Development of entrustable professional activities for advanced practice nurses education

Entrustable professional activity (EPA) framework has gained popularity within competency-based healthcare education programmes across disciplines, professions, and countries. As opposed to traditional time-based approach, EPAs bridge the gaps between competency framework and clinical practice, however, limited information on nursing EPAs highlights a need to develop EPAs specific to graduate nursing education to promote patient safety and quality patient care.

This paper described comprehensively the four-stage approach used to develop and pilot test a set of core EPAs for advanced practice nurse (APN) education.

The four-stage approach used to develop and pilot the EPAs included: 1) team formation, 2) development of conceptual framework, 3) identifying and reviewing core EPAs, and 4) pilot testing the EPAs. Post pilot test and surveys were conducted for the EPA developers, APN preceptors and interns to explore their perceptions and experiences using the EPAs.

A framework of nine core EPAs was developed for APN education, including: 1) perform an initial assessment and formulate management plans, 2) manage follow-up care for a clinical encounter, 3) plan, perform and evaluate care procedures, 4) recognise and manage patients requiring urgent care, 5) manage care transitions within and between health care organisations, 6) recognise and manage pharmacological needs of patients, 7) collaborate with patients, families, and community to improve health through disease prevention and health promotion, 8) participate in health quality improvement initiative, and 9) develop self and others for professional practice.

Despite the stakeholders having generally positive attitudes towards the use of EPAs, it has its drawbacks. More research is needed to examine the psychometric properties of the EPA assessment tools and evaluate the effectiveness of EPAs in graduate nursing education. Additionally, the described set of core APN EPAs needs more refinement and rigorous testing before it can be implemented on a larger scale.