKnowledge base
The encounter documented this morning is the quality measure on the committee dashboard and the clean claim out the door. One capture, one truth — with PHI protected the whole way.
Benefits realized
What changes when the strategy lands.
The shifts below are what the seven focus areas add up to in a healthcare organization — front desk to boardroom, encounter to committee.
BeforeDocumentation gaps found as denied claims
AfterChecked at the point of care
BeforeCommittee packs compiled for weeks
AfterLive measures, refreshed automatically
BeforeClinical and billing numbers disagree
AfterOne encounter record feeding both
Before“Ask the analyst” for every report
AfterSelf-serve measure portal with definitions
BeforeAI experiments near PHI
AfterGoverned AI, HIPAA-aligned by design
BeforeProtocols and payer quirks in a few heads
AfterA searchable, living knowledge base
How we engage
Strategy and execution, delivered together.
We don't spend months writing a roadmap before anything changes. Each phase combines discovery, design, and implementation, so your teams begin using new capabilities while the roadmap continues to evolve.
Discovery & Assessment
We learn how your organization actually runs — from the intake form at the front desk to the measure on the committee agenda.
Interviews across clinical, administrative, and financial teams Inventory of EHR, billing, scheduling, lab, and HR systems Gap map: where patient and operational data break down Audit of existing reports and the manual effort behind them
Mostly conversations, scheduled around clinical time — no disruption to care. You end the phase with a map of every place the same data is re-keyed, and what that costs.
Analysis & Framework Design
We design the central platform and start building — capture, connections, and guardrails, as requirements firm up.
Central platform and customer/vehicle data model on Microsoft Fabric / Azure / Databricks Capture-at-care design: documentation checks built into the workflow Integrations ranked by ROI — encounter to billing first PHI sensitivity tiers and AI guardrails, HIPAA-aligned by design
The first automated reports replace manual ones mid-phase. A pilot clinic runs the new capture in live workflows, and clinician feedback shapes the design.
Roadmap & Validation
You leave with a phased roadmap and a substantially implemented platform — a plan and working capability, together.
Phased roadmap covering every data initiative Priority dashboards and system connections live Measure portal and knowledge base stood up Wish-list platform open to clinical and administrative staff
Committee reporting already runs off live dashboards. There’s one place to find every measure — and a prioritized plan for what comes next.
Phases can be resequenced to fit your priorities. Engagement model and investment are tailored per organization — book a meeting and we'll scope it to you.
Start here
Bring us your systems and your sites.
We'll show you how your data should flow, identify the biggest opportunities for improvement, and define a phased engagement that fits your business.
30 minutes No obligation Microsoft Fabric partners