| 1. |
- Antonacci, Grazia, et al.
(författare)
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How do healthcare providers use national audit data for improvement?
- 2023
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Ingår i: BMC Health Services Research. - London : BioMed Central (BMC). - 1472-6963. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Substantial resources are invested by Health Departments worldwide in introducing National Clinical Audits (NCAs). Yet, there is variable evidence on the NCAs’ effectiveness and little is known on factors underlying the successful use of NCAs to improve local practice. This study will focus on a single NCA (the National Audit of Inpatient Falls -NAIF 2017) to explore: (i) participants’ perspectives on the NCA reports, local feedback characteristics and actions undertaken following the feedback underpinning the effective use of the NCA feedback to improve local practice; (ii) reported changes in local practice following the NCA feedback in England and Wales. Methods: Front-line staff perspectives were gathered through interviews. An inductive qualitative approach was used. Eighteen participants were purposefully sampled from 7 of the 85 participating hospitals in England and Wales. Analysis was guided by constant comparative techniques. Results: Regarding the NAIF annual report, interviewees valued performance benchmarking with other hospitals, the use of visual representations and the inclusion of case studies and recommendations. Participants stated that feedback should target front-line healthcare professionals, be straightforward and focused, and be delivered through an encouraging and honest discussion. Interviewees highlighted the value of using other relevant data sources alongside NAIF feedback and the importance of continuous data monitoring. Participants reported that engagement of front-line staff in the NAIF and following improvement activities was critical. Leadership, ownership, management support and communication at different organisational levels were perceived as enablers, while staffing level and turnover, and poor quality improvement (QI) skills, were perceived as barriers to improvement. Reported changes in practice included increased awareness and attention to patient safety issues and greater involvement of patients and staff in falls prevention activities. Conclusions: There is scope to improve the use of NCAs by front-line staff. NCAs should not be seen as isolated interventions but should be fully embedded and integrated into the QI strategic and operational plans of NHS trusts. The use of NCAs could be optimised, but knowledge of them is poor and distributed unevenly across different disciplines. More research is needed to provide guidance on key elements to consider throughout the whole improvement process at different organisational levels. © 2023, The Author(s).
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| 2. |
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| 3. |
- Reed, Julie, et al.
(författare)
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Quality of locally designed surveys in a quality improvement collaborative : review of survey validity and identification of common errors
- 2024
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Ingår i: BMJ Open Quality. - London : BMJ Publishing Group Ltd. - 2399-6641. ; 13
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Tidskriftsartikel (refereegranskat)abstract
- Objective: Surveys are a commonly used tool in quality improvement (QI) projects, but little is known about the standards to which they are designed and applied. We aimed to investigate the quality of surveys used within a QI collaborative, and to characterise the common errors made in survey design.Methods: Five reviewers (two research methodology and QI, three clinical and QI experts) independently assessed 20 surveys, comprising 250 survey items, that were developed in a North American cystic fibrosis lung transplant transition collaborative. Content Validity Index (CVI) scores were calculated for each survey. Reviewer consensus discussions decided an overall quality assessment for each survey and survey item (analysed using descriptive statistics) and explored the rationale for scoring (using qualitative thematic analysis).Results: 3/20 surveys scored as high quality (CVI >80%). 19% (n=47) of survey items were recommended by the reviewers, with 35% (n=87) requiring improvements, and 46% (n=116) not recommended. Quality assessment criteria were agreed upon. Types of common errors identified included the ethics and appropriateness of questions and survey format; usefulness of survey items to inform learning or lead to action, and methodological issues with survey questions, survey response options; and overall survey design.Conclusion: Survey development is a task that requires careful consideration, time and expertise. QI teams should consider whether a survey is the most appropriate form for capturing information during the improvement process. There is a need to educate and support QI teams to adhere to good practice and avoid common errors, thereby increasing the value of surveys for evaluation and QI. The methodology, quality assessment criteria and common errors described in this paper can provide a useful resource for this purpose. © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
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| 4. |
- Gama, Fábio, Ass. Professor, 1980-, et al.
(författare)
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Implementation Frameworks for Artificial Intelligence Translation Into Health Care Practice : Scoping Review
- 2022
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Ingår i: Journal of Medical Internet Research. - Toronto, ON : JMIR Publications. - 1438-8871. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Significant efforts have been made to develop artificial intelligence (AI) solutions for health care improvement. Despite the enthusiasm, health care professionals still struggle to implement AI in their daily practice.Objective: This paper aims to identify the implementation frameworks used to understand the application of AI in health care practice.Methods: A scoping review was conducted using the Cochrane, Evidence Based Medicine Reviews, Embase, MEDLINE, and PsycINFO databases to identify publications that reported frameworks, models, and theories concerning AI implementation in health care. This review focused on studies published in English and investigating AI implementation in health care since 2000. A total of 2541 unique publications were retrieved from the databases and screened on titles and abstracts by 2 independent reviewers. Selected articles were thematically analyzed against the Nilsen taxonomy of implementation frameworks, and the Greenhalgh framework for the nonadoption, abandonment, scale-up, spread, and sustainability (NASSS) of health care technologies.Results: In total, 7 articles met all eligibility criteria for inclusion in the review, and 2 articles included formal frameworks that directly addressed AI implementation, whereas the other articles provided limited descriptions of elements influencing implementation. Collectively, the 7 articles identified elements that aligned with all the NASSS domains, but no single article comprehensively considered the factors known to influence technology implementation. New domains were identified, including dependency on data input and existing processes, shared decision-making, the role of human oversight, and ethics of population impact and inequality, suggesting that existing frameworks do not fully consider the unique needs of AI implementation.Conclusions: This literature review demonstrates that understanding how to implement AI in health care practice is still in its early stages of development. Our findings suggest that further research is needed to provide the knowledge necessary to develop implementation frameworks to guide the future implementation of AI in clinical practice and highlight the opportunity to draw on existing knowledge from the field of implementation science. ©Fábio Gama, Daniel Tyskbo, Jens Nygren, James Barlow, Julie Reed, Petra Svedberg.
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| 5. |
- Hollestelle, Antoinette, et al.
(författare)
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No clinical utility of KRAS variant rs61764370 for ovarian or breast cancer
- 2016
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Ingår i: Gynecologic Oncology. - : Elsevier BV. - 0090-8258 .- 1095-6859. ; 141:2, s. 386-401
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Tidskriftsartikel (refereegranskat)abstract
- Objective Clinical genetic testing is commercially available for rs61764370, an inherited variant residing in a KRAS 3′ UTR microRNA binding site, based on suggested associations with increased ovarian and breast cancer risk as well as with survival time. However, prior studies, emphasizing particular subgroups, were relatively small. Therefore, we comprehensively evaluated ovarian and breast cancer risks as well as clinical outcome associated with rs61764370. Methods Centralized genotyping and analysis were performed for 140,012 women enrolled in the Ovarian Cancer Association Consortium (15,357 ovarian cancer patients; 30,816 controls), the Breast Cancer Association Consortium (33,530 breast cancer patients; 37,640 controls), and the Consortium of Modifiers of BRCA1 and BRCA2 (14,765 BRCA1 and 7904 BRCA2 mutation carriers). Results We found no association with risk of ovarian cancer (OR = 0.99, 95% CI 0.94-1.04, p = 0.74) or breast cancer (OR = 0.98, 95% CI 0.94-1.01, p = 0.19) and results were consistent among mutation carriers (BRCA1, ovarian cancer HR = 1.09, 95% CI 0.97-1.23, p = 0.14, breast cancer HR = 1.04, 95% CI 0.97-1.12, p = 0.27; BRCA2, ovarian cancer HR = 0.89, 95% CI 0.71-1.13, p = 0.34, breast cancer HR = 1.06, 95% CI 0.94-1.19, p = 0.35). Null results were also obtained for associations with overall survival following ovarian cancer (HR = 0.94, 95% CI 0.83-1.07, p = 0.38), breast cancer (HR = 0.96, 95% CI 0.87-1.06, p = 0.38), and all other previously-reported associations. Conclusions rs61764370 is not associated with risk of ovarian or breast cancer nor with clinical outcome for patients with these cancers. Therefore, genotyping this variant has no clinical utility related to the prediction or management of these cancers.
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| 6. |
- Lennox, Laura, et al.
(författare)
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Conceptualising interventions to enhance spread in complex systems : a multisite comprehensive medication review case study
- 2022
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Ingår i: BMJ Quality and Safety. - London : BMJ Publishing Group Ltd. - 2044-5415 .- 2044-5423. ; 31:1, s. 31-44
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Tidskriftsartikel (refereegranskat)abstract
- Background: Advancing the description and conceptualisation of interventions in complex systems is necessary to support spread, evaluation, attribution and reproducibility. Improvement teams can provide unique insight into how interventions are operationalised in practice. Capturing this 'insider knowledge' has the potential to enhance intervention descriptions.Objectives: This exploratory study investigated the spread of a comprehensive medication review (CMR) intervention to (1) describe the work required from the improvement team perspective, (2) identify what stays the same and what changes between the different sites and why, and (3) critically appraise the 'hard core' and 'soft periphery' (HC/SP) construct as a way of conceptualising interventions.Design: A prospective case study of a CMR initiative across five sites. Data collection included: observations, document analysis and semistructured interviews. A facilitated workshop triangulated findings and measured perceived effort invested in activities. A qualitative database was developed to conduct thematic analysis.Results: Sites identified 16 intervention components. All were considered essential due to their interdependency. The function of components remained the same, but adaptations were made between and within sites. Components were categorised under four 'spheres of operation': Accessibility of evidence base; Process of enactment; Dependent processes and Dependent sociocultural issues. Participants reported most effort was invested on 'dependent sociocultural issues'. None of the existing HC/SP definitions fit well with the empirical data, with inconsistent classifications of components as HC or SP.Conclusions: This study advances the conceptualisation of interventions by explicitly considering how evidence-based practices are operationalised in complex systems. We propose a new conceptualisation of 'interventions-in-systems' which describes intervention components in relation to their: proximity to the evidence base; component interdependence; component function; component adaptation and effort. © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.
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| 7. |
- Marston, C. A., et al.
(författare)
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Working together to co-produce better health : The experience of the Collaboration for Leadership in Applied Health Research and Care for Northwest London
- 2020
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Ingår i: Journal of Health Services Research and Policy. - : Sage Publications. - 1355-8196 .- 1758-1060. ; 26:1, s. 28-36
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: To improve the provision of health care, academics can be asked to collaborate with clinicians, and clinicians with patients. Generating good evidence on health care practice depends on these collaborations working well. Yet such relationships are not the norm. We examine how social science research and health care improvement practice were linked through a programme designed to broker collaborations between clinicians, academics, and patients to improve health care – the UK National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care for Northwest London. We discuss the successes and challenges of the collaboration and make suggestions on how to develop synergistic relationships that facilitate co-production of social science knowledge and its translation into practice. Methods: A qualitative approach was used, including ethnographic elements and critical, reflexive dialogue between members of the two collaborating teams. Results: Key challenges and remedies were connected with the risks associated with new ways of working. These risks included differing ideas between collaborators about the purpose, value, and expectations of research, and institutional opposition. Dialogue between collaborators did not mean absence of tensions or clashes. Risk-taking was unpopular – institutions, funders, and partners did not always support it, despite simultaneously demanding ‘innovation’ in producing research that influenced practice. Conclusions: Our path was made smoother because we had funding to support the creation of a ‘potential space’ to experiment with different ways of working. Other factors that can enhance collaboration include a shared commitment to dialogical practice, a recognition of the legitimacy of different partners’ knowledge, a long timeframe to identify and resolve problems, the maintenance of an enabling environment for collaboration, a willingness to work iteratively and reflexively, and a shared end goal. © The Author(s) 2020.
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| 8. |
- Nilsen, Per, 1960-, et al.
(författare)
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Realizing the potential of artificial intelligence in healthcare : Learning from intervention, innovation, implementation and improvement sciences
- 2022
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Ingår i: Frontiers in Health Services. - Lausanne : Frontiers Media S.A.. - 2813-0146. ; 2
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Artificial intelligence (AI) is widely seen as critical for tackling fundamental challenges faced by health systems. However, research is scant on the factors that influence the implementation and routine use of AI in healthcare, how AI may interact with the context in which it is implemented, and how it can contribute to wider health system goals. We propose that AI development can benefit from knowledge generated in four scientific fields: intervention, innovation, implementation and improvement sciences.Aim: The aim of this paper is to briefly describe the four fields and to identify potentially relevant knowledge from these fields that can be utilized for understanding and/or facilitating the use of AI in healthcare. The paper is based on the authors' experience and expertise in intervention, innovation, implementation, and improvement sciences, and a selective literature review.Utilizing knowledge from the four fields: The four fields have generated a wealth of often-overlapping knowledge, some of which we propose has considerable relevance for understanding and/or facilitating the use of AI in healthcare.Conclusion: Knowledge derived from intervention, innovation, implementation, and improvement sciences provides a head start for research on the use of AI in healthcare, yet the extent to which this knowledge can be repurposed in AI studies cannot be taken for granted. Thus, when taking advantage of insights in the four fields, it is important to also be explorative and use inductive research approaches to generate knowledge that can contribute toward realizing the potential of AI in healthcare. © 2022 Nilsen, Reed, Nair, Savage, Macrae, Barlow, Svedberg, Larsson, Lundgren and Nygren.
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| 9. |
- Petersson, Lena, 1968-, et al.
(författare)
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Challenges to implementing artificial intelligence in healthcare : a qualitative interview study with healthcare leaders in Sweden
- 2022
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Ingår i: BMC Health Services Research. - London : BioMed Central (BMC). - 1472-6963. ; 22
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Tidskriftsartikel (refereegranskat)abstract
- Background: Artificial intelligence (AI) for healthcare presents potential solutions to some of the challenges faced by health systems around the world. However, it is well established in implementation and innovation research that novel technologies are often resisted by healthcare leaders, which contributes to their slow and variable uptake. Although research on various stakeholders’ perspectives on AI implementation has been undertaken, very few studies have investigated leaders’ perspectives on the issue of AI implementation in healthcare. It is essential to understand the perspectives of healthcare leaders, because they have a key role in the implementation process of new technologies in healthcare. The aim of this study was to explore challenges perceived by leaders in a regional Swedish healthcare setting concerning the implementation of AI in healthcare.Methods: The study takes an explorative qualitative approach. Individual, semi-structured interviews were conducted from October 2020 to May 2021 with 26 healthcare leaders. The analysis was performed using qualitative content analysis, with an inductive approach.Results: The analysis yielded three categories, representing three types of challenge perceived to be linked with the implementation of AI in healthcare: 1) Conditions external to the healthcare system; 2) Capacity for strategic change management; 3) Transformation of healthcare professions and healthcare practice.Conclusions: In conclusion, healthcare leaders highlighted several implementation challenges in relation to AI within and beyond the healthcare system in general and their organisations in particular. The challenges comprised conditions external to the healthcare system, internal capacity for strategic change management, along with transformation of healthcare professions and healthcare practice. The results point to the need to develop implementation strategies across healthcare organisations to address challenges to AI-specific capacity building. Laws and policies are needed to regulate the design and execution of effective AI implementation strategies. There is a need to invest time and resources in implementation processes, with collaboration across healthcare, county councils, and industry partnerships. © The Author(s) 2022.
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| 10. |
- Rust, Niki A., et al.
(författare)
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Have farmers had enough of experts?
- 2022
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Ingår i: Environmental Management. - : Springer New York. - 0364-152X .- 1432-1009. ; 69:1, s. 31-44
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Tidskriftsartikel (refereegranskat)abstract
- The exponential rise of information available means we can now, in theory, access knowledge on almost any question we ask. However, as the amount of unverified information increases, so too does the challenge in deciding which information to trust. Farmers, when learning about agricultural innovations, have historically relied on in-person advice from traditional ‘experts’, such as agricultural advisers, to inform farm management. As more farmers go online for information, it is not clear whether they are now using digital information to corroborate in-person advice from traditional ‘experts’, or if they are foregoing ‘expert’ advice in preference for peer-generated information. To fill this knowledge gap, we sought to understand how farmers in two contrasting European countries (Hungary and the UK) learnt about sustainable soil innovations and who influenced them to innovate. Through interviews with 82 respondents, we found farmers in both countries regularly used online sources to access soil information; some were prompted to change their soil management by farmer social media ‘influencers’. However, online information and interactions were not usually the main factor influencing farmers to change their practices. Farmers placed most trust in other farmers to learn about new soil practices and were less trusting of traditional ‘experts’, particularly agricultural researchers from academic and government institutions, who they believed were not empathetic towards farmers’ needs. We suggest that some farmers may indeed have had enough of traditional ‘experts’, instead relying more on their own peer networks to learn and innovate. We discuss ways to improve trustworthy knowledge exchange between agricultural stakeholders to increase uptake of sustainable soil management practices, while acknowledging the value of peer influence and online interactions for innovation and trust building.
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