Case study / Employer outcome

Behavioral Health Growth / AI RevOps

Ivory folds form an open space around a terracotta seed — *Reconnection*People & care

Commercial infrastructure for access, capacity, attribution, and patient-acquisition quality.

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Evidence register

What this case can support.

Evidence class: Employer outcome
Claim boundary: Only aggregate operating outcomes are shown. Provider-level, patient-level, payer-contract, and internal claims files remain private.
Source basis: Executive resume
Aggregate provider analytics
Corrected-data growth roadmap

Case architecture

Ecosystem thesis

I approached behavioral-health growth as a portfolio of local service markets. Payer participation, clinician availability, service line and patient preference determine which demand can become care. The management system had to expose those differences before acquisition spending could be allocated intelligently.

System path

01Capacity
02Lifecycle
03Scoring
04Attribution
05LTV

Executive decision brief

CEO question

Which growth investment expands completed care without overwhelming intake or the clinical schedule?

Operating answer

Revenue operations should connect demand, clinician capacity, reimbursement and patient progression so leadership can see which parts of the growth plan are deliverable.

Proof to inspect

Clinician supply expansion, coverage expansion, acquisition quality, qualified pipeline governance, and cohort discipline matter as a system because they show supply, demand, RevOps, and economics improving together.

Ecosystem context

The conditions that shaped the work.

In behavioral health, demand can look enormous while the operating system underneath is fragile. If clinician supply, appointment availability, insurance fit, patient urgency, acquisition channel quality, and follow-up cadence do not align, growth becomes expensive noise.

The work connected patient reach, service-line economics and clinician capacity in one management view. That made it possible to examine whether commercial activity was producing a usable path into care.

AI assistance has a specific role within that design: support prioritization, routing, attribution and forecasting while respecting coverage, capacity and human decision authority.

Stakeholder tensions

The people and pressures shaping the work.

Patients

Needed faster access to psychiatry, therapy, and addiction recovery services.

Acquisition quality matters because urgent demand is wasted if capacity and routing cannot absorb it.

Clinicians

Provided the supply side of access and service-line expansion.

Recruiting/onboarding volume has to match geography, payer fit, modality, and patient need.

Growth Team

Needed attribution, channel quality, and cohort economics.

Lead volume can hide CAC waste unless the lifecycle architecture is clean.

Operations

Had to convert demand into scheduled, completed, and retained care.

A funnel that does not respect operational capacity creates downstream failure.

Leadership

Needed a single view of supply, demand, CAC, LTV, and service-line performance.

Pipeline optics can mislead strategy when revenue quality is not visible.

Outcome record

The proof signals attached to the case.

operationsSupply expansion

Clinicians activated

1,200+ clinicians activated across behavioral-health growth efforts.

growthCapacity expansion

Coverage expansion

Expanded geographic coverage 25%.

growthAcquisition quality

CAC reduction

Reduced blended CAC 18% through reimbursable cohorts and high-intent referral channels.

growthQualified demand

Pipeline

$420K in qualified pipeline; pipeline is not realized revenue.

analyticsCohort discipline

LTV lift

Increased patient LTV 3.2x.

Interoperability map

How the layers connect.

Follow how the market signal informs the economics, how the workflow responds, and what evidence supports the next decision.

Access

Where does demand need care now?

Patient acquisition was interpreted through service-line urgency, geography, and capacity constraints.

Supply

Can clinician capacity absorb demand?

Clinician onboarding and coverage expansion were connected to service-line growth and patient activation.

RevOps

Can the system see what is happening?

HubSpot lifecycle taxonomy, attribution, referral-source tagging, and scoring made the funnel operationally visible.

Economics

Is growth getting better or just bigger?

CAC reduction, LTV lift, qualified pipeline, and cohort analysis reframed growth around revenue quality.

Operating record

The work, the sequence, and the strategic read.

Read the starting conditions, the work performed and the strategic interpretation separately. Together, they explain both the decision and the limits of the evidence.

Challenge

The platform needed capacity expansion, cleaner acquisition economics, and lifecycle visibility across same-day psychiatric urgent care, therapy, and addiction recovery.

Approach

Architected a Growth OS integrating HubSpot Enterprise, NexHealth, DrChrono, Power BI, and claims analytics across acquisition, referral attribution, intake, scheduling, care, capacity, and executive performance.

Founder takeaway

Revenue operations should connect demand, clinician capacity, reimbursement and patient progression so leadership can see which parts of the growth plan are deliverable.

Strategic read

The management lesson is to review acquisition, clinical capacity and reimbursement together. That cadence shows where growth can improve access, which service lines can support it and which constraint leadership must address next.

Proof interpretation

Operator moves

Built the CRM taxonomy around real operating stages instead of generic funnel labels.
Prioritized reimbursement-aligned behavioral health service lines.
Used AI-assisted scoring where it improved prioritization, not as a cosmetic feature.
Connected clinician activation, patient flow, CAC, and LTV into one cadence.
Designed 24-hour first-contact SLAs, intake assignment, real-time booking, no-show prevention, and capacity-aware load balancing.
Commercialized MicroTherapy, MindFit/group therapy, psychiatry and ADHD pathways, addiction recovery, TMS, and digital care.
Designed patient drop-off, 90-day capacity, ROI, clinical-outcome, and KPI intelligence modules with HIPAA / 42 CFR Part 2 controls, audit logging, and human decision governance.

Expansion path

01
Define lifecycle stages around actual care operations.
02
Map patient demand to clinician capacity and reimbursement fit.
03
Use scoring to prioritize the highest-quality and most launchable demand.
04
Make weekly decisions around CAC, LTV, channel quality, and service-line constraints.
05
Expand only where access quality and economics improve together.

What I would do again

Build lifecycle definitions before automation.
Tie scoring to revenue quality and capacity constraints.
Show founders cohort economics weekly, not just pipeline totals.

The decision principle

My operating principle is to allocate growth resources against serviceable demand. Acquisition efficiency matters only when the receiving service can sustain access and delivery; otherwise the next investment belongs in capacity or intake.

Evidence objects

Proof artifacts

Executive resume

Discuss a related mandate

Bring the decision into focus.

For healthcare leaders connecting market choices, payer economics, partnerships and delivery capacity to an accountable plan.

Contact Azis Download Resume