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The Linear Health Journal

Healthcare AI insights for operational leaders

Practical guides to referral automation, prior authorization AI, care gap closure, AI voice agents, and patient scheduling. Written for the teams who run specialty practices, FQHCs, and PE-backed medical groups.

Key Takeaways

The Linear Health Journal publishes 171 practical guides on AI automation for healthcare operations: referral management, prior authorization workflows and CMS-0057-F compliance, care gap closure and HEDIS quality measures, AI voice agents for patient calls, patient scheduling and no-show reduction, and medical fax automation. Built for operational leaders at specialty practices, FQHCs and community health centers, and PE-backed multi-site medical groups.

Latest articles

Referral vs Prior Authorization: Two Requirements to Check Separately

Give front-office teams a clear way to distinguish a referral from a payer authorization without assuming either guarantees coverage.

Referral Management Best Practices: A Weekly Quality Review

Review an operating referral process with a practical checklist. Look for missing owners, stalled handoffs and records that need attention, then assign a clear follow-up.

All articles

171 entries

Referral vs Prior Authorization: Two Requirements to Check Separately

Give front-office teams a clear way to distinguish a referral from a payer authorization without assuming either guarantees coverage.

Referral Management Best Practices: A Weekly Quality Review

Review an operating referral process with a practical checklist. Look for missing owners, stalled handoffs and records that need attention, then assign a clear follow-up.

Patient Portal Adoption: Help Patients Complete One Useful Task

Turn portal enrollment into a useful patient journey by finding the failed step, offering appropriate help and measuring completed administrative tasks.

Referral Management System Migration: Keep Open Referrals Accounted For

A practical cutover workbook for moving active referral records, pending tasks and supporting history into a replacement system.

How to Reduce a Referral Backlog Without Losing New Work

A bounded recovery plan that separates record cleanup from completed work and keeps new referrals from becoming the next backlog.

Referral Coordinator Staffing: Build a Workload and Capacity Model

A weekly workload worksheet that separates task demand, available staff time and skill constraints before deciding how much coverage to add.

Why Referrals Get Lost Between Primary Care and Specialists

Referrals get lost across manual handoffs: intake, patient contact, authorization follow-up, specialist matching, scheduling and returned consultation notes. Trace each stage separately to see where the process stops and what your team still needs to confirm.

Low Adoption of Referral Automation: A Practical Recovery Plan

Find out why staff bypass an available referral workflow, then test a correction against actual task completion and remaining work.

Appointment Waitlist Management: Fill Open Slots With Clear Offers

An operating guide for cancellation offers, booking conflicts and released appointments, with a worksheet that separates slot fills from added bookings.

Patient Callback Queues: Track the Promise Through Resolution

Keep each administrative callback request accountable from the patient's original request through an accepted owner, an attempt and a documented outcome.

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Explore our complete guides: What is Referral Management? · Referral Software Buyer's Guide · Operational AI in Healthcare

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