Specialty drugs, complex patients and shifting payer rules are landing on pharmacy faster than ever. Each one needs more clinical judgment and more documentation, and pharmacists are expected to manage all of it.
At Mount Sinai Health System, prescription volume growth neared 20% a year, and hiring could no longer keep pace. “We knew that we couldn’t continue to throw people at the process, and we needed to become more efficient,” said Kenny Yu, senior vice president and chief pharmacy officer.
New York City’s largest integrated delivery system turned to an enterprise pharmacy intelligence platform. The AI reads patient charts and payer requirements, completes prior authorizations, drafts appeal letters with supporting clinical literature and routes coverage decisions. Pharmacists review and confirm results before anything is submitted.
What changed, as reported by Mount Sinai:
- Absorbed 15% to 20% year-over-year prescription growth without adding staff
- Cut prior authorization time from 25-30 minutes to under 5
- Won approvals on some of its most complex cases, including pediatric oncology and endocrinology patients
- Got medication into patients’ hands in 2 days instead of 4
- Achieved full enterprise pharmacy intelligence implementation in 1 day from decision
Inside the whitepaper:
- Why hiring to match prescription growth stopped making financial sense
- How a pharmacist-turned-CIO brought in the platform, and what adoption actually took
- How speed became capacity across prior authorizations, appeals and coverage checks
- The evidence that wins hard approvals, including a dermatology appeal built on a little-known study