BY AHAMMAD MAHAMMAD

Ahammad is the Managing Director of Artmac Soft, a company based in Prosper, Texas, that helps healthcare organizations assess workflows, measure administrative effort, and identify where AI and automation can improve efficiency. This issue of The Healthcare Brief is written for healthcare leaders across Dallas–Fort Worth and North Texas. Contact contactus@artmacsoft.com or 405-300-0409.

How to identify operational costs, establish a measurable baseline, and determine where automation and AI can reduce manual effort — without disrupting existing workflows.

The short version

• Start with a measurable healthcare workflow. Prior authorization is a strong use case
  because repetitive requirements, documentation, submissions, tracking, and follow-up create
  measurable administrative effort.
• Reduce manual effort without redesigning the process. The objective is not to replace
  existing workflows, but to reduce repetitive staff touchpoints, improve information flow, and support
  teams across the current process.
• Establish the baseline before selecting technology. Measure volume, staff touch time,
  delays, rework, and handoffs first. A documented baseline makes automation impact and ROI
  objectively evaluable.

01 · THE BURDEN

The Administrative Burden of Prior Authorization
• 40 authorization requests per physician, per week.
• 13 hours of physician and staff time each week.
• Approximately 20 minutes of average staff time per request.
• Approximately 1.6 workdays per physician, each week.

40% of physicians employ staff who work only on prior authorization.

32% say requests are often or always denied.

94% say prior authorization contributes to physician burnout.

Source: 2025 AMA Prior Authorization Physician Survey — 1,000 practicing physicians, fielded December 2025.

BEYOND OPERATIONS

How Prior Authorization Affects Patient Care

Physicians report that prior authorization can delay care, disrupt treatment, and contribute to serious patient outcomes.
• 95% say prior authorization can delay a patient’s care.
• 79% say it can lead patients to abandon treatment.
• 74% say denials have increased over the past five years.
• 26% report it led to a serious adverse event for a patient in their care.
The 26% figure moves this from an efficiency issue to a safety concern.

Source: 2025 AMA Prior Authorization Physician Survey.

02 · THE WORKFLOW · ILLUSTRATIVE CONCEPT

Same six stages. Less manual work at each one.

The workflow does not have to change. Automation supports information retrieval, validation, preparation, monitoring, and follow-up — people remain responsible for exceptions and decisions requiring judgment.

• Order. Today: staff open each case by hand. With AI: eligible EHR orders trigger the case.
• Gather. Today: staff collect records from many systems. With AI: information is retrieved automatically.
• Check. Today: staff find missing information case by case. With AI: gaps are flagged before submission.
• Prepare. Today: staff assemble and submit the request. With AI: documentation is prepared for submission.
• Monitor. Today: staff check payer channels for updates. With AI: status is monitored automatically.
• Resolve. Today: staff handle follow-ups and exceptions. With AI: follow-up is automated, while exceptions go to staff.

03· THE EVIDENCE · EXTERNAL SOURCES — NOT ARTMAC CLIENT RESULTS

AI and Prior Authorization: What the Evidence Shows So Far

Published healthcare examples show where AI and automation are reducing administrative work in prior authorization. Some results are already measured in real workflows, while others are still early expectations.

MEASURED IN PRODUCTION — Montage Health (−22% queue volume). Montage Health automated prior authorization status checks within its Epic workflow. At one hospital, the authorization work queue decreased by 22%, while the team added new services without adding staff.

Source: AKASA case study · one Epic work queue

MEASURED IN PRODUCTION — Calibrate (5–7 submissions → 1 per member). Calibrate reported that, for some members, staff had to make 5–7 separate prior authorization submissions. By checking coverage earlier, the team reduced this to one submission per member and cut hands-on administrative time by about 70%.

Source: Develop Health case study · pharmacy authorizations

EXPECTED IMPACT — Optum (45% fewer manual touches expected). Optum’s Digital Auth Complete uses AI and automation within the EHR to check authorization requirements, gather documentation, submit requests, and monitor status. Optum expects the solution to reduce manual touches by 45%. Earlier deployments of the technology have reported a 96% first-pass approval rate.

Source: Optum, February 2026. Digital Auth Complete is powered by Humata Health. The 45% figure is an expected reduction; the 96% first-pass rate reflects earlier deployments of the technology.

“The goal is fewer manual checks, fewer unnecessary submissions, and less staff time spent moving requests through the process.”

04 · THE METHOD · 10-WEEK WORKFLOW PILOT

How to Measure a Healthcare Workflow Before Automating It

Start with four practical measures: staff touches, submission time, rework, and time unresolved. Measure them before automation, then compare the same measures after the pilot.

• Staff touches. How many times does staff need to work on the same case?
• Submission time. How long does it take from the order to a submission-ready request?
• How often does missing information cause staff to repeat work?
• Time unresolved. How long does a request remain unresolved?

A baseline turns improvement into something measurable.

Measure the workflow before making changes. Then compare the same measures after the pilot to see what improved and whether the approach should scale.

• Weeks 1–2 — Baseline. Measure current staff touches, submission time, rework, and time unresolved. Do not automate yet.
• Weeks 3–5 — Connect. Connect the data sources, EHR workflow, and payer channels needed for the process.
• Weeks 6–9 — Test one workflow. Start with one service line, payer, or authorization type. Keep complex cases and exceptions with the appropriate staff.
• Week 10 — Measure. Measure the same four metrics and compare them with the baseline.
• Then — Scale or stop. Scale what shows measurable improvement. Adjust or stop what does not.

05 · READINESS · BEFORE IMPLEMENTATION

Three Things Healthcare Teams Need Before Implementing AI

Before using AI in a healthcare workflow, organizations need reliable connections, trustworthy data, and clear oversight. These foundations help AI work safely and reliably in day-to-day operations.

Connect. The workflow can securely access the clinical and operational information it needs. Confirm that required EHR data, documents, and payer information can move reliably through the workflow.

Validate. Data is complete, consistent, and reliable enough to support the workflow. Check for missing, incomplete, or inconsistent information before using AI in the workflow.

Protect & Govern. Define privacy, access controls, human oversight, and monitoring before AI is used in the workflow. Clear governance protects patient information, defines who is responsible, and ensures AI use can be monitored.

AI performance alone is not enough. Privacy, human oversight, and trust must be built into the workflow from the beginning.

Start with one workflow. Measure it before you automate it.

Assess the current process, measure the administrative effort involved, and identify where AI or automation can improve efficiency before making a larger investment.

Step one: One working session   ·   Step two: Two-week baseline   ·   Approach: Technology-neutral assessment

Artmac Soft LLC · Prosper, Texas

contactus@artmacsoft.com · 405-300-0409

Smarter technology. Stronger healthcare.