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Copyright © eContent Management Pty Ltd. Contemporary Nurse (2013) 45(1): 95–100.

Organizational change in the health care sector is a complex non linear process often stimulated by shifts in social, economic and political environments (Richer, Ritchie, & Marchionni, 2010). Health care profession- als are constantly required to adapt to the rapid pace of change in contemporary health environ- ments while continuing to deliver high quality and ethical health care (Eagar, Cowin, Gregory, & Firtko, 2010). The general public and the media have become less tolerant of poor levels of health care resulting in rising consumer demand for involvement with health policy development. New reforms such as Australia’s National Health and Hospital Reform Commission (NHHRC) ‘A healthier future for all Australian’s’ (2009), North America’s Department of Health and Human Services (HHS) Affordable Care Act (2010) and the United Kingdom’s Department of Health and National Health Services Corporate Plan (2012) show greater emphasis on developing partnerships and collaborations across sectors and community groups with greater responsi- bilities, accountability to and involvement of consumers.

It is becoming increasingly evident that tra- ditional methods of managing contemporary health care are limited in meeting the needs of patients, health care workers and organiza- tions. This paper discusses how an innovative

Using appreciative inquiry to transform health care

SUZA TRAJKOVSKI*, VIRGINIA SCHMIED*, MARGARET VICKERS+ AND DEBRA JACKSON!

*Family and Community Health Research Group, School of Nursing and Midwifery, University of Western Sydney, Sydney, NSW, Australia; +School of Business, University of Western Sydney, Sydney, NSW, Australia; !University of Technology Sydney, Sydney, NSW, Australia

ABSTRACT: Amid tremendous changes in contemporary health care stimulated by shifts in social, economic and political environments, health care managers are challenged to provide new structures and processes to continually improve health service delivery. The general public and the media are becoming less tolerant of poor levels of health care, and health care professionals need to be involved and supported to bring about positive change in health care. Appreciative inquiry (AI) is a philosophy and method for promoting transformational change, shifting from a traditional problem-based orientation to a more strength-based approach to change, that focuses on affi rmation, appreciation and positive dialog. This paper discusses how an innovative participatory approach such as AI may be used to promote workforce engagement and organizational learning, and facilitate positive organizational change in a health care context.

Keywords: appreciative inquiry, health care, organizational change, nurses, culture

participatory approach such as appreciative inquiry (AI) may be used to facilitate workforce engagement, and promote organizational learn- ing and positive organizational change in the health care context.

BACKGROUND Upward pressures on costs from factors such as technology and increasing consumer demands along with downward economic pressures such as fi scal constraints often result in health orga- nizations seeking new and more effi cient ways of delivering health care (Eagar et al., 2010). Developing new cost-cutting measures and health service reorganization are strategies that are often used to respond to these pressures. With increased fi scal constraints, traditional nursing roles and responsibilities are being chal- lenged (Eagar et al., 2010). The expectations of the nursing workforce are transforming with nurses seeking positive rewards and effective pro- fessional relationships within their work environ- ment. A meta analysis conducted by Zangaro and Soeken (2007) reported nurses are dissatisfi ed in many areas, and highlighted nurse job satisfac- tion as strongly correlated with job stress levels, collaboration with health care professionals and level of nurse autonomy.

Aiken, Clarke, Sloane, Lake, and Cheney (2008) reported improved staffi ng numbers,

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that drive the organization and its members in the process of change (Richer et al., 2009). It searches for what gives ‘life’ to living systems, and acknowledges the best in people, the organization and the world around them (Carter, 2006; van der Haar & Hosking, 2004).

Adopting a participatory approach, AI offers a fl exible framework to facilitate change from the grass roots up. It lends itself to building effec- tive partnerships and collaborations that can be used to meet particular needs of an organization (Koster & Lemelin, 2009; Reed, 2007). AI sup- ports an egalitarian post-bureaucratic form of organization (Cooperrider & Srivastva, 1987). Based within the socio-rational realm of human affairs, AI acknowledges that different social realities co-exist within groups and considers peoples’ voice and contributions as equally valid and important (regardless of social status) result- ing in a stance of freedom, liberation, solidarity and social construction (Cooperrider & Srivastva, 1987). Encouraging less hierarchical structures and more equalized power and input into deci- sion making processes, individuals and groups are empowered to improve their situation and move toward visions for a more egalitarian future. Organizations engaging in AI are reported to have increased system-wide collaborative competence (Barrett, 1995).

AI has been used in various settings includ- ing businesses, education, military services, not-for-profi t organizations, prison, communi- ties, religious institutions and more recently in health care settings (Carter, 2006; Havens et al., 2006; Liebling, Eliot, & Arnold, 2001). It has been reported to be effective in engaging groups and promoting a unifi ed approach to change (Lavender & Chapple, 2004). AI is also being used as a research approach and can reframe research, moving away from a problem orienta- tion to a positive theory of inquiry (Koster & Lemelin, 2009; Reed, 2007). As a research meth- odology, AI roots lie in action research and social constructionism (Carter, 2006).

Five underpinning principles of AI as devel- oped by Cooperrider and Whitney (1999) are the constructionist, simultaneity, poetic, anticipatory and positive principles. The

higher levels of nurse education and improved care environments as factors that are associ- ated with lower patient mortality. Similarly, Havens, Wood, and Leeman (2006) identifi ed improved communication and collaborations across disciplines and sectors and increased nurse involvement in decision making processes as key to successful recruitment and retention of nurses and the delivery of high quality care. Factors affecting work performance and nega- tive organizational culture or sub cultures are also reported to effect workplace effi ciency, effectiveness, and safety of both health care professionals and patients (Aiken et al., 2008; Kennerly et al., 2012).

To promote signifi cant and sustainable changes, health care leaders need to search for ways to fully engage their workforce and open up new opportunities to improve the quality of work life and organizational performance. Kennerly et al. (2012) suggests working within a positively toned cultural environment is impor- tant to achieve high quality health care outcomes. Additionally, nurses are not only participants in the labor force, but also accumulators and pro- ducers of knowledge who are well positioned to be leaders in driving organizational change and building healthy, humanly sustainable organiza- tions (Richer, Ritchie, & Marchionni, 2009). Moving away from a traditional problem solving approach to one of appreciation and openness to future possibilities offers a new approach for health care professionals to bring about positive change in health care.

APPRECIATIVE INQUIRY AI is a relatively new and innovative approach to organizational learning, organizational change and research. First coined in 1986 by Cooperrider, AI adopts a social constructionist view based on affi rmation, appreciation and positive dialog (Cooperrider, 1986). AI is reported to have sig- nifi cant transformational potential that shifts the focus from problems to be solved to discovering and building on what works well within an orga- nization and using that as the beginning point for change (Koster & Lemelin, 2009; Reed, 2007). As an ethos, AI implies a shift in the assumptions

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cycle (see Figure 1) (Cooperrider & Whitney, 1999; Cooperrider, Whitney, & Stavros, 2008, p. 5). At the core of the 4D cycle is an affi rma- tive topic choice which is considered a signifi - cant component of the AI process highlighting change is implicit in the very fi rst question asked (Cooperrider & Whitney, 1999).

The discovery phase seeks to explore ‘what gives life’ to individuals, their work and the organization, through appreciation and valuing what is best of what is or has been (Cooperrider & Whitney, 1999; Cooperrider et al., 2008, p. 5). The dream phase seeks to elicit insights into individuals and practice through the gen- eration of affi rmative stories usually focusing on recalling peak experiences or high points. The dream phase focuses on envisioning ‘what might be’ through affi rmative exploration (Cooperrider & Whitney, 1999; Cooperrider et al., 2008, p. 5). When using an AI approach, often miracle or magic wand questions are used to encourage participants to visualize how things might look like if a miracle occurred, or if they had a magic wand. Provocative propositions are also developed which are confi dent and asser- tive statements of what the organization hopes to achieve. The design phase focuses on working together to construct the ideal of ‘what should be’ (Cooperrider & Whitney, 1999; Cooperrider

constructionist principle suggests human knowledge and organizational destiny are interlinked (Cooperrider & Whitney, 1999). Dynamic human constructs need to be understood and analyzed by managers and leaders to be effective (Cooperrider & Whitney, 1999). Therefore, before change can be initiated leaders and managers need to begin with an understanding of indi- viduals within the organization. The principle of simultaneity recognizes that inquiry and change occurs simul- taneously and emphasizes the implicit nature of questions asked and dialog used (Cooperrider & Whitney, 1999). It is suggested that change begins from when the very fi rst question is asked. The poetic principle suggests organiza- tions are open to endless interpretation and rein- terpretation where stories evolve or new stories are inspired (Cooperrider & Whitney, 1999). The anticipatory principle suggests reframing people’s vision of the future may result in mov- ing toward the envisioned future. The positive principle suggests the more positive the question the greater the change effort (Cooperrider & Whitney, 1999).

The power of positive dialog is emphasized in AI suggesting that such dialog has the abil- ity to positively infl uence organizational growth (Gergen, Gergen, & Barrett, 2004). Generating collective visions and actions are considered an essential component in bringing about change when using the AI process. Underpinning assumptions of AI are that in ‘every group, society or organisation something works; things we focus on become our reality; language and dialogue infl uences the group and our reality; multiple realities exist and are created in the moment; valuing differences is required and lastly, when people have more confi - dence moving to the future, they will carry forward positive aspects of the past’ (Hammond, 1998, p. 13–21).

The 4D cycle AI consists of four iterative phases (discovery, dream, design and destiny) known as the 4D

FIGURE 1: APPRECIATIVE INQUIRY: 4D CYCLE (ADAPTED FROM COOPERRIDER ET AL., 2008, p. 5)

4D cycle

Affirmative Topic Choice

Design “How to empower,

learn and adjust/improvise?”

Sustaining

Discovery “What gives life?”

(The best of what is) Appreciating

Dream “What might be?”

Envisioning results/impact

Design “What should be-the

ideal?” Co-constructing

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knowledge to build a more positive future for the team, unit or organization (Richer et al., 2009). Nurses’ are presented with opportunities to develop effective social networks, high levels of engagement and interdisciplinary collabora- tions. Additionally, AI acknowledges that atten- tion must be given to both micro-level social structures for networking in the production of innovation along with a larger systems perspec- tive (Richer et al., 2009).

Literature reports the need for improved com- munication and increased nursing involvement in decision making; however minimal guidance exists in how to achieve this (Havens et al., 2006). Havens et al. (2006) suggest AI offers nurses a framework to implement and sustain these fea- tures in practice. The inclusive and collaborative nature of AI promotes ownership of the change process and draws on the collective experience, wisdom and resources within the group. Honoring diversity, AI allows all members to have a voice in the change process leading to richer solutions and greater willingness to strive toward mutually ben- efi cial goals.

AI is quality oriented and can be used to set new benchmarks and best practices in nurs- ing and health care (Havens et al., 2006). A key feature is that quality may be explored as it occurs within settings and organizations. The AI process may guide nurses in critical refl ec- tion on existing quality practices. Furthermore, Marchionni and Richer (2007) report that AI can serve as a transformational change process to promote evidence-based practice in health care, where nurses can serve as advocates, sup- porters and agents of change. AI offers nurses the opportunity to identify areas to promote change in the organizations strategic values through refl exivity and action.

As a research method, AI has been reported to complement traditional forms of action research through its ability to inspire generative learn- ing (Barrett, 1995; Carter, 2006; Richer et al., 2009). Carter (2006) reports participants tend to ‘come on side’ more easily than with tradi- tional research methods and approaches (Carter, 2006). Reed, Pearson, Douglas, Swinburne, and Wilding (2002) noted that focusing on positives

et al., 2008, p. 5). Finally, the destiny phase focuses on sustaining the envisioned future (Cooperrider & Whitney, 1999; Cooperrider et al., 2008, p. 5).

Participants or team members are considered experts or co-researchers. The AI process allows team members to exchange tacit and explicit knowledge to transform their organization. The fl exible AI framework allows the specifi c aims and needs of an organization to be addressed in the context of the organization being reviewed (Cooperrider & Whitney, 1999; Cooperrider et al., 2008, p. 5).

Studies are reporting AI as a catalyst for posi- tive organizational change and development (Lavender & Chapple, 2004) and a new way of reframing research practice (Carter, 2006). Most applications of AI have been reported in business, not-for-profi t organizations, govern- ment and community groups. A review of the limited numbers of papers of AI in health care conducted by Richer et al. (2010) reports AI has been used to evaluate and change organiza- tional or clinical processes, explore professional development initiatives, defi ne public health- care services, create team visions and improve health care work environments. A key strength of AI is the inclusive and collaborative nature of this form of inquiry (Carter, 2006; Richer et al., 2009). AI is reported to be effective in facilitat- ing change through collaborations and develop- ing partnerships (Lavender & Chapple, 2004). Collaborations and partnerships varied from use in single units (Lazic, Radenovic, Arnfi eld, & Janic, 2008) to ‘whole system’ events engag- ing multiple stakeholders across disciplines and large geographical areas (Lavender & Chapple, 2004).

AI shares philosophical values with nurs- ing as they both seek to explore the unique- ness, wholeness and the essence of human life (Cowling, 2001). Originally designed as a research method and then a method of prac- tice, AI is a good fi t with the discipline and profession of nursing blending research and practice toward a potential praxis (Cowling, 2001). An AI approach fosters innovative ideas and allows nurses the opportunity to exchange

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Cooperrider, D. L. (1986). Appreciative inquiry: Toward a methodology for understanding and enhancing organi- zational innovation. Cleveland, OH: Western Reserve University.

Cooperrider, D. L., & Srivastva, S. (1987). Research in organizational change and development (Vol. 1, pp. 129–169). Greenwich, CT: JAI Press.

Cooperrider, D. L., & Whitney, D. (1999). Appreciative inquiry: A positive revolution in change. In P. Holman & T. Devane (Eds.), The change handbook: Group methods for shap- ing the future (pp. 245–261). San Francisco, CA: Berrett-Koehler.

Cooperrider, D. L., Whitney, D., & Stavros, J. M. (2008). Appreciative inquiry handbook: For lead- ers of change (2nd ed.). Brunswick, OH: Crown Custom.

Cowling, R. W. (2001). Unitary appreciative inquiry. Advances in Nursing Science, 23(4), 32–48.

Department of Health and National Health Service. (2012). Corporate plan. Retrieved from http://corpo- rateplan2012.dh.gov.uk/

Eagar, S. C., Cowin, L. S., Gregory, L., & Firtko, A. (2010). Scope of practice confl ict in nursing: A new war or just the same battle? Contemporary Nurse, 36(1–2), 86–95.

Gergen, M. M., Gergen, K. J., & Barrett, F. (2004). Appreciative inquiry as dialogue: Generative and transformative. Advances in Appreciative Inquiry, 1, 3–27.

Hammond, S. A. (1998). The thin book of apprecia- tive inquiry (2nd ed.). Plano, TX: Thin Book Publishing Co.

Havens, D. S., Wood, S. O., & Leeman, J. (2006). Improving nursing practice and patient care: Building capacity with appreciative inquiry. Journal of Nursing Administration, 37(10), 463–470.

Jones, R. S. P. (2010). Appreciative inquiry: More than just a fad? British Journal of Health Care Management, 16(3), 114–122.

Kennerly, S. M., Yap, T. L., Hemmings, A., Beckett, G., Schafer, J. C., & Borchers, A. (2012). Development and psychometric testing of the nursing culture assessment tool. Clinical Nursing Research, 21(4), 467–485.

Koster, R. L. P., & Lemelin, R. H. (2009). Appreciative inquiry in rural tourism: A case study from Canada. Tourism Geographies, 11(2), 256–269.

Lavender, T., & Chapple, J. (2004). An exploration of midwives’ views of the current system of maternity care in England. Midwifery, 20(4), 324–334.

appeared to reduce participant defensiveness and encouraged open discussion in complex environ- ments (Reed et al., 2002).

As with all approaches, there are also risks identifi ed in using AI. For example, some indi- viduals may fi nd it diffi cult starting from and maintaining a positive stance (Richer et al., 2010) while others may feel that problems iden- tifi ed are being dismissed (Reed et al., 2002). The fl exible nature and lack of methodological consistency and rigor may also be viewed as a limitation of AI. While Jones (2010) implies AI has many attributes of a management ‘fad’ and consists of ‘grey data’ it was also suggested that strong anecdotal evidence exists highlighting the benefi ts of using an AI approach across disci- plines and settings (p. 116).

CONCLUSION While further rigorous studies are needed to explore AI processes in various healthcare con- texts, AI is an innovative strategy worth con- sidering in contemporary nursing. It provides managers and researchers a constructive new way forward, shifting from a negative and problem- based approach, to a positive form of inquiry that can be tailored to the specifi c needs of the individual, a ward or unit or an organization. The inclusive nature of AI lends itself to build- ing effective partnerships and collaborations. AI provides a way forward to initiate change in the fast paced contemporary health environment and allow management, health professionals and consumers the opportunity to positively infl u- ence the work, design and management of health care organizations.

REFERENCES Aiken, L. H., Clarke, S. P., Sloane, D. M., Lake, E. T., &

Cheney, T. (2008). Effects of hospital care environ- ment on patient mortality and nurse outcomes. Journal of Nursing Administration, 38(5), 223–229.

Barrett, F. J. (1995). Creating appreciative learning cul- ture. Organizational Dynamics, 24(2), 36–49.

Carter, B. (2006). ‘One expertise among many’ – Working appreciatively to make miracles instead of fi nding problems: Using appreciative inquiry as a way of reframing research. Journal of Research, 11(1), 48–63.

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Lazic, J., Radenovic, M., Arnfi eld, A., & Janic, D. (2008). Implementation of a nurse education programme in paediatric oncology using appreciative inquiry: A single centre experience in Belgrade, Serbia. European Journal of Oncology Nursing, 15(5), 524–527.

Liebling, A., Eliot, C., & Arnold, H. (2001). Transforming the prison: Romantic optimism or appreciative realism? Criminal Justice, 1(2), 161–180.

Marchionni, C., & Richer, M. C. (2007). Using appre- ciative inquiry to promote evidence-based practice in nursing: The glass is more than half full. Nursing Leadership, 20(3), 86–97.

National Health and Hospital Reform Commission. (2009). A healthier future for all Australians fi nal report. Retrieved from http://www.health.gov.au/ internet/nhhrc/publishing.nsf/content/nhhrc-report

North America Department of Health and Human Services. (2010). Affordable care act. Retrieved from http:// housedocs.house.gov/energycommerce/ppacacon.pdf

Reed, J. (2007). Appreciative inquiry: Research for change. Thousand Oaks, CA: Sage.

Reed, J., Pearson, P., Douglas, B., Swinburne, S., & Wilding, H. (2002). Going home from hospital: An appreciative inquiry study. Health and Social Care in the Community, 10(1), 36–45.

Richer, M. C., Ritchie, J., & Marchionni, C. (2009). ‘If we can’t do more, lets do it differently!’: Using appre- ciative inquiry to promote innovative ideas for better health care work environments. Journal of Nursing Management, 17(8), 947–955.

Richer, M. C., Ritchie, J., & Marchionni, C. (2010). Appreciative inquiry in health care. British Journal of Health Care Management, 16(4), 164–172.

van der Haar, D., & Hosking, D. M. (2004). Evaluating appreciative inquiry: A realtional con- structionist perspective. Human Relations, 57(8), 1017–1036.

Zangaro, G. A., & Soeken, K. L. (2007). A meta-analysis of studies of nurses’ job satisfaction. Research in Nursing & Health, 30, 445–458.

Received 05 November 2012 Accepted 14 March 2013

A N N O U N C I N G LONGEVITY: SOCIOLOGICAL PERSPECTIVES ON HEALTH, ILLNESS AND SERVICE PROVISION

A special issue of Health Sociology Review – Volume 23 Issue 1 – ii + 126 pages – ISBN 978-1-921980-25-1 – March 2014

Guest Editors: Pauline Savy (La Trobe University, Australia), Anne-Maree Sawyer (La Trobe University, Australia) and Jeni Warburton (La Trobe University, Australia)

This special issue of Health Sociology Review examines the possibility and actuality of living to very old age. In our times, cultural discourses to do with maintaining health and independence for as long as possible pervade social policy and the personal narratives of ageing. Sociologically, these raise interesting, and often contentious, questions about the role of structural support systems, the delivery of appropriate health care, and the phenomenological ex- perience of ageing and dealing with frailty and decline.

Theoretical and empirical submissions contribute to sociological discussion and analysis from across relevant disci- plines within Australia and overseas – providing insight and critical discussion of a broad range of topics relevant to the health of aged persons – for example, immediate health matters as experienced by individuals and particular groups through accounts of the lived experiences of ageing, managing health problems and negotiating health care. Articles focus on or incorporate critical analysis of policy, the work of health care professionals and wider social factors such as access and equity in service provision - as well as showcase and advance methodologies used in re- searching the health and illness experiences of old individuals whose lives are signifi cantly compromised by illness. Topics include:

• Ageing and health of particular groups eg Indig- enous, migrant, gendered groups, rural and remote populations

• Evaluation of specifi c care provision and levels eg acute hospital care, community care, long-term care and health promotion programs

• The ageing body, decline, dying and death • Health and illness in the oldest generation • Ageing and medicalisation

• Dementia • Living with common and chronic conditions including

psychiatric conditions • Family relationships in old age and ill health • Professionalisation and specialisation, for example, chang-

ing role boundaries in aged care, workforce situations and impacts

• Social, structural factors that promote or oppose lon- gevity and wellness

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