OR WAIT 15 SECS
By Kelly M. Pyrek
Editor's note: This is the second article in a series exploring imperatives relating to the research, behavioral and implementation sciences of infection prevention.
When healthcare reform was in its infancy, the Institute of Medicine (IOM, 2001) estimated that it took an average of 17 years for new knowledge generated by randomized controlled trials to be incorporated into practice, and even then, "application is highly uneven." The IOM emphasized that it was critical that scientific evidence became more useful and more accessible to clinicians and patients. to ensure its applicability and acceptability to these stakeholders. To improve the movement that eventually became known as "implementation science," the IOM urged analysis and synthesis of the medical evidence and practice guidelines, identification of best practices in the design of care processes, dissemination of the evidence and guidelines to the professional communities and the general public, development of support tools to help clinicians and patients in applying evidence and making decisions, establishment of goals for improvement in care processes and outcomes, and development of measures for assessing quality of care.
Williams (2017) acknowledges that "Even the most compelling evidence is not sufficient to insure rapid translation into clinical care. Translation of evidence-based best practice into clinical practice is fraught with challenges that were extensively documented in two landmark publications from the IOM, To Err is Human and Crossing the Quality Chasm."
In the latter report, the IOM (2001) observed, "Medical science and technology have advanced at an unprecedented rate during the past half-century. In tandem has come growing complexity of health care, which today is characterized by more to know, more to do, more to manage, more to watch, and more people involved than ever before. Faced with such rapid changes, the nation’s healthcare delivery system has fallen far short in its ability to translate knowledge into practice and to apply new technology safely and appropriately. And if the system cannot consistently deliver today’s science and technology, it is even less prepared to respond to the extraordinary advances that surely will emerge during the coming decades."
The Crossing the Quality Chasm report outlined general principles to reform healthcare, including addressing the imperative that decision-making be evidence-based: "Patients should receive care based on the best available scientific knowledge. Care should not vary illogically from clinician to clinician or from place to place." Additionally, the American Association of Medical Colleges published a report, Clinical Research: A National Call to Action, which emphasized that there is insufficient emphasis on incorporating research findings into clinical practice.
In the first article of this series, we reviewed the importance of research to infection prevention and healthcare epidemiology as part of the implementation science process. As Williams (2017) observes, "Clinical research has historically been focused on determining the efficacy of an intervention, that is does a given intervention produce a measurable effect in a defined population under ideal circumstances? The randomized clinical trial (RCT) is the prototype study design to determine efficacy. This design is the most scientifically rigorous based on the strong internal validity, but limits the generalizability of RCT results in the real world. This has led to the emergence of pragmatic trial designs that take the results from efficacy trials and study them in the “real world” to determine the effectiveness of the intervention. The results of these effectiveness trials have much more relevance to clinical care and have enhanced the translation of research findings into clinical care. Clinical research now must ensure that efficacy trials with positive findings are moved into effectiveness trials to validate the intervention in real-world settings. The combination of efficacy and effectiveness trials is still not sufficient for successful translation. The aim of both trial methodologies is to study the impact of a clinical intervention with the individual as the unit of study. The aim of implementation research is to study the impact of an implementation strategy. This requires interventions to change practices and systems with the clinician or organization as the unit of study."
Williams (2017) describes the elements of successful implementation: "Successful implementation depends on factors including analysis of clinical workflow relevant to the current care process; assessment of how the new care process is likely to alter the workflow; working with representatives of the affected care processes to minimize workflow disruption; identification of early adopters to pilot the implementation; and revision of implementation plan based on pilot results. This provides the information needed to develop a program roll out that is likely to be successful." Most importantly, Williams (2017) notes, "System inertia can erode new processes as systems tend to revert to usual practice. Active process management is needed to ensure optimal performance."
The Evolution of Behavioral Sciences in Infection Control
Seto (1995) advised that the "application of the behavioral sciences is timely and crucial for the continuing practice of hospital infection control."
Many years ago, the Study on the Efficacy of Nosocomial Infection Control (SENIC) project investigated the role of social power, which Raven and Haley (1982) defined as the potential ability of an influencing agent to change the cognitions, attitudes or behavior of another person in infection control. French and Raven (1959) described six bases for social power:
- coercive power: the ability of the influencing agent to mediate punishment for the target
- reward power: the ability to mediate rewards
- legitimate power: the target's acceptance of a role relationship with the influencing agent that obligates the target to comply with the agent's request
- expert power: the target's attribution of superior knowledge or ability to the agent
- referent power: the target's utilization of others as a frame of reference to evaluate his/her behavior
- informational power: the persuasiveness of the information communicated by the agent to the target
The SENIC project explored the base of power most likely to secure the compliance of nurses and found that informational and expert power triggered the best responses. Therefore, as Raven and Haley (1982) suggested, "infection control nurses should exercise these powers to enhance compliance with infection control policies. As suggested by Haley, et al. this should include the provision of 'relevant references and convincing information,' including surveillance data."
Seto (1995) advised that social psychology -- defined as the study of how people think about, influence and relate to one another -- should be used to evaluate better approaches to infection control compliance. Taking the "reasoned action" model into consideration, Seto (1995) suggested that "When a new policy is implemented, it would be an advantage if the infection control team could identify ahead of time those staff who will comply, and predict what is required in the in-service education program." The reasoned action theory assumes that people behave rationally and the in general, the intention to act is the result of considerable mental deliberation.
In recent years, infection prevention and control community has adopted the concept of champions that set an example for desired behavior in healthcare institutions. Seto (1995) alluded to the forerunner of this concept as opinion leaders, defined as the individuals in a social group who exert a significant amount of social influence over others. Seto (1995) reminds us that "new information must often be accepted by these opinion leaders before it can be effectively transmitted to the entire group."
While behavioral sciences are no longer a new frontier in infection prevention and control as it was when Seto was writing in the mid-1990s, Seto (1995) cautions, "… the individuality of the hospital staff must be respected. They must not be manipulated simply to achieve compliance. The intent is rather to coach them in the right direction so that ultimately, the patient will benefit."
Fast-forward a decade or so. In the healthcare quality improvement lexicon, "positive deviance" became one approach to many attempts "flip healthcare on its head," as called for by Bisognano and Schummers (2014). As Baxter, et al. (2016) acknowledge, "Within healthcare, various approaches to patient safety and quality improvement exist. Traditionally these approaches are deficit-based; they focus on identifying and learning from past harm. Their effectiveness is limited as only two-thirds of improvement projects achieve their objectives and deliver sustainable change. Improvements are often short-lived, fail to reach the most disadvantaged and can create unintended consequences. Furthermore, various challenges are faced while using these approaches such as engaging front-line staff, addressing their most pertinent issues and adequately accounting for context. Change is often introduced from the top of organizations and/or by external experts, and additional resources are rarely provided to support this… Despite our negativity, safe, high-quality care is reliably delivered the majority of the time. Asset-based approaches, which focus on the strengths and resources of a community, recognize this and explore how, and why, things go right in to learn from these successes. One such approach, ‘positive deviance’, is increasingly being applied within healthcare settings and has the potential to address a number of the challenges faced when trying to improve quality."
Positive deviance was seen by many as an alternative approach to quality improvement. According to Baxter, et al. (2016), "Positive deviance is a bottom–up approach which identifies and learns from those who demonstrate exceptional performance on an outcome of interest. The approach assumes that problems can be overcome using solutions that already exist within communities. Despite facing the same constraints as others, ‘positive deviants’ identify these solutions and succeed by demonstrating uncommon or different behaviors. Community involvement is integral to the approach, for example, staff select the problem to address, identify the positive deviants and explore how they succeed. Solutions are internally generated rather than externally imposed, ensuring that they are feasible within current resources, acceptable to others and sustainable over time."
Specifically, within healthcare, Bradley, et al. (2009) proposed a four-stage process for adopting the positive deviance approach; positive deviants with exceptionally high performance are identified using widely endorsed routinely collected data. Then, qualitative methods are used to generate hypotheses about how positive deviants succeed. These hypotheses are tested within larger, more representative samples and, finally, the successful, positively deviant practices are disseminated widely.
Improvement Concepts and Compliance
As Saint, et al. (2010) acknowledge, "Consistently implementing evidence-based practices in everyday clinical encounters remains a challenge. Adults in the United States receive recommended practices only 54 percent of the time."
In a survey by Yassi, et al. (2007) the researchers found most workers reported following the rules for infection control (48 percent saying "always" and 47 percent saying "often"); however, 27 percent of respondents felt that precautionary measures interfere with their ability to do their job. Overall, 90 percent of healthcare personnel reported cleaning their hands after removing gloves more than 70 percent of the time; 91 percent reported wearing disposable gloves when there was a possibility of exposure to blood or other bodily fluids more than 70 percent of the time; 62 percent reported wearing a disposable garment when there was a possibility of soiling their clothes more than 70 percent of the time; 71 percent reported wearing an N95 mask when there is potential exposure to an airborne respiratory communicable disease more than 70 percent of the time; and 52 percent reported wearing protective eyewear whenever there was a possibility of splashes of blood or other bodily fluids more than 70 percent of the time.
Yassi, et al. (2007) reported that males across all occupations were less likely to comply with infection control across all questions and were significantly less likely to clean their hands. Physicians reported a lower compliance with hand hygiene, wearing disposable gloves, wearing an N95 mask, wearing protective eyewear and wearing a face shield when compared with nurses. However, physicians had higher self-reported compliance with wearing a disposable outer garment. Additionally, younger workers (19-29 years) had better self-reported compliance than older workers (50-plus years). Overall, only 5 percent of respondents rated their training with respect to protective measures against infectious diseases as excellent. According to Yassi, et al. (2007), many respondents felt that their level of training was below what it should be in their current profession. The researchers reported a significant correlation between scoring in the high range for environmental factors (availability of resources) and reporting high levels of safety behavior compliance, with those people scoring high on environmental factors being almost 12 times as likely to also report high compliance. Similar results were found for organizational factors as well; respondents who rated their workplace highly relating to management support and safety climate were almost 10 times as likely to also report high compliance.
Saint, et al. (2010) acknowledge the gap between what should be done and what is now being done, and ask how can we better implement evidence-based practices in infection prevention: "Perhaps we can learn from implementation science, which is defined as 'the scientific study of methods to promote the systematic uptake of research findings and other evidence-based practices into routine practice.' The term implementation science is synonymous with 'T3' translation, theory-practice gap, knowledge transfer, and knowledge utilization. Although Semmelweis lacked a conceptual model, Everett Rogers’ work over the past six decades on 'diffusion of innovation' has provided implementation researchers with a strong conceptual foundation. While 'diffusion' (or spread) of an 'innovation' (a new practice or idea) was originally applied to the study of agriculture, it has been helpful in describing what occurs in other areas, including healthcare. For example, Krein, et al. have modified the Rogers’ model for use in infection prevention. The decision to adopt and implement an infection prevention practice is influenced by practice characteristics (e.g., cost, evidence, usability), the organization (e.g., leadership, personnel, resources), and the environmental context (e.g., public reporting, pay-for-performance).The decision to adopt – for example, to codify the use of MSB during central line insertion into the hospital's formal infection prevention policies – is distinct from the decision to implement, in which the hospital somehow ensures that central lines are consistently inserted using MSB. Only by effectively implementing evidence-based infection prevention practices can we reduce healthcare-associated infection."
Sarah Krein, PhD, RN, a co-author on the 2010 paper with Sanjay Saint and Joel Howell, alludes to the variation in practice that still exists. "I believe that some of the variation may relate to the level of evidence regarding certain practices or recommendations," she says. "However, variation is also driven by the implementation context, which can include such things as resources, culture, and competing demands or initiatives. It can be helpful to standardize the key recommendations for preventing infection based on the best available evidence. Standardizing how those recommendations or practices are implemented within a given setting is much more challenging. Although general strategies and guidance for implementation are now incorporated into the SHEA/IDSA practice recommendations, for example (see as an example Lo, et al., Strategies to Prevent Catheter-Associated Urinary Tract Infections in Acute Care Hospitals: 2014 Update, Infect Control and Hosp Epidemiol. Vol. 35, No. 5. May 2014), we still need more information and research as to how to promote effective implementation while taking context into account. While one implementation strategy may work in a certain hospital or even a certain unit within a hospital it may not work in another hospital or unit given key contextual differences. However, a systematic and easy to apply approach to identify those key contextual factors and based on that information determine the most effective implementation strategy for ensuring use of a given infection prevention practice remains an elusive goal.
In the revised Rogers model by Krein, the organizational characteristics of adoption decision, implementation and the HAI rate describe what is occurring in an institution but does not necessarily help hospital epidemiologists figure out what to do to implement change in their hospital.
"I believe the Roger’s model still provides a useful framework for studying and trying to understand certain issues related to the adoption and potential use of infection prevention practices," Krein says. "Depending on the focus or objective of the study other frameworks may be needed. However, as there are by some counts now more than 60 implementation related frameworks deciding which to use can be a daunting task. On the other hand, this task can be simplified somewhat based on the purpose for which the model is being used as some are more process focused, others are better for understanding or explaining what affects implementation outcomes, while others are primarily evaluation frameworks. With respect to the issue of healthcare worker compliance it can also be important to recognize that there are some models or frameworks that relate primarily to understanding individual behaviors, while others are more organizationally focused. So, it may be useful to also consider whether one or both types of frameworks might be useful based on the study objective."
Some healthcare institutions use the '4 E's' (Engage, Educate, Execute and Evaluate) model for successful infection prevention, and Krein says it is "a useful approach for implementing infection prevention practices as demonstrated by Pronovost and colleagues in their work to reduce bloodstream infections in Michigan." She adds, "It is an action-oriented framework that provides specific steps targeting critical areas for implementation involving engagement, education, evaluation and execution. Indeed, the 4-Es was also used in the implementation strategy section of the SHEA/IDSA practice recommendations for CAUTI prevention."
Saint, et al. (2010) enumerate the challenges to implementation science, despite recent advances: "The first is determining how to sustain meaningful change. Ideally, any successful initiative should be institutionalized. Too often, healthcare organizations fail to consolidate gains made during one change process before proceeding to the next problem. Second, understanding context is incredibly important, but not straightforward. Implementation within healthcare is often highly dependent on the setting, hospital personnel – both leadership and followership – and organizational culture (and micro-culture). Healthcare settings are unpredictable and non-linear. Implementation science is a clinical and a social discipline that has both 'technical' components and 'adaptive' ones. Therefore, using the tools from social science – such as qualitative research – may be necessary to better understand context. Finally, while much attention has focused on underuse, given the rise in healthcare costs – in part driven by the use of new technologies – tackling overuse (or over-diffusion) of an innovation will be vital. In short, we need models to help us focus on 'appropriate' use."
Relating to the challenges of sustaining meaningful change, Krein says, "Understanding context and focusing on appropriate use are still important areas for implementation research. One area where I think we have seen advancement is in the acceptance of and appreciation for using qualitative and mixed methods research as well as drawing on other disciplines, such as psychology, anthropology and human factors, to study and address the critical implementation related aspects of infection prevention."
Saint, et al. (2010) suggest that infection preventionists embrace implementation science by:
- Continuing to define the technical components (what should be the key items in the toolkits or part of the bundle) while focusing also on the adaptive ones (how to adapt or tailor the intervention given the context).
Collaborating with organizational behaviorists, other social scientists, and each other to develop approaches to address the dynamic role of context.
- Establishing a research network to find out not only what works, but how it works and in what settings.
- Determining how to “institutionalize” change while avoiding the over-adoption of fads.
- Identifying funders (e.g., National Institutes of Health, Agency for Healthcare Research and Quality, Centers for Disease Control and Prevention) that are willing to make large investments in understanding implementation science using infection prevention as an appropriate clinical model.
While not an improvement model per se, hospitals have become attracted to the concept of making it easier for healthcare workers to do the right thing, to boost compliance with evidence-based practices.
"I do believe that making it easier for healthcare personnel to do the right thing is an important strategy for implementing and ensuring the effective use of infection prevention practices," Krein emphasizes. "This is nicely described by one of my collaborators, Frank Drews, and his work involving adherence engineering. His work expands upon concepts from the field of human factors engineering by suggesting that 'some aspects of behavior are shaped externally and that behavior-shaping factors can be used to increase protocol adherence” and demonstrating how this concept can be used to improve central line maintenance.' However, I also believe that this is likely not the only strategy and that continuing focus on understanding and addressing behavioral factors as well as behavior shaping factors within the organization context and perhaps even broader environment are necessary to ensure effective practice use. Also, with respect to the behavioral side, the testing and use of theory-based behavior change interventions is an active area of ongoing research with applications in infection prevention as well as practice change in healthcare settings more broadly."
Slightly more than a decade ago, the Institute for Healthcare Improvement (IHI) established a research and development team and a process to consistently produce new thinking that would challenge the entrenched models that result in low-value, poor-quality care. IHI experts looked outside of healthcare, studying the work of leading innovators from the fields of industry, manufacturing and energy and then borrowing and adapting a systematic approach to creating new knowledge - sequential 90-day “waves” of projects (three to five projects per wave) to tackle vexing questions raised by IHI's partners, communities and patients. Recently, the IHI made available a curated publication that highlights 10 ideas that reshaped healthcare improvement.
For example, in the IHI's Breakthrough Series Collaborative Model, participants first select a topic that is ripe for improvement; that is, evidence exists but is not widely used, and better results have been demonstrated. Combine subject matter experts in specific clinical areas with application experts who are skilled in quality improvement. Name a chairperson who is a respected expert in the field, and convene expert faculty to create the specific content for the collaborative, including aims, changes and measures. Convene 20 to 40 healthcare organizations for a specific period of time (six to 15 months), setting a collective aim, testing changes, and reporting measures. Finally, end the collaborative with a summative congress and publication.
Another IHI approach is called a framework for spread and scale-up. As the IHI explains, "A key factor in closing the gap between best practice and common practice is the ability of health care providers, organizations, and community groups to rapidly scale up new ideas and practices. Pockets of excellence may exist in a system, but knowledge of these better ideas and practices often remains isolated and unknown to others." IHI’s Scale-Up Framework describes three core components of successful scale-up: a sequence of activities that are required to get a program of work to full scale, the mechanisms that are required to facilitate the adoption of interventions, and the underlying support systems required for successful scale-up.
An example most familiar to clinicians may be the Evidence-Based Care Bundles. As IHI explains, "A bundle is a small set of evidence-based interventions for a defined patient segment/population and care setting that, when implemented together and reliably, will result in significantly better outcomes than when implemented individually. The power of a bundle comes from implementing a small set of evidence-based interventions with 100 percent reliability - for every patient, every time."
According to the IHI, a bundle has the following key characteristics:
- Three to five evidence-based interventions (elements). The interventions in a bundle are all based on randomized controlled trials. They’ve been proven in scientific tests and are well established. A bundle focuses on how to deliver the best care - not what the care should be.
- Used on a defined patient population, in one care setting. Bundle elements occur in the same time and space continuum: at a specific time and in a specific place, no matter what - for example, patients on ventilators in the ICU. Involving care teams that physically work together in the same location with a defined patient population allows for strategies to achieve all-or-none bundle compliance that are not always transferable when multiple teams across multiple locations are involved.
- All-or-none measurement. Compliance with bundles is measured by documentation of adherence to all elements of the bundle, using a simple “yes” or “no.” If all elements have been accomplished, or if an element was documented as medically contraindicated (with the goal that all care team members know the rationale for exceptions, which may change over time), the bundle is counted as complete for that patient. If any of the elements are absent in the documentation, the bundle is incomplete.
"A well-designed bundle is a series of evidence-based practices necessary and sufficient to create an impact on whatever it is you are working on," confirms Kedar Mate, MD, chief innovation and education officer for the IHI. "To me, a bundle is a tool much like a clinical practice guideline, a decision rule or a checklist -- it is a practical tool to ensure that your system is designed to consistently deliver the best possible care or to create the positive change you want to see happen in your institution. A bundle or checklist aims to improve processes to the highest levels of reliability, which in turn drives improved outcomes. To achieve these improved outcomes, all practices in a bundle must be implemented and executed reliably and requires critical thinking and implementation expertise. The criticism of bundles -- or any form of standardization -- that they supposedly take the place of critical thinking, leading to so-called 'cookbook medicine,' is an overstatement. We have lived with clinical practice guidelines and decision trees for a very long time. These tools have not taken the thought out of medicine. As caregivers, we still must think through evidence-based guidelines and the potential outcomes from implementing a bundle. These tools support execution but they don't remove diagnostic enterprise or the notion of clinical intuition. Simply put, standardization doesn't remove the very human side of caregiving and the psychology of helping your patients make a fundamental change to their lives."
Mate encourages the healthcare community to reframe the issue of an individual's compliance with evidence-based practices to one of reforming the entire system to make it function in concert with the highest principles and expectations of quality care.
"The notion of compliance suggests that at its core there are those who wish to be non-compliant and those who would become compliant," says Mate. "Originally, the concept of compliance in healthcare was applied to patient safety and medicine. We moved away from that and toward adherence and now increasingly to co-management and self-management. This evolution is from extrinsic pressure -- an external auditor compelling physicians and healthcare professionals -- to embrace best practices, to intrinsic motivation based on what brought us to healthcare in the first place. Our professional credo as physicians and nurses, and what brings most people to join the field, is to do what's best for patients. What gets in the way of that is a system architected in a way that prevents clinicians from reaching or fulfilling his or her own intrinsic motivations, to do what is right and best for their patients -- that which is evidence-based and can maximize what healthcare can achieve."
As in every industry, there are bad actors; not everyone may share the noble credo of not doing harm. "Certainly, there is a very small segment of the clinician workforce that is not motivated by the desire to do the right thing, for whatever constellation of reasons," Mate confirms. "However, most clinicians are in it to do what's right. Sometimes the system in which they work is not operating in a way that allows them to do what is best for their patients in accordance with best clinical practices. In most cases, the workforce's motivation is to do good but it's something in the organization or system itself that produces poor compliance, or what I would describe as error, defect, harm, delay or discoordination. If you accept that reframing of the issue, then it gives you an opportunity. It moves you away from what is potentially a 'name, blame and shame' exercise that may result from a compliance perspective. Instead, we must shift our attention to the barriers that are preventing a system from operating in a way that keeps people safe and allows patients to receive the best possible care. When we do that, we are opened up to a universe of tools, many borrowed from industries outside healthcare that can help drive system-level change. We can take those tools, tweak them healthcare and then apply them to help engineer safer and higher-quality health systems."
Mate says it's a fallacy to think that healthcare professionals work as individuals these days. "Perhaps it's a last vestige of the days of old in clinical practice when we had the notion of the 'Doctor Superhero,' this sort of action-figure who would march into the room and save the day. We now know that trope is outdated. Today in the hospital setting, a patient probably experiences more than 100 visits from different caregivers within a three- to five-day admission. Every individual caregiver has responsibility for their piece of the puzzle, but unless those caregivers are organized in a way that allows them to seamlessly communicate, collaborate and achieve maximum impact, the system breaks down and we are left with individual caregiving without a comprehensive operation."
Mate says he believes in positive reinforcement and recognition rather than punitive approaches to foster cooperation among healthcare professionals. "Some individuals are done a disservice by the way a system is organized," Mate explains. "Healthcare professionals may still find a way to function within a system behaving in a way that is disadvantageous to patients and caregivers; that is, a system that is fraught with discoordination, disarray, confusion, and a lack of patient centeredness. In these situations, there may be no positive incentive to change. It's not so much that clinicians were trying to do bad, they are just not incentivized to do better. Now, I think we have an environment where we can change that.
As an historical example, when complications arose for patients in the hospital, complications that are now considered by CMS to be 'no-pay events' -- those complications historically were paid for, as there was no system in place to them. You had a system that was perfectly designed to allow an adverse event rate that was much too high because there was no good reason to change it. When the incentives did change, policy-makers believed that payment was the 'silver bullet.' It's not. It's part of it, as you must give people positive incentives to do something different.
But you must also provide them with the knowledge they need to change. You must give them a learning path, a way of systematically improving so they can reduce and eliminate infections and not incur penalties. They must begiven the tools to do better and the positive incentives to be moved from their state of inertia, putting those tools into action."
Mate continues, "We have the knowledge to act differently; we have known what to do about many things for quite some time, so our ability to narrow the differences between the leading edge of our knowledge and the lagging edge of our action is where implementation experts play. The heartening news is that there have been examples of knowledge-to-action gap closures in patient safety work, but we, as clinicians, must pay attention, do the research and act on that knowledge. Our deepening knowledge of the psychology of change has been significant, as has our improved understanding of how systems behave. We know there are ways that we can successfully influence behavior. Among physicians, peer-to-peer knowledge exchange is known to be a critical driver of positive change. Transparency in peer-to-peer situations can impact whether clinicians adopt certain behaviors. The primary concern of implementation science is the behavior of systems -- and the behaviors of us as actors in that system -- to close those knowledge-to-action gaps."
Baxter R, Taylor N, Kellar I and Lawton R. Systematic review: What methods are used to apply positive deviance within healthcare organizations? A systematic review. BMJ Quality & Safety. Vol. 25, No. 3. Pages 190-201. 2016.
Bisognano M, Schummers D. Flipping healthcare: an essay by Maureen Bisognano and Dan Schummers. BMJ 2014;349:g5852.
Bradley EH, Curry LA, Ramanadhan S, et al. Research in action: using positive deviance to improve quality of healthcare. Implement Sci 2009;4:25.
French JRP and Raven BH. The bases of social power. In: Cartright D, ed. Studies in Social Power. University of Michigan. Pages 150-167. 1959.
Institute for Healthcare Improvement. 10 IHI Innovations to Improve Health and Health Care. 2017. Available at: www.ihi.org
Institute of Medicine. Crossing the Quality Chasm. March 2001.
Krein SL, Olmsted RN, Hofer TP, et al. Translating infection prevention evidence into practice using quantitative and qualitative research. American Journal of Infection Control. 2006;34:507-12.
Pronovost PJ, Berenholtz SM, Needham DM. Translating evidence into practice: a model for large scale knowledge translation. BMJ. 2008;337:a1714.
Raven BH and Haley RW. Social influence and compliance of hospital nurses with infection control policies. In: Eiser RJ, ed. Social Psychology and Behavioral Medicine. Wiley. Pages 413-438. 1982.
Saint S, Howell JD and Krein SL. Implementation Science: How to Jumpstart Infection Prevention. Infect Control Hosp Epidemiol. 2010 Nov; 31(Suppl 1): S14-S17.
Seto WH. Staff compliance with infection control practices: application of behavioral sciences. J Hosp Infection. 30 (supplement) 107-115. 1995.
Williams MS. Implementation Science and Integration into Healthcare Systems. Genomic and Precision Medicine. 2017.
Yassi A, Lockhart K, Copes R, Kerr M, Corbiere M, Bryce E, et al. Determinants of Healthcare Workers’ Compliance with Infection Control Procedures. Healthcare Quarterly. Vol. 10, No.1. 2007.