There are a number of theories that can be used to define and analyze IPL (Hean, Craddock, Hammick, & Hammick, 2012) and QIE. The approach to theory in papers on QIE/IPL has evolved from not using any theory at all, to using multiple theories to explain the concept. However, that progression has been very gradual. Even today, significant numbers of CME/CPD papers do not reference theory (Curtis A. Olson, 2013). QIE/IPL papers, as a subset of that group, follow the same trend.
As described below, in most cases, a specific theory can describe just part of the process. Therefore we have to combine theories. Relevant theories can be categorized primarily as theories that explain QIE/IPL educational process, and theories that describe interprofessional QI practices. A secondary level of classification, mainly based on historical divisions, are theories related to QIE and theories related to IPL.
QI theory. The value and function of theory in healthcare quality improvement has been seriously neglected (Davidoff, Dixon-Woods, Leviton, & Michie, 2015). At the same time, factors influencing sustainability of QI interventions have been poorly understood (Hovlid, Bukve, Haug, Aslaksen, & von Plessen, 2012). That is a huge issue – very often causing QI interventions to fail. Following such QI intervention, returning to old underperforming work practices is a significant waste of resources and, in the long run, can fuel resistance to future/better QI initiatives. Therefore, more vigorous and better-informed use of theory is essential to strengthen QIE/IPL programs, ensure vaid assessment of their impact, and promote their sustainability and generalizability of outcomes (Davies, Walker, & Grimshaw, 2010).
Role of theory. Unfortunately, theory is usually perceived as something mystical and impractical; something even quality professionals do not want deal with. That contradicts practice needs. Theory or “the reasons why things are happening” is intimately integrated into almost all of our activities. Theories may be formal or informal, public and shared, or private. Yet theories drive our decisions and shape our impact (Hean et al., 2012). Whether the theory says: “This is how it has been always done – and therefore we should not change it,” whether it is an informal experience-based theory used by a small team, or it is an official, publicly developed theory, it will have an impact on our activities (Tilly, 2006). The question is not: Are we using theory? We know we are. We should ask: Are we aware of that theory, how good is it, and is it the right theory?
Practice shows that when we lose sight of the importance of theory, bad things happen. A weak hypothesis or even just a hunch, biased and limited in scope (Kahneman, 2011), can be used to drive our actions, often with negative results. Lack of a theoretical background is a common reason why QI and patient-safety interventions in healthcare often result in limited positive changes or no relevant changes at all (Shojania & Grimshaw, 2005). If the intervention proves to be successful, but lacks a sound theoretical basis, it is usually hard to make it permanent and generalize it in other contexts (Dixon-Woods, Leslie, Tarrant, & Bion, 2013).
The literature provides a variety of theories that may foster sustainable QI change. That variety ranges from a big set of learning theories and change agent theories, to organizational change and economic theories. Shojania, McDonald, Wachter, and Owens (2004) argue that it may be challenging to develop interventions based only on one of those theories. Effective QI strategy can be developed more easily when theory and implementation are tested simultaneously. As a manual to help users navigate through that process, Kaplan, Provost, Froehle, and Margolis (2012) developed Model for Understanding Success in Quality (MUSIQ). The model describes 25 contextual factors that may influence success of QI projects. It serves as a checklist of elements that should be included in a QI theoretical plan.
IPL. In the early days of IPL research, a significant number of papers were very pragmatic and didn’t describe a theoretical background. Many later papers grounded IPL research in a single theory – usually related to a specific school of thought and academic discipline (Barr, 2013). Today, a growing number of papers build a sound, flexible and inclusive IPL framework by combining multiple theories and practices. As a result, Hean, Craddock, and O’Halloran (2009) argue that a large number of theories currently used to describe IPL have created a hard-to-navigate quantifier.
Social theories (social constructivism, social capital) (Hean et al., 2012), adult learning (P. G. Clark, 2006), identity theories, situated learning (Ranmuthugala et al., 2011; Wenger, 1998, 1999) and networked learning (Dev & Heinrichs, 2008) are the main theories relevant to QIE/IPL learning processes. On the other hand, the theories most relevant to QIE/IPL context are sociology of professions, organizational theory and activity theory. They present a compelling example of how different theories complement each other. For example, Larson (1979) argues that professional guilds are actively engaged in monopolizing knowledge in specific areas, to ensure cognitive exclusivity. That may explain why, despite learning organization (Roberts & Thomson, 1994; Senge, 2006) being a very popular theory concept (Barr, 2013), it is especially hard to achieve it among different professional organizations and patients. Fortunately, activity theory allows us to analyze organizations as “distributed, decentered and emergent systems of knowledge” (Blackler, Crump, & McDonald, 2000, p. 278); it provides insight into connections between activities and context and reasoning behind complex social activities.
The connected, networked nature of modern life and work is at the heart of learning as a social activity, and knowledge as a social construct. (Hean et al., 2009) Therefore, to fully understand learning, we have to analyze curricula through a social theoretical lens. Only through that lens will we be able to comprehend how organizations, professional societies, professional regulations, education providers and communities of learners shape the knowledge development process.
Social capital theories are focused on the benefits individuals and society can achieve by being part of and nurturing a social network. They suggest the equilibrium concept (Boix & Posner, 1998). Social capital will increase through repeated cooperation and collaboration. In return, strong social capital will boost social collaboration and the happiness of individuals. Research of Leung, Kier, Fung, Fung, and Sproule (2013) showed that social capital is one of the major cornerstones of happiness. In the healthcare field, social capital is popular due to the known relationship between social capital (strong social network) and health benefits. Ultimately, social capital, happiness and collaborative behaviors can significantly improve tacit and explicit knowledge-sharing among employees – creating a basis for a productive learning organization (Hau, Kim, Lee, & Kim, 2013). Therefore social capital theory can be used to describe benefits of interprofessional, networked learning, and guide us to maximize benefits from that learning model.
Adult learning theories are often described as a cornerstone of successful QIE/IPL. They provide a toolset or learning modalities that motivate students as individuals and groups to activate existing knowledge and use it as a platform to develop new knowledge. In that context they can be viewed as an extension of constructivist learning theories.
Networked learning theory uses connections between students, students and teachers, and between student resources and tools to create a framework where students (working professionals) as individuals and groups have access to all elements needed for successful continuous professional development. It created a framework that connects CME/CPD providers and the professional learning community (Jackson & Temperley, 2007). Whether they need access to content, expertise, QI tools or peer moral support, students will be helped by networked learning principles. With that, students can combine real world context and highly integrative learning activites to address complex situated problems (G. Campbell, 2016).
Community of practice, as situated learning theory, can explain many benefits professional societies provide to their members (Webster-Wright, 2009). The society and profession acts as a community of practice; a community of professionals that jointly work together to improve practice in a specific domain (health, nursing, surgery) (Simons & Ruijters, 2004). There is potential to further support that community with social media .
Each mentioned theory deserves detailed description, which is out of scope of this literature review.
What we can notice from the aforementioned brief descriptions is that there is lot of overlapping between theories and that theories often complement each other (Hean et al., 2012). For example, networked learning will benefit if social capital is strong, and social capital can be further enhanced with properly designed networked activities. Adult learning in the QIE/IPL context will also be enhanced if social capital is strong and the proper networked practices are in place. Ultimately, community of practice can benefit from all aforementioned theories – and create a framework where they can be better implemented.
Activity theory, being a macro theory, will be discussed last as a separate example. A macro theory can be used as a descriptive framework taking into account all elements of a complex healthcare activity system. Examples of an activity system include a perioperative surgical home team or an organization such as the ASA. Therefore, activity theory can serve as a lens to analyze human activities in such a complex and dynamic system. The third generation of activity theory is specifically interesting for this research because it is focused on how different activity systems interact (Engeström, 2001). Each profession (anesthesiologists, nurse anesthetists, surgeons, etc.) and patients or the public can be analyzed as a separate activity system. The third generation of activity theory can help us understand how those systems interact during preparation for implementation of QIE/IPL activities. A small detail that confirms the suitability of activity theory is that in the paper introducing the third generation of activity theory, (Engeström, 2001) uses interaction among healthcare activity systems (hospital, patient’s family) as the main examples.
- Barr, H. (2013). Toward a theoretical framework for interprofessional education. Journal of interprofessional care, 27(1), 4-9. doi:10.3109/13561820.2012.698328
- Blackler, F., Crump, N., & McDonald, S. (2000). Organizing processes in complex activity networks. Organization, 7(2), 277-300.
- Boix, C., & Posner, D. N. (1998). Social capital: Explaining its origins and effects on government performance. British journal of political science, 28(04), 686-693.
- Campbell, G. (2016). Networked learning as experiential learning. Educause Review, Vol. 51 No., 50(1, January 11), 1.
- Clark, P. G. (2006). What would a theory of interprofessional education look like? Some suggestions for developing a theoretical framework for teamwork training 1. Journal of interprofessional care, 20(6), 577-589.
- Davidoff, F., Dixon-Woods, M., Leviton, L., & Michie, S. (2015). Demystifying theory and its use in improvement. BMJ quality & safety, bmjqs-2014-003627.
- Davies, P., Walker, A. E., & Grimshaw, J. M. (2010). A systematic review of the use of theory in the design of guideline dissemination and implementation strategies and interpretation of the results of rigorous evaluations. Implement Sci, 5(14), 5908-5905.
- Dev, P., & Heinrichs, W. L. (2008). Learning medicine through collaboration and action: collaborative, experiential, networked learning environments. Virtual reality, 12(4), 215-234.
- Dixon-Woods, M., Leslie, M., Tarrant, C., & Bion, J. (2013). Explaining Matching Michigan: an ethnographic study of a patient safety program. Implementation Science : IS, 8, 70-70. doi:10.1186/1748-5908-8-70
- Engeström, Y. (2001). Expansive learning at work: Toward an activity theoretical reconceptualization. Journal of education and work, 14(1), 133-156.
- Hau, Y. S., Kim, B., Lee, H., & Kim, Y.-G. (2013). The effects of individual motivations and social capital on employees’ tacit and explicit knowledge sharing intentions. International Journal of Information Management, 33(2), 356-366.
- Hean, S., Craddock, D., Hammick, M., & Hammick, M. (2012). Theoretical insights into interprofessional education: AMEE Guide No. 62. Medical teacher, 34(2), e78-e101.
- Hean, S., Craddock, D., & O’Halloran, C. (2009). Learning theories and interprofessional education: A user’s guide. Learning in Health and Social Care, 8(4), 250-262.
- Hovlid, E., Bukve, O., Haug, K., Aslaksen, A. B., & von Plessen, C. (2012). Sustainability of healthcare improvement: what can we learn from learning theory? BMC Health Services Research, 12(1), 235.
- Jackson, D., & Temperley, J. (2007). From professional learning community to networked learning community. In K. S. L. Louise Stoll (Ed.), Professional learning communities: Divergence, depth and dilemmas (pp. 45-62). UK: McGraw-Hill Education.
- Kahneman, D. (2011). Thinking, fast and slow. Farrar, Sraus and Giroux, 18 West 18th Street, New York, USA.: Macmillan.
- Kaplan, H. C., Provost, L. P., Froehle, C. M., & Margolis, P. A. (2012). The Model for Understanding Success in Quality (MUSIQ): building a theory of context in healthcare quality improvement. BMJ quality & safety, 21(1), 13-20.
- Larson, M. S. (1979). The rise of professionalism: A sociological analysis (Vol. 233). USA: Univ. of California Press.
- Leung, A., Kier, C., Fung, T., Fung, L., & Sproule, R. (2013). Searching for happiness: The importance of social capital The exploration of happiness (pp. 247-267): Springer.
- Olson, C. A. (2013). Reflections on Using Theory in Research on Continuing Education in the Health Professions. Journal of Continuing Education in the Health Professions, 33(3), 151-152. doi:10.1002/chp.21178
- Ranmuthugala, G., Plumb, J., Cunningham, F., Georgiou, A., Westbrook, J., & Braithwaite, J. (2011). How and why are communities of practice established in the healthcare sector? A systematic review of the literature. BMC Health Services Research, 11(1), 273.
- Roberts, C., & Thomson, S. B. (1994). Our Quality Program Isn’t Working. In P. M. Senge (Ed.), The Fifth Discipline Fieldbook: Strategies and Tools for Building a Learning Organization. USA: Doubleday.
- Senge, P. M. (2006). The Fifth Discipline: The Art & Practice of the Learning Organization. USA: Doubleday.
- Shojania, K. G., & Grimshaw, J. M. (2005). Evidence-based quality improvement: The state of the science. Health Affairs, 24(1), 138-150.
- Shojania, K. G., McDonald, K. M., Wachter, R. M., & Owens, D. K. (2004). Toward a Theoretic Basis for Quality Improvement Interventions. Retrieved from
- Simons, P. R.-J., & Ruijters, M. C. (2004). Learning professionals: towards an integrated model Professional learning: Gaps and transitions on the way from novice to expert (pp. 207-229): Springer.
- Tilly, C. (2006). Why?:[what happens when people give reasons… and why]. Princeton, New Jersey, US: Princeton University Press.
- Webster-Wright, A. (2009). Reframing professional development through understanding authentic professional learning. Review of Educational Research, 79(2), 702-739.
- Wenger, E. (1998). Communities of Practice: Learning, Meaning, and Identity. Cambridge: Cambridge University Press.
- Wenger, E. (1999). Learning as social participation. Knowledge Management Review, 1(6), 30-33. Retrieved from https://modules.lancs.ac.uk/pluginfile.php/210525/mod_page/content/37/W3_Wenger%281999%29.pdf
QIE and IPL in a connected world. As described earlier, QIE and IPL have 45-plus years of history behind them. Therefore, our perception of them is to a significant extent shaped by how they looked, acted and interacted during the pre-Internet era. It was a very different world from today. We can now videoconference with peers on another continent, or use one-click access to read up-to-date detailed dynamic reports, activities that would be seen as science fiction by earlier generations. In the past 25 years, technology has reshaped how we communicate, learn, live and perceive the world around us (Siemens, 2005). In that context, we can revisit how QIE and IPL look today.
Knowing that the traditional CPD has a limited impact on quality of care (Hager et al., 2008; IoM, 2010; Macy, 2013) and is focused on individuals, it is fair to say that IPL and QIE have different learning formats and different goals than traditional CPD.
QIE and IPL have numerous similarities. They assume that the best way to ensure individual and system-wide professional development and QI is to have a well-integrated and coordinated system (Shortell, Bennett, & Byck, 1998), where healthcare workers from all professions are connected and focused on meeting the needs of individuals and communities (Macy, 2013). They are both described as great tools to address the same three goals: better care, better health and reduced cost (Batalden & Davidoff, 2007; IoM & 2013). Finally, WHO (2010) presented IPL as an important prerequisite for a high-performing collaborative practice and continuous quality improvement. Therefore, QIE and IPL can be viewed as two different entry/view points of the same system-wide QI system (learning/networked health system) – as Figure 6 illustrates. IPL will start with creation of a skilled, collaborative, practice-ready workforce that can practice quality improvement and deliver optimal health services. On the other hand, QIE will start with system changes that require the collaborative practice-ready workforce IPL can produce. Ultimately, they should be treated as two related parts of the same system. Further on, I will refer to them as QIE/IPL.
The QIE roadmap confirms the same assumption. The Alliance for Continuing Education in the Health Professions (ACEHP) in 2015 launched the Alliance QIE Initiative (Sulkes, 2014) and Roadmap (Figure 7). As Figure 6 illustrates, QIE by ACEHP is a continuation of the gradual evolution of CME to CPD – from didactic lectures to practice-based activities with real impact on clinical performance. It assumes incorporation and integration of education professionals, tools, resources and methods into system-wide QI efforts. Since successful QIE changes are usually system-wide, and involve multiple professions, the QIE roadmap presented below (Diamond et al., 2015) predicts the current model of siloed education of healthcare professionals will evolve into interprofessional education during next 10-15 years. In other words, implementation of QIE and IPL is happening simultaneously, and we cannot separate them.
During that process, current pedagogies focused on content transmission and didactic events that are not well-integrated in clinical work will be replaced with pedagogies that integrate quality improvement, clinical practice, interprofessional collaboration, and student- and team-centric approaches (Ladden, Bednash, Stevens, & Moore, 2009).
1.1 Networked learning and quality
As mentioned, the CPD of healthcare professionals in the U.S. and CPD services the ASA provides are going through significant changes. Arguably, enhancing connections among healthcare professionals and the system is an important part of that process (Margolis & Parboosingh, 2015). Thus far, professional organizations are serving as learning networks (Margolis & Parboosingh, 2015). However, depending on our perspective, visibility of networked learning will change. For example, Jackson and Temperley (2007) argue that if a professional organization and profession is perceived as an established indivisible entity, then facilitating productive discussions about networked learning may be a challenge. However, if we perceive a profession as a network of professionals spread through numerous institutions and communities of practices, most of them interprofessional, then we may say that the profession is primed for networked learning.
Recently Curtis A Olson and Tooman (2012) provided a series of vivid examples explaining how didactic CME has an impact on clinical outcomes. Although participation in didactic sessions at live learning conferences was an important part of all three cases they chose, in all three instances it was just a small part of continuous networked learning. Yet, the cases were used to demonstrate the value of didactic leaning, and did not even mention networked learning. That illustrates how, depending on our ontological and epistemological perspective, the same event can be seen as networked learning and an example of didactic learning. Arguably, the cases presented how networked and social learning, which encompasses didactic lectures and uses conferences to connect people and build social capital, can improve clinical practice.
As the examples suggest, the main, and usually the only, networking “technology” have been live meetings (face-to-face conferences). Therefore, the impact of those learning networks has been limited to a specific time and place. The first Journal of Continuing Education in the Health Profession article using keyword networked learning was recently published by Margolis and Parboosingh (2015). The article highlights how networked learning initiated through live meetings can be enhanced through an online community.
Fully-featured networked learning is “learning in which information and communication technology (ICT) is used to promote connections: between one learner and other learners, between learners and tutors; between a learning community and its learning resources” (Goodyear, Banks, Hodgson, & McConnell, 2006, p. 1). Such a network can foster a shared vision, create collaborative space used to discuss solutions for complex issues, support CPD of participants and help them built trusting relationships (Margolis & Parboosingh, 2015).
Dirckinck-Holmfeld, Jones, and Lindström (2009) explained that development of networked learning environments is essential for successful networked learning. Due to cultural, organizational, legal and technological issues, wide adoption of such an environment hasn’t happened thus far. However, in all four areas, positive changes are happening very quickly. For example, the healthcare social media landscape is very versatile and dynamic (Fogelson, Rubin, & Ault, 2013). And the number of healthcare professionals using social media is growing exponentially. Sermo.com provides secure networking and crowdsourcing opportunities to 550,000 credentialed physicians from 25 countries (sermo.com, 2016). Steele et al. (2015) argues that social media has become a necessary component of surgery practice. Furthermore, gaps in networked care between healthcare teams and groups have been recognized as a serious challenge. Knowing that strategies to support networked systems are well-established among some non-healthcare groups, Braithwaite (2015) systematically reviewed non-healthcare literature.
Team-based and networked learning for healthcare teams
Arguably, team-based education and networked learning have many characteristic of QIE and IPL (Bornkessel et al., 2014). Many programs delivered through team-based education and/or networked learning are in essence QIE/IPL modalities (Bate, 2000; Carter, Ozieranski, McNicol, Power, & Dixon-Woods, 2014). Therefore, they can be used as a basis for future development of QIE/IPL. A few promising examples are described in the following paragraphs.
MOOCs. The potential of Massive Open Online Courses (MOOCs) in medical education that focus on specific topics is recognized. For example, Murphy and Munk (2013) convincingly argue that radiology residents get only limited teaching of medical imaging, radiology management, economics and technology. They propose MOOCs as an optimal solution to address those learning gaps, engage all professions (physicians, nurses and technologists) and have a positive impact on U.S., Canadian and international radiology education. In the same manner, Liyanagunawardena and Williams (2014) reviewed 98 MOOCS offered on healthcare topics in 2013. A significant majority of the MOOCs were offered in English-speaking institutions from the developed world, primarily in North America, and focused on introductory-level material. Numerous examples prove the potential of MOOCs to provide continuous professional development of healthcare professionals, students, the public and patients. Some courses offered CPD credits for healthcare professionals. “Collaboration and Communication in Healthcare: Interprofessional Practice” is a good example. That MOOC, created by the University of California, San Francisco, has run since 2014. Based on those characteristics of successful healthcare MOOCs, it is fair to expect that more advanced MOOCs on IPL and QIE will be successful – especially if the offerings are associated with CME credits.
On the other hand, Davidson (2014) warns that reliance primarily on xMOOCs (extendable MOOCs) instead of cMOOCs (connectivity MOOCs) will allow a few providers to monopolize learning. cMOOCs and xMOOCs are massive online courses, but they are based on different pedagogies (Rodriguez, 2013) and different levels of openness. xMOOCs are built around video streaming and automated MCQ exams, while cMOOCs are more open and built around collaboration and connectivism. As a result, instead of delivering connected, collaborative education, MOOCs may promote keeping more with forms of siloed education specific for the Taylorized 19th-century industrial era, than for the current era (Davidson, 2014).
Therefore, depending on which MOOCs modality we choose, the target audience, how activities are organized and how outcomes are connected with quality improvement, MOOCs can have (or not) each of these characteristics: networked, IPL and QIE.
Simulation education proves to be a great context for interprofessional, quality-focused team-based training (Hinde, Gale, Anderson, Roberts, & Sice, 2016; Navedo, Pawlowski, & Cooper, 2015). In that context, multiple healthcare professions (physicians, nurses) and associated healthcare professionals (computer science, law, etc.) can learn together through highly interactive, hands-on learning experience (Paige et al., 2014). Liaw, Siau, Zhou, and Lau (2014) showed that simulations can promote mutual respect, open communication and shared decision-making, while breaking down stereotypes toward physician-nurse collaboration. At the same time, the impact of simulations can be significantly improved it they are well-integrated into reflective, collaborative learning and working, if they reflect the cultural and social context of a team, and if participants are in a network of peers, teachers and resources while they are implementing changes in their local environment (Stocker, Burmester, & Allen, 2014; Zigmont, Kappus, & Sudikoff, 2011).
The ASA maintains the ASA Simulation Education Network – a network of high-fidelity simulation providers of exercises for the purpose of maintenance of certification. After an interprofessional simulation exercise and reflection, all participants must create a performance improvement plan. All three elements – simulations, IPL and QIE – are very noticeable. A framework that will network participants with peers, tutors and resources should be developed in 2016.
Quality improvement initiatives have been significantly promoted with the new pay for performance reimbursement system (Britton, 2015). Healthcare providers are required to track their performance and are awarded for QI initiatives. Therefore, QI initiatives have become mainstream. Almost as a rule, QI initiatives are multiprofessional. However, QI initiatives do not have direct connections with CME and maintenance of the certification credit system. Therefore, the American Board of Medical Specialties has created Multi-Specialty Portfolio Approval Program. Through that program, participants can get MOC credits for institutional, multispecialty-team-based quality-improvement activities (Irons & Nora, 2015).
Experiential learning. (G. Campbell, 2016) convincingly argues that any form of experiential learning in a digital age is at least partially built on participation “within a digitally mediated network of discovery and collaboration” (G. Campbell, 2016, p. 71) – therefore it is a form of networked learning.
Furthermore, Campbell reminds us that we still use a collection of pre-digital networked learning practices, the library. “Enter the stacks, and run your fingers along the spines of the books on the shelves. You’re tracing nodes and connections. You’re touching networked learning — slow-motion and erratic, to be sure, but solid and present and, truth to tell, thrilling.” (G. Campbell, 2016, p. 70)
(Bates, 2015) criticizes that argument, stating that Campbell’s high-level pedagogical justification of networked learning lacks detailed support. The quality of networked learning and experiential learning can vary – just as the quality of any teaching method can vary. Therefore, it is fair to say that Campbell’s statement is correct only if we can deliver high-quality networked learning. Otherwise, we should consider alternative modalities.
This paper will build on those thoughts, and look for ways to deliver more effective networked learning modalities – so that networked learning can become a viable CME option.
- 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.
- Bate, P. (2000). Changing the culture of a hospital: from hierarchy to networked community. Public Administration, 78(3), 485-512.
- Bates, A. W. T. (2015, 1/27/2016). Is networked learning experiential learning? Retrieved from http://www.tonybates.ca/2016/01/27/is-networked-learning-experiential-learning/
- 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.
- Braithwaite, J. (2015). Bridging gaps to promote networked care between teams and groups in health delivery systems: a systematic review of non-health literature. BMJ open, 5(9), e006567.
- Britton, J. R. (2015). Healthcare Reimbursement and Quality Improvement: Integration Using the Electronic Medical Record: Comment on” Fee-for-Service Payment-an Evil Practice That Must Be Stamped Out?”. International journal of health policy and management, 4(8), 549.
- Campbell, G. (2016). Networked learning as experiential learning. Educause Review, Vol. 51 No., 50(1, January 11), 1.
- Carter, P., Ozieranski, P., McNicol, S., Power, M., & Dixon-Woods, M. (2014). How collaborative are quality improvement collaboratives: a qualitative study in stroke care. Implementation Science, 9(1), 32.
- Davidson, C. N. (2014). Why Higher Education Demands a Paradigm Shift. Public Culture, 26(1 72), 3-11.
- 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
- Dirckinck-Holmfeld, L., Jones, C., & Lindström, B. (2009). Analysing networked learning practices in higher education and continuing professional development: Sense Publishers.
- Fogelson, N. S., Rubin, Z. A., & Ault, K. A. (2013). Beyond likes and tweets: an in-depth look at the physician social media landscape. Clinical obstetrics and gynecology, 56(3), 495-508.
- Goodyear, P., Banks, S., Hodgson, V., & McConnell, D. (2004). Advances in Research on Networked Learning (Vol. 4). Boston, USA: Springer Science & Business Media.
- 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.
- Hinde, T., Gale, T., Anderson, I., Roberts, M., & Sice, P. (2016). A study to assess the influence of interprofessional point of care simulation training on safety culture in the operating theatre environment of a university teaching hospital. Journal of interprofessional care, 1-3.
- 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. (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.
- Irons, M. B., & Nora, L. M. (2015). Maintenance of Certification 2.0—strong start, continued evolution. New England Journal of Medicine, 372(2), 104-106.
- Jackson, D., & Temperley, J. (2007). From professional learning community to networked learning community. In K. S. L. Louise Stoll (Ed.), Professional learning communities: Divergence, depth and dilemmas (pp. 45-62). UK: McGraw-Hill Education.
- Ladden, M. D., Bednash, G., Stevens, D. P., & Moore, G. T. (2009). Educating interprofessional learners for quality, safety and systems improvement. Journal of interprofessional care.
- Liaw, S. Y., Siau, C., Zhou, W. T., & Lau, T. C. (2014). Interprofessional simulation-based education program: a promising approach for changing stereotypes and improving attitudes toward nurse–physician collaboration. Applied Nursing Research, 27(4), 258-260.
- Liyanagunawardena, T. R., & Williams, S. A. (2014). Massive open online courses on health and medicine: Review. Journal of Medical Internet Research, 16(8).
- 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.
- Margolis, A., & Parboosingh, J. (2015). Networked Learning and Network Science: Potential Applications to Health Professionals’ Continuing Education and Development. Journal of Continuing Education in the Health Professions, 35(3), 211-219.
- Murphy, K., & Munk, P. L. (2013). Continuing medical education: MOOCs (Massive Open Online Courses) and their implications for radiology learning. Canadian Association of Radiologists Journal, 3(64), 165.
- Navedo, A., Pawlowski, J., & Cooper, J. B. (2015). Multidisciplinary and Interprofessional Simulation in Anesthesia. International anesthesiology clinics, 53(4), 115-133.
- Olson, C. A., & Tooman, T. R. (2012). Didactic CME and Practice Change: Don’t Throw That Baby Out Quite Yet. Advances in health sciences education, 17(3), 441-451.
- Paige, J. T., Garbee, D. D., Kozmenko, V., Yu, Q., Kozmenko, L., Yang, T., . . . Swartz, W. (2014). Getting a head start: high-fidelity, simulation-based operating room team training of interprofessional students. Journal of the American College of Surgeons, 218(1), 140-149.
- Rodriguez, O. (2013). The concept of openness behind c and x-MOOCs (Massive Open Online Courses). Open Praxis, 5(1), 67-73.
- sermo.com. (2016). WHAT IS SERMO? Retrieved from sermo.com
- Shortell, S. M., Bennett, C. L., & Byck, G. R. (1998). Assessing the impact of continuous quality improvement on clinical practice: what it will take to accelerate progress. Milbank Q, 76(4), 593-624, 510.
- Siemens, G. (2005). Connectivism: A learning theory for the digital age. International Journal of Instructional Technology and Distance Learning, 2(1).
- Steele, S. R., Arshad, S., Bush, R., Dasani, S., Cologne, K., Bleier, J. I., . . . Kelz, R. R. (2015). Social media is a necessary component of surgery practice. Surgery, 158(3), 857-862.
- Stocker, M., Burmester, M., & Allen, M. (2014). Optimisation of simulated team training through the application of learning theories: a debate for a conceptual framework. BMC Medical Education, 14(1), 69.
- Sulkes, D. (Producer). (2014, 10/26/2014). ACEhHP’s Quality Improvement Education Initiative, October 24, 2014. Alliance Town Hall Webinar. Retrieved from http://www.acehp.org/imis15/acme/pdfs/Alliance_Town_Hall_Oct2014.pdf
- 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/
- Zigmont, J., Kappus, L., & Sudikoff, S. (2011). Theoretical foundations of learning through simulation. Semin Perinatol, 35, 47 – 51.
Interprofessional learning (IPL) and Quality Improvement Education (QIE) are increasingly recognized as important tools to improve performance of U.S. healthcare teams and address the changes the U.S. healthcare system and the Continuing Professional Development (CPD) system are undergoing (Hager, Russell, Fletcher, & Macy Jr, 2008; IoM, 2010; Macy, 2013; WHO, 2010). The need for change is clear: Healthcare is increasingly delivered by teams, yet healthcare teams are not trained as teams or familiar with team-based quality improvement (QI) methodology – and therefore their ability to address the need for quality improvement is limited.
To address that gap, the Institute of Medicine concluded that professional development of the healthcare workforce and healthcare system should be analyzed together. To improve our healthcare outcomes, it is important to better align the transformation of healthcare workforce CPD with the massive reform of the U.S. healthcare system, and ensure widespread adoption of IPL (IoM, 2015).
This research aims to contribute to that goal by finding how QIE and IPL are perceived by four professions participating in the perioperative team (physician anesthesiologists, surgeons, nurse anesthetists and anesthesiologist assistants), and which QIE- and IPL-related technologies and practices each profession involved in the research have available or plan to implement soon. Results of this research will help healthcare leaders better plan implementation of technology-enhanced QIE and IPL in the context of the perioperative team. In addition, although the perioperative context is specific, a significant part of the findings will be applicable to other interprofessional healthcare teams.
I believe that the research will show that technology-enhanced QIE and IPL are in many ways related to networked learning, and that their successful implementation will require creation of networked learning communities.
Ontology. Social constructivism is my dominant worldview. It assumes that meanings are created in social interaction. They are constructed on individual and group/organizational/professional levels and influenced by numerous historical, cultural and technological factors.
Epistemology. The social constructivism learning theory (Curran, Fleet, & Kirby, 2010; Vygotsky, 1978) is associated with that worldview. I will use it as a lens to analyze potential challenges of QIE/IPL.
Social constructivism assumes that groups actively construct knowledge through social interaction internally among team members, and as a team interacting with the external world. In that process they create group culture, a collection of shared artifacts and shared mental models. Ultimately, according to a social constructivist view, the society exists simultaneously as subjective and objective reality (Andrews, 2012).
As the literature review shows, education focused on quality improvement of clinical practice and IPL has been grabbing our attention for more than half a century, and there is a wealth of publications on that topic. However, very few changes were accepted. It is fair to say that QIE/IPL are still in the early stages. On the other hand, recent strong political-economic forces and technology-enhanced learning solutions have created an environment that can enable implementation of QIE and IPL on a scale that was never possible before. Therefore, the research questions are:
- How are QIE/IPL and technologies and policies that shape QIE/IPL perceived by four groups involved in perioperative teams: anesthesiologists, surgeons, anesthesiologist assistants and nurse anesthetists?
- How is technology-enhanced collaborative learning used and perceived in the context of QIE/IPL and perioperative teams?
- How are professional cultures and contextual factors related to collaborative learning influencing implementation of technology-enhanced QIE/IPL?
Answers to those questions will help us better utilize technology to support QIE/IPL, to the benefit of all healthcare professions involved, and their patients; it will help us understand cultural and contextual factors so we can navigate more quickly and safely to successful QIE/IPL programs.Read More