Limitations and Weaknesses of Research Design

Staying focused on a wealth of data. As a research analyzing a very complex, very dynamic phenomenon of great importance for society, this research was crafted as a delicate balance between two opposites: (1) insight to just a fraction of data and (2) too much data to analyze. While, from my perspective, the balance seems to be well established, from the perspective of other stakeholders, a different balance may seem more suitable. Combining the outcomes of this research with the results of similar research, especially similar future research, is probably the best approach to address this limitation.

Bias. As a phenomenographic researcher working for the ASA, there is a risk that my personal or ASA bias might influence the research. Since per social constructivism, perceived reality is a social construct that exists on an individual and group/organizational level, my goal is to recognize how my and the ASA’s realities look and how the two realities compare with the realities of other individuals and organizations involved in this research. Ultimately, the goal is not to neutralize them but to recognize and combine them with the realities of other stakeholders.

The main steps to address bias are the following:

• Actively hold back my assumptions and theories that I would get a better insight into how the phenomenon is understood by respondents (Sandbergh, 1997) without the influence of personal perspectives, material world, and subjects (Chan, Fung, & Chien, 2013).
• Use phenomenographic research to gather insight into the realities of other stakeholders and, through follow-up interviews, ask them to evaluate how I interpreted their reality.
• Share a part of my findings with selected leaders and the public and ask them for feedback.

The data from those four clinical professions will allow me to define the main themes and interactions among different professions while remaining focused and on scope; however, insight from other professions will be very valuable. Therefore, future research should include perspectives from the following:

• Other clinical groups involved in care, such as operating room nurses, surgical technicians, pharmacists, and nonclinical professions like IT and management
• Students—future professionals and residents

References

Chan, Z. C., Fung, Y.-l., & Chien, W.-t. (2013). Bracketing in phenomenology: only undertaken in the data collection and analysis process? The Qualitative Report, 18(30).

Sandbergh, J. (1997). Are phenomenographic results reliable? Higher Education Research & Development, 16(2), 203-212.

Interviews

Sample Size

The literature states that there is “no prescriptive sample size for a phenomenographic study” (Yates, Partridge, & Bruce, 2012, p. 103). Bowden (2005) suggests that the sample should be large enough to find sufficient variation in perceptions but small enough that the amount of data is manageable. A concept close to sufficient variation in perceptions is the saturation point. The research will achieve the saturation point when additional perceptions cannot be detected (Kaapu & Tiainen, 2012).

Study participants. Following that recommendation, I interviewed five to eight  members of each of the four groups: physician anesthesiologists, nurse anesthetists (NA), anesthesiologist assistants (AA), and surgeons. Majority of the participants are clinicians and leaders who are clinically active. The rest are CPD professionals and staff leaders.

This study analyzed twenty-two transcripts, gained through interviewing

• five anesthesiologist assistants (AAs),
• four surgeons and one CPD expert involved in the education of surgeons,
• five anesthesiologist physicians and two CPD professionals, and
• seven certified, registered nurse anesthetists (CRNAs).

In addition to that, because of technical issues, the recordings with one anesthesiologist and one CRNA were damaged and were not included in the analysis.

The in-depth, open-ended interviews were recorded and transcribed verbatim. The interviews lasted between 22 minutes and 115 minutes, and in all cases, a state of mutual understanding was achieved (discussion was exhausted) (Booth, 1997). The variation of length was because of different backgrounds and experiences with IPL. The participants involved in education and leadership had longer interviews than those working solely as clinicians. There are two possible explanations for that: (a) they are more familiar with the complexities of QIE and IPL, and (b) clinicians, especially physicians, usually give very precise and short answers that, in many ways, mimic the way they talk in OR.

Additional materials

The opening sessions during the last three ASA Annual Meetings (2014, 2015, and 2016) have tackled answers to the questions in this research. Since the speeches were delivered as opinion-shaping contemplations of leaders—and the profession in general—I decided to treat those presentations as separate interviews. Additional reasons for that decision are the following:

• The actions of top leaders are critical to the success or failure of IPL (IoM, 2013).
• The provided messages were very clear and can be paired with the questions asked in this research, and those messages have influenced how IPL and QIE are viewed.
• The key speeches delivered during yearly meetings of professional societies and promoted on their websites suggest the direction a profession is taking.
• The videos of those sessions are available online.

The interviews I did for my research on perception of IPL among anesthesiologists (Hlede, 2015) provide information that complement well with this research; therefore, I included them in the analysis.

Special label. Knowing that it is not a standard phenomenographic procedure, I clearly labeled all the comments I received through those channels.

Recruitment

The participants were recruited through references and direct personal contact, mainly through LinkedIn. A few leaders were willing to help me recruit participants. In comparison to my previous research participant recruitment campaigns, the references had a much smaller impact. Prior to this research, I have completed three phenomenographic papers, and I did not have problems recruiting participants. Actually, while I was doing phenomenographic research on anesthesiologists’ perspectives of IPL (Hlede, 2015), I had more leaders willing to be interviewed than I was able to handle. I was not able to replicate that ease of recruitment in this case.

Updating recruitment protocol. In an attempt to improve recruitment, on July 7, 2016, I requested permission to

1. update the research participant recruitment scripts,
2. offer participants’ insight into the summary of research data (described in the scripts), and
3. reward participation in the research with $60 Visa gift cards.

As reasoning for that change, I used the following:

1. This research requires interviews with eight groups of people. These include both clinicians and education professionals from four professions—physician anesthesiologists, surgeons, nurse anesthetists, and anesthesiologist assistants—a total of eight groups of participants. The recruitment of participants from all groups can be challenging.
2. Sensitive nature of the study topic. Interprofessional politics is an important factor at this moment. As health-care reform progresses and team-based care become standard, anesthesiologists, surgeons, and nurse anesthetists have very passionate discussions about the new team structure and payment models. For example, the debate on the nursing scope of practice (what nurses can do without the supervision of physician anesthesiologists) (Nader, Massarweh, & Safety, 2016) was culminating during this research; therefore, the mere mention of IPL and QIE as elements that assume more intensive collaboration with other professions may be perceived negatively.
3. Not comfortable talking about the topic. Interprofessional learning and QIE are still emerging phenomena; therefore, those topics are not commonly discussed among potential interviewees who are not accustomed to explaining their positions on this topic (Namageyo-Funa et al., 2014).
4. Extensive health-care reform creates instability, and users are exposed to numerous surveys and interviews related to the reform; therefore, they are not interested in additional surveys/interviews.
5. Concerns about confidentiality, a common issue, are exacerbated by the perception that I am an employee of a competing professional group (ASA) with an ulterior motive.
6. Perceptions of bias may be exacerbated because of my work for the ASA.
7. No-participation policy. Wiebe, Kaczorowski, and MacKay (2012) found that more than one-third of physicians may have an office policy of not participating in research. It is fair to assume that the same policy affects all clinicians in the organization.
8. Make participation a revenue-neutral experience. U.S. clinicians are well-paid and busy professionals; however, in the case of anesthesiologists or surgeons, they start their career in their early thirties with significant student debt that, with interest, could exceed $350,000 (AAMC, 2014). Therefore, they are more likely to prefer opportunities where they will be paid for their time.
9. Reducing nonresponse bias. Nonresponse bias or the likelihood that the survey respondent group may be significantly different from the population in this research (VanGeest & Johnson, 2013) can be reduced if payment can encourage additional participants.
10. Build trust by showing respect and underline the seriousness of this research. Trust is the key in participant recruitment. This initiative can contribute to trust by respecting their time and presenting this as a serious research with a budget.

On July 18, 2016, the change was approved.

As a result, one surgeon and one anesthesiologist assistant were recruited through references. All other participants were recruited through LinkedIn or through previous contacts. The representatives of all organizations were willing to participate in the research except the AANA. That was at odds with the fact that the recruitment of nurse anesthetists through LinkedIn was the most productive.

Interview Questions

The questions below were selected to provide critical variation among participants. Those variations were categorized and organized in an outcome space (Cope, 2004):

1. Can you please reflect on your previous experience of working in multi-professional teams?
2. How would you describe IPL and QIE? For example, what is the purpose of each? Is it the same purpose?
3. What are the differences or similarities?
4. How about benefits and challenges?
5. Can technology help us address those challenges or enhance the benefits? If yes, how?
6. What, in your opinion, are the most important benefits and challenges associated with the perioperative surgical home (PSH)?
7. How is PSH related to IPL and/or QIE? Is it related?
8. Is there something QIE/IPL related that members of your profession can learn from those other professions?

The in-depth, open-ended interviews were recorded and transcribed verbatim.

Since this is a phenomenographic research, the participants were informed that there are no right or wrong answers (Daly, 2008).

References

1. Booth, S. (1997). On phenomenography, learning and teaching. Higher Education Research & Development, 16(2), 135-158.
2. Bowden, J. A. (2005). Reflections on the phenomenographic research process. In J. A. Bowden & P. Green (Eds.), Doing Developmental Phenomenography. Melbourne, Victoria: RMIT University Press.
3. Cope, C. (2004). Ensuring validity and reliability in phenomenographic research using the analytical framework of a structure of awareness. Qualitative Research Journal, 4(2), 5-18.
4. Daly, S. R. (2008). Design Across Disciplines. Purdue University. Engineering, Education, Ann Arbor, MI, U.S. Retrieved from http://books.google.hr/books?id=dSE4uvnBskMC
5. Hlede, V. (2015). Interprofessional Learning: Anesthesiologists’ Perspectives. Assignment, Doctoral Programme in E-Research and Technology Enhanced Learning. Department of Educational Research. Lancaster University.
6. IoM, Institute of Medicine. (2013). Interprofessional Education for Collaboration: Learning How to Improve Health from Interprofessional Models Across the Continuum of Education to Practice: Workshop Summary: National Academies Press.
7. Kaapu, T., & Tiainen, T. (2012). Phenomenography: Alternative Research Approach for Studying the Diversity of Users’ Understandings. Paper presented at the European Conference on Information Systems, http://aisel.aisnet.org/ecis2012/29.
8. Nader, N., Massarweh, M., & Safety, M. E. (2016). Veterans Affairs Proposed Rule for Advanced Practice Registered Nurses in the Operating Room A Step Forward or Overstepping?
9. Namageyo-Funa, A., Rimando, M., Brace, A. M., Christiana, R. W., Fowles, T. L., Davis, T. L., . . . Sealy, D.-A. (2014). Recruitment in qualitative public health research: Lessons learned during dissertation sample recruitment. The Qualitative Report, 19(4), 1-17.
10. VanGeest, J. B., & Johnson, T. P. (2013). Surveying clinicians: An introduction to the special issue. Evaluation and the Health Professions, 36(3), 275-278.
11. Wiebe, E. R., Kaczorowski, J., & MacKay, J. (2012). Why are response rates in clinician surveys declining? Canadian Family Physician, 58(4), e225-e228.
12. Yates, C., Partridge, H., & Bruce, C. (2012). Exploring information experiences through phenomenography. Library and Information Research, 36(112), 96-119.

Methodology

Introduction

In previous chapters, the purpose of the study was described and the literature reviewed. In the continuation, this chapter will present the methodology used in this study: a set of methods and tools I will use to collect and analyze data and deliver conclusions. A methodology is the activity “of choosing, reflecting upon, evaluating and justifying the methods you use” (Wellington, 2015, p. 33).

The theoretical framework used in this research is described first since the theoretical background can heavily influence the selection of methods, how methods are used, and data interpretation. I will use the theoretical framework as a lens to observe and analyze the world. As described in the literature review, theories are important contributors of all our intellectual endeavors; therefore, they should be well-defined, whether they are well-constructed and publicly evaluated concepts or personal hunches, fears, or beliefs.

The methods rooted in that theoretical framework, data collection, analysis, and interpretation practices are presented. Since this research uses data from multiple sources, data triangulation and the validation of findings are described.

The ethical issues and protection of research participants and critical elements of research are described in the last section of this chapter.

The completion of this chapter will serve as the preparation for research activity and data collection.

Theoretical Framework

Importance of ontology and epistemology. Our personal, professional, and societal perceptions and interpretations of the world around us and our interpretation of the educational process have a crucial impact on our intellectual endeavors and research; therefore, knowing them may help interpret and evaluate findings (Cleland & Durning, 2015; Guba & Lincoln, 1994). That is especially important in the context of the Continuing Professional Development (CPD) of health-care professionals in the United States, where, as it is described in the literature review, the culture of quantitative, positivist research is very strong and where qualitative, interpretative, social research methodologies are perceived with suspicion. Positivists argue that educational research and social science should follow positivist methods used in the natural science and deliver “hard” quantitative data (Wellington, 2015).

Feminist research tradition. On the other hand, health-care professions that historically have the majority of their constituents as females (e.g., nurses) are arguably more prone to feminist research (Hall & Stevens, 1991) that promotes collaboration, equality, subjectivity, emancipation, and egalitarian qualitative research (Cohen, Manion, & Morrison, 2007). It is focused on the feelings and experiences of individuals in their unique social and historical context (Holloway & Wheeler, 2013).

Stereotypes. Arguably, that bipolarization is exacerbated by historic stereotypes where the medical profession is male dominated while nursing is a typically female occupation and where relationships between doctors and nurses were typically described as dominant-subservient relationships with man-woman stereotypes (Carpenter, 1993; Gjerberg & Kjølsrød, 2001; Vasey & Mitchell, 2015).

Influence of stereotypes. Although in recent decades, we can see a significant shift from that male-female norm, cultures of professions are still heavily influenced by those stereotypes (Braun, O’Sullivan, Dusch, Antrum, & Ascher, 2015). For example, Vasey and Mitchell (2015) note that not so long ago, in a teaching hospital theater room in 2008, it was stated, “There are only two types of women in surgery—those who shouldn’t be surgeons and those who shouldn’t be women.”

Clash of medical civilizations. That internal cultural and ontological debate is exacerbated with external forces. For example, in his paper on the clash of medical civilizations, (McKenna, 2012) argues that the neoliberal movement has converted the U.S. health-care system into a highly competitive business and has contributed to the creation of a hidden medical curriculum that promotes hierarchy and focuses solely on biomechanical elements of disease while discouraging students from social critique.

Ultimately, the contexts in which this research is conducted is marked by strong ontological and epistemological conflicts; therefore, a clear definition of points this research will take will ease the understanding of how data are analyzed.

Ontology. Social constructivism is my dominant worldview. It assumes that meanings are created in social interaction. They are constructed on individual and group/organizational/professional levels and influenced by numerous historical, cultural, and technological factors.

Epistemology. The social constructivism learning theory (Curran, Fleet, & Kirby, 2010; Vygotsky, 1978) is associated with that worldview. I will use it as a lens to analyze the potential challenges of Quality Improvement Education and Interprofessional Learning (QIE/IPL).

Social constructivism assumes that groups actively construct knowledge through social interaction internally among team members and as a team interacting with the external world. In that process, they create a group culture, a collection of shared artifacts and mental models. Ultimately, according to a social constructivist view, society exists simultaneously as subjective and objective reality (Andrews, 2012).

Phenomenography. The social constructivist worldview allows me to focus “on the participants’ views of the situation being studied” (Creswell, 2009). It suggests open-ended questioning to find out what people think or do in their daily lives. A phenomenographic approach is a good tool for that task, providing insight into the more subjective side of the world and insight on how the phenomena of QIE and IPL are preceded at this moment. Since QIE/IPL is a social construct happening in a very complex environment, that insight can help us understand the status, trends, and ways we can address those trends.

Case study. On the other hand, although IPL and QIE have become quite well-known concepts, most interviewees have not had a chance to practice them. They have not experienced them as something real and objective. To better understand the objective aspects of the phenomenon, the case study focused on how their professions and their professional associations are tackling that issue I used.

Methodology of Choice

The methodology of choice is a qualitative, interpretive, multiple-case case study (Yin, 2003) that encompasses phenomenographic analysis. Activity theory is used as a lens to analyze interrelations among multiple elements in this complex system.

Nesting Methods

Figure 1. Nested and interconnected elements of the research designed to address the complexity of health-care learning

Roles. Phenomenography will help me map the territory by analyzing how people perceive that phenomenon. The case study will help analyze the most important elements of the system and craft “the big picture.” Knowing that the system is extremely complex and very dynamic, with multiple stakeholders and multiple contradictions, it is essential to select a toolset to analyze relationships and processes in such a system. Complex metatheory and activity theory are selected as a match to that task. Complex metatheory will serve as a lamp that exposes multiple interconnected elements of this dynamic system, including interactions among different methods and methodologies (Bleakley & Cleland, 2015). Activity theory will, as a lens, help us analyze interactions among different elements of the system.

The image on the right illustrates how methods and theories are nested in this research.

Research design and learning questions. The interaction among those elements of research design will contribute to all three questions; however, it is fair to say that specific elements of research frameworks are associated with specific research questions. Those connections are the following:

• Phenomenography will mainly address question 1: How are QIE/IPL and technologies and policies that shape QIE/IPL perceived by four groups involved in perioperative teams: anesthesiologists, surgeons, anesthesiologist assistants, and nurse anesthetists?
• The case study has the dominant role to address question 2: How is technology-enhanced collaborative learning used and perceived in the context of QIE/IPL and perioperative teams?
• Activity and complexity theories provide a general context for the whole study and are essential tools for the last research question: How are professional cultures and contextual factors related to collaborative learning influencing the implementation of technology-enhanced QIE/IPL?

Case Study

Multiple-case design is the approach of choice (Yin, 2003). QIE/IPL-related practices and learning technology that can support QIE/IPL used by each profession are analyzed as independent cases. The four cases are

• the American Society of Anesthesiologists (ASA),
• the American Association of Nurse Anesthetists (AANA),
• the American College of Surgeons (ACS), and
• the American Academy of Physician Assistants (AAPA).

An alternative solution was to use a single case with embedded multiple units of analysis. That approach would be appropriate if we had collaboration and shared programs among two or more of the specialties in place. In that situation, the case would be shared QIE/IPL-related practices and learning technology that can support QIE/IPL of all professions together. Activities specific to each profession would be embedded units of analysis.

Since now I am not aware of a formal interprofessional collaboration on QIE/IPL, the QIE/IPL activities in each specialty were analyzed as separate entities.

The case study data sources were interviews with staff and physician members and a professional association’s website and published literature. Two interviews (nonphenomenographic) were scheduled with representatives of the three involved professions. The representatives of the American Association of Nurse Anesthetists were not able to participate. Phenomenographic interviews also served as a source of data over and above standard phenomenographic research.

Phenomenographic Analysis

Phenomenographic analysis focused on how CPD professionals, clinicians (anesthesiologists, nurse anesthetists, surgeons, and anesthesiologist assistants), and their respective leaders perceive QIE/IPL; and technology that supports those practices is the central part of the case study. Phenomenography appears to be the optimal method for this approach because although at this point QIE/IPL is in its early stage, it is a very hot topic, and human perceptions are the dominant factor.

The additional reasons are the following:

1. Attempts to implement QIE/IPL in the U.S. health-care system have a long but troubling history, and drivers influencing the implementation of QIE/IPL create a very complex picture. The phenomenographic approach is recognized as a good tool to analyze changes in such a complex system (Bunniss & Kelly, 2010; Stenfors‐Hayes, Hult, & Dahlgren, 2013).
2. Understanding the perceptions of groups involved in the learning and teaching process can enable us to address current and emerging challenges in that dynamic environment (Richardson, 2005).
3. QIE/IPL is ultimately a social endeavor (Hean, Craddock, & O’Halloran, 2009).

Phenomenography and medical education. During the past two decades, phenomenography proved to be very useful in medical education (Stenfors‐Hayes et al., 2013). It provides insight into the different ways that people perceive phenomena in the world around them and how those perceptions relate one to another (Marton, 1981; Marton & Booth, 1997); therefore, it can serve as a lens to analyze a specific research question and direct how research is carried out. In a medical setting, phenomenographic research is valuable for topics like clinical practice, communication, health-care learning, and especially the processes and outcomes of learning (Larsson & Holmström, 2007; Richardson, 1999). According to Stenfors‐Hayes et al. (2013), phenomenography can serve as a link among three important elements this research is tackling—research, organizational change, and educational development. That feature can be especially valuable in the context where, as the Macy (2013) expert team concluded, huge changes affecting the U.S. medical system are not linked effectively with changes affecting the CPD of health-care professionals in the United States.

Alternatives. Phenomenography was chosen over phenomenology because QIE/IPL is, in this context, an emerging concept; therefore, we can expect numerous, sometimes contradicting ways in which QIE/IPL is perceived (Larsson & Holmström, 2007). Furthermore, the research is interested in the differences of how the phenomena are perceived among four different professions, and phenomenography is an optimal tool for that task.

Two additional approaches that I considered but did not include as the first choice are action research and realist evaluation. As described below, I considered those methods as potential augmentation of the research framework, and they may help me address possible changes, for example, if the leadership of the ASA decided to start an interprofessional program during this research. While not used in this paper, the methodologies below can be very beneficial to the studies that may follow.

The action research method is a collaborative study focused on solving a problem through a cyclical and reflective process built around the following:

• Research and planning>>action>>collecting and analyzing evidence>>reflecting>>research and planning

Through those cycles, the researcher actively works with the participants to prepare and implement changes (Boet, Sharma, Goldman, & Reeves, 2012; Coghlan & Brannick, 2014). Focusing on QIE/IPL as an emerging concept, which the ASA has considered implementing, suggests that action research may be a method of choice.

On the other hand, the collaboration between the participants and the researcher is a potential source of political and ethical challenges affecting researchers and participants (Williamson & Prosser, 2002). Since the changes of CPD are described primarily as a political process (Balmer, 2013; Cervero & Moore Jr., 2011), using action research as a dominant methodology would be too risky an approach. It can affect the researcher and the participants, and political forces may stop what is needed for action research.

The realist method is a theory-driven approach used for the evaluation of complex social intervention in the field of health care (Marchal, van Belle, van Olmen, Hoerée, & Kegels, 2012). Some research asks simplistic questions like “Does IPL work?” The realist method attempts to answer if something works under specific social circumstances. It asks how and why something works. It attempts to dig deeper and find what works for whom, under what circumstances, and to what extent. It tries to determine how to improve or reduce the impact of what is being studied (Wong, Greenhalgh, Westhorp, & Pawson, 2012). The realist method may be useful for this research since the implementation of QIE/IPL is a very complex process influenced by numerous societal factors and affecting a variety of different stakeholders. On the other hand, per Wong et al., the realist method will be especially beneficial if we have the new intervention and a rich source of qualitative data in place. Hopefully, in a few years, we will have a wealth of data on QIE/IPL, but that is not the case now.

Complexity and Activity Theory

It is complex. For quite a long time, we have been rediscovering that the majority of learning for health-care professionals happens in the work environment and that it is socially constructed (Engeström, 2001; Fenwick, 2014). That is especially true for QIE and IPL; however, we have been experiencing challenges implementing learning designed for that context. Therefore, very often, our QIE and IPL attempts would result in retreat to the comfort zone of the traditional content-focused learning modalities. For example, the Accreditation Council for Continuing Medical Education annual report revealed that in 2015, only 0.7% of accredited learning activities were performance/quality improvement activities (ACCME, 2016). Arguably, the lack of tools that can help us analyze how health-care learning systems work is the reason why we are prone to forget the importance of workforce learning until the next research rediscovers that fact again.

Complexity and activity theories can help us address that challenge by providing insight on how learning embedded in a complex system works and how various factors of such a system interact.

Activity Theory

Lens to analyze complexity. Activity theory (AT, sometimes called cultural historical activity theory or CHAT) is the third element of the research framework. AT is a descriptive sociopsychological framework taking into account all elements of a complex activity/work system (Johnston & Dornan, 2015). It explains divisions between the material and the mental, history and present, theory and praxis, and—for interprofessional education, especially troubling issue—the individual and the group (Stetsenko, Arievitch, & Blunden, 2014). Examples of such an activity system may be teams like a perioperative surgical home team or organizations such as the ASA. AT can help us analyze interactions among professionals in the system—in our case, that can be doctors, nurses, and patients—and their learning shaped by interpersonal, cultural, economic, political, and historical aspects (Foot, 2014); therefore, activity theory can serve as a lens to analyze collective, culturally mediated, and object-oriented human activities in such a complex and dynamic system (Barab, Evans, & Baek, 2004; Jonassen & Rohrer-Murphy, 1999).

Activity theory is probably the most complicated, and for some readers, it can be the most abstract tool in my research toolset; therefore, I will describe it in more detail.

Under the umbrella of complexity. With communities of practices and actor-network theory, activity theory is nested under the umbrella of complexity, a metamethodology described below (Bleakley & Cleland, 2015; Jonassen & Land, 2012).

Ontology. Activity theory, same as phenomenography, rejects positivist approach and Cartesian dualism. Cartesian dualism is the idea that our body and our mind are two separate entities and that our mind can objectively analyze everything happening in the “real world” without being affected by real-world activities (Baker & Morris, 2005). AT is rooted in the idea that our perception of the world is interwoven with our physical existence in it; therefore, AT provides a map to understand the main drivers that may influence our interaction with and perception of the world (Roth & Lee, 2007), a map to help us understand processes, individuals, and teams used to manage change and learning in daily (clinical) practice (Engeström, 2001).

History. Activity theory has had a dynamic and troubling evolution. It is rooted in Vygotsky’s sociocultural psychology (Verenikina, 2010) and Marxist’s praxis-focused dialectical materialism (DeVane & Squire, 2012). It was crafted during the 1920s and the early 1930s in Soviet Russia. Dialectical materialism assumes that progress is built through a clash between opposites (Spirkin, 1983). Sociocultural psychology/theory explains that teaching and learning (and QI projects) are embedded in the cultural and historical context of learners’ daily practices and intimately connected with the way learners interact with peers, teachers, and society.

Political context – complex network society. The Western opinion of early Soviet Russia is usually based on recollections of Cold War and the relatively small economical, intellectual, and cultural impact socialistic Russia had on the world. Early Soviet Russia, located between the dictatorship of the czar and the dictatorship of the Communist Party led by Lenin, may give a different picture. During the 1920s, Russia seemed to be a place of significant intellectual production (Johnston & Dornan, 2015). The country was going through massive and complex reforms: the imperial political structures crashed and they were replaced informal personal networks (Easter, 1996); the belief that the new system will be better that the old monarchy was crushed by failed reforms, subsequent famines that took many millions of lives (Brooks & Gardner, 2004), and the rising, cruel dictatorship of the new government. Arguably, the country was well networked and on the edge of chaos; and that, as explained under complexity theory, created a great context for innovation. One important innovation initiated during that time is AT.

Suppression in SSSR. During early postrevolutionary Soviet Russia, the first generation of activity theory was created by Vygotsky and collaborators. Because of the Cold War and the suppression of dialectical materialist psychology in SSSR (Bickley, 1977), AT was not well known to the West until the 1980s (Engeström, Miettinen, & Punamäki, 1999).

The development of activity theory went through three generations. Each generation created a more complex extension of the previous one. Each generation has a bigger, more inclusive, and more complex unit of analysis; therefore, each generation is worth mentioning for a better understanding of AT.

The first generation of activity theory is focused on the interaction between individuals and the world. That interaction is never direct. We need psychological tools to communicate our thoughts and/or technical tools to physically communicate with the world. The most common psychological tool is language. Technical tools are physical artifacts we use in our daily life. The pen, the fork, and the scalpel are just a few examples. We use those tools to achieve a specific objective. Therefore, the map of the first generation of AT looks like this (Engeström et al., 1999):

Image 2: First generation of AT

The second generation of AT extends a notion of context by adding rules, division or labor, and community to the picture. Those are integral elements of each activity system, and they may have a crucial impact on how we interact with the world. The second generation of the AT map is presented in the image below. The lines with arrowheads symbolize connections and contradictions, which make the system dynamic and create a fuel for progress.

Image 3. The second generation of AT

The second generation of AT can be used, for example, to analyze how an operation room team interacts in the attempt to achieve, for example, object: patient safety. The inherited limitation in that analysis may be the differences among groups in that team (e.g., surgery, anesthesia, management); each one is with their own unique culture, and rules and roles are not recognized. That limitation is addressed in the third-generation AT.

The third generation of activity theory is specifically interesting for this research because it is focused on how different activity systems interact (Engeström, 2001). Each profession (anesthesiologists, nurse anesthetists, surgeons, etc.) and patient or the public can be analyzed as a separate activity system. The third generation of activity theory can help us understand how those systems interact during work or QIE/IPL activities.

AT and health care. Activity theory is often used to analyze complex interactions among and inside health-care activity systems (Bardram & Doryab, 2011; de Feijter, de Grave, Dornan, Koopmans, & Scherpbier, 2011; Engestrom, 2000; Skipper, Musaeus, & Nøhr, 2016). That link between activity theory and health care was noticeable since the early beginning. For example, the paper introducing the third generation of activity theory (Engeström, 2001) uses interaction among health-care activity systems (hospital, patient’s family) as the main example.

An example of the third-generation AT diagram is presented below:

Figure. Two interacting activity systems are the minimal model for the third generation of activity theory (Source: Engeström, 2001). Each profession can be analyzed as a separate activity system. The outcomes (Object₂) of each profession interact, creating the outcome of collaboration—Object₃.

In our perioperative model, the interaction between the patient’s anesthesiology and surgery activity systems may look like this:

Figure. The operating room as an activity system for acute patient care (Adaptation of: Engestrom, 2000; Kerosuo, Kajamaa, & Engeström, 2010)

AT is a system-based design. Instead of being a predictive theory, activity theory can serve better as metatheory or a framework we can use to understand cultural and historical aspects of relations in complex social systems (Iivari & Linger, 1999). Since it is focused on activity systems, a concept of collective and socially and object-mediated human activity, AT can bridge the gap between individual actors and very complex, socially constructed, and technology-enhanced reality. For example, AT has proven to be a powerful tool for researching how people adapt and learn in the workplace (Engeström, 2001; Engeström, Virkkunen, Helle, Pihlaja, & Poikela, 1996).

Expansive learning. Finally, the last important element of AT is expansive learning. Expansive learning theory was created as an application of activity theory to showcase how workforce learning and innovation arise. AT showcases multiple voices, multiple drivers, and multiple contradictions among them. When those voices and contradictions merge and create something new, innovatively, that is called expansive learning (Engeström, 1987). In the other words, expansive learning is a “constant comparative process or adaptation” (Johnston & Dornan, 2015).
Challenges and opportunities of expansive learning. While expansive learning as a complex model may be hard to grasp and may not be the best solution for industrial, standardized learning products delivery (Hean et al., 2009), it serves as a promising model to explain and improve learning in complex systems such as health care. We are well aware that in an increasingly complex world, our attempts to have complete control or chunk our world into smaller, isolated, “manageable” entities play a central cause of numerous failures (Dorner, Nixon, & Rosen, 1990).

Change laboratory. To address the challenges of learning in complex systems, Virkkunen and Newnham (2013) have created The Change Laboratory: A Tool for Collaborative Development of Work and Education. The Change Laboratory method is built on AT and the theory of expansive learning. In this model, the outcomes are developed by participants while they create expansive answers to contradictions (read: QI challenges) in their activity system (read: local context). That is significantly different from the traditional learning development approach, whereby teachers or instructional designers create a learning activity for learning objectives they have selected and activities happen in time and space separated from daily practice.

Complexity Theory

The big, final piece of methodology is complexity theory. It serves as a metatheory that provides insight on how multiple dynamic elements of a complex system interact.

About complex health-care education, the very formalized word of surgery and perioperative medicine and its cousin, the world of medical education is complex (Bleakley & Cleland, 2015; Plsek & Wilson, 2001). It is created as a dynamic network of multiple teams—anesthetic, surgical, laboratory, medical technology, radiology, pathology, management, and physiotherapy—shaped by five dominant cultures. In addition to management, education, and research, the three cultures described by Bleakley and Cleland, the cultures of health-care professions and QI play significant roles. An addition to that very dynamic complex is the empowered patients with their beliefs, knowledge (or lack of knowledge), and expectations (Wald, Dube, & Anthony, 2007). Therefore, to make a positive and sustainable change in that system, we must understand how complexity works.

Complexity has two important sides. It is harder to analyze it, but it can be very beneficial for innovation.

It is complex. From one side, analyzing and managing complex systems is much harder than analyzing simple or complicated systems. That is why when we have a choice between a complex system and a simple or complicated system, our preference will go toward a simpler one (image below). Senge (2006, p. 73) explains it: “The reality is made of circles, but we see straight lines.” In other words, reality is complex, but we see only a simple and complicated process. Very often we will deconstruct a complex system on a set of simple processes and attempt to analyze those processes as separate entities. While on short run, those attempts may provide valuable information, at the end we may understand elements of the system, but we do not understand the system. Fortunately, as described in this chapter, we have tools to analyze complex systems; therefore, we can use Prochaska’s words: “The days of searching for simple solutions to complex problems should be behind us” (Prochaska & DiClemente, 1986, p. 4).

Human preferences. Illustration by Wiley Miller (used with permission)

Complexity and innovation. On the other hand, complexity provides a framework for innovation. Complex systems, especially highly complex systems on the edge of chaos, have the highest potential for creativity. Looking through the lens of activity theory, dynamic complex systems have the highest amount of contradictions, which drive change and innovation. Kauffman (1996) convincingly argues that the edge of chaos, a space between order and complete randomness, is a context where serendipity has the highest potential. The same context is forcing us to critically analyze our actions and impact on the world around us, increasing our potential for learning and discovery. That explains why some of the most valuable contributions Russia made to the world’s science and culture (especially avant-garde) happened during 1920 (Von Hagen, 1996).

Treating complex as complicated. On the other hand, we usually experience challenges in that innovative side of complexity. Glouberman and Zimmerman (2002) use examples of Brazil, France, and Canada health-care systems to point out that health-care systems are complex; therefore, emerging health-care challenges should be treated as complex issues. Unfortunately, most health-care fixes perceive health-care systems as merely complicated systems. Thus, those complicated interventions serve primarily as a waste of time, opportunity, and resources and contribute to the deterioration of health care.

A vivid example and scale of such a misconception was given by Mr. Donald Trump on February 24, 2017, when he noted, “Nobody knew that health care could be so complicated” (Howell, 2017). That showcases that after seven years of intensive debate over U.S. health care, part of policymakers and the person who acts as the president of the United States perceive health care merely as a complicated system. Consecutive to that misconception, the American Health Care Act of 2017, a U.S. Congress bill aimed to replace the Patient Protection and Affordable Care Act (ACA) known as Obamacare, failed to deliver on some of the main promises made by the administration. Therefore, the U.S. Congressional Budget Office estimated that instead of “insurance for everybody” (Costa & Goldstein, 2017), the bill promises twenty-four million more uninsured Americans by 2016 (CBO, 2017); instead of lower health-care costs, insurance can rise significantly, especially for older Americans (Sarlin, 2017). As result, the law did not pass in its original form.

The drive back to the simple zone. The image below illustrates that drive from complexity to a “simple, evidence-based zone” (O’Riordan et al., 2011). Very often, we end up in the evidence-based zone simply by neglecting complexity and ignoring everything that is not certain or generally accepted. In a stage of high uncertainty like the U.S. health-care system is experiencing recently, the drive to go to a safe zone can be much stronger, blocking the possibility to make the needed change (Engel, 1997).

Figure. Stacey matrix (adopted from O’Riordan et al. (2011)

Fortunately, the forces pushing in the other direction toward complexity are becoming stronger and better supported by science.

The evolution of dominant epistemologies has contributed to the increased awareness of learning complexities. Traditional learning theories like behaviorism and cognitivism were focused on the individual student, usually perceived as a completely autonomous entity separated from the rest of the world and her possibility to “absorb” knowledge (Siemens, 2005). Learning was perceived as a simple, longitudinal, and content transmission (Jonassen & Land, 2012). During the last four decades, our perception of learning has transformed. Now dominant constructivist and sociocultural learning theories perceive learning as an active, social process where, instead of knowledge reproduction, students collaborate on knowledge production, helping one another access and evaluate distributed knowledge. This is a significantly more complex process that involves socialization, identity formation (Cruess, Cruess, & Steinert, 2015), and (for CME/CPD context) new course delivery formats (Curran et al., 2010).

Personal and professional epistemologies are an important element of the complexity mosaic. They are processes in which individuals and groups do or do not construct knowledge from learning experiences. Those epistemologies are shaped by learners’ ambitions, interests, capacities, identities, and social structures (Billett, 2009). Because of significant variations of personal and group epistemologies, the impact on a learning event, as a society-constructed activity, can significantly vary.

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Literature review: Theories behind IPL and QIE

There are a number of theories that can be used to define and analyze IPL (Hean, Craddock, Hammick, & Hammick, 2012) and QIE. The approach to theory in papers on QIE/IPL has evolved from not using any theory at all, to using multiple theories to explain the concept. However, that progression has been very gradual. Even today, significant numbers of CME/CPD papers do not reference theory (Curtis A. Olson, 2013). QIE/IPL papers, as a subset of that group, follow the same trend.

As described below, in most cases, a specific theory can describe just part of the process. Therefore we have to combine theories. Relevant theories can be categorized primarily as theories that explain QIE/IPL educational process, and theories that describe interprofessional QI practices. A secondary level of classification, mainly based on historical divisions, are theories related to QIE and theories related to IPL.

QI theory. The value and function of theory in healthcare quality improvement has been seriously neglected (Davidoff, Dixon-Woods, Leviton, & Michie, 2015). At the same time, factors influencing sustainability of QI interventions have been poorly understood (Hovlid, Bukve, Haug, Aslaksen, & von Plessen, 2012). That is a huge issue – very often causing QI interventions to fail. Following such QI intervention, returning to old underperforming work practices is a significant waste of resources and, in the long run, can fuel resistance to future/better QI initiatives. Therefore, more vigorous and better-informed use of theory is essential to strengthen QIE/IPL programs, ensure vaid assessment of their impact, and promote their sustainability and generalizability of outcomes (Davies, Walker, & Grimshaw, 2010).

Role of theory. Unfortunately, theory is usually perceived as something mystical and impractical; something even quality professionals do not want deal with. That contradicts practice needs. Theory or “the reasons why things are happening” is intimately integrated into almost all of our activities. Theories may be formal or informal, public and shared, or private. Yet theories drive our decisions and shape our impact (Hean et al., 2012). Whether the theory says: “This is how it has been always done – and therefore we should not change it,” whether it is an informal experience-based theory used by a small team, or it is an official, publicly developed theory, it will have an impact on our activities (Tilly, 2006). The question is not: Are we using theory? We know we are. We should ask: Are we aware of that theory, how good is it, and is it the right theory?

Practice shows that when we lose sight of the importance of theory, bad things happen. A weak hypothesis or even just a hunch, biased and limited in scope (Kahneman, 2011), can be used to drive our actions, often with negative results. Lack of a theoretical background is a common reason why QI and patient-safety interventions in healthcare often result in limited positive changes or no relevant changes at all (Shojania & Grimshaw, 2005). If the intervention proves to be successful, but lacks a sound theoretical basis, it is usually hard to make it permanent and generalize it in other contexts (Dixon-Woods, Leslie, Tarrant, & Bion, 2013).

The literature provides a variety of theories that may foster sustainable QI change. That variety ranges from a big set of learning theories and change agent theories, to organizational change and economic theories. Shojania, McDonald, Wachter, and Owens (2004) argue that it may be challenging to develop interventions based only on one of those theories. Effective QI strategy can be developed more easily when theory and implementation are tested simultaneously. As a manual to help users navigate through that process, Kaplan, Provost, Froehle, and Margolis (2012) developed Model for Understanding Success in Quality (MUSIQ). The model describes 25 contextual factors that may influence success of QI projects. It serves as a checklist of elements that should be included in a QI theoretical plan.

IPL. In the early days of IPL research, a significant number of papers were very pragmatic and didn’t describe a theoretical background. Many later papers grounded IPL research in a single theory – usually related to a specific school of thought and academic discipline (Barr, 2013). Today, a growing number of papers build a sound, flexible and inclusive IPL framework by combining multiple theories and practices. As a result, Hean, Craddock, and O’Halloran (2009) argue that a large number of theories currently used to describe IPL have created a hard-to-navigate quantifier.

Social theories (social constructivism, social capital) (Hean et al., 2012), adult learning (P. G. Clark, 2006), identity theories, situated learning (Ranmuthugala et al., 2011; Wenger, 1998, 1999) and networked learning (Dev & Heinrichs, 2008) are the main theories relevant to QIE/IPL learning processes. On the other hand, the theories most relevant to QIE/IPL context are sociology of professions, organizational theory and activity theory. They present a compelling example of how different theories complement each other. For example, Larson (1979) argues that professional guilds are actively engaged in monopolizing knowledge in specific areas, to ensure cognitive exclusivity. That may explain why, despite learning organization (Roberts & Thomson, 1994; Senge, 2006) being a very popular theory concept (Barr, 2013), it is especially hard to achieve it among different professional organizations and patients. Fortunately, activity theory allows us to analyze organizations as “distributed, decentered and emergent systems of knowledge” (Blackler, Crump, & McDonald, 2000, p. 278); it provides insight into connections between activities and context and reasoning behind complex social activities.

The connected, networked nature of modern life and work is at the heart of learning as a social activity, and knowledge as a social construct. (Hean et al., 2009) Therefore, to fully understand learning, we have to analyze curricula through a social theoretical lens. Only through that lens will we be able to comprehend how organizations, professional societies, professional regulations, education providers and communities of learners shape the knowledge development process.

Social capital theories are focused on the benefits individuals and society can achieve by being part of and nurturing a social network. They suggest the equilibrium concept (Boix & Posner, 1998). Social capital will increase through repeated cooperation and collaboration. In return, strong social capital will boost social collaboration and the happiness of individuals. Research of Leung, Kier, Fung, Fung, and Sproule (2013) showed that social capital is one of the major cornerstones of happiness. In the healthcare field, social capital is popular due to the known relationship between social capital (strong social network) and health benefits. Ultimately, social capital, happiness and collaborative behaviors can significantly improve tacit and explicit knowledge-sharing among employees – creating a basis for a productive learning organization (Hau, Kim, Lee, & Kim, 2013). Therefore social capital theory can be used to describe benefits of interprofessional, networked learning, and guide us to maximize benefits from that learning model.

Adult learning theories are often described as a cornerstone of successful QIE/IPL. They provide a toolset or learning modalities that motivate students as individuals and groups to activate existing knowledge and use it as a platform to develop new knowledge. In that context they can be viewed as an extension of constructivist learning theories.

Networked learning theory uses connections between students, students and teachers, and between student resources and tools to create a framework where students (working professionals) as individuals and groups have access to all elements needed for successful continuous professional development. It created a framework that connects CME/CPD providers and the professional learning community (Jackson & Temperley, 2007). Whether they need access to content, expertise, QI tools or peer moral support, students will be helped by networked learning principles. With that, students can combine real world context and highly integrative learning activites to address complex situated problems (G. Campbell, 2016).

Community of practice, as situated learning theory, can explain many benefits professional societies provide to their members (Webster-Wright, 2009). The society and profession acts as a community of practice; a community of professionals that jointly work together to improve practice in a specific domain (health, nursing, surgery) (Simons & Ruijters, 2004). There is potential to further support that community with social media .

Each mentioned theory deserves detailed description, which is out of scope of this literature review.

What we can notice from the aforementioned brief descriptions is that there is lot of overlapping between theories and that theories often complement each other (Hean et al., 2012).  For example, networked learning will benefit if social capital is strong, and social capital can be further enhanced with properly designed networked activities. Adult learning in the QIE/IPL context will also be enhanced if social capital is strong and the proper networked practices are in place. Ultimately, community of practice can benefit from all aforementioned theories – and create a framework where they can be better implemented.

Activity theory, being a macro theory, will be discussed last as a separate example. A macro theory can be used as a descriptive framework taking into account all elements of a complex healthcare activity system. Examples of an activity system include a perioperative surgical home team or an organization such as the ASA. Therefore, activity theory can serve as a lens to analyze human activities in such a complex and dynamic system. The third generation of activity theory is specifically interesting for this research because it is focused on how different activity systems interact (Engeström, 2001). Each profession (anesthesiologists, nurse anesthetists, surgeons, etc.) and patients or the public can be analyzed as a separate activity system. The third generation of activity theory can help us understand how those systems interact during preparation for implementation of QIE/IPL activities. A small detail that confirms the suitability of activity theory is that in the paper introducing the third generation of activity theory, (Engeström, 2001) uses interaction among healthcare activity systems (hospital, patient’s family) as the main examples.

Figure 8. Two interacting activity systems are the minimal model for the third generation of activity theory (Source: Engeström, 2001). Each profession can be analyzed as a separate activity system. Outcomes (Object₂) of each profession interact creating outcome of collaboration – Object₃.

References

• Barr, H. (2013). Toward a theoretical framework for interprofessional education. Journal of interprofessional care, 27(1), 4-9. doi:10.3109/13561820.2012.698328
• Blackler, F., Crump, N., & McDonald, S. (2000). Organizing processes in complex activity networks. Organization, 7(2), 277-300.
• Boix, C., & Posner, D. N. (1998). Social capital: Explaining its origins and effects on government performance. British journal of political science, 28(04), 686-693.
• Campbell, G. (2016). Networked learning as experiential learning. Educause Review, Vol. 51 No., 50(1, January 11), 1.
• Clark, P. G. (2006). What would a theory of interprofessional education look like? Some suggestions for developing a theoretical framework for teamwork training 1. Journal of interprofessional care, 20(6), 577-589.
• Davidoff, F., Dixon-Woods, M., Leviton, L., & Michie, S. (2015). Demystifying theory and its use in improvement. BMJ quality & safety, bmjqs-2014-003627.
• Davies, P., Walker, A. E., & Grimshaw, J. M. (2010). A systematic review of the use of theory in the design of guideline dissemination and implementation strategies and interpretation of the results of rigorous evaluations. Implement Sci, 5(14), 5908-5905.
• Dev, P., & Heinrichs, W. L. (2008). Learning medicine through collaboration and action: collaborative, experiential, networked learning environments. Virtual reality, 12(4), 215-234.
• Dixon-Woods, M., Leslie, M., Tarrant, C., & Bion, J. (2013). Explaining Matching Michigan: an ethnographic study of a patient safety program. Implementation Science : IS, 8, 70-70. doi:10.1186/1748-5908-8-70
• Engeström, Y. (2001). Expansive learning at work: Toward an activity theoretical reconceptualization. Journal of education and work, 14(1), 133-156.
• Hau, Y. S., Kim, B., Lee, H., & Kim, Y.-G. (2013). The effects of individual motivations and social capital on employees’ tacit and explicit knowledge sharing intentions. International Journal of Information Management, 33(2), 356-366.
• Hean, S., Craddock, D., Hammick, M., & Hammick, M. (2012). Theoretical insights into interprofessional education: AMEE Guide No. 62. Medical teacher, 34(2), e78-e101.
• Hean, S., Craddock, D., & O’Halloran, C. (2009). Learning theories and interprofessional education: A user’s guide. Learning in Health and Social Care, 8(4), 250-262.
• Hovlid, E., Bukve, O., Haug, K., Aslaksen, A. B., & von Plessen, C. (2012). Sustainability of healthcare improvement: what can we learn from learning theory? BMC Health Services Research, 12(1), 235.
• Jackson, D., & Temperley, J. (2007). From professional learning community to networked learning community. In K. S. L. Louise Stoll (Ed.), Professional learning communities: Divergence, depth and dilemmas (pp. 45-62). UK: McGraw-Hill Education.
• Kahneman, D. (2011). Thinking, fast and slow. Farrar, Sraus and Giroux, 18 West  18th Street, New York, USA.: Macmillan.
• Kaplan, H. C., Provost, L. P., Froehle, C. M., & Margolis, P. A. (2012). The Model for Understanding Success in Quality (MUSIQ): building a theory of context in healthcare quality improvement. BMJ quality & safety, 21(1), 13-20.
• Larson, M. S. (1979). The rise of professionalism: A sociological analysis (Vol. 233). USA: Univ. of California Press.
• Leung, A., Kier, C., Fung, T., Fung, L., & Sproule, R. (2013). Searching for happiness: The importance of social capital The exploration of happiness (pp. 247-267): Springer.
• Olson, C. A. (2013). Reflections on Using Theory in Research on Continuing Education in the Health Professions. Journal of Continuing Education in the Health Professions, 33(3), 151-152. doi:10.1002/chp.21178
• Ranmuthugala, G., Plumb, J., Cunningham, F., Georgiou, A., Westbrook, J., & Braithwaite, J. (2011). How and why are communities of practice established in the healthcare sector? A systematic review of the literature. BMC Health Services Research, 11(1), 273.
• Roberts, C., & Thomson, S. B. (1994). Our Quality Program Isn’t Working. In P. M. Senge (Ed.), The Fifth Discipline Fieldbook: Strategies and Tools for Building a Learning Organization. USA: Doubleday.
• Senge, P. M. (2006). The Fifth Discipline: The Art & Practice of the Learning Organization. USA: Doubleday.
• Shojania, K. G., & Grimshaw, J. M. (2005). Evidence-based quality improvement: The state of the science. Health Affairs, 24(1), 138-150.
• Shojania, K. G., McDonald, K. M., Wachter, R. M., & Owens, D. K. (2004). Toward a Theoretic Basis for Quality Improvement Interventions. Retrieved from
• Simons, P. R.-J., & Ruijters, M. C. (2004). Learning professionals: towards an integrated model Professional learning: Gaps and transitions on the way from novice to expert (pp. 207-229): Springer.
• Tilly, C. (2006). Why?:[what happens when people give reasons… and why]. Princeton, New Jersey, US: Princeton University Press.
• Webster-Wright, A. (2009). Reframing professional development through understanding authentic professional learning. Review of Educational Research, 79(2), 702-739.
• Wenger, E. (1998). Communities of Practice: Learning, Meaning, and Identity. Cambridge: Cambridge University Press.
• Wenger, E. (1999). Learning as social participation. Knowledge Management Review, 1(6), 30-33. Retrieved from https://modules.lancs.ac.uk/pluginfile.php/210525/mod_page/content/37/W3_Wenger%281999%29.pdf

Thesis index

The draft thesis content will be shared as series of blog posts. Therefore, you will be able to find posts by browsing through the blog or checking this index page.

Dictionary

Literature Review

1. Introduction
2. Key points
3. Context: the U.S. healthcare system and healthcare teams
4. CME/CPD of anesthesia team in the U.S.
5. Quality improvement education and interprofessional learning
6. Theories behind IPL an QIE
7. Conclusion

Methodology

1. Introduction 
2. Theoretical Framework 
3. Methodology of Choice
   1. Nesting Methods
4. Case Study
5. Phenomenographic Analysis
6. Complexity and Activity Theory
   1. Activity Theory
   2. Complexity Theory
7. Interviews
   1. Sample Size
   2. Recruitment
   3. Interview Questions
8. Data Analysis
   1. Tools Used for Data Analysis
      1. NVivo
9. Ethics and Risk
10. Limitations and Weaknesses of Research Design

Table of contents will contain the following elements:

Introduction

Interprofessional learning (IPL) and Quality Improvement Education (QIE) are increasingly recognized as important tools to improve performance of U.S. healthcare teams and address the changes the U.S. healthcare system and the Continuing Professional Development (CPD) system are undergoing (Hager, Russell, Fletcher, & Macy Jr, 2008; IoM, 2010; Macy, 2013; WHO, 2010). The need for change is clear: Healthcare is increasingly delivered by teams, yet healthcare teams are not trained as teams or familiar with team-based quality improvement (QI) methodology – and therefore their ability to address the need for quality improvement is limited.

Figure 1. Rising interest in IPL. Source: CIHC (2008)

To address that gap, the Institute of Medicine concluded that professional development of the healthcare workforce and healthcare system should be analyzed together. To improve our healthcare outcomes, it is important to better align the transformation of healthcare workforce CPD with the massive reform of the U.S. healthcare system, and ensure widespread adoption of IPL (IoM, 2015).

This research aims to contribute to that goal by finding how QIE and IPL are perceived by four professions participating in the perioperative team (physician anesthesiologists, surgeons, nurse anesthetists and anesthesiologist assistants), and which QIE- and IPL-related technologies and practices each profession involved in the research have available or plan to implement soon. Results of this research will help healthcare leaders better plan implementation of technology-enhanced QIE and IPL in the context of the perioperative team. In addition, although the perioperative context is specific, a significant part of the findings will be applicable to other interprofessional healthcare teams.
I believe that the research will show that technology-enhanced QIE and IPL are in many ways related to networked learning, and that their successful implementation will require creation of networked learning communities.

Dr. McMahon encourages innovation and experimentation in CME

We want to do everything we can to encourage innovation and experimentation in CME, so that educators are free to respond nimbly to their learners’ changing needs while staying true to core principles for educational excellence and independence. We thank accredited CME providers for their participation in this process and look forward to their feedback on our proposal and to our continued work together to drive quality in postgraduate medical education and improve care for the patients and communities we all serve,” said Graham McMahon, MD, MMSc, President and CEO, ACCME.

Find more: http://www.accme.org/news-publications/news/ama-and-accme-announce-call-comment-proposal-align-credit-and-accreditation

Methodology

The social constructivist worldview allows me to focus “on the participants’ views of the situation being studied” Creswell (2009). It suggests open-ended questioning to find what people think or do in their daily lives. A phenomenographic approach is a good tool for that task – providing insight into the more subjective side of the world.

On the other hand, although IPL and QIE have become quite well-known concepts, most interviewees haven’t had a chance to practice it. They haven’t experienced it as something real and objective. To better understand objective aspects of the phenomenon, case study focused on how their professions and their professional associations are tackling that issue may be needed.

Methodology is the systematic, theoretical analysis of the methods applied to a field of study.

Case study

Therefore, the methodology of choice will be a qualitative, interpretive multiple-case case study (Yin, 2003) that encompasses phenomenographic analysis. Activity theory will be used as a lens to analyze interrelations among multiple elements in this system.

QIE/IPL-related practices and learning technology that can support QIE/IPL used by each profession will be analyzed as an independent case. The four cases are:

• ASA,
• American Association of Nurse Anesthetists (AANA),
• American College of Surgeons (ACS), and
• American Academy of Physician Assistants (AAPA).

An alternative solution was to use single-case with embedded multiple units of analysis. That approach would be appropriate if we had collaboration and shared programs among two or more of the specialties in place. In that situation the case would be shared QIE/IPL-related practices and learning technology that can support QIE/IPL of all professions together. Activities specific to each profession would be embedded units of analysis.

Since at this time I’m not aware of any collaboration on QIE/IPL, QIE/IPL activities in each specialty should be analyzed as separate entities.

Case study data sources will be interviews with staff and physician members, the website of a professional association, and literature published by a professional association. Two interviews (non-phenomenographic) and one site visit/meeting will be scheduled with representatives of each profession. Phenomenographic interviews will also serve as a source of data over and above standard phenomenographic research.

Phenomenographic analysis

Phenomenographic analysis focused on how CPD professionals, clinicians (anesthesiologists, nurse anesthetists, surgeons and anesthesiologist assistants) and their respective leaders perceive QIE/IPL and technology that supports those practices will be the central part of the case study. Phenomenography appears to be the optimal method for this approach, because at this point QIE/IPL is in its early stage and human perceptions are the dominant factor. Additional reasons are:

1. Attempts to implement QIE/IPL in the U.S. healthcare system have a long but troubling history, and drivers influencing implementation of QIE/IPL create a very complex picture. The phenomenographic approach is recognized as a good tool to analyze changes in such a complex system (Bunniss & Kelly, 2010; Stenfors‐Hayes, Hult, & Dahlgren, 2013).
2. Understanding the perceptions of groups involved in the learning and teaching process can enable us to address current and emerging challenges in that dynamic environment (Richardson, 2005).
3. QIE/IPL is ultimately a social endeavor.

During the past two decades, phenomenography proved to be very useful in medical education (Stenfors‐Hayes et al., 2013). It provides insight into the different ways that people perceive phenomena in the world around them and how those perceptions relate one to another (Marton, 1981; Marton & Booth, 1997). Therefore, it can serve as a lens to analyze a specific research question and direct how research is carried out. In a medical setting, phenomenographic research is valuable for topics like clinical practice, communication and healthcare learning, and, especially, the processes and outcomes of learning (Larsson & Holmström, 2007; Richardson, 1999). According to Stenfors‐Hayes et al. (2013), phenomenography can serve as a link between three important elements this research is tackling: research, organizational change and educational development. That feature can be especially valuable in the context where, as the Macy (2013) expert team concluded, huge changes affecting the U.S. medical system are not linked effectively with changes affecting CPD of healthcare professionals in the U.S.

Phenomenography was chosen over phenomenology because QIE/IPL is in this context an emerging concept. Therefore, we can expect numerous ways in which QIE/IPL is perceived (Larsson & Holmström, 2007).

Activity theory

The third element of the research framework is activity theory: a descriptive framework taking into account all elements of a complex activity/work system. Examples of such an activity system may be teams like a perioperative surgical home team or organizations such as the ASA. Therefore, activity theory can serve as a lens to analyze human activities in such a complex and dynamic system. The third generation of activity theory is specifically interesting for this research because it is focused on how different activity systems interact (Engeström, 2001). Each profession (anesthesiologists, nurse anesthetists, surgeons, etc.) and patients or the public can be analyzed as a separate activity system. The third generation of activity theory can help us understand how those systems interact during preparation for implementation of QIE/IPL activities. A small detail that confirms the suitability of activity theory is that in the paper introducing the third generation of activity theory, (Engeström, 2001) uses interaction among healthcare activity systems (hospital, patient’s family) as the main example.

Figure 4. Two interacting activity systems are the minimal model for the third generation of activity theory (Source: Engeström, 2001). Each profession can be analyzed as a separate activity system. Outcomes (Object₂) of each profession interact creating outcome of collaboration – Object₃.

Resources

• Bunniss, S., & Kelly, D. R. (2010). Research paradigms in medical education research. Medical Education, 44(4), 358-366.
• Creswell, J. W. (2009). Research design: Qualitative, Quantitative, and mixed methods approaches. London: SAGE.
• Engeström, Y. (2001). Expansive learning at work: Toward an activity theoretical reconceptualization. Journal of education and work, 14(1), 133-156.
• Larsson, J., & Holmström, I. (2007). Phenomenographic or phenomenological analysis: Does it matter? Examples from a study on anaesthesiologists’ work. International Journal On Qualitative Studies On Health And Well-being, 2(1), 55-64. doi:10.1080/17482620601068105
• Macy, Josiah Macy Jr. Foundation. (2013). Transforming Patient Care:  Aligning Interprofessional Education with Clinical Practice Redesign. Paper presented at the Macy Conference on Transforming Patient Care: Aligning Interprofessional Education with Clinical Practice Redesign, January 2013.
• Marton, F. (1981). Phenomenography — describing conceptions of the world around us. Instructional science, 10(2), 177-200.
• Marton, F., & Booth, S. (1997). Learning and awareness. Mahwah, NJ, US: Lawrence Erlbaum Associates, Publishers.
• Richardson, J. T. E. (1999). The concepts and methods of phenomenographic research. Review of Educational Research, 69(1), 53-82.
• Richardson, J. T. E. (2005). Students’ approaches to learning and teachers’ approaches to teaching in higher education. Educational Psychology, 25(6), 673-680.
• Stenfors‐Hayes, T., Hult, H., & Dahlgren, M. A. (2013). A phenomenographic approach to research in medical education. Medical Education, 47(3), 261-270.
• Yin, R. K. (2003). Designing case studies. In R. K. Yin (Ed.), Case study research: design and method (pp. 19-56). London: Sage.

Literature review

Evolution

Distance learning of the U.S. healthcare workforce has a long history, starting with correspondence education in the 1960s (Josseran & Chaperon, 2001). Some popular correspondence programs, such as Refresher Courses in Anesthesiology, were initiated in the early 1970s (ASA, 1973).

Online has become the dominant way of delivering CPD. Five years ago, Harris, Sklar, Amend, and Novalis‐Marine (2010) predicted that “online CPD is likely to be 50% of all CPD consumed within 7-10 years.” Four years later, in 2014, all education delivered by the American Society of Anesthesiologists (ASA) is online or enhanced by online formatting. On the other hand, it has been known for a long time that online CPD programs are as effective as traditional CPD programs (Wutoh, Boren, & Balas, 2004).  Consequently 97% of physicians expect more online CPD in the future (archemedx.com, 2013).

Historically, the focus of CPD was primarily on content transmission. More recently, strong societal forces are converging focus shift toward behavior changing learning activities with impact on patient population (Moore, Green, & Gallis, 2009; Russell, Maher, Prochaska, & Johnson, 2012). We can also notice a shift of focus from individuals towards to CPD of groups and organizations (Webster-Wright, 2009).

Five generations of distance education, as described by (Taylor, 2001) and later elaborated on by (Bates, 2008), can categorize the evolution of CPD as provided by the ASA.

1. The Correspondence Model, based on print technology, is losing its share and is enhanced with online delivery. However, it still plays a significant part. In 2014, approximately 30% of CPD credits claimed by ASA users was done through that model.
2. The Multi-media Model – delivery of multimedia content on print, digital storage devices (CD/DVD, flash memory), or through the Internet, but without any communication among humans. It is well-suited for industrial mass production. It is the dominant method of delivery, with around 68% of credit hours delivered in this format.
3. The Telelearning Model delivers synchronous communication, such as webinars, and is used quite rarely in CPD. There were no CPD credits awarded by ASA this year through this model.
4. The Flexible Learning Model is based on asynchronous online communication (Bates, 2008). In the U.S., CPD context it is very rarely used. The current LMS used by the ASA does not provide support for it.
5. The Intelligent Flexible Learning model will become possible after implementation of the new LMS. It builds on the functionality of the Flexible Learning Model. Some of the additions are: easy access to institutional guidelines and resources; computer-mediated communication; user- generated content; and peer assessment. The system will be integrated with the Anesthesia Quality Institute clinical outcomes tracking system(Dutton, 2014), allowing individuals and groups to assess and reflect on their clinical performance and create improvement and learning plans. The system will also deliver a business intelligence layer that suggests learning based on users’ clinical performance, and performance in courses and certification status.

Specific learning theories are associated with each of those generations. Generations 1 and 2 are associated primarily with behaviorism and cognitivism (Bates, 2008). A majority of CPD is delivered through the first two generations of distance education. Generation 3 is not popular anymore and instead of implementing generation 4 the ambition is to go straight to generation 5. Simultaneously, generation 5 utilizes constructivist approaches like collaborative learning, knowledge construction, communities of practice and self-directed learners (Peters, 2002). Between the first two generations and the fifth generation we have significant technological, theoretical and cultural differences. As described below, the U.S. healthcare reform and recently adopted educational technology solutions will enable those changes to happen in the form of IPL and QIE. However, the technology is just one element in that formula. This research will contribute to those efforts by providing insight into human perceptions of QIE and IPL, and technology enhanced learning solutions available to perioperative care teams.

Definitions

IPL is a situation “when two or more professions learn with, from and about each other to improve collaboration and the quality of care” (CAIPE, 2002).
QIE is a system-wide educational framework focused on three goals: better care, better health and reduced-cost patient care (Batalden & Davidoff, 2007). Its holistic system design approach tackles all potential barriers for quality improvement (QI), attempting to make permanent system-wide changes. In that context, QI is coordinated with the continuous efforts of all stakeholders – healthcare professionals, patients, researchers, educators and the public – toward better patient outcomes, better system performance and better professional development.

QIE roadmap

The Alliance for Continuing Education in the Health Professions (ACEHP) in 2015 launched the QIE roadmap (Figure 2). As Figure 2 illustrates, QIE by ACEHP is a continuation of the gradual evolution of CPD from didactic lectures to practice-based activities with real impact on clinical performance. It assumes incorporation and integration of education professionals, tools, resources and methods into system-wide QI efforts. Since successful QIE changes are usually system-wide, and involve multiple professions, the QIE roadmap presented below (Diamond, Kues, & Sulkes, 2015) predicts the currently siloed education of healthcare professionals will evolve in interprofessional education during next 10-to-15-years.

Figure 2. Alliance QIE Initiative: A Transformation Shift – toward interprofessional team-based QIE (Source: Diamond et al., 2015)

QIE and IPL

Knowing that the traditional CPD has limited impact on quality of care (Hager, Russell, Fletcher, & Macy Jr, 2008; IoM, 2010; Macy, 2013), it is fair to say that IPL and QIE have different learning formats and different goals than traditional CPD.

QIE and IPL have numerous similarities. They assume that the best way to ensure individual and system- wide professional development and QI is to have a well-integrated and coordinated system (Shortell, Bennett, & Byck, 1998), where healthcare workers from all professions are connected and focused on meeting the needs of individuals and communities (Macy, 2013). They are each individually described as great tools to address the same three goals: better care, better health and reduced cost (Batalden & Davidoff, 2007; IoM & 2013). Finally, WHO (2010) presented IPL as an important prerequisite for a high-performing collaborative practice and continuous quality improvement. Therefore, QIE and IPL can be viewed as two different entry/view points of the same system-wide QI system (learning/networked health system) – as Figure 3 illustrates. IPL will start with creation of a skilled, collaborative, practice-ready workforce that can practice quality improvement and deliver optimal health services. On the other hand, QIE will start with system changes that require the collaborative practice-ready workforce IPL can produce. Ultimately, they should be treated as two related parts of the same system. Further on, I will refer to them as QIE/IPL.

Figure 3. IPL and QIE entry point or lenses into Health and Learning Health Systems. Left lens is more focused on IPL. Right lens is more focused on QIE. Together they provide the full picture (Adopted from: WHO, 2010, p. 9).

Need

Healthcare is a team sport (Salas, DiazGranados, Weaver, & King, 2008). Healthcare professionals participate in it daily, and each one of us as patients participates in important healthcare events at least a few times in our lives. However, it is a very dangerous team sport. No other team sport has a greater potential for fatal outcomes. For example, the Institute of Medicine concluded that between 44,000 and 98,000 Americans die each year as a result of medical errors (IoM & 2001). Yet healthcare practitioners in the U.S. are rarely trained as a team and they have limited insight into QI methodology (Starr et al., 2015) .

Political-economic drivers

Strong political-economic and social factors shape CPD of healthcare professionals in the U.S. (Balmer, 2013; Cervero & Moore Jr., 2011) and have obstructed interprofessional learning for decades (Hayes, 2012). As history shows, those factors (pay-for service, siloed guilds or accreditation systems, for example) may have a stronger impact than professional and educational factors.

This research will be done in the context of the perioperative care team (surgery and anesthesia professionals). The literature suggests that due to rivalry between professionals or specialties, learning and change in networked practices may be difficult (Norman, 2013). That may be very noticeable in this context where one very relevant issue is a long, intense and passionate debate between physician anesthesiologists and nurse anesthetists over nurse scope of practice (Hayes, 2012). In addition to the main factor – patient safety – nurse scope of practice directly influences positions and payment of physician anesthesiologists and nurse anesthetists, making it a strong political-economic factor (with a huge impact on social capital). For example, in a recent article Johnstone (2015) showed that, in addition to high membership fees ($665), one of the main reasons cited by anesthesiologists for not joining the ASA was related to the ASA’s policy toward Nurse Anesthetists (NAs). It is interesting that while some non-member anesthesiologists think the ASA is working too closely with NAs, others think it is not working closely enough.

On the other hand, new political-economic and social factors started changing that power dynamic recently. Rising costs of U.S. healthcare-associated quality and patient safety issues (Berwick & Hackbarth, 2012; Davis, Stremikis, Schoen, & Squires, 2014) have triggered massive changes in the U.S. healthcare system. IPL is recognized as an important tool to improve performance of U.S. healthcare teams and address the changes that the U.S. healthcare system and the CPD system are undergoing (IoM, 2010; Macy, 2013; WHO, 2010).

Clinical microsystems

One important feature of the current healthcare reform is focus on development and performance of clinical microsystems. Clinical microsystems are small, interdependent groups of healthcare professionals who work collaboratively to deliver optimal and comprehensive healthcare for specific groups of patients (Batalden, Nelson, Edwards, Godfrey, & Mohr, 2003). Clinical microsystems are made up of groups that participate in immediate delivery of care and interact directly with patients, such as physicians, nurses or pharmacists, and groups that support the microsystem, like laboratory, IT and leadership professionals.
Communities of practice can be an important tool to improve performance of microsystems (Webster-Wright, 2009; Wenger, 2006). It is a very flexible tool and depending on purpose, communication methods an structure, they can vary significantly (Ranmuthugala et al., 2011). Results of this research may contribute toward better utilization of technology enhanced CoP methodology in this specific context.

Selected professions

Perioperative surgical home (PSH), a clinical microsystem focused on delivery of perioperative care – from the decision for surgery to complete recovery (ASAHQ.org, 2014) – is the context of this study. The four professions participating in PSH involved in this research will be: physician anesthesiologists, surgeons, nurse anesthetists and anesthesiologist assistants. Those professions were selected because:

• Clinicians are the main stakeholders in the healthcare microsystems and their interactions and professional cultures greatly shape how teams work and the quality of service they deliver (Macy, 2013)
• There is a specific political-economic dynamic between these professions mainly focused on questions of who will lead the PSH team and the role of each profession in that team (Hayes, 2012).
• For the scope of this research, it was important to limit the number of professions involved.

Maintenance of Board Certification – Another political-economic factor

Turbulent changes that affect Maintenance of Board Certification (MOC) of physicians in the U.S. may significantly influence context and implementation of QIE/IPL. Current MOC practices are mainly developed around multiple-choice questions and credit hours. Criticism toward them has been building during the past few years (Gray et al., 2014; Kempen, 2012, 2014; O’Gara & Oetgen, 2014; Strasburger, 2011). In 2014, the Association of American Physicians and Surgeons took the American Board of Medical Specialties and MOC to court, claiming that MOC “imposes enormous ‘recertification’ burdens on physicians, which are not justified by any significant improvements in patient care” (AAPS, 2014). The beginning of 2015 was marked by a nation-wide revolt against MOC. Significant amounts of criticism were supported with the current educational theory and online learning formats that QIE/IPL will promote. As a result, majority of the boards are reorganizing their MOC programs (Baron, 2015).

Organizational and technological context

Thus far, a majority of CPD providers rely on LMS (if they use LMS), which has limited functionality. Such LMS systems are built around a combination of SCORM + files + quiz + survey + certificates, and usually are completely lacking in support for collaborative education. They can address needs of content-focused education, but can’t address needs of collaborative or networked learning. The ASA’s leadership has recognized that and at this moment the ASA is in the process of implementing a new Moodle-based LMS – Totara. Totara comes with all the collaborative features of Moodle. Therefore, it will be a big change. In addition, Totara provides strong support for learning plans and organizational structure/hierarchies.[1] Through the Totara hierarchies’ framework, the ASA can assign specific competencies and courses to specific roles in a team/organization. That feature may enable the ASA to deliver programs for multiprofessional teams.

This research is located in the context of perioperative team. Associations representing the other two key players in the perioperative team – the American College of Surgeons and American Association of Nurse Anesthetists – are planning to select LMSes with the functionality similar to the LMS ASA selected by the end of August 2015. Those selections may significantly influence the context and perspectives interviewees have on QIE/IPL.  This research will help better navigate toward better and more coordinated utilization of learning technology available to members of perioperative team.

Theories

There are a number of theories that can be used to define and analyze IPL (Hean, Craddock, Hammick, & Hammick, 2012) and QIE. The approach to theory in papers on IPL has been evolving. At the beginning, a significant number of papers were very pragmatic and didn’t describe a theoretical background. Many later papers grounded IPL research in a single theory – usually related to a specific school of thought and academic discipline (Barr, 2013). Finally, at this point, a growing number of papers build a sound, flexible and inclusive IPL frame of references by combining multiple theories and practices. Following that evolution of thought, this research will reflect on a few major theories that can be used to describe IPL and possible interactions/overlaps between different theories.

Social theories (social constructivism, social capital) (Hean et al., 2012), adult learning (Clark, 2006), identity theories, situated learning (Ranmuthugala et al., 2011; Wenger, 1998, 1999) and networked learning (Dev & Heinrichs, 2008) are the main theories relevant to QIE/IPL learning processes. On the other hand, theories most relevant to QIE/IPL context are sociology of professions, organizational theory and activity theory. They may present a compelling example of how different theories complement each other. For example, Larson (1979) argues that professional guilds are actively engaged in monopolizing knowledge in specific areas, to ensure cognitive exclusivity. That may explain why, despite learning organization (Roberts & Thomson, 1994; Senge, 2006) being a very popular theory concept (Barr, 2013), it is especially hard to achieve it among different professional organizations and patients. Fortunately, activity theory allows us to analyze organizations as “distributed, decentered and emergent systems of knowledge” (Blackler, Crump, & McDonald, 2000, p. 278); it provides insight into connections between activities and context and reasoning behind complex social activities.

Resources

• AAPS, Association of American Physicians and Surgeons. (2014, Oct 24, 2014). AAPS Takes MOC to Court.   Retrieved from AAPS Takes MOC to Court
• archemedx.com. (2013). 2013 Healthcare Professional Continuing Education Preference Survey.   Retrieved from http://www.archemedx.com/blog/2013-clinician-continuing-education-preference-survey/
• ASA, Americaln Society of Anesthesiologists (1973). ASA Refresher Courses in Anesthesiology – Volume 1. ASA Refresher Courses in Anesthesiology, 1(1), 1-167.
• ASAHQ.org. (2014). The Perioperative Surgical Home (PSH) Model of Care.   Retrieved from http://www.asahq.org/For-Members/Perioperative-Surgical-Home.aspx
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[1] Totara: Frequently Asked Questions for Positions, Organizations and Competency Hierarchies http://help.totaralms.com/FAQs_for_Hierarchies.htm

Interviews

Sample size

Literature states that there is “no prescriptive sample size for a phenomenographic study” (Yates, Partridge, & Bruce, 2012, p. 103). Bowden (2005) suggested that the sample should be large enough to find sufficient variation in perceptions, but small enough that the amount of data is manageable. A concept close to sufficient variation in perceptions is the saturation point. Research will achieve the saturation point when additional perceptions cannot be detected (Kaapu & Tiainen, 2012).

Following that recommendation, I plan to interview 5-8 members of each of the four groups: physician anesthesiologists, nurse anesthetists (NA), anesthesiologist assistants (AA) and surgeons.. Optimally, the majority of participants (~60%) will be members and leaders who are clinically active. The rest will be CPD professionals and staff leaders (for example, a CEO).

Interview questions

The questions below were selected to provide the critical variation among participants. Those variations will be categorized and organized in an outcome space (Cope, 2004).

1. Can you please reflect on your previous experience of working in multi-professional teams?
2. How would you describe IPL and QIE? For example, what is the purpose of each? Is it the same purpose?
3. What are the differences or similarities?
4. How about benefits and challenges?
5. Can technology help us address those challenges, or enhance the benefits? If yes, how?
6. What, in your opinion, are the most important benefits and challenges associated with perioperative surgical home (PSH)?

Reference

Bowden, J. A. (2005). Reflections on the phenomenographic research process. In J. A. Bowden & P. Green (Eds.), Doing Developmental Phenomenography. Melbourne, Victoria: RMIT University Press.

Cope, C. (2004). Ensuring validity and reliability in phenomenographic research using the analytical framework of a structure of awareness. Qualitative Research Journal, 4(2), 5-18.

Kaapu, T., & Tiainen, T. (2012). Phenomenography: Alternative Research Approach for Studying the Diversity of Users’ Understandings. Paper presented at the European Conference on Information Systems, http://aisel.aisnet.org/ecis2012/29.

Yates, C., Partridge, H., & Bruce, C. (2012). Exploring information experiences through phenomenography. Library and Information Research, 36(112), 96-119.

Theoretical framework

Ontology. Social constructivism is my dominant worldview. It assumes that meanings are created in social interaction. They are constructed on individual and group/organizational/professional levels and influenced by numerous historical, cultural and technological factors.

Epistemology. The social constructivism learning theory (Curran, Fleet, & Kirby, 2010; Vygotsky, 1978) is associated with that worldview. I will use it as a lens to analyze potential challenges of QIE/IPL.

Social constructivism assumes that groups actively construct knowledge through social interaction internally among team members, and as a team interacting with the external world. In that process they create group culture, a collection of shared artifacts and shared mental models. Ultimately, according to a social constructivist view, the society exists simultaneously as subjective and objective reality (Andrews, 2012).

Research questions

As the literature review shows, education focused on quality improvement of clinical practice and IPL has been grabbing our attention for more than half a century, and there is a wealth of publications on that topic. However, very few changes were accepted. It is fair to say that QIE/IPL are still in the early stages. On the other hand, recent strong political-economic forces and technology-enhanced learning solutions have created an environment that can enable implementation of QIE and IPL on a scale that was never possible before. Therefore, the research questions are:

1. How are QIE/IPL and technologies and policies that shape QIE/IPL perceived by four groups involved in perioperative teams: anesthesiologists, surgeons, anesthesiologist assistants and nurse anesthetists?
2. How is technology-enhanced collaborative learning used and perceived in the context of QIE/IPL and perioperative teams?
3. How are professional cultures and contextual factors related to collaborative learning influencing implementation of technology-enhanced QIE/IPL?

Answers to those questions will help us better utilize technology to support QIE/IPL, to the benefit of all healthcare professions involved, and their patients; it will help us understand cultural and contextual factors so we can navigate more quickly and safely to successful QIE/IPL programs.