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.

Ethics and Risk

The key to recruiting participants and obtaining successful interviews is to gain their trust and respect. To achieve that, the initial contact with a group or individual included a clear statement of the research goals, format, and ethical considerations. I made it clear that their involvement in the research is voluntary, their participation in the study is anonymous, and the results will be presented in a way that assures confidentiality.

Identity protection. The participants were informed that they can cease participation up to four weeks after they receive the transcript and ask that their data be destroyed. The interviews were recorded with a Galaxy 5 password-protected Android smartphone. A few hours after the interview, the audio files were erased from the smartphone. The data were stored in a password-protected and encrypted Google for a business server. The recordings and transcripts were anonymized, and a separate digital file not stored on the computer was used to connect transcripts, recordings, and participants. That measure assured that even in the case of the computer being hacked, the anonymity of participants would be assured.

The ethics for this study were approved by Lancaster University’s Department of Educational Research. The ASA Committee on Professional Oversight was informed about the project.

Data Analysis

Data analysis was based on three segments (Figure 1):

1. Phenomenographic research was used to draw a picture of how QIE/IPL is perceived. If there are moderate differences among groups, I will reflect on them. If those differences are significant, it may be possible to create separate outcome spaces for each group.
2. A case study of each professional organization involved in the research was focused on QIE/IPL-related practices and technology and the official policy used in the organization. That can help us better interpret data from phenomenographic research and gather insight into what is possible in reality. For example, in my recent research (Hlede, 2015), I found that in the ASA, all research participants indicated that IPL is the preferred way to go; however, the official policy of the organization in 2015 did not reflect that.
3. The interaction among groups and existing and potential QIE/IPL projects was analyzed through activity theory so we can get a better picture of interprofessional activities that, at this moment, shape perceptions of each profession.

Figure. Data analysis

Phenomenographic analysis. During the interviews and the analysis of the transcripts, the focus was on what the informants said about the phenomenon and how they talked about it (Larsson & Holmström, 2007) and how they perceive the relationships among them. The first step was to become familiar with each transcript and all concepts mentioned in the transcript (Figure 5).

Image. Visual display in NVivo—combining audio, text, and graphical displays of categories

Following that, during the compilation phase, passages that provided comments about QIE/IPL were tagged with short descriptions. These descriptions were grouped into categories based on concepts to which they were referring. To optimize the validity of phenomenographic research, the categories were created as logically separate and exclusive, and they correspond to a significant degree with the data from the literature on IPL/QIE and health-care reform. Therefore, as suggested by Ornek (2008), the probability of categories being considered by other researchers is high.

A unique color was assigned to each category, and an NVivo graphical display was used to track categories and sets of categories. This system helped with cross-referencing categories and estimating the theme, thematic field, and margin of each category (Sjöström & Dahlgren, 2002).

Figure 2. Object and process of phenomenographic research based on Sjöström and Dahlgren (2002) and Bowden (2005)

The outcome space is created as an image illustrating interrelations among categories. All categories are tightly connected. Their themes and thematic fields (Sjöström & Dahlgren, 2002) are of varying size in individual transcripts; however, after summarizing the transcripts, that difference was not very noticeable, even inside each interviewee group. Therefore, the outcome space was presented as a summary of all groups. The outcome spaces specific for each profession may be created in follow-up research.

Tools Used for Data Analysis

NVivo

Qualitative data analysis software (QDAS). NVivo 11 Pro for Windows, 64-bit (QSR, 2016), was used in the research. The QDAS can significantly enhance qualitative data analysis (Yuen & Richards, 1994). Although analysis and theory construction is a task for the researcher and not the software (Zamawe, 2015), the software creates an additional layer over established research methods and can alter outcomes (Paulus, Woods, Atkins, & Macklin, 2015); therefore, how the software was used is worth mentioning.

Selection. I selected NVivo because it is with ATLAS.ti, one of the two QDAS options supported by Lancaster University. The university has provided valuable lessons on NVivo best practices, and a wealth of materials is available online.

Utilization. NVivo was used for two groups of tasks. The first group covers data management and support for data analysis. The process of coding and analysis was, in many ways, identical as if it was done on Google Docs or paper. The benefit was that the process was easier and faster, and it is easier to track progress. Another group of tasks covers activities that are hardly possible with traditional pen and paper toolset. A quantitative analysis of content and data visualization is the most important example.

Data visualization. In this case, the role of NVivo is enhanced compared to traditional QDAS usage. Knowing that Paulus et al. (2015) stated that 87.5% of 763 articles they analyzed reported only the software name, it is fair to believe that in most cases, QDAS is used only to ease the process of standard phenomenographic practice and that a significant number of researchers did not master advanced features of the software. In this research, I will showcase some of the unique features NVivo provides, primarily data visualization and the utilization of dynamic connections between data from interviews and external resources. There are five main reasons for that approach:

1. Graphics can enhance the understanding of connections and differences between various elements of the complex health-care system, which are the focus of this research.
2. Data visualization is emerging as an important tool in online research (Kennedy & Allen, 2016).
3. Advanced NVivo functionality is underreported in research (Zamawe, 2015).
4. Majority of CME/CPD readers are not familiar with QDAS.
5. Contemporary visual culture expects well-visualized materials. Addressing that expectation may help bridge the gap between the methodology used in this research and a still-strong preference toward a positivist worldview among health-care professionals.

References

1. 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.
2. 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).
3. Hlede, V. (2015). Interprofessional Learning: Anesthesiologists’ Perspectives. Assignment, Doctoral Programme in E-Research and Technology Enhanced Learning. Department of Educational Research. Lancaster University.
4. Kennedy, H., & Allen, W. (2016). Data Visualisation as an Emerging Tool for Online Research. In N. G. Fielding, R. M. Lee, & G. Blank (Eds.), The SAGE Handbook of Online Research Methods (pp. 307-326). London, UK: SAGE Publications.
5. 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
6. Ornek, F. (2008). An overview of a theoretical framework of phenomenography in qualitative education research: An example from physics education research. Asia-Pacific Forum on Science Learning and Teaching, 2(11).
7. Paulus, T., Woods, M., Atkins, D. P., & Macklin, R. (2015). The discourse of QDAS: reporting practices of ATLAS. ti and NVivo users with implications for best practices. International Journal of Social Research Methodology, 1-13.
8. QSR, I. (2016). NVivo 11 Pro for Windows.
9. Sandbergh, J. (1997). Are phenomenographic results reliable? Higher Education Research & Development, 16(2), 203-212.
10. Sjöström, B., & Dahlgren, L. O. (2002). Applying phenomenography in nursing research. Journal of Advanced Nursing, 40(3), 339-345. doi:10.1046/j.1365-2648.2002.02375.x
11. Yuen, H. K., & Richards, T. J. (1994). Knowledge representation for grounded theory construction in qualitative data analysis. Journal of Mathematical Sociology, 19(4), 279-298.
12. Zamawe, F. C. (2015). The Implication of Using NVivo Software in Qualitative Data Analysis: Evidence-Based Reflections. Malawi Medical Journal, 27(1), 13-15.

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

Literature review – introduction

The previous chapter – background – explained the importance of this research. In this chapter, I will review published literature in an attempt to present the most important perspectives for implementation of QIE and IPL by professionals involved in perioperative teams, with special focus on technology-enhanced collaborative learning and cultural and contextual factors.

Implementation of interprofessional learning and quality improvement education is seen as an important part of the transformative changes the U.S. healthcare system is undergoing (IoM, 2010; Macy, 2013; WHO, 2010). Furthermore, as this chapter will show, IPL and QIE have a very intricate and vigorous interrelation. Therefore, the goal of this literature review is to present the current state of knowledge and how this research fits in that, reflect on strengths and limitations of available literature, identify major debates, and provide insight into relations between those elements.

In an attempt to see the forest as well as the trees, this review will use “the big picture approach.” The lines between learning, professional development and quality improvement activities were artificially created in the siloed, pre-Internet world. In our digital and networked world, those lines are becoming increasingly blurred (Price, Havens, & Bell, 2012). Therefore, the focus of this thesis will be primarily on how QIE and IPL interact and evolve in this very dynamic healthcare environment.

References

IoM. (2010). Institute of Medicine: Redesigning Continuing Education in the Health Professions (9780309140782). Retrieved from http://www.ama-assn.org/resources/doc/cme/iom-report-cme.pdf

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.

Price, D., Havens, C., & Bell, M. J. (2012). Continuing Professional Development and Improvement to Meet Current and Future Continuing Medical Education Needs of Physicians In D. K. Wentz (Ed.), Continuing Medical Education: Looking Back, Planning Ahead (pp. 1-14). Hanover, NH, USA, and London: Dartmouth College Press.

WHO, World Health Organization. (2010). Framework for Action on Interprofessional Education and Collaborative Practice. Retrieved from http://www.who.int/hrh/resources/framework_action/en/

Literature review: CME/CPD of anesthesia team in the U.S.

The previous chapter explained socio-economic and political processes that shape the professional and educational landscape of healthcare professions. This section will describe how education is changing in that very dynamic context. It will start with a reflection on more general technology-related changes, which share many similarities with processes affecting our society in general. The focus will continue to be on topics that are specific to education of healthcare professionals in the U.S.

1     Evolution of technology-enhanced learning used by U.S. anesthesiologists

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 learning 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.” Five years later, in 2015, all education delivered by the American Society of Anesthesiologists (ASA) was online or enhanced by online formatting. That happened significantly faster than expected, and it aligns with the now widely accepted opinion that online CPD programs are as effective as traditional CPD programs (Wutoh, Boren, & Balas, 2004), and that a physician’s time is very expensive.  Consequently, 97% of physicians expect more online CPD in the future (archemedx.com, 2013).

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 2015, approximately 30% of CPD credits claimed by ASA users were earned 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 offered in this format.
3. The Tele-learning Model delivers synchronous communication, such as webinars, and is used quite rarely in CPD. There were no CPD credits awarded by ASA this year using this model.
4. The Flexible Learning Model is based on asynchronous online communication (Bates, 2008).  In the U.S. CPD context, it is at this moment very rarely used, and there is significant potential to extend usage of that model (Cheston, Flickinger, & Chisolm, 2013). The first ASA course that utilizes a discussion board was launched in March 2016. .
5. The Intelligent Flexible Learning model is being engineered around 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 future learning topics 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 goal 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 of that formula, and there are numerous challenges that have to be addressed prior to successful implementation. For example, ASA faculty, just like faculty at medical schools, is not well-informed of learning theories used in this context (Flynn, Jalali, & Moreau, 2015). That is a major strategic challenge. Without faculty who know how to lead and give structure to learning activities,  “social media can negatively impact student learning” (Gikas & Grant, 2013, p. 19) and cause significant frustration.

2     Transformation of healthcare CPD

Technology is just one driver transforming healthcare CPD. The list of additional drivers is extensive. They include the evident need for better implementation of adult and collaborative learning principles, the need for more outcome-focused education, and involvement of patients in the learning process (Price et al., 2012).
The CME/CPD model currently used in the U.S. has been heavily criticized (Cooke, Irby, & O’Brien, 2010, IoM, 2010 #456,Hager, 2008 #809; Mehta, Hull, Young, & Stoller, 2013). Weaknesses include low efficiency, inflexibility and not being learner-centered. Mehta et al. (2013) explain that the current teaching methods are often designed to address “arcane assessment methods (e.g., Multiple-choice examinations)” (p. 1418). Consequently, the learning process is focused more on test performance than on development of professional competencies, and grades will reflect more on students’ memory and test-taking skills, rather than behaviors, skills and attributes needed by an effective physician.

CPD focus and cultural change. Historically, the focus of CME/CPD was primarily on content transmission and clinic topics. More recently, strong societal forces are converging in a focus shift toward behavior-changing learning activities with impact on patient population (Donald E Moore, Green, & Gallis, 2009; Russell, Maher, Prochaska, & Johnson, 2012). We can also notice a shift of focus from individuals (CME) toward CPD of groups and organizations (Webster-Wright, 2009). That transformation is part of a focus shift from continuing medical education (CME) toward CPD (image below). In that context, the CPD term serves as an umbrella (Karle et al., 2012) that encompasses formal CME focused on medical practice, and all other forms of medical education – including QIE/IPL. Furthermore, CPD covers multifaceted competencies important for patient care – such as awareness of cultural differences, communication skills, managerial, social and interprofessional education, and humanitarian and psychological aspects of care (WFME, 2003). That is a huge cultural change for all traditional members of the medical education continuum and newly associated groups, such as anesthesiology assistants, technologists, managers and leaders.

Figure 4. Evolution from CME to CPD

Quality vs. Education. Until recently, continuing education of healthcare professionals and quality improvement initiatives existed as two very separate entities. It was common to hear that CME and QI people may have offices next to each other – but they do not talk to each other; they do not speak the same language; they do not have the same focus (Shershneva, Mullikin, Loose, & Olson, 2008). For example, CME focused on credit hours has been awarding credit for seating time. Simultaneously, QI initiatives are focused on implementing sustainable organizational and individual behavioral change. In recent years, we have seen a significant shift (Balmer, 2013). Innovative approaches to integrate education and QI and IPL are being developed and implemented (Shojania, Silver, & Levinson, 2012).

Repeating history? Although recent developments may suggest that integration of education and QI and IPL is a new phenomenon, that is not true. A recently republished article focused on “Relating Continuing Education Directly to Patient Care [Quality]” (Brown & Fleisher, 2014), was first published 45 years ago – in 1971. In the same manner, the first report created by the Institute of Medicine (IoM, 1972) was focused on IPL. Therefore, while analyzing interaction between QI/IPL and education, the question should not be: “Why haven’t we figured that out before?” but “Knowing what we do, why haven’t we made the required changes?” Or even better: “When and why did education and quality improvement become disconnected?”

Interprofessional apprenticeship. Apprenticeships have historically been the main form of medical education (Dornan, 2005). Nowadays, their role in undergraduate and graduate medical education is a bit reduced, but residency programs are created around the apprenticeship model. Rodriguez-Paz et al. (2009) argue that the traditional “see one, do one, teach one” model is not adequate because inexperienced trainees learn by practicing on real patients, making it a safety issue. However, the model should not be replaced, but updated. Oversimplification and disintegration of professional competence in knowledge, skills and attitudes is counter-productive, because they are interwoven parts of the same fabric of competence. If they are learned in isolation from one another, the outcome (Makovsky Health, 2013) will be less than ideal (Dornan, 2005). Furthermore, experts have “tacit competence” – things they can do skillfully but without ability to describe properly. The best way to gain those unteachable competencies is through mentorship in practice settings.

Share the care. A variety of educational tools and concepts, like the competency-based training paradigm, technology-enhanced patient safety and quality-improvement educational interventions, can ensure that trainees practice with real patients without risk. A good example is value-added medical education. It is a team-based “share the care” concept, where numerous clinical and non-clinical professionals, patients and learners work together so that each team member contributes to his or her maximum potential (Lin et al., 2014). Medical and other healthcare students participate in such a team according their competencies. Therefore, instead of shadowing a physician and attempting to do only the things physicians are supposed to do, early medical students can start as health and behavioral change coaches or quality-improvement project administrators or data collectors.

Those concepts, enhanced by technology like high-fidelity simulation, virtual reality, and the collaborative Web healthcare will enable learners from college thorough retirement “to… see one, simulate many, do one competently, and teach everyone.” (Vozenilek, Huff, Reznek, & Gordon, 2004, p. 1153).

3     Failure of didactic format and perpetual status quo

Didactic lectures are still the main learning delivery format, yet the impact of such learning on competencies and patient outcomes is questionable (D. Davis et al., 1999; Holm, 1998). That is not a new debate. Abraham Flexner, the author of the famous Flexner report (Flexner, 1910) and the person who helped change the face of American medical education (Cooke, Irby, Sullivan, & Ludmerer, 2006), was very vocal about it. Flexner criticized the lecture system, stating that although it allows schools to “handle cheaply by wholesale otherwise unmanageable numbers” (Flexner, 1908, p. 194), it doesn’t prepare students for real-life tasks. The programming should be created around integration between formal learning with clinical practice and research. Therefore, Flexner concludes by describing lectures as “an astonishing failure of pedagogic insight” (Flexner, 1908, p. 197). That criticism was muted with the fact that, didactic, content-focused lectures, as a short periodic interaction with a group of unnamed students allow industrialized education. Lecturers can “educate” large numbers of students in a short time. Less time spent on lectures means that the lecturer has more time for the research necessary for career development (Colbeck, 1998).

Flexner explains that, a century ago, increased reliance on didactic lectures was perceived as a sign that the college was “grown-up” (Flexner, 1908, p. 199). At that time, industrialization and mass production were prominent signs of progress. Therefore, industrialization and mass production gained popularity in education and universities started competing in research instead of quality of education. However, Flexner sharply criticized that approach, explaining that “rapidly won distinction as research centers is not compensation for college failure“ (Flexner, 1908, p. 217), and that as soon as people started looking closely at educational function “it will become evident that the college is nowadays educationally headless.“ (Flexner, 1908, p. 218)

Today, more than 100 years after the Flexner report  (Flexner, 1908, 1910, 1912) we can see that the basic teaching model went through only minor changes during past 100 years (Mehta et al., 2013). Furthermore, some of Flexner’s recommendations are in the same stage of implementation as they were a century ago.

4     Back to performance

Learning for quality. Balmer (2013) explains that reduced funding from industry, mainly the pharmaceutical industry, creates a context where CPD of physicians and healthcare professionals is paid for mainly by healthcare institutions or individuals. Therefore, instead of selecting a program because it is free, healthcare professionals and institutions more often select programs because they will improve their performance and have good return on investment. That trend correlates with pay-for-performance initiatives and performance-tracking frameworks that are increasingly being used in the U.S. Through such frameworks, individuals or teams can monitor their performance, diagnose performance gaps, and, based on that plan, their professional development.

Vision of Qualiy.  Those trends align well with the vision proposed in “Health Professions Education: A Bridge to Quality,“ IoM and (2003, p. 45):

“All health professionals should be educated to deliver patient-centered care as members of an interdisciplinary team, emphasizing evidence-based practice, quality improvement approaches, and informatics.”

As Dr. Edward Hundert, M.D., and Mary Wakefield, Ph.D., R.N., explain in the preface to Health Professions Education: A Bridge to Quality, (IoM & 2003, p. ix), the main message of the book is: “…reform of health professions education is critical to enhancing the quality of health care in the United States.” Furthermore, that reform must involve all healthcare professionals.

Changes – Five themes. Numerous themes have been initiated in response to the aforementioned challenges. (Balmer, 2013) described five dominant themes grounded in political, economic and educational U.S. context. They are:

1. Shift of focus from time-based attendance metric (awarding seating time) to measurement of competences with impact on patient care.
2. Common usage of inter-professional education to enhance profession-specific CPD.
3. Integration of quality improvement with continuing education – creating quality improvement education or organization-wide CPD.
4. Increased focus on the big picture where CPD is seen as a tool to address public health and population issues.
5. Defining and standardization of professional competencies needed for successful healthcare services, as well as needed for CPE interventions.

5     Assessment drives learning – in wrong direction?

In previous chapters, a few conflicts inherent in the current political, social or research culture have been described. Those conflicts inhibit change. Could it be that in the same manner a cultural conflict hidden inside the educational system is blocking change? Could it be that the most popular assessment method is sending us in a wrong direction? Let’s check it out.

Debate on multiple choice questions (MCQ) has a long history (Anderson, 2004; Pickering, 1979). MCQ exams are known to be a reproducible, cost-effective and reliable tool to test medical knowledge. However, they have limited validity in assessing clinical competencies, have limited flexibility in different settings, and are not comprehensive as a single assessment tool (Tetzlaff, 2007).

In other words, as the table below illustrates, MCQ, the most commonly used assessment method, has many features different from what is perceived as optimal for continuous quality improvement. Therefore, it is fair to ask if part of the challenges we are experiencing are caused by the current assessment methods. The table below illustrates differences between continuous quality improvement and MCQ. Since “assessment drives learning” (Frederiksen, 1984; Wood, 2009), if we change what and how learning is assessed, learning practices would be changed. Is it possible that MCQ exams, which are  often stressful, isolating, competitive, content-focuse learning experience with known potential negative effects on learning (Bailey, Mossey, Moroso, Cloutier, & Love, 2012; Roediger III & Marsh, 2005), are contributing to the challenges we face today?

Table 3.

6     Assessment pyramid

Miller’s pyramid of clinical competencies (Figure 5) links assessment tools with evidence we can use to determine if the healthcare professional is “competent to practice.” The pyramid (Miller, 1990) was developed with the individual practitioner in mind. Now we can observe it through lens of team-based QIE/IPL.

Knowledge is at the bottom of the pyramid. Assessing knowledge is quite easy (Miller, 1990). With MCQ we can easily do it on a mass scale. It can be automatic. Furthermore, “very precise” numbers we can get as outcomes can overshadow questions about the impact of MCQ. Although knowledge is essential to function as a professional, merely knowing is insufficient for practicing good medicine. Therefore, if we are focused on assessing knowledge, we will not be able to distinguish candidates who can, from those who cannot, practice medicine well.

Assessing teams. Looking at Miller’s pyramid through the lens of QIE/IPL, Level 1 and Level 2 (Knows and Knows how) are primarily focused on individuals. Therefore, although the two levels can help assess individuals who will participate in the QIE/IPL, they are only of limited value to assess teams or performance of individuals in team-based activities.
The top levels of the pyramid focus on how “Shows how” and “Does” can better assess individual and group competencies. However, those assessment modalities are more time-consuming, cannot be automated as MCQ, and as a result are less often used. Therefore, more focus on skill-based assessment (Levels 3 and 4) may be needed for QIE/IPL.
Clinical performance assessment tools used as part of performance improvement CME are valuable assets. At this moment, they are used in limited scope, mainly because the performance assessment methodology is still maturing, and QI CME courses are not very popular.

Figure 5. Miller’s model of clinical competence.(Miller, 1990; Mitchell et al., 2015)

Evolving professionalism. Currently professionalism is taught to healthcare students through the continuum of healthcare education. It is based on the belief that healthcare professionals must come together to continuously research, debate and improve competencies and beliefs (Wynia, Papadakis, Sullivan, & Hafferty, 2014) so they are better prepared for the societal expectations. In that context, our focus is on what a team does, and then shows how it succeeds.

Professionalism as a belief and value system, that describes professional identity or “being” of individuals and groups, is according many authors stronger basis for consistent professional behavior than “doing.”(Goldie, 2012; Weaver, Peters, Koch, & Wilson, 2011). In an era when transformative changes are common, when knowledge is growing exponentially, and graduation or specialty board certifications are important steps in continuous professional development, “doing” should be constantly re-evaluated and improved to better reflect who we are and how we as individuals, teams and professions contribute to the society. To address that, Cruess, Cruess, and Steinert (2015) proposed updating Miller’s pyramid by adding the professional identity of “Is” to the top of the pyramid.
A team-based lens adds more complexity to this model. As team-based care becomes standard, we can see that participation in a team becomes the first identity; team members perceive themselves first as a team and then as a specialty (Hlede, 2015). One interviewee noted:

“Instead of, ‘I’m an anesthesiologist,’ or, ‘I’m a nurse anesthetist,’ it’s, ‘I’m a member of the joint replacement team.’ ‘I’m a member of the spine team.’ ‘I’m a member of the cardiac team.’ You can see that in the hospitals now in some very focused areas. … That’s the first identity.” (Hlede, 2015, p. 17)

7     CME as human capital vs. a requirement for licensure

One of the bigger obstacles to wider implementation of QIE/IPL has been accreditation requirements and ways to measure completion and award credits. The impact of traditional CME formats is heavily debated (Hager, Russell, Fletcher, & Macy Jr, 2008; IoM, 2010), and critics argue that the majority of CME credits are awarded for “seat time” (Schmitt, Baldwin, & Reeves, 2012). Despite that, nobody can argue that if your main goal is to get the required number of credits, this approach is very convenient. You were sitting in this lecture room for one hour, please claim your credits; you completed that MCQ quiz, please claim your credits. Quite often, online MCQ quizzes allow an unlimited number of attempts per each question. Therefore, users can select A-B-C-D until they get the correct answer, and then move to another question. The simplicity of that system – while users are focused primarily on getting credits instead of learning outcomes – creates a combination that is hard to match in the IPL context.

Fortunately, challenges associated with credit-focused CME are well-recognized. E. G. Campbell and Rosenthal (2009) convincingly argue that a huge positive and transformational driver would be a situation where healthcare professional perceive CME primarily as a tool to improve their personal and team human capital. The current model where CME credits serve as a requirement for licensure foster negative selection, and learners, rather than look for the best course, seek the easiest way to gain credits. (Cook et al., 2015).

Pharma is/was shaping CME. Sponsorship from the healthcare industry contributes to the aforementioned challenges. For example, in 2009 the Institute of Medicine published extensive research on conflict of interest in medical research, education and practice (IoM & 2009). The conclusion was that continuing medical education “has become far too reliant on industry funding” (p. 161). The industry funding fosters CME as a marketing tool where the primary focus is on promoting products, while broader education, alternative methods to improve healthcare, and system-based issues like prevention or communication are often ignored.

In reflecting on that situation, (E. G. Campbell & Rosenthal, 2009) used arguments from the Flexner report (Flexner, 1910), saying, “A century later, another component of the continuum of medical education requires equally sweeping reform – continuing medical education.” (p. 1807) They explained that three of Flexner’s main criticisms of the undergraduate medical education in 1910 are applicable to CME now. The aforementioned excessive comercialization is one. Nonstandardized curricula is another. Lack of impact on patient care is the third.  E. G. Campbell and Rosenthal (2009, p. 1807) explain: “Traditional CME is not adequately focused on improving patient outcomes. In fact, there is scant evidence that CME actually improves patient outcomes.“

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Literature Review: Context: the U.S. healthcare system and healthcare teams

As part of the big-picture approach, it is important to describe the current U.S. healthcare context. It is shaped by a series of very strong drivers. Some of these are:

• U.S. healthcare CME/CPD research culture is influenced by positivist, quantitative traditions.
• U.S. healthcare system is undergoing massive transformation. That process is heavily politicized.
• Professional education system is also going through changes, but those changes are not well-synchronized with changes to the healthcare system (Macy, 2013). QIE and IPL are important parts of those changes.
• Rise of such team-based, patient-centric and quality-focused healthcare delivery models as Perioperative Surgical Home has become a noticeable trend.
• Empowerment of patients: From passive recipients of healthcare services, patients have become well-informed team members.
• Professional identity, relationship and trust between different professions are cornerstones of successful team-based healthcare delivery. Historically, compensation models that promote competition among team members negatively influenced that trust.
• Maintenance of certification modalities and requirements for practicing clinicians, and their impact on clinical practices and outcomes, are heavily criticized in academic, professional and public debates.
• Technology has a huge impact on education, collaboration and how healthcare data is managed. In our private lives, we live in a networked world, while our professional systems are lagging behind.
• Quality improvement education initiative – headed by the national Alliance for Continuing Education in Healthcare Professions – perceived QIE and interprofessional, quality focused learning system (Diamond, Kues, & Sulkes, 2015).

Those drivers are very interrelated and each of them is going through changes – creating a very dynamic, ever-changing mosaic.

1     U.S. healthcare CME/CPD research culture

“There are no facts, only interpretations.”
(Nietzsche, Bittner, & Sturge, 2003)

Cultural elements have significant impact on how the areas this thesis investigates (healthcare education and quality improvement) are practiced and analyzed in the U.S. healthcare CME/CPD literature. Arguably, CME/CPD healthcare education literature is overly reliant on context-free, predominantly randomized controlled trials, and positivist and quantitative research used in medical research (D. E. Moore, Bennett, & Mann, 2012). On the other hand, social science education research usually uses context-specific qualitative methods and has a strong theoretical basis. Since qualitative and quantitative research traditions can be viewed as separate cultures marked by distinct norms, values and beliefs, as well as skepticism toward each other (Mahoney & Goertz, 2006), that gap can cause challenges. In the U.S. CME/CPD context, communication across those two cultures can be troublesome, with misunderstandings being common.
For example, recent literature review done by Cervero and Gaines (2014) showed that reliance on quantitative methodologies without theoretical background resulted in two huge groups of articles that answered the following questions: “Does CME have an impact?” and “Which methods can improve impact?” However, the articles did not provide a sound theoretical basis for future research, or explore impact in a specific context.

Elliott (2001) explains that the research design usually matches the professional practices and values. Medical professions desire very specific, quantitative data while dealing with human lives. Simultaneously, as the body of healthcare research exponentially grows, healthcare professionals rely on systematic literature review. Therefore, evidence-based medicine, built around randomized control trials (RCT) and systematic reviews based on RCT, is widely popular. It has provided a robust base for very specific clinical interventions (Clegg, 2005).

As a result, the design of healthcare educational research quite often follows the format used for quantitative clinical research, relying heavily on RCT or meta-analysis of RCT, while very often missing the theoretical background and analytical methods appropriate for educational research. The tendency of that approach is to reduce complex educational problems to simplified bulletproof and socially thin (reductionist and positivist) medical research models. In that context “hierarchy of study design” has been described.  According that hierarchy RCT are the gold standard (Concato, Shah, & Horwitz, 2000), while socially thick qualitative social science methods like methods used in this research – qualitative interviews and ethnography have least credibility.

There are two challenges associated with the very rigid hierarchy of evidence-based medicine:

• Validity of evidence-based medicine in healthcare is questionable. That is important for clinical practice and QIE.
• Validity of the same approach in educational contexts is very doubtful. That affects literature used in this review, and ultimately this research.

Numerous clinical practitioners argue that evidence-based medicine builds fake confidence; it does not enhance objectivity but it obscures the subjective elements that are associated with all types of human research (Donald M. Berwick, 2007; Goldenberg, 2006).

Evidence-based medicine is rooted in positivism. Simultaneously, the positivistic view of scientific methodology has been challenged over the last half century in two respects (Goldenberg, 2006):

1. Our observations and conclusions are heavily influenced by our personal and societal background, theories, knowledge and values. Therefore, even in an ideal situation they cannot deliver an absolute picture of the world (Clark, 1998)
2. Link between “the evidence” and selected theories is never absolute (Duhem, 1991)

Donald Berwick explained that although rigorous randomized control trials can neutralize variations and deliver answers to very specific questions, they cannot be used to assess complex activities like perioperative teams or QI collaborative. We cannot remove variations without ignoring the context. Dr. Berwick explains: “We need evidence… We can’t allow subjective hopes, wishes and dreams to pretend to be truth when unforgiving nature is at work, or we will… do harm. But the harm is equal if we treat a very complex world as if it were simple, if we treat each other as less than whole people and complex systems as simple and separate from us, and thereby reduce our capacity to learn, to converse, to explore and to grow.”(Donald M. Berwick, 2007)

Arguably, that common mismatch between research topic and methodology had influenced outcome of CME research and practices. A significant number of papers attempted to analyze very complex social phenomena through the lens of one-dimensional, context-free qualitative research. As a result, the research did not deliver good, actionable data, and CME/CPD providers have been forced to “improvise.” For example  Fox (2012, p. 192) explains that CME practices are “primarily a function of mimicry, rather that investigation and systemic learning,” and “isolated findings from small, poor studies become justification for adoption of ‘innovative’ educational methods.” In the same manner, Dr. Janet Grant[1] concluded: “There are a lot of declamatory statements and a lot of assertions made about continuing medical education, but not a lot of evidence, no common rationale, no systematic relationship to need, and no robust evidence of beneficial effects on a doctor’s practice” (Hawkes, 2013, p. 4255).

This paper analyzes phenomena that are deeply embedded into the social, cultural, economic, technological and educational mosaic of the U.S. healthcare system. Therefore context-free quantitative RCT and rule-driven meta analysis can be of limited use.

The aforementioned divide can explain debate over the change from the term CME to CPD. The change reflects a significant cultural and epistemological shift in the ways majority stakeholders envision lifelong learning of medical professionals (Karle, Paulos, & Wentz, 2012). It is a move from formal, unprofessional content-focused didactic lessons toward an interprofessional team and student-focused learning system. The process started in 1993 when the UK Standing Committee on Postgraduate Medical and Dental Education proposed the term CPD, reasoning that the CME approach was not enough to cover the complete development needs of modern health professionals. Although we now know the direction in which we are going, the debate is far from settled.

The table below illustrates the divide is widespread. It is affecting significant amounts of our activities.  Epistemological differences between literature review approached in CME and social science as described by Singh, McPherson, and Sandars (2014) are added under epistemology.

Tabel 1.

2     Political context

The U.S. healthcare environment is going through massive, complex, dynamic changes. The drivers of those changes are multiple and strong. For example, the analysis provided by the Commonwealth Fund, a U.S.-based private foundation supporting independent research on healthcare practices, showed that while the U.S., with yearly healthcare cost per capita of $8,508, has the most expensive healthcare, the  system underperforms when compared to other industrialized countries on most measurements (Davis, Stremikis, Schoen, & Squires, 2014). As the table below illustrates, the scale is significant: U.S. healthcare costs are 50% more than the second-most expensive system – Switzerland, and 2.5 times more than the best-performing county – the UK. As a result, the Institute of Medicine reports that Americans suffer from more illnesses and injuries and have shorter life spans than people in other high-income countries. That is happening despite well-described ways to address those issues and the enormous healthcare costs (Woolf & Aron, 2013).

Mirror, Mirror on the Wall, 2014 Update: How the U.S. Health Care System Compares Internationally

Figure 1. 2014 Update: How the U.S. Health Care System Compares Internationally. Source (Davis et al., 2014). Used with permission of the Commonwealth Fund.

Performance trends

The diagram below illustrates that age-adjusted mortality rates per 100,000 population have been falling steadily in the 34 Organization for Economic Cooperation and Development (OECD) countries, and in the U.S. 1986 is the year when the U.S. started underperforming in comparison with other OECD countries.

Figure 2. Trends in mortality rates. Mortality rates have been falling steadily in the U.S. and comparable OECD countries. 1986 was the year when U.S. started underperforming in comparison to OECD average. Source healthsystemtracker.org (2016) (CC BY-NC-ND 3.0 US)

Figure 2. Trends in mortality rates. Mortality rates have been falling steadily in the U.S. and comparable OECD countries. 1986 was the year when U.S. started underperforming in comparison to OECD average. Source  healthsystemtracker.org (2016) (CC BY-NC-ND 3.0 US)

In an attempt to improve the U.S. healthcare, the U.S. government adopted the Affordable Care Act (ACA), also known as Obamacare, on March 23, 2010. The law is described as “the most sweeping legislation affecting every individual in the United States in the last century.” (Diaz, 2015, p. 81).

Knowing the important role healthcare has in the lives of individuals as well as society, it is fair to say that this reform is profoundly affecting everybody in the U.S.: healthcare providers, patients, government and U.S. society in general. For example, it is estimated that in the first three years of the ACA, 50,000 patient deaths were prevented and $12 billion was saved (ahrq.gov, 2014; Kessler, 2015).

Strong political-economic and social factors shape CPD of healthcare professionals in the U.S. (Balmer, 2013; Cervero & Moore Jr., 2011) and have obstructed QIE and IPL 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.

Interprofessional relationship. This research is 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 (NAs) over nurse scope of practice (Hayes, 2012). Nurse scope of practice defines procedures nurses are permitted to undertake in keeping with the terms of professional nursing license. The primary debate is over actions nurses can take without physicians’ supervision.
In addition to the main factor – patient safety – nurse scope of practice directly influences positions and payment of physician anesthesiologists and NAs, 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 + membership in local state society), one of the main reasons cited by anesthesiologists for not joining the American Society of Anesthesiologists (ASA) was related to the ASA’s policy toward NAs. What is especially interesting, the article showed that while some non-member anesthesiologists think the ASA is working too closely with NAs, others think it is not working closely enough.

Socio-economic, professional identity drivers and changes in roles and degrees bring a few additional layers of complexity that influence the relationship between anesthesiologist and nurse anesthetists’ professional groups.

For example, from a socio-economic perspective:

• Physicians start their anesthesiology career in their early 30s or later, after 12 years of highly competitive higher education (4 undergraduate, 4 graduate and 4 residency) and with average student debt of $176,348, where 10% of graduates have debt of $300,000+ (AAMC, 2014).
• Fee-for-service is still the dominant payment method in the healthcare setting (Schroeder & Frist, 2013). In that context, if somebody else wants to provide the same service as you do, that person is a competitor who may reduce your income (and your ability to repay your student loan).
• Debate about NAs’ role in the anesthesia process (scope of practice) contributes to disagreements between physicians anesthesiologists and nurse anesthetists (Hayes, 2012). In most states, NAs work under supervision of anesthesiologists. However, 17 states do not have that safety requirement. In addition to being a patient-safety issue (Hansen & Philp, 2014), that is perceived as unfair competition, because NAs’ certification requires six fewer years of education. Since education of NAs is evolving to all-doctorate programs by 2022 (COA, 2007) – we may expect this debate to continue.

On the other hand, recent political-economic and social factors started changing that power dynamic. Rising costs of U.S. healthcare-associated quality and patient safety issues (Donald M Berwick & Hackbarth, 2012; Davis et al., 2014) have triggered massive changes in the U.S. healthcare system. For example, the fee-for-service model is being replaced by pay-for-performance. In that model, healthcare teams are rewarded for doing good work, and penalized for poor performance. Therefore, other professions have shifted from being competitors to being valuable members of your high-performing team; your team will succeed (and be properly rewarded) only if all of your team members succeed.

3     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 the context and implementation of QIE/IPL. Current MOC learning and assessment practices are to a significant degree developed around multiple-choice questions (MCQ) and credit hours. Criticism of MOC 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 nationwide revolt against MOC. Significant criticism was supported by the current educational theory and online learning formats that QIE/IPL will promote. Critics argue that the authoritarian, one-size-fits-all approach rooted in behavioristic principles should be replaced with more collaborative, outcomes-focused and constructive methods (Brooks, 2009). Instead of policing bad physicians (or physicians that are not good with MCQ), the system should foster development of physicians as knowledge workers, as professionals who safely and effectively use knowledge to lead their team and deliver optimal care (Centor, Fleming, & Moyer, 2014; Cook, Holmboe, Sorensen, Berger, & Wilkinson, 2015).  As a result, a majority of the boards started reorganizing their MOC programs (Baron, 2015).

Grounded theory research done by Cook et al. (2015) found that most internal medicine and family medicine physicians perceive MOC as an unnecessarily cumbersome process that does not properly support individual and group professional development needs. Physicians perceive a lack of meaningful learning in MOC activities. Therefore, instead of being intrinsically motivated, the need for CME credits is physicians’ main motivation to participate. To address that, Cook, et al., proposed a series of changes: better integration with clinical practice, better integration between different MOC modules, relevance to individual needs, and meaningful learning.
One important finding was that physicians stated that “all phases of MOC were more effective and efficient when done as a group” (Cook et al., 2015).

Maintenance of Certification in Anesthesiology (MOCA) is being transformed to address those challenges. In 2011, the American Board of Anesthesiologists (ABA) pioneered researching ways to improve the process, and the next year it hosted a learning technology summit to discuss the best ways to utilize technology to enhance the program (ABA, 2015). Consequently, the ABA is recognized as the leader in delivering innovative MOC products, and presentations on changes they are making are being well-received. But there is still a long way to go. While ABA diplomats are concerned about the MOC formatting, they respect ABA certification, and 80% of respondents find it valuable for daily practice (Culley, Sun, Harman, & Warner, 2013). They also recognize that the ABA is investing significant efforts in improvement. As a result, McEvoy, Niconchuk, Ehrenfeld, and Sandberg (2015, p. 171) invited anesthesiologists to “think of the current MOCA system as an imperfect but evolving system that itself is under continuous QI,” and to join the efforts to improve the program.

4     Organizational and learning technology context

Thus far, a majority of CPD providers rely on a Learning Management System (LMS – if they use LMS), which has limited functionality. Such LMS systems are built around a combination of SCORM modules + files + quiz + survey + certificates, and often completely lack support for collaborative education. They can address needs of content-focused education, but cannot address needs of collaborative or networked learning. The ASA’s leadership has recognized that gap, and the ASA implemented a new Moodle-based LMS – Totara – in August 2015. Totara comes with all the collaborative features of Moodle. Therefore, it is a big change. In addition, Totara provides strong support for learning plans and organizational structure/hierarchies.^[2] 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 the perioperative team. Therefore, in addition to learning technology and practices used by anesthesiologists, the technology and practices used by nurse anesthetists, surgeons and anesthesia assistants will have an impact. The American Association of Nurse Anesthetists selected new Moodle-based LMSs in 2015. Therefore their LMS is compatible with ASA’s LMS. That opens numerous possibilities for collaboration; from cooperative course development to establishing a dynamic directory of courses that will list courses from both LMSs. The American College of Surgeons are just finalizing its LMS selection. Finally, the American Academy of Anesthesiologist Assistants plans to use the ASA’s LMS. Those selections may significantly influence the context and perspectives interviewees have on QIE/IPL. This research will help to better navigate toward improved and coordinated utilization of learning technology available to members of the perioperative team.

5     Roles and academic degrees

Understanding the evolution of roles and academic degrees in healthcare is important:

• They reflect how public and peers perceive individuals and professions.
• They involve a social contract that defines how healthcare teams work.
• The situation is rapidly changing. For example, nurse anesthetists are becoming doctors, teams are being reorganized, and interprofessional collaboration is becoming standard.

Roles and qualifications of healthcare providers have been evolving throughout history, from priests, shamans and healers, through physician-centric, patient-centric and team-based models, and finally to networked care. Arguably, different individuals and organizations may be at different stages (physician-centric, patient-centric, team-based, networked care). The stages are described below:

Physician-centric. During late 18th century, we started understanding the mechanism of diseases, and hospitals emerged as places patients were treated (Wall, 2012). The authority of the healer started to increase and the economic, social and political distance between healers and patients began to grow. Therefore, healers started to be recognized as doctors (lat. teachers) of medicine. With the increasing amount of required knowledge and tools (pharmacy and surgery, for example) the gap between what physician and patients know has also been on the rise. Furthermore, healthcare has become more complex, more industrialized. The widespread belief was that patients were too ignorant to make or participate in medical decisions (Rose, 1998). Therefore, presenting details about limitations and risks of the interventions could not only be a time-consuming endeavor, it could undermine the patient’s faith in the proposed therapy. That resulted in a very physician-centric model, where doctors would make decisions, and patients (and support staff) would silently comply with the instructions.

Patient-centered. Today, the doctor-dominated, one-sided mode is being replaced with a patient-centered alliance built upon cooperation between the doctor and the patient. In that alliance, the doctor is not only the technical expert, but also the teacher and coach helping patients to understand and manage their role in healthcare process and cope with strong emotions and dilemmas. Patients, on the other hand, can become experts in managing their chronic disease (Tattersall, 2002). Therefore, mutual respect, active participation of all parties, and shared decision-making is replacing patient passivity (Kaba & Sooriakumaran, 2007). The doctor serves as a teacher-expert who is the connection between the world of medicine and the patient’s experiences and needs.
My most recent visit to a doctor was a perfect example. After thoughtful explanation of the issue and addressing my questions, my doctor handed me a piece of paper with handwritten keywords. “Here is a list of things you can Google to learn more about the things we discussed today,” he said. “Prepare questions for the next visit.”

Team-based care has evolved as an advanced model of the patient-centered approach, where the healthcare team and patients work together to deliver optimal patient-centered care. Goldberg, Beeson, Kuzel, Love, and Carver (2013) describe it as the most important, practice-transforming tool used to provide patient-centered care. Lin, Schillinger, and Irby (2014) convincingly argue that to address extensive changes needed in practice redesign and medical education, a “share the care” paradigm is necessary. “Share the care” means empowering teams made of clinicians, non-clinicians (nurses, educators, pharmacists and medical assistants), and patients to share responsibility – so each team member can contribute to his or her maximum potential. That paradigm includes a cultural shift from “I” to “we” (Ghorob & Bodenheimer, 2012). “I” stands for the lone doctor-with-the-helpers model, where the clinician makes all decisions, assumes all responsibility and delegates tasks to other team members – helpers. On the other hand, “we” stands for sharing responsibilities, not just tasks.  “We” also stands for team-based learning where the doctor, in addition of consulting and coaching patients, teaches and mentors team members.

Networked care. Finally, networked care, or technology-enhanced team-based care, is where all participants – healthcare providers, patients and their families – collaborate on healthcare delivery. It is increasingly seen as the model of the future (Bornkessel, Furberg, & Lefebvre, 2014; Gaugler & Kane, 2015). It uses digital social media platforms and networks to connect patients and healthcare providers, empowering patients to be more involved in their personal health activities, and driving providers to improve quality of their service. That aligns perfectly with the findings by (Little et al., 2001) that, from the patients’ perspective, the three main domains of patient centeredness are: communication, partnership and health promotion. Patients perceive lack of communication as the biggest issue. For example, on average U.S. healthcare users spend 52 hours a year using online healthcare information and networks, and only one hour talking with a physician (Makovsky Health, 2013). As a result, the majority of patients experience challenges using available health information.

That is a huge opportunity. A significant body of evidence shows that engaged patients have better healthcare experiences and better health outcomes (Hibbard & Greene, 2013). Networked care can engage them and empower them to make better-informed decisions.

Proper usage of social media can help the providers address that gap. Bornkessel et al. (2014) suggests:

• Be active on social networks; listen to patients and observe trends.
• Use information therapy – prescribe appropriate information to your patients (or peers).
• Actively build opportunities for people-centered, collaborative, networked care.
• Learn about it and use it for learning.

A few issues associated with networked care, which should be addressed in advance, are confidentiality, privacy and liability. If not addressed properly, they can become minefield of legal issues. (Moses, McNeese, Feld, & Feld, 2014).

Mayo Clinic is an excellent example of networked care. They created a Social Media Network because (mayoclinic.org, 2016):

At Mayo, we believe individuals have the right and responsibility to advocate for their own health, and it’s our responsibility to help them use social networking tools to get the best information, and connect with providers as well as one another.

The migration toward networked care aligns well with what Allen and Cherrey (2000, p. 1) described 16 years ago: “Two major shifts occurring in the world are having a significant effect on how we work together, influence change and lead our organizations. The first shift is from a world of fragmentation to one of connectivity and integrated networks. The second shift is from an industrial to a knowledge era…All of us need to explore new ways of working that keep pace with this networked knowledge era.”

That is exactly what this thesis is doing – exploring how anesthesia teams can work and learn better in an era of networked knowledge.

6     Medical home

That leads us to another trend, with arguably the same direction – medical home. Medical home is a team-based healthcare delivery model that utilizes collaboration to deliver high-quality, comprehensive and continuous care. Medical home is a microsystem made up of groups that participate in immediate delivery of care and interact directly with patients. The structure comprises physicians, nurses or pharmacists, and groups that support the microsystem, like laboratory, IT and leadership professionals (Batalden, Nelson, Edwards, Godfrey, & Mohr, 2003).

The ASA recently launched for surgical care a specific version of medical home called perioperative surgical home (PSH). Schweitzer, Fahy, Leib, Rosenquist, and Merrick (2013, p. 58) describes PSH is a collaborative, interprofessional and “team-based system of coordinated care that guides the patient throughout the entire surgical experience,” from diagnosis to recovery (Figure 4). The PSH model of care is receiving significant attention. As of now, PSH is one of the ASA’s top priorities. For example, it was the official theme of the ASA’s 2014 Annual Meeting (~15,000 participants), and the dominant theme during the 2015 Annual Meeting.

Perioperative Surgical Home (ASAHQ.org, 2014)

Figure 3. Perioperative Surgical Home (ASAHQ.org, 2014)

Where did the medical home idea start? What can we learn from history?
Since PSH is a new version of medical home, we can learn a lot from the history of medical home.
Patient-centered medical home was first introduced by the American Academy of Pediatrics (AAP). In 1974, the AAP Council on Pediatric Practice proposed a policy statement titled “Fragmentation of Health Care Services for Children”(AAP, 1974). The policy statement was not accepted, but the document clearly indicated that 1) fragmented care is inefficient, expensive and can be harmful for health, and 2) medical home is an important tool to address fragmented care. (Sia, Tonniges, Osterhus, & Taba, 2004).

During the following decade, as the medical home concept gained greater recognition, obstacles to implementing it become noticeable. B. Moore and Tonniges (2004) explained that three major barriers were 1) unfamiliarity of pediatricians with the medical home concept; 2) communication and coordination between professionals; and 3) reimbursement for new tasks associated with medical home.  (Kain et al., 2014) reports that the same challenges face implementation of PSH today. Therefore, it is fair to assume that insight in medical home implementation can enhance implementation of PSH.

It is interesting to notice how the term medical home has evolved since 1974.
At first, it was envisioned as a physical place that provided all medical information relevant to that patient ( i.e., centralized medical records). Between the 1960s and the 1980s, gaining access to healthcare data was a bottleneck and the medical home model then provided a workable answer to that challenge. As we were improving access to healthcare data, it become obvious that consolidated healthcare data is just a first step; better coordination among healthcare professionals, families and patients was and is still needed. That is especially noticeable now, when technology can provide instantaneous access to needed medical information.
Therefore the term medical home now means a comprehensive, team-based healthcare delivery system, where well-coordinated multiprofessional healthcare teams, in partnership with patients and their families, deliver healthcare that is accessible, coordinated, comprehensive, compassionate, culturally effective, cost-effective and, most importantly, centered on the patient and the patient’s family (AAP, 2002; Sia et al., 2004).

That evolution is in many ways similar to the evolution described under roles and degrees, and if we assume that participants communicate via social media, it leads to networked care.

Table 2. Evolutions of healthcare team roles and medical home – different origins, but the same end.

PSH Collaborative. ASA initiated a PSH learning collaborative (ASAHQ.org, American Society of Anesthesiologists, 2014a) to bring together healthcare organizations from across the U.S. to work on development, testing and implementation of the PSH model. It provides face-to-face and online networked and collaborative learning opportunities. It has two generations/classes. Learning Collaborative 1.0 was launched on July 1, 2014, and was scheduled to end by the beginning of 2016. Learning collaborative 2.0 is scheduled to start in April 2016 and last for two years. Each collaborative is a time-limited (2 years) community of practice, where numerous institutions work together mainly via live, phone and web conference meetings.
Opportunity? The existing learning collaborative framework can serve as a springboard for a more open, continuous and technology-enhanced community of practice. Use of asynchronous online collaborative tools (social media) will be the main addition to the existing toolset. Until August 2015, the ASA didn’t have technology that could support such a community. During 2016, significant efforts were invested in customizing and learning about the framework so a collaborative learning community could be properly supported. We have the technology and intention in place. Therefore, at this moment, the critical elements needed are people. This is ultimately a social endeavor, and for successful outcomes we need an engaged and properly supported learning community. This paper will research what PSH professions think about that option.

PSH and IPL. Since effective IPL enables effective collaborative practice (WHO, 2010) we can assume that IPL may be an important part of this interprofessional model. PSH has the same three goals as the national healthcare transformation (ASAHQ.org, American Society of Anesthesiologists, 2014b): 1) improving health care delivery (patient experience); 2) improving health; and 3) reducing cost. That suggests that the stated goal of the Macy conference of Aligning IPL with Clinical Practice Redesign and reforming CPD to incorporate IPL can be achieved  in this context (Macy, 2013).

However, probably due to the aforementioned challenges associated with QIE/IPL in the U.S., QIE/IPL in the U.S. anesthesiology context is in its early stages.

ASA’s cautious approach to IPL may be a reflection of the extensive efforts needed to make it happen and potential mistrust between anesthesiologists and nurse anesthetists described earlier. In addition to that, the Institute of Medicine (IoM) workshop on IPL and collaboration has recognized that successful implementation of IPL requires these essentials: leadership from the top, extensive planning, repeated IPL experience through the educational continuum, focus on real-life work, utilization of new technologies, and strong faculty development (IoM & 2013). Strong faculty development and repeated IPL experiences seem to be the biggest obstacles at this moment. To address that, ASA plans to create a faculty development course in 2016.

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• Singh, G., McPherson, M., & Sandars, J. (2014). Healthcare Electronic Continuing Professional Development: 5 Key Design Features to Improve Impact. In G. Trentin (Ed.), Network-based Continuing Medical Education: Social Media and Professional Development (pp. 171-192). Hauppauge, NY, USA: Science Publishers Inc.
• Strasburger, V. C. (2011). Ain’t Misbehavin’: Is It Possible to Criticize Maintenance of Certification (MOC)? Clinical pediatrics, 50(7), 587-590.
• Tattersall, R. (2002). The expert patient: a new approach to chronic disease management for the twenty-first century. Clinical Medicine, 2(3), 227-229.
• Wall, B. M. (2012). History of hospitals. Nursing History and Health care.
• WHO, World Health Organization. (2010). Framework for Action on Interprofessional Education and Collaborative Practice. Retrieved from http://www.who.int/hrh/resources/framework_action/en/
• Woolf, S. H., & Aron, L. (2013). US Health in International Perspective:: Shorter Lives, Poorer Health: National Academies Press.

[1] Educational psychologist Director of The Centre for Medical Education in Context (CenMEDIC) and Emeritus Professor of Education in Medicine at The Open University in the United Kingdom.

[2] Totara: Frequently Asked Questions for Positions, Organizations and Competency Hierarchies http://help.totaralms.com/FAQs_for_Hierarchies.htm

Literature Review – Key Points

• Quality improvement education (QIE) and interprofessional learning (IPL) are from a macro-perspective very interwoven and we can perceive them as two lenses observing the same healthcare learning system.
• Medical home models are built around the concept of networked care – where all healthcare providers, patients and their families work as one well-connected team.
• In the modern digital and networked world, any form of experiential learning uses some form of networked learning.
• Historically, strong societal factors have been obstructing successful implementation of QIE and IPL. However, the world is changing – it is becoming more collaborative, networked and, ultimately quality-focused. New societal drivers are switching the balance.
• Change is a complex socio-politico-economical process. Without careful planning, and well-defined benefits, the resistance to change can be strong.
• Continuing medical education (CME) is evolving from didactic lectures focused on clinical practice, and designed for clinicians, to continuing professional development (CPD). CPD is a much broader term that covers a holistic approach to professional development of all healthcare professionals (as individuals, teams and systems).
• Continuing medical education research is heavily influenced by a quantitative, positivist research approach used in medicine and sponsored by the pharmaceutical industry. Therefore, very often it is at odds with traditions established by social science educational research.

Dictionary

This paper is focused on continuing professional development of clinicians in the United States. Therefore, the terminology and concepts discussed are specific to that context and culture.

Key concepts used are:

Interprofessional Learning (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).

Quality Improvement Education (QIE) is a system-wide educational framework focused on four goals: better care, better health, reduced-cost and better professional development (Batalden & Davidoff, 2007). Its holistic system design approach tackles all potential barriers for quality improvement (QI), attempting to make permanent system-wide changes through coordinated and continuous efforts of all stakeholders – healthcare professionals, patients, researchers, educators and the public.

QIE/IPL is a view on healthcare learning organization that perceives QIE and IPL as two integrated parts of the same system.

Quality improvement is the combined and continuous effort of all stakeholders to improve outcomes, system performance and professional development (Batalden & Davidoff, 2007 ); it is a change management approach that utilizes self-reflection, assessment of needs and gaps, and is focused on improvement in a multifaceted manner (The Health Foundation, 2012).

Learning is the process where individuals, teams, organizations or networks develop knowledge, skills and competencies to improve understandings, perspectives or practices (Nisbet, Lincoln, & Dunn, 2013, p. 469)

Medical home is a team-based healthcare delivery mode build around patient-centered, coordinated and integrated (networked) care.

Perioperative Surgical Home (PSH) is a surgical care-focused version of medical home. It serves as a patient-centered, team-based, coordinated, practice model encompassing all elements of surgical care – from decision for surgery to complete recovery. It is delivered through interprofessional collaboration among all clinical and non-clinical staff, patients and their families.

Networked care is a health delivery model that builds on the team-based, patient-centered medical home concept, and extends it by encouraging use of digital collaborative tools to listen, inform, collaborate, learn and network (Gaugler & Kane, 2015).

Physician anesthesiologist is a physician who has completed an accredited residency program in anesthesiology after medical school training. It requires 12 years (4 undergraduate + 4 graduate + 4 residency) of education.

Nurse anesthetist is a certified registered nurse anesthetist (CRNA) who has acquired master-level education and board certification in anesthesia. Nurse anesthetist programs in the U.S. are moving to requiring doctorate degrees for new nurse anesthetists.

Continuing Medical Education (CME) is a uni-professional approach to continuing education of physicians, mainly built around content-focused didactic formatting.

Continuing Professional Development (CPD) refers to professional development of all healthcare providers. It is a much broader term than CME. It covers all methods we can use to support professional development of individuals, team and systems. The CPD term is perceived as more complete and up-to-date than CME, but CME is still more widely used – especially for uni-professional education of physicians. Therefore, often those terms are used interchangeably or combined as CME/CPD. In this paper, both terms will be used.

References

• Batalden, P. B., & Davidoff, F. (2007). What is “quality improvement” and how can it transform healthcare? Quality and safety in health care, 16(1), 2-3.
• CAIPE, Centre For The Advancement Of Interprofessional Education. (2002). Interprofessional Education – The definition.   Retrieved from http://caipe.org.uk/resources/defining-ipe/
• Gaugler, J., & Kane, R. L. (2015). Family Caregiving in the New Normal: Elsevier Science.
• Nisbet, G., Lincoln, M., & Dunn, S. (2013). Informal interprofessional learning: an untapped opportunity for learning and change within the workplace. Journal of interprofessional care, 27(6), 469-475.
• The Health Foundation. (2012). Quality improvement training for healthcare professionals, Evidence scan. Retrieved from http://www.health.org.uk/: http://www.health.org.uk/sites/default/files/QualityImprovementTrainingForHealthcareProfessionals.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: