Precision Occupational Therapy Using Data-Driven Decision-Making: Creating Evidence for Practice

Abstract Translation of knowledge about the evidence for occupational therapy interventions is critical to support the profession’s evidence base. It has become increasingly important to guide occupational therapy practice in an evidence-based, outcomes-oriented way and to identify strategies that can foster dissemination and integration of evidence into practice. In this Eleanor Clarke Slagle Lecture, Roseann C. Schaaf introduces the concept of precision occupational therapy using data-driven decision-making (DDDM) as a process to enhance practice, create evidence for occupational therapy, and foster knowledge translation. Precision occupational therapy embodies a personalized approach that respects the individual and considers multiple streams of information simultaneously to design treatments that are individually tailored and measure meaningful, personalized outcomes. It considers the individual’s strengths and needs and customizes interventions to enhance wellness and quality of life; it thus can be a guide for practice and research and can create evidence through practice. Schaaf presents three case examples to exemplify the application of precision occupational therapy using DDDM.