An effective tool for improving patient care.
- Appreciative inquiry focuses on acknowledging strengths and values of individuals and organizations while understanding, accepting, and searching for positive meanings.
- It’s effective at building teamwork that’s geared toward perpetuating what works and improving performance.
Editor’s note: This is an early release web exclusive article, and will appear in the upcoming November 2020 issue of the American Nurse Journal.
In the clinical microsystem where high care quality is expected, changes are common, and expectations for continuous improvement are the norm, unit circumstances and individuals function interdependently, adding to environment complexity. Communication and collaboration are crucial for achieving the best outcomes, and leaders should investigate innovative strategies, such as appreciative inquiry (AI), to improve processes. AI is a transformational tool that focuses on what’s best in people and the environment while engaging in collaborative work and empowering participation for positive change. This article explains AI and explores how it can be used in healthcare teamwork and leadership.
AI—originally developed by David L. Cooperrider, PhD, in 1986, and first introduced in an article written with his mentor Suresh Srivastva, in 1987—is an organizational tool that can be used as a framework for improvement projects or system-wide change. It engages stakeholders in leading change using a social constructionist approach, which states that meaning is developed in collaboration with others rather than individually, rather than a problem-solving approach, which many believe to be counterproductive and may lead to more problems. Shifting from problem-focus to discovering what works well in an organization can result in effective partnerships and sustainable changes.
In collaboration with Cooperrider, Diana Whitney, PhD, helped expand AI knowledge by developing the 4D model and AI’s 5 principles. In healthcare, AI focuses on affirmative and positive communication to discover and build upon organizations’ positive aspects. AI asserts that negative inquiries receive negative responses, while positive questions lead to positive affirmations. Searching for what’s working well and exploring the reasons why can lead to more accomplishments.
The 4Ds of AI are discovery, dream, design, and destiny. This cycle serves to identify a topic of interest—such as a practice improvement project or building effective teamwork—that the staff agrees on and wants to explore. The discovery phase emphasizes the current strengths and accomplishments of the change project or individual team members. This phase identifies and appreciates what keeps the team motivated and what’s currently working well. The dream phase pursues ideas and encourages individuals to visualize possible outcomes. It envisions what will be different in the environment and imagines what would work well in the future. The design phase involves collaborative work to achieve the best outcomes. It requires active participation and commitment from those involved. In the destiny phase, sustainable design implementation is created and accomplishments are celebrated.
Embedded within AI’s 4Ds are the five core principles, which are critical to shifting focus from a problem to a possibility. The constructionist principle emphasizes that conversation creates change. It stresses the value of human interaction through dialogue and knowledge sharing. The simultaneity principle states that inquiry stimulates the beginning of change and inspires creative thinking. The poetic principle is the collaboration of ideas to strengthen the goals leading to desired outcomes. The anticipatory principle uses positive affirmation and imagery to stimulate change. The positive principle states that a positive attitude creates positive relationships for effective planning, which leads to better performance and outcomes. (See AI challenges.)
AI in healthcare
Similar to nursing, AI aims to understand the uniqueness and wholeness of individuals and it combines practice with research. According to an integrative review by Watkins and colleagues, studies have found that the AI approach helped develop a trusting relationship among participants, encouraged positive self-reflection for nurses, improved staff morale and communication, increased nurse awareness of their role in influencing change, and enhanced engagement in quality improvement initiatives.
Job dissatisfaction among nurses frequently is related to stress, ineffective interdisciplinary collaboration, and insufficient autonomy. AI, which eliminates blame and empowers positive and meaningful cooperation, draws on interactions that foster positive professional relationships and communication to support a nurse’s advocacy role and team member influence. The approach is appropriate when conducting small group and large-scale meetings, disseminating valuable information, and planning and implementing change initiatives.
AI extends to patient care via coaching, which focuses on a patient’s strengths and motivation to influence behavioral changes. It emphasizes current positive behaviors and practices to effectively make changes. According to Scala and Costa, this strategy requires active patient participation as their values, effective routines, best experiences, and health perspectives are explored. AI supports the idea of patient-centered care and encourages patient autonomy.
With AI coaching, patients select personal goals they want to achieve. For example, a 36-year-old woman who’s overweight and has been diagnosed with diabetes wants to improve her healthy eating habits. She wants to increase her vegetable intake by eating three different vegetables daily but worries about making repetitive choices and eventually giving up. For a short-term goal, she makes a list of vegetables she likes and explores other choices as well. AI coaching allows the patient to explore the kinds of vegetables she prefers and also discover others she might enjoy. She’s able to maintain her increased vegetable intake goal.
AI and teamwork
AI is an effective tool for breaking down barriers between healthcare disciplines and promoting successful teamwork that draws on individuals’ complementary specialties, knowledge, and skills to ensure high-quality patient outcomes and address quality and safety issues. The barriers that continue to affect partnership and interdisciplinary collaboration may be due to the nature of healthcare itself, where professions may have different and conflicting approaches. Establishing organization-wide interdisciplinary policies that allow team collaboration can address this issue. Effective collaboration, however, requires productive communication and coordination. AI can break down barriers between professions and help individuals work together to understand what’s working well.
Sharing stories and experiences may help uncover professional similarities in thinking and perception. Interprofessional group meetings where new information is shared or joint interpretations of knowledge are created can help improve current practices and develop future practices.
AI doesn’t assume perfection when individuals are functioning at their best. According to Whitney, the best way to learn, develop, and change is to study what works well when people, teams, and organization are at their best. With the AI approach, work environments can transform into cultures of appreciation that recognize strengths, value contributions, and encourage innovation and practice improvement. Consider the nurse manager or clinical nurse leader who’s trying to engage staff in decreasing fall rates on the unit. During staff meetings, previous unit improvement project accomplishments are explored. The focus turns to fall prevention, and the team begins exploring and discussing what’s working well and what needs to be improved. The team then works together to develop actions to decrease the fall rate. Using AI, staff are empowered to share ideas without fear of blame or criticism.
AI and leadership
Lack of effective teamwork and inefficient collaboration and communication result in fragmented care, increased medical errors, and threatened patient safety. Ineffective teamwork also can lead to resistance, defensiveness, and increased disparities among team members. In the Journal of Advanced Nursing, Trajkovski and colleagues note that AI is a powerful tool for managing change and facilitating improvements when boundaries are crossed, groups are engaged, and a united approach to organizational change is promoted. AI success requires strong leaders who engage in meaningful conversation and share knowledge while blending strengths and experiences as the team moves toward positive transformations.
Clinical nurse leaders
Clinical nurse leaders with AI knowledge recognize the unique attributes and skills of individuals and allow them to realize their own capabilities and gain confidence in their contributions and ability to succeed. These leaders apply AI during informal daily interactions and formal meetings to promote evidence-based practice and engage staff in quality-improvement processes. When clinical nurse leaders promote affirmative conversations and focus on potential rather than failure, they can emphasize strengths, identify actions and processes that require improvement, advocate high-quality patient care, and support a culture of safety. (See AI in action.)
Transform relationships, influence improvement
AI isn’t without its flaws, and it warrants further study. However, its value as a method for transforming professional relationships and influencing positive workplace improvements makes it worthy of consideration. AI’s focus on positive inquiry rather than negative problems makes it an effective leadership tool to engage active participation, unleash creativity and innovation, and support effective collaboration. AI can be applied to mobilize improvement projects, implement sustainable processes, and create a healthy work environment with a sense of community and teamwork.
Kathleen J. Naca-Abell is a staff nurse at Michael E. DeBakey VA Medical Center in Houston, Texas.
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