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.

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.“

References 

• Anderson, J. (2004). Medical teacher 25th anniversary series multiple-choice questions revisited. Medical teacher, 26(2), 110-113.
• archemedx.com. (2013). 2013 Healthcare Professional Continuing Education Preference Survey.   Retrieved from http://www.archemedx.com/blog/2013-clinician-continuing-education-preference-survey/
• ASA, Americaln Society of Anesthesiologists (1973). ASA Refresher Courses in Anesthesiology – Volume 1. ASA Refresher Courses in Anesthesiology, 1(1), 1-167.
• Bailey, P. H., Mossey, S., Moroso, S., Cloutier, J. D., & Love, A. (2012). Implications of multiple-choice testing in nursing education. Nurse Education Today, 32(6), e40-e44. doi:http://dx.doi.org/10.1016/j.nedt.2011.09.011
• Balmer, J. T. (2013). The transformation of continuing medical education (CME) in the United States. Advances in medical education and practice, 4, 171.
• Bates, A. W. T. (2008). Transforming distance education through new technologies. In T. Bates (Ed.).
• Brown, C. R., & Fleisher, D. S. (2014). The Bi‐Cycle Concept—Relating Continuing Education Directly to Patient Care. Journal of Continuing Education in the Health Professions, 34(2), 141-148.
• Campbell, E. G., & Rosenthal, M. (2009). Reform of continuing medical education: investments in physician human capital. JAMA, 302(16), 1807-1808.
• Cheston, C. C., Flickinger, T. E., & Chisolm, M. S. (2013). Social media use in medical education: a systematic review. Academic Medicine, 88(6), 893-901.
• Colbeck, C. L. (1998). Merging in a seamless blend: How faculty integrate teaching and research. Journal of Higher Education, 647-671.
• Cook, D. A., Holmboe, E. S., Sorensen, K. J., Berger, R. A., & Wilkinson, J. M. (2015). Getting Maintenance of Certification to Work: A Grounded Theory Study of Physicians’ Perceptions. JAMA internal medicine, 175(1), 35-42.
• Cooke, M., Irby, D. M., & O’Brien, B. C. (2010). Educating physicians: a call for reform of medical school and residency (Vol. 16). San Francisco, CA, USA: John Wiley & Sons.
• Cooke, M., Irby, D. M., Sullivan, W., & Ludmerer, K. M. (2006). American Medical Education 100 Years after the Flexner Report. New England Journal of Medicine, 355(13), 1339-1344. doi:doi:10.1056/NEJMra055445
• Cruess, R. L., Cruess, S. R., & Steinert, Y. (2015). Amending Miller’s Pyramid to Include Professional Identity Formation. Academic medicine: journal of the Association of American Medical Colleges.
• Davis, D., O’Brien, M. A., Freemantle, N., Wolf, F. M., Mazmanian, P., & Taylor-Vaisey, A. (1999). Impact of formal continuing medical education: Do conferences, workshops, rounds, and other traditional continuing education activities change physician behavior or health care outcomes? JAMA, 282(9), 867-874. doi:10.1001/jama.282.9.867
• Dornan, T. (2005). Osler, Flexner, apprenticeship and’the new medical education’. J R Soc Med, 98(3), 91-95.
• Dutton, R. P. (2014). Quality management and registries. Anesthesiology clinics, 32(2), 577-586.
• Flexner, A. (1908). The American college: a criticism: Century Company.
• Flexner, A. (1910). Medical education in the United States and Canada bulletin number four (The Flexner Report). New York (NY): The Carnegie Foundation for the Advancement of Teaching.
• Flexner, A. (1912). Medical education in Europe: a report to the Carnegie Foundation for the Advancement of Teaching: Carnegie Foundation for the Advancement of Teaching.
• Flynn, L., Jalali, A., & Moreau, K. A. (2015). Learning theory and its application to the use of social media in medical education. Postgraduate medical journal, postgradmedj-2015-133358.
• Frederiksen, N. (1984). The real test bias: Influences of testing on teaching and learning. American psychologist, 39(3), 193.
• Gikas, J., & Grant, M. M. (2013). Mobile computing devices in higher education: Student perspectives on learning with cellphones, smartphones & social media. The Internet and Higher Education, 19, 18-26.
• Goldie, J. (2012). The formation of professional identity in medical students: Considerations for educators. Medical teacher, 34(9), e641-e648.
• Hager, M., Russell, S., Fletcher, S. W., & Macy Jr, J. (2008). Continuing education in the health professions: improving healthcare through lifelong learning: Josiah Macy, Jr. Foundation.
• Harris, J. M., Sklar, B. M., Amend, R. W., & Novalis‐Marine, C. (2010). The growth, characteristics, and future of online CME. Journal of Continuing Education in the Health Professions, 30(1), 3-10.
• Hlede, V. (2015). Interprofessional Learning: Anesthesiologists’ Perspectives. Assignment, Doctoral Programme in E-Research and Technology Enhanced Learning. Department of Educational Research. Lancaster University.
• Holm, H. A. (1998). Quality issues in continuing medical education. British Medical Journal, 316(7131), 621-624. doi:10.1136/bmj.316.7131.621
• IoM. (1972). Institute of Medicine: Educating for the health team. Washington, DC.: ERIC Clearinghouse.
• 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
• IoM, & , Institute of Medicine. (2003). Health Professions Education: A Bridge to Quality (E. Knebel & A. C. Greiner Eds.): National Academies Press.
• IoM, & , Institute of Medicine. (2009). Conflict of interest in medical research, education, and practice (M. J. Field & B. Lo Eds.). 500 Fifth Street, N.W. Washington, DC 20001: National Academies Press.
• Josseran, L., & Chaperon, J. (2001). History of continuing medical education in the United States. Presse medicale (Paris, France: 1983), 30(10), 493-497.
• Karle, H., Paulos, G., & Wentz, D. K. (2012). Continuing Professional Development: Concept, Origins, and Rationale. In D. K. Wentz (Ed.), Continuing Medical Education: Looking Back, Planning Ahead (pp. 281-289). Hanover, NH, US and London: Dartmouth College Press.
• Lin, S. Y., Schillinger, E., & Irby, D. M. (2014). Value-Added Medical Education: Engaging Future Doctors to Transform Health Care Delivery Today. Journal of general internal medicine, 30(2), 150-151.
• Makovsky Health. (2013, Sept. 9, 2013). Online Health Research Eclipsing Patient-Doctor Conversations.   Retrieved from http://www.makovsky.com/insights/articles/25-insights/articles/article/229-as-the-web-goes-mobile-healthcare-stands-still
• Mehta, N. B., Hull, A. L., Young, J. B., & Stoller, J. K. (2013). Just Imagine: New Paradigms for Medical Education. Academic Medicine, 88(10), 1418-1423 1410.1097/ACM.1410b1013e3182a1436a1407.
• Miller, G. E. (1990). The assessment of clinical skills/competence/performance. Academic Medicine, 65(9), S63-67.
• Mitchell, S., Simonds, A., Andreas, S., Bonsignore, M. R., Cooper, B., Donic, V., . . . Prest, G. (2015). Introducing a core curriculum for respiratory sleep practitioners. Breathe, 11(1), 50.
• Moore, D. E., Green, J. S., & Gallis, H. A. (2009). Achieving desired results and improved outcomes: integrating planning and assessment throughout learning activities. Journal of Continuing Education in the Health Professions, 29(1), 1-15.
• Peters, O. (2002). Distance education in transition: New trends and challenges: BIS Verlag.
• Pickering, S. G. (1979). Against multiple choice questions. Medical teacher, 1(2), 84-86.
• 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.
• Rodriguez-Paz, J., Kennedy, M., Salas, E., Wu, A., Sexton, J., Hunt, E., & Pronovost, P. (2009). Beyond “see one, do one, teach one”: toward a different training paradigm. Quality and safety in health care, 18(1), 63-68.
• Roediger III, H. L., & Marsh, E. J. (2005). The positive and negative consequences of multiple-choice testing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 31(5), 1155.
• Russell, B., Maher, G., Prochaska, J. O., & Johnson, S. S. (2012). Strategic approaches to continuing medical education: applying the transtheoretical model & diffusion of innovation theory. CE Measure, 6(3), 27-31.
• Schmitt, M. H., Baldwin, D. C., & Reeves, S. (2012). Continuing Interprofessional Education; Collaborative Learning for Collaborative Practice. In D. K. Wentz (Ed.), Continuing Medical Education: Looking Back, Planning Ahead (pp. 281-289). Hanover, NH, USA, and London: Dartmouth College Press.
• Shershneva, M. B., Mullikin, E. A., Loose, A.-S., & Olson, C. A. (2008). Learning to collaborate: A case study of performance improvement CME. Journal of Continuing Education in the Health Professions, 28(3), 140-147. doi:10.1002/chp.181
• Shojania, K. G., Silver, I., & Levinson, W. (2012). Continuing medical education and quality improvement: a match made in heaven? Ann Intern Med, 156(4), 305-308.
• Taylor, J. C. (2001). Fifth generation distance education. Instructional Science and Technology, 4(1), 1-14.
• Tetzlaff, J. E. (2007). Assessment of competence in anesthesiology. Current Opinion in Anesthesiology, 22(6).
• Vozenilek, J., Huff, J. S., Reznek, M., & Gordon, J. A. (2004). See one, do one, teach one: advanced technology in medical education. Academic Emergency Medicine, 11(11), 1149-1154.
• Weaver, R., Peters, K., Koch, J., & Wilson, I. (2011). ‘Part of the team’: professional identity and social exclusivity in medical students. Medical Education, 45(12), 1220-1229.
• Webster-Wright, A. (2009). Reframing professional development through understanding authentic professional learning. Review of Educational Research, 79(2), 702-739.
• WFME. (2003). Continuing Professional Development (CPD) of Medical Doctors – WFME Global Standards for Quality Improvement. Retrieved from http://www.who.int/workforcealliance/knowledge/toolkit/47/en/index.html
• Wood, T. (2009). Assessment not only drives learning, it may also help learning. Medical Education, 43(1), 5-6. doi:10.1111/j.1365-2923.2008.03237.x
• Wutoh, R., Boren, S. A., & Balas, E. A. (2004). ELearning: a review of Internet‐based continuing medical education. Journal of Continuing Education in the Health Professions, 24(1), 20-30.
• Wynia, M. K., Papadakis, M. A., Sullivan, W. M., & Hafferty, F. W. (2014). More than a list of values and desired behaviors: A foundational understanding of medical professionalism. Academic Medicine, 89(5), 712-714.

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.

References

• AAMC, Association of American Medical Colleges (2014). Medical Student Education: Debt, Costs, and Loan Repayment Fact Card. Retrieved from https://www.aamc.org/download/152968/data/debtfactcard.pdf
• AAP. (1974). Fragmentation of Health Care Services for Children. Evanston, IL, USA: American Academy of Pediatrics.
• AAP. (2002). The Medical Home – Medical Home Initiatives for Children With Special Needs Project Advisory Committee. Pediatrics, 110(1), 184-186.
• AAPS, Association of American Physicians and Surgeons. (2014, Oct 24, 2014). AAPS Takes MOC to Court.   Retrieved from AAPS Takes MOC to Court
• ABA, The American Board of Anesthesiology. (2015). Changing the Paradigm – A New Approach to Assessment in Maintenance of Certification. MOCA Summit White Paper – The American Board of Anesthesiology.
• ahrq.gov. (2014). Interim Update on 2013 Annual Hospital-Acquired Condition Rate and Estimates of Cost Savings and Deaths Averted From 2010 to 2013. Retrieved from USA: http://www.ahrq.gov/sites/default/files/wysiwyg/professionals/quality-patient-safety/pfp/interimhacrate2013.pdf
• Allen, K. E., & Cherrey, C. (2000). Systemic leadership: enriching the meaning of our work: University Press of America, Lanham, MD, USA.
• ASAHQ.org. (2014). Diagram of Perioperative Surgical Home. In PSH (Ed.), ASAHQ.org.
• ASAHQ.org, American Society of Anesthesiologists. (2014a). Learning Collaborative to Advance the Perioperative Surgical Home (PSH) [Press release]. Retrieved from http://www.asahq.org/~/media/PSHMicro/May2014PSH_Information.pdf
• ASAHQ.org, American Society of Anesthesiologists. (2014b). Perioperative Surgical Home Overview.   Retrieved from http://www.asahq.org/psh
• Balmer, J. T. (2013). The transformation of continuing medical education (CME) in the United States. Advances in medical education and practice, 4, 171.
• Baron, R. J. (2015, 2/3/2015). ABIM Announces Immediate Changes to MOC Program.   Retrieved from http://www.abim.org/news/abim-announces-immediate-changes-to-moc-program.aspx
• Batalden, P. B., Nelson, E. C., Edwards, W. H., Godfrey, M. M., & Mohr, J. J. (2003). Microsystems in health care: Part 9. Developing small clinical units to attain peak performance. Joint Commission Journal on Quality and Patient Safety, 29(11), 575-585.
• Berwick, D. M. (2007). Eating Soup with a Fork. 19th National Forum on Quality Improvement in Healhtcare keynote address.  Retrieved from http://www.ihi.org/education/webtraining/ondemand/soupwithfork/Pages/default.aspx
• Berwick, D. M., & Hackbarth, A. D. (2012). Eliminating waste in US health care. JAMA, 307(14), 1513-1516.
• Bornkessel, A., Furberg, R., & Lefebvre, R. C. (2014). Social media: opportunities for quality improvement and lessons for providers—a networked model for patient-centered care through digital engagement. Current cardiology reports, 16(7), 1-9.
• Brooks, M. A. (2009). Medical education and the tyranny of competency. Perspectives in Biology and Medicine, 52(1), 90-102.
• Centor, R. M., Fleming, D. A., & Moyer, D. V. (2014). Maintenance of certification: beauty is in the eyes of the beholder. Ann Intern Med, 161(3), 226-227.
• Cervero, R. M., & Gaines, J. K. (2014). Effectiveness of Continuing Medical Education: Updated Syntheses of Systematic Reviews. Retrieved from http://www.accme.org/sites/default/files/2014_Effectiveness_of_Continuing_Medical_Education_Cervero_and_Gaines_0.pdf
• Cervero, R. M., & Moore Jr., D. E. (2011). The Cease Smoking Today (CS2day) initiative: A guide to pursue the 2010 IOM report vision for CPD. Journal of Continuing Education in the Health Professions, 31(S1), S76-S82.
• Clark, A. M. (1998). The qualitative‐quantitative debate: moving from positivism and confrontation to post‐positivism and reconciliation. Journal of Advanced Nursing, 27(6), 1242-1249.
• Clegg, S. (2005). Evidence‐based practice in educational research: A critical realist critique of systematic review. British journal of sociology of education, 26(3), 415-428.
• COA, The Council on Accreditation of Nurse Anesthesia Educational Programs. (2007). COA Position Statements.   Retrieved from http://home.coa.us.com/about/Pages/COA-Position-Statements.aspx
• Concato, J., Shah, N., & Horwitz, R. I. (2000). Randomized, controlled trials, observational studies, and the hierarchy of research designs. New England Journal of Medicine, 342(25), 1887-1892.
• Cook, D. A., Holmboe, E. S., Sorensen, K. J., Berger, R. A., & Wilkinson, J. M. (2015). Getting Maintenance of Certification to Work: A Grounded Theory Study of Physicians’ Perceptions. JAMA internal medicine, 175(1), 35-42.
• Culley, D. J., Sun, H., Harman, A. E., & Warner, D. O. (2013). Perceived value of Board certification and the Maintenance of Certification in Anesthesiology Program (MOCA®). J Clin Anesth, 25(1), 12-19.
• Davis, K., Stremikis, K., Schoen, C., & Squires, D. (2014). Mirror, Mirror on the Wall, 2014 Update: How the US Health Care System Compares Internationally.   Retrieved from http://www.commonwealthfund.org/publications/fund-reports/2014/jun/mirror-mirror
• Diamond, L., Kues, J., & Sulkes, D. (2015). The Quality Improvement Education (QIE) Roadmap: A Pathway to Our Future. Retrieved from http://www.acehp.org/p/cm/ld/fid=209
• Diaz, F. G. (2015). How Obamacare Will Affect You: An Editorial. Neurosurgery, 62, 81-91.
• Duhem, P. M. M. (1991). The aim and structure of physical theory (Vol. 13): Princeton University Press.
• Elliott, J. (2001). Making evidence‐based practice educational. British educational research journal, 27(5), 555-574.
• Fox, R. D. (2012). Four Pillars in the Evolution of Continuing Medical Education. In D. K. Wentz (Ed.), Continuing Medical Education: Looking Back, Planning Ahead (pp. 193-201). Hanover, NH, USA, and London: Dartmouth College Press.
• Gaugler, J., & Kane, R. L. (2015). Family Caregiving in the New Normal: Elsevier Science.
• Ghorob, A., & Bodenheimer, T. (2012). Share the care™: building teams in primary care practices. The Journal of the American Board of Family Medicine, 25(2), 143-145.
• Goldberg, D. G., Beeson, T., Kuzel, A. J., Love, L. E., & Carver, M. C. (2013). Team-based care: a critical element of primary care practice transformation. Population health management, 16(3), 150-156.
• Goldenberg, M. J. (2006). On evidence and evidence-based medicine: lessons from the philosophy of science. Social Science & Medicine, 62(11), 2621-2632.
• Gray, B. M., Vandergrift, J. L., Johnston, M. M., Reschovsky, J. D., Lynn, L. A., Holmboe, E. S., . . . Lipner, R. S. (2014). Association between imposition of a Maintenance of Certification requirement and ambulatory care-sensitive hospitalizations and health care costs. JAMA, 312(22), 2348-2357.
• Hansen, J., & Philp, E. (2014). State Beat: 2014 State Policy Highlights. American Society of Anesthesiologists, Newsletter, 78(12).
• Hawkes, N. (2013). Educational “events” have only a small part in how doctors learn, conference is told. British Medical Journal, 347.
• Hayes, J. C. (2012). Anesthesiologist-CRNA Teamwork Common, but Groups at Odds. Medscape Anesthesiology.
• healthsystemtracker.org. (2016). Mortality rates have fallen steadily in the U.S. and in comparable OECD countries. Peterson-Kaiser Health System Tracker.  Retrieved from http://www.healthsystemtracker.org/chart-collection/how-does-the-quality-of-the-u-s-healthcare-system-compare-to-other-countries/
• Hibbard, J. H., & Greene, J. (2013). What The Evidence Shows About Patient Activation: Better Health Outcomes And Care Experiences; Fewer Data On Costs. Health Affairs, 32(2), 207-214. doi:10.1377/hlthaff.2012.1061
• 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.
• Johnstone, R. E. (2015, 4/10/2015). ASA Membership: Some Say No. Anesthesiology News. Retrieved from http://www.anesthesiologynews.com/ViewArticle.aspx?d=Commentary&d_id=449&i=April+2015&i_id=1168&a_id=30903
• Kaba, R., & Sooriakumaran, P. (2007). The evolution of the doctor-patient relationship. International Journal of Surgery, 5(1), 57-65.
• Kain, Z. N., Vakharia, S., Garson, L., Engwall, S., Schwarzkopf, R., Gupta, R., & Cannesson, M. (2014). The Perioperative Surgical Home as a Future Perioperative Practice Model. Anesthesia & Analgesia, 118(5), 1126-1130. doi:10.1213/ane.0000000000000190
• Karle, H., Paulos, G., & Wentz, D. K. (2012). Continuing Professional Development: Concept, Origins, and Rationale. In D. K. Wentz (Ed.), Continuing Medical Education: Looking Back, Planning Ahead (pp. 281-289). Hanover, NH, US and London: Dartmouth College Press.
• Kempen, P. M. (2012). Maintenance of Certification (MOC), and Now Maintenance of Licensure (MOL): Wrong Methodologies – Wrong Methodologies to Improve Medical Care. Journal of American Physicians and Surgeons, 17(1), 12-14.
• Kempen, P. M. (2014). Maintenance of Certification and Licensure: regulatory capture of medicine. Anesthesia & Analgesia, 118(6), 1378-1386.
• Kessler, G. (2015, April 1, 2015). Obama’s claim the Affordable Care Act was a ‘major reason’ in preventing 50,000 patient deaths. Fact Checker.  Retrieved from https://www.washingtonpost.com/news/fact-checker/wp/2015/04/01/obamas-claim-the-affordable-care-act-was-a-major-reason-in-preventing-50000-patient-deaths/
• Lin, S. Y., Schillinger, E., & Irby, D. M. (2014). Value-Added Medical Education: Engaging Future Doctors to Transform Health Care Delivery Today. Journal of general internal medicine, 30(2), 150-151.
• Little, P., Everitt, H., Williamson, I., Warner, G., Moore, M., Gould, C., . . . Payne, S. (2001). Preferences of patients for patient centred approach to consultation in primary care: observational study. British Medical Journal, 322(7284), 468.
• 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.
• Mahoney, J., & Goertz, G. (2006). A tale of two cultures: Contrasting quantitative and qualitative research. Political Analysis, 14(3), 227-249.
• Makovsky Health. (2013, Sept. 9, 2013). Online Health Research Eclipsing Patient-Doctor Conversations.   Retrieved from http://www.makovsky.com/insights/articles/25-insights/articles/article/229-as-the-web-goes-mobile-healthcare-stands-still
• mayoclinic.org. (2016). About MCSMN. Mayo Clinic Social Media Network.  Retrieved from http://socialmedia.mayoclinic.org/about-mcsmn/
• McEvoy, M. D., Niconchuk, J. A., Ehrenfeld, J. M., & Sandberg, W. S. (2015). Maintenance of Certification in Anesthesiology Part 4: Improvement in Medical Practice. Advances in Anesthesia, 33(1), 157-173.
• Moore, B., & Tonniges, T. F. (2004). The “every child deserves a medical home” training program: more than a traditional continuing medical education course. Pediatrics, 113(Supplement 4), 1479-1484.
• Moore, D. E., Bennett, N., & Mann, K. V. (2012). Research in Continuing Medical Education In D. K. Wentz (Ed.), Continuing Medical Education: Looking Back, Planning Ahead (pp. 177-187). Hanover, NH, US and London: Dartmouth College Press.
• Moses, R. E., McNeese, L. G., Feld, L. D., & Feld, A. D. (2014). Social media in the health-care setting: benefits but also a minefield of compliance and other legal issues. The American journal of gastroenterology, 109(8), 1128-1132.
• Nietzsche, F., Bittner, R., & Sturge, K. (2003). Nietzsche: Writings from the Late Notebooks: Cambridge University Press.
• Norman, A.-C. (2013). The Implicit or Explicit Character of Negotiation: how Quality Improvements are discussed in Communities of Practicein Health Care. Paper presented at the Microsystems in Healthcare-a scientific perspective 2013.
• O’Gara, P. T., & Oetgen, W. J. (2014). The American College of Cardiology’s Response to the American Board of Internal Medicine’s Maintenance of Certification Requirements. Journal of the American College of Cardiology, 64(5), 526-527.
• Rose, A. M. (1998). Human behavior and social processes: An interactionist approach. Milton Park Abingdon Oxfordshire OX14 4RW, UK: Routledge, Houghton Miffin Company.
• Schroeder, S. A., & Frist, W. (2013). Phasing out fee-for-service payment. New England Journal of Medicine, 368(21), 2029-2032.
• Schweitzer, M., Fahy, B., Leib, M., Rosenquist, R., & Merrick, S. (2013). The perioperative surgical home model. American Society of Anesthesiologists, Newsletter, 77(6), 58-59.
• Sia, C., Tonniges, T. F., Osterhus, E., & Taba, S. (2004). History of the medical home concept. Pediatrics, 113(Supplement 4), 1473-1478.
• 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

Indicative thesis contents

Table of contents will contain the following elements:

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 will include a clear statement of the research goals, format and ethical considerations. I will make clear that involvement in the research is voluntary; their participation in the study will be anonymous; the results will be presented in a way that assures confidentiality. They will be informed that they can cease participating at any time and ask that their data be destroyed. Data will be stored in a password-protected computer. Users will explicitly be asked for permission to use transcription services. If I do not receive that permission, I will transcribe the interviews myself. Since it is phenomenographic research, I will inform them that there are no right or wrong answers (Daly, 2008).

The ethics for this study were submitted for approval to Lancaster University, the Department of Educational Research. In addition, I will request approval by the ASA Committee on Professional Oversight.

Reference:

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

Data analysis

Data analysis will rely on three segments (Figure 5):

1. Phenomenographic research will draw a picture of how QIE/IPL is perceived. My goal is to make the process as collaborative, iterative and transparent as possible/approved. Therefore, in addition to the standard phenomenographic method illustrated below, to evaluate the findings I will 1) organize a follow-up interview with selected participants and 2) share findings with a few leaders and the public (if approved) and ask for feedback. If there are moderate differences between 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 will be 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 get insight into what is possible in reality. For example, in my most 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 doesn’t reflect that.
3. Interaction between groups and existing and potential QIE/IPL projects will be analyzed through activity theory, so we can get a better picture of interprofessional activities that at this moment shape perceptions of each profession.

Figure 5. Data analysis.

Reference

Hlede, V. (2015). Interprofessional Learning: Anesthesiologists’ Perspectives. Assignment, Doctoral Programme in E-Research and Technology Enhanced Learning. Department of Educational Research. Lancaster University.