Successful demand management in diagnostic immunology testing

Area of Science:

• Clinical laboratory science
• Health informatics
• Primary care medicine

Background:

• Primary care clinicians often face challenges in appropriate immunology test ordering.
• Service evaluation identified over-requesting of specific immunology tests and under-requesting of others.
• Lack of clinician knowledge and confidence contributed to suboptimal test ordering practices.

Purpose of the Study:

• To assess the impact of evidence-based algorithms integrated into test ordering software on immunology test ordering in primary care.
• To improve the utilization of immunology tests by addressing both overuse and underuse.

Main Methods:

• A quality improvement program was implemented, embedding decision-support algorithms into existing ordering software.
• Algorithms were developed for antinuclear antibody, allergen-specific IgE, total IgE, and urine protein electrophoresis tests.
• The intervention was iteratively designed based on general practitioner feedback and made available regionally.

Main Results:

• Significant reductions in testing workload were observed for over-requested tests (36%-88%).
• Substantial increases in testing were noted for under-requested tests (28%-135%).
• These positive changes in test ordering were sustained over time with minimal clinician complaints or lab queries.

Conclusions:

• Integrating evidence-based algorithms into ordering software is an effective strategy for optimizing immunology test utilization in primary care.
• This approach leads to sustained improvements in reducing test overuse and addressing underuse.
• The developed algorithms are replicable by other healthcare institutions.