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SFHSS APCD dashboard shows heavy specialty drug spend and rising autism visits
Summary
Staff presented the All Payer Claims Database dashboard for 2017, highlighting that a small set of specialty drugs drive high costs (many tied to HIV), diabetes is a top expensive chronic condition, and autism diagnoses and visits rose notably year over year; presenter flagged data‑quality issues in Kaiser Medicare RX counts.
Marina Coleridge, enterprise systems and analytics manager, presented SFHSS’s All Payer Claims Database (APCD) express dashboard that summarizes cost, utilization and quality metrics for calendar year 2017.
Coleridge said city plan members remain the system’s costliest population and that specialty drugs are a major driver of prescription costs: 14 of the top 15 drugs by spend are specialty medications, and eight of those are used to treat HIV, accounting for a substantial share of drug dollars. She reported 441 non‑Medicare members with an HIV diagnosis and 155 Medicare members with an HIV diagnosis in SFHSS’s population.
The dashboard also shows diabetes as the third most prevalent chronic condition but the costliest chronic condition in the active and early‑retiree population; the presenter reported roughly 3,827 diabetic patients in the non‑Medicare cohort and a little over 4,000 in Medicare. Coleridge flagged autism as the top mental‑health‑category increase year over year, with the non‑Medicare autism cohort increasing from 198 to 214 patients and total visits rising from 7,444 to 13,101 year over year.
Coleridge and commissioners discussed benchmarking and quality metrics such as readmission rates and preventive screening. Commissioners asked for normative comparators for readmission and screening rates and for HEDIS‑style measures where feasible; staff said they would explore normative data and incorporate it where budget and data allow. Coleridge also acknowledged a Kaiser Medicare RX data‑quality issue and said Truven is investigating and the dashboard will be updated once corrected.
The board requested follow‑up on data quality and additional benchmarks to contextualize readmission and screening rates; staff committed to return with explanations or corrected numbers.
