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.
Distance learning of the U.S. healthcare workforce has a long history, starting with correspondence education in the 1960s (Josseran & Chaperon, 2001). Some popular correspondence programs, such as Refresher Courses in Anesthesiology, were initiated in the early 1970s (ASA, 1973).
Online has become the dominant way of delivering CPD. Five years ago, Harris, Sklar, Amend, and Novalis‐Marine (2010) predicted that “online CPD is likely to be 50% of all CPD consumed within 7-10 years.” Four years later, in 2014, all education delivered by the American Society of Anesthesiologists (ASA) is online or enhanced by online formatting. On the other hand, it has been known for a long time that online CPD programs are as effective as traditional CPD programs (Wutoh, Boren, & Balas, 2004). Consequently 97% of physicians expect more online CPD in the future (archemedx.com, 2013).
Historically, the focus of CPD was primarily on content transmission. More recently, strong societal forces are converging focus shift toward behavior changing learning activities with impact on patient population (Moore, Green, & Gallis, 2009; Russell, Maher, Prochaska, & Johnson, 2012). We can also notice a shift of focus from individuals towards to CPD of groups and organizations (Webster-Wright, 2009).
Five generations of distance education, as described by (Taylor, 2001) and later elaborated on by (Bates, 2008), can categorize the evolution of CPD as provided by the ASA.
- The Correspondence Model, based on print technology, is losing its share and is enhanced with online delivery. However, it still plays a significant part. In 2014, approximately 30% of CPD credits claimed by ASA users was done through that model.
- The Multi-media Model – delivery of multimedia content on print, digital storage devices (CD/DVD, flash memory), or through the Internet, but without any communication among humans. It is well-suited for industrial mass production. It is the dominant method of delivery, with around 68% of credit hours delivered in this format.
- The Telelearning Model delivers synchronous communication, such as webinars, and is used quite rarely in CPD. There were no CPD credits awarded by ASA this year through this model.
- The Flexible Learning Model is based on asynchronous online communication (Bates, 2008). In the U.S., CPD context it is very rarely used. The current LMS used by the ASA does not provide support for it.
- The Intelligent Flexible Learning model will become possible after implementation of the new LMS. It builds on the functionality of the Flexible Learning Model. Some of the additions are: easy access to institutional guidelines and resources; computer-mediated communication; user- generated content; and peer assessment. The system will be integrated with the Anesthesia Quality Institute clinical outcomes tracking system(Dutton, 2014), allowing individuals and groups to assess and reflect on their clinical performance and create improvement and learning plans. The system will also deliver a business intelligence layer that suggests learning based on users’ clinical performance, and performance in courses and certification status.
Specific learning theories are associated with each of those generations. Generations 1 and 2 are associated primarily with behaviorism and cognitivism (Bates, 2008). A majority of CPD is delivered through the first two generations of distance education. Generation 3 is not popular anymore and instead of implementing generation 4 the ambition is to go straight to generation 5. Simultaneously, generation 5 utilizes constructivist approaches like collaborative learning, knowledge construction, communities of practice and self-directed learners (Peters, 2002). Between the first two generations and the fifth generation we have significant technological, theoretical and cultural differences. As described below, the U.S. healthcare reform and recently adopted educational technology solutions will enable those changes to happen in the form of IPL and QIE. However, the technology is just one element in that formula. This research will contribute to those efforts by providing insight into human perceptions of QIE and IPL, and technology enhanced learning solutions available to perioperative care teams.
IPL is a situation “when two or more professions learn with, from and about each other to improve collaboration and the quality of care” (CAIPE, 2002).
QIE is a system-wide educational framework focused on three goals: better care, better health and reduced-cost patient care (Batalden & Davidoff, 2007). Its holistic system design approach tackles all potential barriers for quality improvement (QI), attempting to make permanent system-wide changes. In that context, QI is coordinated with the continuous efforts of all stakeholders – healthcare professionals, patients, researchers, educators and the public – toward better patient outcomes, better system performance and better professional development.
The Alliance for Continuing Education in the Health Professions (ACEHP) in 2015 launched the QIE roadmap (Figure 2). As Figure 2 illustrates, QIE by ACEHP is a continuation of the gradual evolution of CPD from didactic lectures to practice-based activities with real impact on clinical performance. It assumes incorporation and integration of education professionals, tools, resources and methods into system-wide QI efforts. Since successful QIE changes are usually system-wide, and involve multiple professions, the QIE roadmap presented below (Diamond, Kues, & Sulkes, 2015) predicts the currently siloed education of healthcare professionals will evolve in interprofessional education during next 10-to-15-years.
Figure 2. Alliance QIE Initiative: A Transformation Shift – toward interprofessional team-based QIE (Source: Diamond et al., 2015)
Knowing that the traditional CPD has limited impact on quality of care (Hager, Russell, Fletcher, & Macy Jr, 2008; IoM, 2010; Macy, 2013), it is fair to say that IPL and QIE have different learning formats and different goals than traditional CPD.
QIE and IPL have numerous similarities. They assume that the best way to ensure individual and system- wide professional development and QI is to have a well-integrated and coordinated system (Shortell, Bennett, & Byck, 1998), where healthcare workers from all professions are connected and focused on meeting the needs of individuals and communities (Macy, 2013). They are each individually described as great tools to address the same three goals: better care, better health and reduced cost (Batalden & Davidoff, 2007; IoM & 2013). Finally, WHO (2010) presented IPL as an important prerequisite for a high-performing collaborative practice and continuous quality improvement. Therefore, QIE and IPL can be viewed as two different entry/view points of the same system-wide QI system (learning/networked health system) – as Figure 3 illustrates. IPL will start with creation of a skilled, collaborative, practice-ready workforce that can practice quality improvement and deliver optimal health services. On the other hand, QIE will start with system changes that require the collaborative practice-ready workforce IPL can produce. Ultimately, they should be treated as two related parts of the same system. Further on, I will refer to them as QIE/IPL.
Figure 3. IPL and QIE entry point or lenses into Health and Learning Health Systems. Left lens is more focused on IPL. Right lens is more focused on QIE. Together they provide the full picture (Adopted from: WHO, 2010, p. 9).
Healthcare is a team sport (Salas, DiazGranados, Weaver, & King, 2008). Healthcare professionals participate in it daily, and each one of us as patients participates in important healthcare events at least a few times in our lives. However, it is a very dangerous team sport. No other team sport has a greater potential for fatal outcomes. For example, the Institute of Medicine concluded that between 44,000 and 98,000 Americans die each year as a result of medical errors (IoM & 2001). Yet healthcare practitioners in the U.S. are rarely trained as a team and they have limited insight into QI methodology (Starr et al., 2015) .
Strong political-economic and social factors shape CPD of healthcare professionals in the U.S. (Balmer, 2013; Cervero & Moore Jr., 2011) and have obstructed interprofessional learning for decades (Hayes, 2012). As history shows, those factors (pay-for service, siloed guilds or accreditation systems, for example) may have a stronger impact than professional and educational factors.
This research will be done in the context of the perioperative care team (surgery and anesthesia professionals). The literature suggests that due to rivalry between professionals or specialties, learning and change in networked practices may be difficult (Norman, 2013). That may be very noticeable in this context where one very relevant issue is a long, intense and passionate debate between physician anesthesiologists and nurse anesthetists over nurse scope of practice (Hayes, 2012). In addition to the main factor – patient safety – nurse scope of practice directly influences positions and payment of physician anesthesiologists and nurse anesthetists, making it a strong political-economic factor (with a huge impact on social capital). For example, in a recent article Johnstone (2015) showed that, in addition to high membership fees ($665), one of the main reasons cited by anesthesiologists for not joining the ASA was related to the ASA’s policy toward Nurse Anesthetists (NAs). It is interesting that while some non-member anesthesiologists think the ASA is working too closely with NAs, others think it is not working closely enough.
On the other hand, new political-economic and social factors started changing that power dynamic recently. Rising costs of U.S. healthcare-associated quality and patient safety issues (Berwick & Hackbarth, 2012; Davis, Stremikis, Schoen, & Squires, 2014) have triggered massive changes in the U.S. healthcare system. IPL is recognized as an important tool to improve performance of U.S. healthcare teams and address the changes that the U.S. healthcare system and the CPD system are undergoing (IoM, 2010; Macy, 2013; WHO, 2010).
One important feature of the current healthcare reform is focus on development and performance of clinical microsystems. Clinical microsystems are small, interdependent groups of healthcare professionals who work collaboratively to deliver optimal and comprehensive healthcare for specific groups of patients (Batalden, Nelson, Edwards, Godfrey, & Mohr, 2003). Clinical microsystems are made up of groups that participate in immediate delivery of care and interact directly with patients, such as physicians, nurses or pharmacists, and groups that support the microsystem, like laboratory, IT and leadership professionals.
Communities of practice can be an important tool to improve performance of microsystems (Webster-Wright, 2009; Wenger, 2006). It is a very flexible tool and depending on purpose, communication methods an structure, they can vary significantly (Ranmuthugala et al., 2011). Results of this research may contribute toward better utilization of technology enhanced CoP methodology in this specific context.
Perioperative surgical home (PSH), a clinical microsystem focused on delivery of perioperative care – from the decision for surgery to complete recovery (ASAHQ.org, 2014) – is the context of this study. The four professions participating in PSH involved in this research will be: physician anesthesiologists, surgeons, nurse anesthetists and anesthesiologist assistants. Those professions were selected because:
- Clinicians are the main stakeholders in the healthcare microsystems and their interactions and professional cultures greatly shape how teams work and the quality of service they deliver (Macy, 2013)
- There is a specific political-economic dynamic between these professions mainly focused on questions of who will lead the PSH team and the role of each profession in that team (Hayes, 2012).
- For the scope of this research, it was important to limit the number of professions involved.
Turbulent changes that affect Maintenance of Board Certification (MOC) of physicians in the U.S. may significantly influence context and implementation of QIE/IPL. Current MOC practices are mainly developed around multiple-choice questions and credit hours. Criticism toward them has been building during the past few years (Gray et al., 2014; Kempen, 2012, 2014; O’Gara & Oetgen, 2014; Strasburger, 2011). In 2014, the Association of American Physicians and Surgeons took the American Board of Medical Specialties and MOC to court, claiming that MOC “imposes enormous ‘recertification’ burdens on physicians, which are not justified by any significant improvements in patient care” (AAPS, 2014). The beginning of 2015 was marked by a nation-wide revolt against MOC. Significant amounts of criticism were supported with the current educational theory and online learning formats that QIE/IPL will promote. As a result, majority of the boards are reorganizing their MOC programs (Baron, 2015).
Thus far, a majority of CPD providers rely on LMS (if they use LMS), which has limited functionality. Such LMS systems are built around a combination of SCORM + files + quiz + survey + certificates, and usually are completely lacking in support for collaborative education. They can address needs of content-focused education, but can’t address needs of collaborative or networked learning. The ASA’s leadership has recognized that and at this moment the ASA is in the process of implementing a new Moodle-based LMS – Totara. Totara comes with all the collaborative features of Moodle. Therefore, it will be a big change. In addition, Totara provides strong support for learning plans and organizational structure/hierarchies. Through the Totara hierarchies’ framework, the ASA can assign specific competencies and courses to specific roles in a team/organization. That feature may enable the ASA to deliver programs for multiprofessional teams.
This research is located in the context of perioperative team. Associations representing the other two key players in the perioperative team – the American College of Surgeons and American Association of Nurse Anesthetists – are planning to select LMSes with the functionality similar to the LMS ASA selected by the end of August 2015. Those selections may significantly influence the context and perspectives interviewees have on QIE/IPL. This research will help better navigate toward better and more coordinated utilization of learning technology available to members of perioperative team.
There are a number of theories that can be used to define and analyze IPL (Hean, Craddock, Hammick, & Hammick, 2012) and QIE. The approach to theory in papers on IPL has been evolving. At the beginning, a significant number of papers were very pragmatic and didn’t describe a theoretical background. Many later papers grounded IPL research in a single theory – usually related to a specific school of thought and academic discipline (Barr, 2013). Finally, at this point, a growing number of papers build a sound, flexible and inclusive IPL frame of references by combining multiple theories and practices. Following that evolution of thought, this research will reflect on a few major theories that can be used to describe IPL and possible interactions/overlaps between different theories.
Social theories (social constructivism, social capital) (Hean et al., 2012), adult learning (Clark, 2006), identity theories, situated learning (Ranmuthugala et al., 2011; Wenger, 1998, 1999) and networked learning (Dev & Heinrichs, 2008) are the main theories relevant to QIE/IPL learning processes. On the other hand, theories most relevant to QIE/IPL context are sociology of professions, organizational theory and activity theory. They may present a compelling example of how different theories complement each other. For example, Larson (1979) argues that professional guilds are actively engaged in monopolizing knowledge in specific areas, to ensure cognitive exclusivity. That may explain why, despite learning organization (Roberts & Thomson, 1994; Senge, 2006) being a very popular theory concept (Barr, 2013), it is especially hard to achieve it among different professional organizations and patients. Fortunately, activity theory allows us to analyze organizations as “distributed, decentered and emergent systems of knowledge” (Blackler, Crump, & McDonald, 2000, p. 278); it provides insight into connections between activities and context and reasoning behind complex social activities.
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