Proceedings from the 9th annual conference on the science of dissemination and implementation
Notice bibliographique
Résumé
At a time of significant upheaval in American health policy, maintaining a focus on a "North Star" is critical.For implementation science, this star is the knowledge base on how to optimally disseminate evidence related to health and health care, how to implement interventions to improve care within the many settings where people receive health care and make health-related decisions, and how to improve the health of the global population.To that end, the end of 2016 brought over 1100 engaged and activated "disciples of D & I" to Washington, DC for the 9 th Annual Conference on the Science of Dissemination and Implementation in Health.Once again, the accompanying abstracts in this issue demonstrate the breadth, depth and vigor of this continually expanding and evolving subset of health research.During three dynamic plenaries with rows and rows of filled seats and packed concurrent sessions presenters and attendees shared findings, raised methodologic and other challenges, and discussed future priorities, trends, and next steps for this community of research.For the third year in a row, we were buoyed by a strong partnership, co-led by AcademyHealth and the National Institutes of Health (NIH), with co-sponsorship from others committed to implementation science: the Agency for Healthcare Research and Quality (AHRQ), the Patient Centered Outcomes Research Institute (PCORI), the Robert Wood Johnson Foundation (RWJF), and the US Department of Veterans Affairs (VA).The multidisciplinary program planning committee informed the development of the key themes for the conference, identified the plenary sessions topics and speakers, established track leads to manage the review process for concurrent panels, papers, and posters, and convened a scientific advisory panel to advise on the overall conference, thus ensuring a robust, inclusive, and rigorous process.Together, the opening keynote address and the three plenary panel sessions set a tone of innovation and dialogue, raised critical issues, surfaced different perspectives, and ensured that follow on lunchtime and hallway discussions delved deeper into thorny challenges facing the field.Roy Rosin, Chief Innovation Officer for the University of Pennsylvania's Perelman School of Medicine, introduced the audience to a range of methods for rapid testing, innovation in healthcare delivery, and lessons learned from other industries to maximize potential of new practices to be scaled-up.Each of the three plenary panels presented a general discussion on a high priority challenge for dissemination and implementation (D & I) research.A panel on the balance between intervention and implementation fidelity and local adaptation touched on the very real dynamic that is playing out in communities across this country as policy and payment changes are driving providers and others to seek new ways to solve the challenges in their particular contexts.A panel on the longerterm decisions around sustainment or de-implementation of interventions could not be more timely given the "improvement fatigue" of some systems and providers and the very real limits on providers' time and focus.Too often, the imperative is to "do more"; much more attention needs to be about stopping what is not working, particularly in light of estimates that 30 percent of care provided is either unnecessary, of low value or wasteful (Institute of Medicine, 2013).The third plenary panel brought different perspectives on the enduring and evolving challenges in the dissemination of evidence and evidence-based practices as well as the opportunities emerging from innovations in the digital health sector.The plenary sessions were complemented by facilitated lunchtime discussions on these topics, as well as additional research priorities, which enabled more in-depth discussions, additional question and answer time, and brainstorming of future directions.Synopses of the lunchtime discussions are included in this supplement.The concurrent sessions were once again organized by tracks.Last year's tracks-Behavioral Health, Big Data and Technology for Dissemination and Implementation Research, Clinical Care Settings, Global Dissemination and Implementation, Promoting Health Equity and Eliminating Disparities, Health Policy Dissemination and Implementation, Prevention and Public Health, and Models, Measures and Methods-were maintained, and a new track on Precision Medicine was added, built upon the significant interest that emerged from last year's plenary and subsequent discussions at NIH, National Academy of Medicine, and beyond.The tracks again enabled conference participants to follow a consistent theme across the multiple sessions of the conference and to better group thematically the individual papers and posters submitted by the conference participants.This supplement also is organized by these track themes.The call for abstracts, including individual paper presentations, individual posters and panel presentations, resulted in 601 submissions, spread across the nine thematic tracks.Over one hundred reviewers from multiple disciplines, sectors, settings and career stage devoted their time to ensuring a comprehensive and expert review, and reviews were conducted within each track and coordinated by the track leads.For the final program, 19 oral abstract sessions, 9 panels, and 334 posters were presented over the two-day meeting, in addition to a "poster slam".Slides for the oral presentations and panels (with the agreement of the authors) were posted on the conference website (https://academy- health.confex.com/academyhealth/2016di/meetingapp.cgi/Home/0) and all abstracts were included on the conference webapp (https:// academyhealth.confex.com/academyhealth/2016di/meetingapp.cgi).New this year was a presentation format that combined the
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,127 | 0,180 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,020 | 0,012 |
| Science ouverte | 0,005 | 0,011 |
| Intégrité de la recherche | 0,011 | 0,015 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,112 | 0,048 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».