Decision intelligence in healthcare speeds up the administrative and operational decisions around care — prior-authorization triage, eligibility and claims routing, care-gap outreach, member service and capacity — by assembling context from claims, EHR and contact-center systems, recommending the next best action with evidence, and keeping clinical decisions with licensed clinicians under HIPAA-grade governance.
A clear principle: AI never diagnoses
Payer decisions
| Decision | Signal | Context it needs | Authority | Outcome measured |
|---|---|---|---|---|
| Prior-authorization triage | New request received | Policy criteria, member history, provider history, missing documentation | Augmented — clinical reviewer decides | |
| Claim routing / pend | Claim fails an edit or looks anomalous | Eligibility, benefits, coding rules, provider contract | Automated for clean claims; augmented for exceptions | |
| Eligibility & benefits answer | Member or provider inquiry | Coverage, accumulators, plan documents | Automated with citation; agent confirms | |
| Member outreach | Renewal, care gap or churn risk | Plan, preferences, history, channel consent | On-the-loop | |
| Contact-center next best action | Live call intent detected | Member 360, open claims, prior interactions | Augmented — agent decides |
Provider decisions
| Decision | Signal | Context it needs | Authority | Outcome measured |
|---|---|---|---|---|
| Care-gap outreach order | Rising risk markers, missed refill | Labs, pharmacy claims, visit history, care plan | Clinician decides; care manager executes | |
| Bed and discharge flow | Census peak, pending discharges | Orders, transport, post-acute availability | Augmented — house supervisor | |
| OR and clinic scheduling | Cancellations, overruns | Case durations, staff, equipment | On-the-loop — scheduler | |
| Denial prevention | Claim likely to deny | Payer rules, documentation, coding | Augmented — revenue-cycle specialist |
Systems and data
Payer
Core administration (e.g. Facets), claims, utilization management, EDI 270/271, 278, 837, member 360, contact center.
Provider
EHR, scheduling, ADT, revenue cycle, pharmacy and lab feeds.
Knowledge
Medical policy, benefit documents and contracts — retrieved and cited, never guessed.
Governance
HIPAA minimum-necessary access, audit logs, human review of adverse decisions.
Example: prior-authorization triage
- Request arrivesAn imaging request comes in with partial documentation.
- ContextPolicy criteria, the member’s history and the ordering provider’s approval history are assembled.
- Gap foundA required prior-therapy note is missing; the provider office is asked for it automatically.
- RouteComplete, criteria-met requests go to a fast clinical review queue; complex ones go to a specialist reviewer with evidence attached.
- MeasureTurnaround time, overturn rate and reviewer agreement are tracked.
What to measure
| KPI | Why |
|---|---|
| Prior-auth turnaround | Faster access to care |
| First-contact resolution | Members get answers once |
| Clean-claim rate | Less rework and abrasion |
| Denial rate | Revenue protected |
| Care gaps closed | Outcomes and quality measures |
| Human override rate | Where policy or models need work |
- Healthcare DI prioritizes, prepares and explains; clinicians decide.
- Start with administrative decisions: prior auth, claims, member service.
- Cite policy and benefit sources for every answer.