Appreciative Inquiry: A radically different approach to change
Positive thinking’ brought to identifying, solving problems
In a traditional approach to problem solving, a team or teams are assembled with the task of identifying errors and creating and implementing strategies to minimize the likelihood that they will be repeated.
However, a new approach just beginning to take hold in health care approaches these issues from precisely the opposite direction: It seeks to identify what went right and duplicate that experience.
Called Appreciative Inquiry, or AI, it was first developed about 15 years ago. Perhaps its most notable success story is a remarkable turnaround at GTE, resulting in that company receiving the 1997 ASTD (American Society for Training and Development) award for best organization-change program in the country.
AI makes a clean break with traditional total quality management (TQM), says Joe Roebuck, director of organization development at Atlantic Health System in Florham Park, NJ. "The pre- vailing TQM approach starts off by identifying negative things or problems," he says. "I don’t think any halfway decent manager wants to make process improvements by stressing things people do wrong."
Duke Rohe, FHIMSS, performance improvement specialist at M.D. Anderson Cancer Center in Houston, agrees. "My first impression of AI is the sense that it uses inquiry in order to help people go ahead and collect the strengths they have to make change, and growing that to where they need to be," he says. "We don’t need to bolster weaknesses."
What AI is
James Espinosa, MD, FACEP, FAAFP, chairman of the emergency department (ED) at Overlook Hospital in Summit, NJ, part of Atlantic Health System, offers this description of AI: "Its approach, in concept, is to ask a number of questions with an intuition and an attitude that looks to ask what’s the best the organization has been in an area that may have been identified as a problem space," Espinosa says.
"It could be patient satisfaction, for example. What story can you tell us about where everything was aligned with your customers?" At its roots, he adds, "[AI] or management is as much an intuition as it is a thing in the world."
Most AI organization-change efforts flow through what is known as the 4-D cycle, as illustrated in Appreciative Inquiry, by David L. Cooperrider and Diana Whitney.1
The cycle is outlined as follows:
- Discovery. "What gives life (the best of what is)?" — Appreciating.
- Dream. "What might be (what the world is calling for)?" — Envisioning impact.
- Design. "What should be (the ideal)?" — Co-constructing.
- Destiny. "How to empower and adjust/improvise?" — Sustaining.
This cycle, say the authors, can be as simple as a single conversation between colleagues, or as complex as an organizationwide process involving every stakeholder.
Another way of viewing AI is to contrast it directly with traditional problem solving, as Cooperrider and Whitney do in their book. For example, they note, problem solving is characterized by a "Felt Need" identification of a problem, while AI focuses on appreciating and valuing the best of what is.
Problem-solving analyzes causes, while AI envisions what might be. Problem solving is characterized by action planning, or treatment, while AI focuses on dialoguing — what should be. Finally, they assert, problem solving’s basic assumption is that an organization is a problem to be solved; AI asserts that an organization is a mystery to be embraced.
Putting it into action
Roebuck recalls that when he first became involved with health care in 1998, he started noticing a fear of problem solving or making improvements. "I sensed a defensive posture after all the years of cost-cutting pressure," he says.
Deciding he needed a more positive approach, he conducted an Internet search and discovered AI. "I called several people who had tried it and then tried to introduce the concept to a health care system," he says.
Roebuck began with the 4-D cycle, starting with discovery, and immediately met his first challenge.
"When I asked a group to relate what we were doing well together as team, there was silence," he says.
"Most of us in health care have never been asked about what we really do. We’re not even asked about the lives we’ve saved. There’s so much focus on money, we have lost the appreciation for healing people," Roebuck points out.
"It’s hard to identify what we do really well and seek to discover other places we can apply it," he says.
People loved the approach, he says, but it remained hard for them to start thinking positively. "At the end of one meeting, I asked the group what we did really well together as a group in the meeting. There was silence again," Roebuck says. "That told me I had a real challenge."
Meeting the challenge
This is not to say that the mindset of health care professionals is an obstacle that cannot be overcome. For example, at M.D. Anderson, Rohe asks participants in inquiry sessions to go home and write down their positive responses.
Recently, he conducted a "Disney Scavenger Hunt" in the pharmacy department. "I asked the participants to go out and find something they liked in a service and write it down," he recalls. The department was broken down into small teams, and about half of the members of the team would do their homework.
"But when we then discussed the homework responses, others came up with ideas within the meeting itself," Rohe notes.
"Then, we moved to the next step, which is saying, This is how we like to be treated, so we will do the same for our customers.’ By collecting these best practices, we got a commitment from the group to do just that," he adds.
It may have been the writing component that helped the process succeed, or it may have been the size of the group. At Overlook Hospital, for example, Espinosa has had significant success with AI in a microsystem setting.
The work centered around flu season. "We could have approached it with traditional, problem-oriented QI bring me the data that show the problem space’ — and that’s a very important perspective — but the problem emotionally is there’s not a lot of energy to be gained among the staff with that approach," Espinosa says.
"There’s a painful neuro-association in place; by definition, it’s almost like blaming. Also, in practical terms, you run up against the fact that there’s no really overarching resolution there. It cuts to load distribution, reimbursement, predictability, public health," he says. "In the long term, one could develop all kinds of strategies, open up new space or capacity, and we all have done that. The problem is that root-cause analysis doesn’t liberate energy. You don’t really bring to the surface the genius of the group or of one practitioner."
In this initiative, Espinosa and staff met in a system of four microsystems.
One of the stories was about a special event on one of the toughest flu days. "The hospital dietary department brought down a big soup tureen and sandwiches to the ED," Espinosa relates.
"Both patients and staff partook, and suddenly there was a remarkable sense of comfort. Staff have a hard time getting off during flu season, and they felt appreciated and valued, and felt a sense of community. The patients, too, felt this was a special day," he continues.
Anecdotal exchanges bring out information
This was just one of a number of individual stories that came out of the meetings. "It’s amazing the kinds of things that can pop out," Espinosa says. "People interviewed each other and asked what was the best they had been, and we heard stories of some amazingly good things — strategies people recalled as particularly effective and felt good about over the years."
Espinosa says that by employing AI in a microsystem setting, the initiative can be framed around a problem.
"In industry, you might ask what’s the best our company has been," he asserts. "But in a microsystem, AI can be the way to approach a problem space."
This provides a different perspective for how to add value, Espinosa continues.
"The experience in the intensive care unit might be a different set of community responses than the one in the ED," he notes. "If you say you are looking for best practices across a system, but you only ask for the best things have been among a homogenous cohort, you might have to work real hard to find — if you can find them at all — the underlying themes you could derive learning principals of change around. Nor would they necessarily spread quickly.
"But if you have the soup-tureen’ concept and four EDs sit down together, the likelihood is that the problem space in the four EDs is shockingly similar. Therefore, it’s more likely the soup delivery idea is going to be something that is appreciated by others on face value, and spread quickly to the other EDs," he explains.
Will it work systemwide?
The experience of GTE and other private-industry firms demonstrates that AI will work across large organizations, but Roebuck says health care still has a way to go before it can successfully apply AI systemwide.
"It will never replace traditional problem solving, but it may complement it and help us start to look in new areas for best practices, and to spread them around," Roebuck says. "It’s a better way of identifying best practices."
"AI hyperlinks beautifully into best practices," Espinosa adds. "It gets past the formality and closer to what might come up during a discussion in the hallway. You get down to context-specific change concepts. The deep payoff is you can dissolve the concept specificity and derive more general concepts — like applying those dietary- department concepts in other areas."
Is it worth the time and effort?
But is AI worth the time and attention required to get staff comfortable with such a unique concept? For Roebuck, the answer is a definitive yes. "I’m sold on it," he says.
The hard part, he concedes, is that AI is not as comfortable and well known as other methodologies. "It still needs to be accepted on a system-wide basis," he asserts. "But it’s exactly what we need. We’ve driven almost all the costs out that we can control. What we need now is a technology like AI to start to look at those things we need to get back on our agendas.
"For health care, the systems and hospitals that are standing now are the survivors," Roebuck continues. "We’ve been through the emphasis on costs. We now have more enlightened leadership than ever before, and better managers."
So, will AI find a permanent home in the arsenal of the quality professional? "It’s just a question of time," Roebuck concludes.
Key Points
- Appreciative Inquiry, or AI, seeks to identify what went right and duplicate the experience.
- Adjustment in thinking may be difficult for defensive-minded health care professionals.
- Likelihood of success appears greater when smaller groups are involved.
Reference
1. Cooperrider DL, Whitney D. Appreciative Inquiry. San Francisco: Berrett-Koehler Communications Inc.; 1999. n
Need More Information?
For more information, contact:
- James Espinosa, MD, FACEP, FAAFP, Chairman, Emergency Department, Overlook Hospital, 99 Beauvoir Ave., P.O. Box 220, Summit, NJ 07902-0229. Telephone: (908) 522-5310.
- Joe Roebuck, Director of Organization Development, Atlantic Health System, 325 Columbia Turnpike, Florham Park, NJ 07932. Telephone: (973) 660-3262. E-mail: [email protected].
- Duke Rohe, FHIMSS, Performance Improvement Specialist, M.D. Anderson Cancer Center, Houston. Telephone: (713) 745-4433. E-mail: [email protected].
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