Literature DB >> 29447351

Research versus practice in quality improvement? Understanding how we can bridge the gap.

Lisa R Hirschhorn1, Rohit Ramaswamy2, Mahesh Devnani3, Abraham Wandersman4, Lisa A Simpson5, Ezequiel Garcia-Elorrio6.   

Abstract

The gap between implementers and researchers of quality improvement (QI) has hampered the degree and speed of change needed to reduce avoidable suffering and harm in health care. Underlying causes of this gap include differences in goals and incentives, preferred methodologies, level and types of evidence prioritized and targeted audiences. The Salzburg Global Seminar on 'Better Health Care: How do we learn about improvement?' brought together researchers, policy makers, funders, implementers, evaluators from low-, middle- and high-income countries to explore how to increase the impact of QI. In this paper, we describe some of the reasons for this gap and offer suggestions to better bridge the chasm between researchers and implementers. Effectively bridging this gap can increase the generalizability of QI interventions, accelerate the spread of effective approaches while also strengthening the local work of implementers. Increasing the effectiveness of research and work in the field will support the knowledge translation needed to achieve quality Universal Health Coverage and the Sustainable Development Goals.

Entities:  

Mesh:

Year:  2018        PMID: 29447351      PMCID: PMC5909640          DOI: 10.1093/intqhc/mzy018

Source DB:  PubMed          Journal:  Int J Qual Health Care        ISSN: 1353-4505            Impact factor:   2.038


Introduction

After mixed results from the Millennium Development Goals (MDGs) strategy, the global agenda recognized the critical role of ensuring not just access but quality of health care delivery. As a result, quality and improvement have become a core focus within the Universal Health Coverage movement to achieve the goal of better population health and Sustainable Development Goals (SDGs)[1-3]. In low- and middle-income countries, quality improvement (QI) is used to identify performance gaps and implement improvement interventions to address these problems at the local, sub national and national levels. Methods used by these improvement interventions range from process improvements using incremental, cyclically implemented changes appropriate to the local context, to system-level interventions and policies to improve and sustain quality. Regardless of the scope of improvement efforts and methods employed, the impact and spread of QI has often fallen short. Causes of these lost opportunities include how decisions about improvement interventions are made, the methodology for measuring the effectiveness of the intervention, what data are collected and used and how the information on both the implementation and the intervention is communicated to drive spread and knowledge translation [4, 5]. Practitioners engaged in improvement in their organizations are frustrated by research reviews which often show a lack of conclusiveness about the effectiveness of QI when many of them see the local benefits from their work. Researchers complain about the lack of rigor in the application of QI methods in practice sittings and about poor documentation of the implementation process [6]. There is a growing realization of the need for common ground between implementers and researchers that promotes use of more systematic and rigorous methods to assess the improvement intervention effectiveness when appropriate but does not demand that all QI implementations be subject to the experimental methods commonly considered to be the gold standard of evidence. To explore the causes of this gap and address how to bridge the gap and better engage the targeted consumers of generated knowledge, including communities, governments and funders, a session ‘Better Health Care: How do we learn about improvement?’ was organized by Salzburg Global Seminar (SGS) [7]. The session brought together experts from a range of fields and organizations, including researchers, improvement implementers from the field, policy makers, and representatives from countries and international organizations. For a partnership between researchers and implementers to become more consistent in improvement projects and studies, the incentives and priorities of each of these groups need to be better aligned in QI work and its evaluation. In this paper, we build on the Salzburg discussions, existing literature, and our own experience to explore the barriers to collaboration and offer suggestions on how to start to address these barriers. In the spirit of quality improvement, we hope that these recommendations are adopted and tried by groups interested in advancing the research and the practice of QI.

Why the gap exists

Both groups use data to evaluate whether improvements have taken place and are interested in the question of ‘did it work’. However, these gaps have occurred in part because of differences in goals, evidence needs and methods used and incentives for results and dissemination.

Goals

As we consider the major differences between researchers and implementers, we should recognize that there is not a clearly defined dichotomy between these two groups. Rather, those who are focused on in improvement are part of a continuum and are driven by a range of goals from driving and demonstrating local improvements to a focus on attributing these improvements to QI methods that can be generalized and spread, as illustrated in Table 1, which also describes differences in incentives, discussed further below. Organization-based implementers focus on quality improvement projects, where the primary goal is driving change to a local problem to improve care. Policy and decision makers' goals are broader improvement, needing evidence for current and future decision on what methods and implementation strategies to use. Researchers have a goal of developing new and generalizable knowledge about the effectiveness of QI methods.
Table 1

Selected participants and stakeholders in quality improvement work and research and their incentives and goals

GoalsIncentives
QI team members and institutional championsImplement effective QI projects and promote and support change in their institutions through good improvement practiceLocal improvement and disseminate the best local knowledge about what works
Policy makers whose goals arePrioritization to invest in improvement projects based on best available evidence from academic research and practical wisdomMake effective, yet timely and practical decisions given constraints on time and knowledge to choose and spread efficient, effective and sustainable improvement
Embedded (practice-based) researchers, QI implementers engaged in researchDrive improvement in their own setting, advance the best improvement methods in their own settings and create generalizable knowledge to make a plausible case linking the QI activities to observed outcomes for broader disseminationCreate practical yet generalizable knowledge linking improvement activities to observed outcomes for dissemination to both practice and research audiences
Academic and other researchersEstablish strong causal relationships between QI and outcomes, promoting more rigorous experimental research in QIUse of rigorous science that can be published in peer-reviewed journals and establish objective standards of evidence
Selected participants and stakeholders in quality improvement work and research and their incentives and goals

Incentives for results and dissemination

The differences in goals and evidence are related to often competing incentives. Implementers are incentivized to improve quality and meet the demands of stakeholders, whether local communities, government or funders. Researchers are rewarded through dissemination of evidence in high-impact peer-reviewed journals, research grants and academic promotions. Policy makers are rewarded by timely response to gaps with broad visible changes in their populations. Timeframes of these incentives are also often different, with the most rigorous studies taking years to measure impact, followed by careful analysis and dissemination. Implementers and policy makers, however, are often under pressure to show short-term change and respond to new and emerging issues even as they continue with existing improvement work. The goals of documentation and dissemination of projects can also differ between researchers and implementers and their stakeholders. There is a strong recognition that the evidence generated by even the best QI efforts is not effectively translated into further spread and adoption [8]. This is because implementers working on QI interventions in their organizations are incentivized by improvement and do not usually have a demand to document their work beyond communication with organizational leaders. While there are growing venues for sharing of case reports through learning collaboratives and local meetings designed to facilitate peer learning, this documentation typically involves a description of the process of implementation, but not at a level of detail or rigor of value to researchers and the broader community. There are a number of disincentives for implementers to increase the rigor and detail of their local work including competing demands to deliver services and ongoing improvement, and the paucity of journals interested in publishing even well- documented local results because they prioritize rigorous results of evaluations with strong designs involving carefully constructed QI research studies. Researchers are incentivized by more academic dissemination through these peer-reviewed journals and presentation at conferences. This nonalignment results in practitioners being deprived of access to broader venues to disseminate their work and researchers losing rich contextual data that is critically important to evaluate the effectiveness of QI.

Evidence needed and methods prioritized

The differences in the goals and incentives of different stakeholders lead to differences in the amount of evidence that is considered adequate and the methods used to generate this evidence. Implementers are interested in the evidence of change in their local projects, with less emphasis on transferring or generalizing what they did for use in other settings. They may rely on a combination of pre-and-post intervention data, QI statistical methods such as run charts and tacit organizational knowledge to assess the evidence of change in their projects. Policy makers have an interest in evidence which is robust enough from the QI to inform resource allocation, but may still have a focus on a specific geography rather than generalizability at scale. They are interested in generalizable knowledge about successful QI methods, but are sensitive to the burden and costs and time of requiring rigorous research methods on implementing groups. Researchers aim for evidence which is robust enough to provide globally relevant conclusions with limited threats to internal validity. This group is most supportive of the use of rigorous experimental research designs to generate the highest possible standards of evidence. Traditionally, this had been limited to a small set of rigid experimental designs with appropriate controls or comparison groups driven in part by research funders and academic standards to be able to attribute change to the improvement interventions. This set of designs has been expanding in the past few years as better understanding of the value of quasi-experimental methods has emerged. [9, 10]

Why better alignment is needed

QI interventions differ from many fixed clinical or public health interventions [11]. In this supplement, Ramaswamy and others describe QI interventions as complex (multi-pronged and context-specific) interventions in complex systems (non-linear pathways and emergent behaviors). For better learning from QI, implementers, policy makers and researchers both need to know not just effectiveness (the focus of local measurement, outcomes research and impact evaluation) but also 'how and why' the change happened (implementation), cost and sustainability ensuring that the evidence produced will be more relevant to the stakeholders at the local and broader level. Therefore, finding a common ground through ‘development of a culture of partnership’ [12] to co-identify appropriate methods and data collection to understand and disseminate implementation strategies is critical to inform how to how to create the different knowledge products: generalizable evidence for dissemination (researchers), insights into how to scale (policy makers) and how to sustain the improvements (implementers) [13]. A well-known and commonly cited example is the Surgical Safety Checklist, which was found to improve adherence to evidence-based practices and save lives across a range of settings [14]. However, attempts to replicate these successes were not always effective since capturing generalizable knowledge on how to introduce and support the implementation of this intervention with fidelity was not part of the original research dissemination, [15] a lesson understood by the original researchers and addressed through accompanying toolkits [16]. Another important area where collaboration between implementers and researchers is needed to improve learning from QI in understanding the impact of different contextual factors to identify which aspects of an improvement intervention are generalizable, which are context-specific and which are critical to address when planning replication. During the seminar, a study of antenatal corticosteroids (ANCS), an intervention found in higher income settings to reduce death among premature infants, was discussed to identify how contextual factors can be better addressed through local knowledge to inform implementation [17]. The randomized controlled trial showed that implementation of ANCS in low-resource settings resulted in increased mortality among some of the infants who were given steroids; the published conclusion was that ANCS was not a recommended improvement intervention in these settings. The group identified the gap in the translation of ANCS use from resource richer settings did not consider the different contextual factors which required adaption such as the lack of capacity to accurately determine prematurity needed to determine eligibility for the steroids.

Starting the work to bridge the gap

Based on the reasons for the gaps identified above, we recommend a number of initial steps to better bridge the gap between researchers and implementers: Aligning project goals and joint planning: Before QI projects get launched, the initial work must start with implementers and researchers discussing and agreeing on the goals and objectives of the work including and beyond local improvement. In addition to alignment of improvement goals, all stakeholders must be engaged at the start of the QI project to agree on the purposes and uses of the results, local learning or broader dissemination or both. This work needs to happen at the design phase and continue with ongoing planned communication throughout the work. This will ensure that all stakeholders are jointly engaged in identifying the most appropriate research questions and the most appropriate methods to answer them. Choosing the right research design. The joint framing of goals and research questions can lead to a selection of evaluation and research designs at an appropriate, mutually agreed upon level of rigor including right research methodology for success [18]. This balancing of rigor versus flexibility, described in the meeting as a ‘bamboo scaffold that bends in the wind’ can only be accomplished when there is an open discussion of trade-offs between investments in data collection for research and data collection for demonstrating local improvements. Detailed documentation of implementation approaches is time consuming and resource intensive, and cannot be routinely expected for every project. On the other hand, some improvement in documentation as part of routine practice will benefit practitioners by providing important insights about local sustainability, and can be used by researchers to assess generalizability, attribution and scale. The need to understand both process and context in the evaluation and study of QI interventions also cannot be accomplished without engaging both researchers and practitioners in the process [13]. The knowledge about how the project was implemented, and what was relevant to the context often resides with those responsible for implementation. However, as mentioned previously, the implementers often have neither the incentives nor the support to systematically document and disseminate this knowledge in a way that makes it available for general use. Researchers can play a key role in influencing the QI research integration by supporting systematic documentation of the implementation process in addition to an evaluation of outcomes and by partnering with implementers to make this happen. Introduction of adaptive designs such as SMART trials into improvement research may also offer a common ground where improvement implementers and researchers can collaborate introducing use of data to make mid-course changes to the implementation design. Building implementer research capacity. Building capacity of implementers as potential producers of and better consumers of research and evaluation results in another important approach to bridge the gap. For example, empowerment evaluation is designed to increase the likelihood that programs will achieve results by increasing the capacity of program stakeholders to plan, implement and evaluate their own program [19]. Building capacity within implementing organizations through technical support provided by researchers for interested implementers can establish a viable infrastructure for practitioners and researchers to work together more effectively. For example, multi-year research practice partnerships in facilities in Kenya has led to sustainable QI programs with dissemination of methods and results through co-authored peer-reviewed journals and conference presentations [20] Similar results were seen for research capacity building targeting implementers in the Africa Health Initiative in five countries in Africa [21]. Support for practice-based researchers to build their capacity in QI and in process evaluation using implementation science methods can also increase the potential of improvement projects to produce the knowledge needed about the implementation to spread learning within and beyond their organization. Aligning incentives to drive collaboration: Creating areas of shared incentives will require initiatives from funders and universities to appreciate the higher value of co-produced research, reward capacity building of researchers in the field and fund innovative models of embedded research where researchers are part of or embedded into the implementing organization [22]. In addition, offering opportunities for meaningful participation in research and building capacity for this work among implementers has also been associated with better improvement and dissemination [23]. Simplifying documentation for dissemination of learning: As mentioned earlier, it is useful for both implementers and researchers if documenting the implementation of QI programs becomes part of routine practice. However, this will not happen without simplifying documentation standards. SQUIRE and TiDieR guidelines are very helpful for academic publications. However, they are not always a good fit for projects whose primary purpose is not research but who have the potential to add to the knowledge needed to improve QI [24, 25]. Researchers could partner with implementers to develop simpler, practice-based research guidelines and to create other venues such as through existing organizations focused on quality and improvement where methods and results could be posted using these guidelines without a formal peer-review process. Templates and examples could be provided to improve the quality of documentation as well as editorial staff to assist with structure and formatting. The incentive for implementers is to get their stories told, and at the same time provide an opportunity for researchers to get data on where to focus further research. In addition, there are growing options to share knowledge and research findings such as the WHO Global Learning Lab for Quality UHC which provides a forum for implementers to disseminate work available to broader community [26].

Conclusion

To improve learning from and effectiveness of QI work requires involvement and collaboration between both researchers and practitioners. Researchers can advance the field by creating generalizable knowledge on the effectiveness of interventions and on implementation strategies and practitioners improve outcomes on the ground by implementing QI interventions. By increasing the collaboration, more systematic evaluations of interventions in local contexts and better design of research will result in production of the generalizable knowledge needed to increase the impact of QI. In order for this to take place, there needs to be an intentional effort to address the gaps that challenge researchers and practitioners working together. This can occur by aligning incentives, increasing the value and utility of produced research to implementers, and as a shared community developing new guidance to bring these different groups to more effective collaboration. The growing experience in QI and improvement science offers many opportunities for better collaboration between researchers and implementers to increase the value of this partnership to accelerating progress toward quality Universal Health Coverage and the Sustainable Development Goals.
  19 in total

1.  Evidence-based quality improvement: the state of the science.

Authors:  Kaveh G Shojania; Jeremy M Grimshaw
Journal:  Health Aff (Millwood)       Date:  2005 Jan-Feb       Impact factor: 6.301

2.  Bridging the ivory towers and the swampy lowlands; increasing the impact of health services research on quality improvement.

Authors:  Martin N Marshall
Journal:  Int J Qual Health Care       Date:  2013-10-17       Impact factor: 2.038

Review 3.  Recommendations for evaluation of health care improvement initiatives.

Authors:  Gareth J Parry; Andrew Carson-Stevens; Donna F Luff; Marianne E McPherson; Donald A Goldmann
Journal:  Acad Pediatr       Date:  2013 Nov-Dec       Impact factor: 3.107

Review 4.  Bridging research and practice: models for dissemination and implementation research.

Authors:  Rachel G Tabak; Elaine C Khoong; David A Chambers; Ross C Brownson
Journal:  Am J Prev Med       Date:  2012-09       Impact factor: 5.043

5.  A population-based, multifaceted strategy to implement antenatal corticosteroid treatment versus standard care for the reduction of neonatal mortality due to preterm birth in low-income and middle-income countries: the ACT cluster-randomised trial.

Authors:  Fernando Althabe; José M Belizán; Elizabeth M McClure; Jennifer Hemingway-Foday; Mabel Berrueta; Agustina Mazzoni; Alvaro Ciganda; Shivaprasad S Goudar; Bhalachandra S Kodkany; Niranjana S Mahantshetti; Sangappa M Dhaded; Geetanjali M Katageri; Mrityunjay C Metgud; Anjali M Joshi; Mrutyunjaya B Bellad; Narayan V Honnungar; Richard J Derman; Sarah Saleem; Omrana Pasha; Sumera Ali; Farid Hasnain; Robert L Goldenberg; Fabian Esamai; Paul Nyongesa; Silas Ayunga; Edward A Liechty; Ana L Garces; Lester Figueroa; K Michael Hambidge; Nancy F Krebs; Archana Patel; Anjali Bhandarkar; Manjushri Waikar; Patricia L Hibberd; Elwyn Chomba; Waldemar A Carlo; Angel Mwiche; Melody Chiwila; Albert Manasyan; Sayury Pineda; Sreelatha Meleth; Vanessa Thorsten; Kristen Stolka; Dennis D Wallace; Marion Koso-Thomas; Alan H Jobe; Pierre M Buekens
Journal:  Lancet       Date:  2014-10-15       Impact factor: 79.321

Review 6.  Countdown to 2015: a decade of tracking progress for maternal, newborn, and child survival.

Authors:  Cesar G Victora; Jennifer Harris Requejo; Aluisio J D Barros; Peter Berman; Zulfiqar Bhutta; Ties Boerma; Mickey Chopra; Andres de Francisco; Bernadette Daelmans; Elizabeth Hazel; Joy Lawn; Blerta Maliqi; Holly Newby; Jennifer Bryce
Journal:  Lancet       Date:  2015-10-22       Impact factor: 202.731

7.  Strengthening health systems through embedded research.

Authors:  Abdul Ghaffar; Etienne V Langlois; Kumanan Rasanathan; Stefan Peterson; Lola Adedokun; Nhan T Tran
Journal:  Bull World Health Organ       Date:  2017-02-01       Impact factor: 9.408

8.  Using Value Stream Mapping to improve quality of care in low-resource facility settings.

Authors:  Rohit Ramaswamy; Claire Rothschild; Funmi Alabi; Eric Wachira; Faith Muigai; Nick Pearson
Journal:  Int J Qual Health Care       Date:  2017-11-01       Impact factor: 2.038

9.  Implementation research to catalyze advances in health systems strengthening in sub-Saharan Africa: the African Health Initiative.

Authors:  Kenneth Sherr; Jennifer Harris Requejo; Paulin Basinga
Journal:  BMC Health Serv Res       Date:  2013-05-31       Impact factor: 2.655

Review 10.  The role of embedded research in quality improvement: a narrative review.

Authors:  Cecilia Vindrola-Padros; Tom Pape; Martin Utley; Naomi J Fulop
Journal:  BMJ Qual Saf       Date:  2016-04-29       Impact factor: 7.035

View more
  10 in total

1.  Comparing Rates of Adverse Events and Medical Errors on Inpatient Psychiatric Units at Veterans Health Administration and Community-based General Hospitals.

Authors:  Sara W Cullen; Ming Xie; Jentien M Vermeulen; Steven C Marcus
Journal:  Med Care       Date:  2019-11       Impact factor: 2.983

Review 2.  Culture of Safety: Impact on Improvement in Infection Prevention Process and Outcomes.

Authors:  Barbara I Braun; Salome O Chitavi; Hiroyuki Suzuki; Caroline A Soyemi; Mireia Puig-Asensio
Journal:  Curr Infect Dis Rep       Date:  2020-12-02       Impact factor: 3.725

3.  Developing a national patient safety plan in Guatemala.

Authors:  Randall Lou-Meda; Sindy Méndez; Erwin Calgua; Mónica Orozco; Bria J Hall; Natalie Fahsen; Brad M Taicher; Joseph P Doty; Julio García Colindres; Carlos Soto Menegazzo; Henry E Rice
Journal:  Rev Panam Salud Publica       Date:  2019-07-31

4.  Experience of Health Leadership in Partnering With University-Based Researchers in Canada - A Call to "Re-imagine" Research.

Authors:  Sarah Bowen; Ingrid Botting; Ian D Graham; Martha MacLeod; Danielle de Moissac; Karen Harlos; Bernard Leduc; Catherine Ulrich; Janet Knox
Journal:  Int J Health Policy Manag       Date:  2019-12-01

5.  Partnering with patients in quality improvement: towards renewed practices for healthcare organization managers?

Authors:  Nathalie Clavel; Marie-Pascale Pomey; Djahanchah Philip Sacha Ghadiri
Journal:  BMC Health Serv Res       Date:  2019-11-08       Impact factor: 2.655

Review 6.  Developing criteria for research translation decision-making in community settings: a systematic review and thematic analysis informed by the Knowledge to Action Framework and community input.

Authors:  Marilyn E Wende; Sara Wilcox; Zoe Rhodes; Deborah Kinnard; Gabrielle Turner-McGrievy; Brooke W McKeever; Andrew T Kaczynski
Journal:  Implement Sci Commun       Date:  2022-07-16

7.  What shapes research and research capacity building in rural health services? Context matters.

Authors:  Anna Wong Shee; Claire Quilliam; Denise Corboy; Kristen Glenister; Carol McKinstry; Alison Beauchamp; Laura Alston; Darryl Maybery; Drew Aras; Kevin Mc Namara
Journal:  Aust J Rural Health       Date:  2022-02-21       Impact factor: 2.060

8.  Not yet 90-90-90: A quality improvement approach to human immunodeficiency virus viral suppression in paediatric patients in the rural Eastern Cape, South Africa.

Authors:  James D Porter; Mireille N M Porter; Maresa Du Plessis
Journal:  S Afr Fam Pract (2004)       Date:  2020-10-15

9.  Team-based primary health care for non-communicable diseases: complexities in South India.

Authors:  Dorothy Lall; Nora Engel; Narayanan Devadasan; Klasien Horstman; Bart Criel
Journal:  Health Policy Plan       Date:  2020-11-01       Impact factor: 3.344

10.  The Role of Local Leaders in the Implementation of Adult-Initiated Motor Skill Development and Physical Activity in Preschool-A Case Study.

Authors:  Trine Top Klein-Wengel; Jonas Vestergaard Nielsen; Søren Smedegaard; Thomas Skovgaard
Journal:  Int J Environ Res Public Health       Date:  2021-12-12       Impact factor: 3.390

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.