Accelerate the implementation of evidence-based health promotion in healthcare
About the author:
Director, Clinical Health Promotion Centre, Bispebjerg & Frederiksberg Hospital, University of Copenhagen, Copenhagen, Denmark.
Professor at Lund University, Skåne University Hospital, Malmö, Sweden
Professor, University of Southern Denmark
CEO, International HPH Secretariat
Implementation of solid evidence and related policies is a critical problem in healthcare as well as in other organizations. The delay from evidence to full implementation has been described to be over 10 years (1). It has major consequence for the individual patients and their families as well as for the healthcare and society. The implementation may be even slower for activities that actively involve the patients, such as health promotion in hospitals and primary care (2). The consequences include increased morbidity and mortality, in addition to reduced work power and quality of life – all of which could have been limited by timely implementation.
Evidence-based policies and guidelines do not implement themselves
The delayed implementation of new solid evidence takes place in spite of well-established national, regional or local policies and guidelines one smoking, risky drinking, malnutrition, overweight and sedentary lifestyle, e.g. from the Surgeon General (US), the National Institute for Health and Care Excellence (UK), the Danish National Board of Health and Welfare and Korea Health Promotion Foundation. High-effective programs are part of health planning world-wide and should be offered to all in need – regardless of the setting – keeping in mind that these conditions have a social gradient and strike harder among the vulnerable and disadvantaged patient groups. However, this is not the case today!
Slow implementation strikes the hardest among vulnerable and disadvantaged patients
In best case, the patients with the highest needs should receive most related services, but as the implementation of new solid evidence is slow, it may require high health literacy and a strong network to ask for and receive the evidence-based health services. Those characteristics are less frequent among the vulnerable and disadvantaged patients. The fact is that slow implementation limits access to new evidence-based health services and increase the inequity in health.
Faster implementation is required
The obvious solution is just to speed up the implementation. To support implementation and dissemination in the healthcare over 60 theoretical frameworks and models have been described (3), but the large majority yet have to be proven effective and speed up the implementation in practice, and there is a general call for evaluation in high-quality research design (4;5).
The two most used framework for reporting the on the implementation is the Framework of Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) and the Consolidated Framework for Implementation Research (CFIR) (6;7). The RE-AIM is easy-to-use, both for structured reporting of the implementation results with a follow-up period of 2 years and for comparing across settings and different activities, such as quit smoking campaigns and individual smoking cessation interventions. The benefit of the CFIR is the detailed structure for in-depth discussions and understanding of local barriers and facilitators for implementation, but it is very time-consuming and does not report the level of implementation. The two framework may be complementary, but that also remain to be tested. None of the frameworks include drivers to accelerate the implementation.
Implementation science represents a new tradition and culture for evaluation of implementation strategies. It is a fast growing area of research defined as the scientific study of methods to promote the uptake of research findings into routine practice (8;9) thus improving quality and effectiveness of health services.
Some new and comprehensive studies have reported that specific models do not necessarily facilitate implementation. The first multi-national European randomised trial in this area included 23 long-term nursing care in England, Sweden, Netherlands, Republic of Ireland. It did, however, not show a difference in implementation of two models of structured support compared to a control group. (10) Independent accreditation of hospitals and other healthcare is another facilitator of implementation, but also a big business. A new cohort study on 4 400 hospitals and 4 242 684 patients in the US concluded that the Joint Commission was not associated with consistently better mortality and readmission rates at 30 days or patient experiences when compared to other independent accrediting organizations (11).
More to come
Overall, we need more models and tools that has proven effective in putting new evidence into practice. This might be the reason that the development and evaluation of the new model for fast-track implementation (FAST-IM) in the HPH Network has been warmly welcomed, when presented at international health forums for managers, clinicians, public health professionals, health planners and other groups. It took place at 38 HPH member hospitals in 8 European and Asian areas, and the results are in the final step of the editorial process for publication. The managers, clinicians and patients reported positive experiences from the process (12). More evidence will be collected in the nearest future as several study protocols have been published, so hopefully we will soon be able to accelerate the implementation using effective tools and models based on solid evidence.
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(8) Implementation Science www.implementationscience.biomedcentral. com
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(10) Seers K, Rycroft-Malone J, Cox K, Crichton N, Edwards RT, Eldh AC, Estabrooks CA, Harvey G, Hawkes C, Jones C, Kitson A, McCormack B, McMullan C, Mockford C, Niessen T, Slater P, Titchen A, Zijpp Tvd, Wallin L. Facilitating Implementation of Research Evidence (FIRE): an international cluster randomised controlled trial to evaluate two models of facilitation informed by the Promoting Action on Research Implementation in Health Services (PARIHS) framework. Implementation Science (2018) 13:137 https://doi. org/10.1186/s13012-018-0831-9
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