Participate in the QI Enablers Study

Five iterations of D2D data show that some teams tend to improve more over time compared to others. AFHTO members want to know what some of the “tricks of the improvement trade” are so they can try them out in their own teams. This QI enablers study is aimed at learning more about what makes it easier or harder to improve so that all teams can take advantage of the wisdom from the field.

What is the study about, and why? How will the study be done? When will the study happen?
What we want to talk with teams about What we won’t ask teams about Frequently Asked Questions

 

What is the study about and why?

The QI Enablers study will be based on in-person interviews with teams. It will provide a snapshot of how teams think and work to get better at what they do. We will ask teams “what works and why” when they try to get better at what they do. Details on the interview process are outlined below. The study will describe what is happening with teams at a single point in time – ie it is not ongoing, the way that D2D is. The data from the interviews (which will mostly be in the form of stories) will be compared to D2D performance. This will point out any patterns between the stories of how teams work and their D2D scores which will provide hints regarding what works best to move beyond measurement to improvement. The key is to have teams from ALL stages of the QI journey so we can compare and contrast. We will share the stories first with the participating teams to confirm that we have heard them right. Then we will be sharing the collective wisdom from the stories with all members and also with external partners, so that everyone (AFHTO members and beyond) can learn together. The stories will be shared anonymously – unless a team is keen to see their name in lights, in which case we would happily oblige!

How will the study be done?

The team visits and interviews will be done by Carol Mulder, Provincial Lead for Quality Improvement and Decision Support and Laura Belsito, Clinical Knowledge Translation and Exchange Specialist, supported by any graduate students we are able to recruit and the QIDS program staff at AFHTO. We will spend about 4 hours at each team site, talking to whoever the team wants us to talk to.  We have put together a “straw dog” schedule to give teams a sense of who might be included. However, it is totally up to the team to decide who will meet with us to tell their story.  In addition, the conversations can take place in any order the team wants – ie Hour 1 doesn’t have to be the first hour if that doesn’t work for the team.

  • Hour 1: ED, Medical Lead and Board Chair
  • Hour 2 (2 groups): Separate conversations with QI staff (QIDSS and others?) and patients
  • Hour 3: IHPs and physicians together
  • Hour 4 (2 groups): Separate conversations with clerical staff (including physician staff, if different from FHT clerical staff) and possibly LHIN performance staff

When will the study happen?

Visits to teams will be scheduled starting September 2017. See below for draft timeline.  Note that this study will be taking place at the same time as patient focus groups to learn more about patient priorities for primary care measurement (see the patient priorities survey information on the AFHTO web site for more information). Interested teams may choose to volunteer for both the QI enablers visits and a patient focus group if they choose.

Activity Start End
Invite teams to participate NOW! July 31, 2017
Schedule interviews August 4, 2017 September 26, 2017
Conduct interviews September 27, 2017 ongoing
Summarize input October 30, 2017 January 31, 2018
Reflection with participants and QSC February 15, 2018 February 22, 2018
Take action NOW!  April 30, 2018

What we want to talk with teams about

We will visit teams and ask them “what works and why” when they try to get better at what they do. This approach is loosely grounded in theories of “appreciative inquiry”, “solutions focus” and “positive deviance.” In keeping with these theories, the interview questions will follow the stories of the people we are talking to. That means the questions won’t be the same for each person or team we talk to.  However, the stories we are looking for are the same for all teams. They include:

  • Stories about your attempts to get better at something: How did you know you needed to get better? Who decided? What happened when you tried to change things? Who worked on it? How do you know if it worked or not? Who was happy about it? Who wasn’t? Why?
  • Stories about learning from what you tried in the past: How do you feel now about being able to make something else better? What makes you feel that way?
  • Stories about the “perfect storm” for improvement: When did it last happen for you? What does it look like? Who is there? What made the storm? Who likes the storm?
  • Stories about your special skills/people/processes (ie superpowers) for improvement or good primary care: What are they? How did you get them? What do you use them for?

When we are hearing the stories, we will be looking for some particular ideas in the data (see below). Even if they are not there, that might mean something. For example, if nobody talks about how many people need to be on board for improvement to work, that might be as interesting as finding out that teams agree on a certain minimum number.

  • Drivers for quality improvement
  • Triggers for improvement
  • Confidence and appetite for change in the team (improvement = change)
  • Culture of innovation/tendency to try new things FIRST vs wait for tried/tested solutions
  • Minimum critical mass of staff to enable improvement (if any)
  • Role of leadership and/or intentional planning in successful improvement
  • Absolute requirements for successful improvement (if any)
  • Role of EMR functionality and data
  • QI as an approach to work vs a separate project
  • Significant team events (eg Change in ED) that might affect QI activity

What we won’t ask teams about

Teams will not be asked why they are doing better (or worse) than others in making things better over time. This is partly because they might not know – and partly because it doesn’t matter that much. For example, maybe all (or no?) teams feel they have superpowers. Yet some teams may find it easier to get better than other teams, even if they all have the same superpower.  This might mean that superpowers matter for other reasons but might not be the answer we thought they were in terms of making things better.

Frequently Asked Questions

 

Is this a formal research study? Yes. This is an observational, qualitative cross-sectional study. AFHTO will be getting approval from the Research Ethics Board for it. Why do this as a formal research study? AFHTO Board has recently affirmed its commitment to playing a leadership role in primary care and, more broadly, in the Ontario healthcare sector. AFHTO needs to be able to tell the story of its leadership in a wide variety of forums to demonstrate that leadership. A formal research study (with formal ethical approval) makes it possible to share the collective wisdom of AFHTO members in credible and high profile way to support leadership activity. Do members HAVE to participate? Practically everything AFHTO does is voluntary and intended to serve the members. Members can choose not to be interviewed simply by not volunteering. Nobody but they themselves will ever know that. Can I tell my story to AFHTO but not be in the research study? We will only include the stories of teams who agree to be part of the published study but we will listen to and share ALL the stories among the members for their own use. And all the stories will be anonymous unless a team is keen to have their name in lights, in which case we would happily oblige! What if our team is really struggling to improve? You are so not alone! And your story is really important. You may be doing everything “right” and still be in the place you are. That is the kind of story that will help us all see what actually is important on the ground (vs in theory). If we only talk to teams who are making good progress, we will not get useful information for those who are in the trenches, pulling out all the stops and still frustrated. You (all of you!) really are the answer! Who should be part of the interviews? Bring whoever you want to the table. We have a hunch about some roles that tend to be important in a team’s efforts to get better – see our list above. You may have different ideas. It is your call. What is the risk for our team? All of your stories will be masked (i.e., “Team X”) unless you want to see your team’s name in lights. No team’s story will be shared without their consent with any external group (Eg MOHLTC) except in an anonymous way as part of the collected stories from the study. Why don’t we just go to the literature to find out what the enablers of Quality improvement are? We would love to. If you have suggestions of studies we should look at, please tell us! So far, most studies about “high performing teams” describe the way teams work but don’t compare that to a measure of performance. Teams are identified as high performers mostly by self-report or nomination by peers. Teams that self-report as high performers may or may not be the same as those with high performance on measures of quality such as those in D2D. Other studies identify high performers on the basis of administrative data (eg cancer screening rates, readmissions etc). These indicators do not reflect the overall quality of care provided nor the contribution of the team, which is problematic, given the interest in high performing teams. This study addresses those gaps by comparing team characteristics (such as those examined in other studies) with demonstrated ability to improve over several iterations of D2D (which we define as “high performance”). What is a “high performing” team? This study focuses on enablers for improvement. That means high performance is defined as “demonstrated improvement in D2D indicators over time”. D2D indicators reflect the patient perspective (patient experience survey indicators), the provider perspective (eg cancer screening etc) and the system perspective (e.g., readmissions). This is not a perfect definition of performance. It is, however, the most broad, current and ongoing source of primary care performance data available to describe the performance of primary care teams.  

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