Autoantibody Ordering Patterns Across a Tertiary Hospital: A Retrospective Audit.

Background: Autoantibody testing supports the diagnosis of systemic autoimmune diseases, but indiscriminate use in low pre-test probability settings can reduce test positivity and inflate direct laboratory costs. Hospital-wide audits of real-world ordering practices across specialties remain scarce and, to our knowledge, have not been reported in the Gulf region. Objectives: To describe the test positivity rate, direct laboratory cost, and departmental variation of hospital-wide autoantibody testing in a tertiary center in the Eastern Province of Saudi Arabia. Methods: We conducted a retrospective hospital-wide audit of all autoantibody tests ordered across 15 clinical departments at King Fahd University Hospital between 1 January and 30 April 2024. Test volumes, positivity rates, and direct laboratory costs were summarized at departmental and subspecialty levels. Rheumatology was compared with all non-rheumatology services as a pre-specified inferential contrast using chi-square or Fisher exact tests with 95% Wilson confidence intervals and Benjamini-Hochberg adjustment across per-marker comparisons; the unit of analysis was the test order. Results: A total of 5973 autoantibody tests were performed in 1059 patients, with an overall test positivity rate of 16.3% (95% CI 15.4-17.2). Total direct laboratory expenditure was USD 509,136, of which 87% was attributable to negative results. Test positivity ranged from 26% in Pediatrics to ≤7% in Neurology and Neurosurgery. Rheumatology had a higher positivity rate (24.4%, 95% CI 22.2-26.8) than non-rheumatology services combined (13.9%, 95% CI 12.9-14.9; p<0.001), with the largest absolute differences for antinuclear antibodies (88.7% vs 35.7%; p<0.001) and SSA antibodies (27.9% vs 5.9%; p<0.001). Direct cost per positive result was USD 364 in Rheumatology versus USD 606 in non-rheumatology services. Conclusions: In this single-center audit, autoantibody ordering practices clustered into two descriptive patterns: hypothesis-driven, higher-positivity testing within specialist care and broader, lower-positivity panel use in several non-specialist services. These differences were statistically significant and most plausibly reflect more disciplined application of pre-test probability by specialists, although referral filtering and case-mix differences contribute and cannot be fully separated from clinician-level reasoning in this dataset. These patterns suggest that targeted diagnostic stewardship-reflex-cascade algorithms, order-menu redesign, and indication-based gating-could concentrate autoantibody testing where pre-test probability is highest, improving positivity and reducing avoidable cost without restricting clinical access.