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Health promotion and disease prevention as a complement to community health indicators - Working group 1

2002· article· en· W7010278988 sur OpenAlexaboutno aff

Notice bibliographique

RevueLund University Publications (Lund University) · 2002
Typearticle
Langueen
DomaineHealth Professions
ThématiqueHealth, psychology, and well-being
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésHealth promotionHealth policyCommunity healthPopulation healthPublic healthHRHISInternational healthEuropean unionHealth education
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The aim of Working Group 1 has been to assess health promotion and disease prevention activities in terms of benefits, risks, and economic, social, and ethical implications as a complement to community health indicators. Objectives: The objectives delineated for Working Group 1 were: 1) to analyze current initiatives to assess health promotion and disease prevention activities in European countries; 2) to provide an overview of beneficial health promotion and disease prevention activities; and 3) to examine the extent to which HTA has been implemented in health policy and health practice in relation to health promotion. Discussion: This part of the report deals with preventive technology, health technology assessment (HTA), and health policy in the European Union (EU), plus Norway and Switzerland. The ECHTA/ECAHI project is funded by the European Commission's Community Health Monitoring Programme (HMP). One of the pillars of the HMP is to establish community health indicators. Community health indicators are intended to allow monitoring of the health status of the population of the EU, to facilitate evaluation of health system performance, and to enable international comparisons. In fact, standard community health indicators do not tell a great deal about health system performance. The health system generally does not have a great influence on the most common comparable indicators of health, such as overall mortality and life expectancy, which are quite similar in all EU member states. One of the basic goals of Working Group 1 was to test and perhaps demonstrate an alternative or complementary method: examining the use of proven preventive technologies in the EU as a measure of health policy and health system performance. Public health, prevention, and health promotion activities, including screening, are priorities for the EU's health activities. Obviously, preventing disease is of importance to the general public, to the health systems of Europe, and to health policy makers. When disease can be prevented and health promoted or enhanced, the entire society of Europe profits. Furthermore, public health and prevention are major tasks for the public sector in all EU member states. HTA has developed during the last 25 years as an aid to decision makers in determining health policy and practice. In its early years, HTA dealt mainly with large, visible, expensive technology. More recently, HTA has turned toward evaluating a wider range of health technologies, including those in prevention. This report offers some insight into how far this process of evaluation has gone and how useful the evaluations of prevention are or could be. It is often said that there are relatively few proven interventions in the prevention field. The report of Working Group 1 has demonstrated that this impression is not correct. It is not difficult to compile a list of 70 or more interventions that have been found effective by systematic review of the scientific literature. Such a list is presented in this report, without a detailed evaluation of each intervention, taken from systematic reviews carried out in the United States, Canada, the United Kingdom, the Netherlands, and other countries. Few interventions in the area of health promotion have been tested-and of these, only a few were found to be efficacious. On the other hand, evaluation of cost-effectiveness is difficult, because the needed studies have not been done in most cases. As for broader assessments of ethical and social implications of preventive technologies, these are almost entirely lacking. Much of this evidence, whether dealing with effectiveness, cost-effectiveness, or other issues, may not be entirely reliable because of the poor quality of many of the original studies and the gaps in available information. The HTA agencies, members of INAHTA, have developed a large database of their own studies, including those in the area of prevention. The working group examined the HTA Database (formerly the INAHTA Database) to determine how useful it might be in evaluating prevention. The database has many assessments in the area of prevention, whereof most are systematic reviews. Therefore, as a source of information immediately available, the HTA Database is certainly useful. On the other hand, it could be improved in several ways, some of which will be discussed in the body of this report. However, almost all of the interventions assessed by HTA agencies concern technologies provided by the healthcare system, not considering interventions or strategies under the jurisdiction of government agencies or other sectors not associated with the ministries of health. Working Group 1 also wished to gain an idea of how much HTA is used in the member states of the EU in the field of prevention and if these assessments had affected policy and practice. There are several indications, including the results of the survey carried out by the working group, that the potentials of prevention are not realized in European countries because of lack of effective policies. The survey was organized to further explore this problem. From the large number of apparently effective preventive interventions, the working group decided to focus on eight technologies. Those technologies were selected from the longer list because they cover a wide range of topics and considerations. They were not selected randomly and are not necessarily representative. In the sense that other good examples could have been used, this effort must be considered a pilot project. The eight selected areas are: 1. Genetic aberrations and congenital malformations; 2. Detection and treatment of hypertension; 3. Cigarette smoking/lung cancer; 4. Counseling and sexual behavior; 5. Cervical cancer screening; 6. Colorectal cancer screening; 7. Detection of excessive drinkers; and 8. Traffic injuries. An exhaustive literature review was carried out in these eight areas, focusing on systematic reviews. As can be seen, some of the areas are broad and could be addressed by several different technologies, while a few (e.g., cervical cancer screening) are rather discrete. In summary, there is little doubt that each of these areas has one or more effective technologies that could be implemented with benefits to the population of most European countries. The literature review showed some serious shortcomings. While information on efficacy is often available, this literature is not always of the best quality. Relatively little information on other assessment dimensions is found. Specifically, and in terms of this project, cost and cost-effectiveness information is scant. When it is available, it is often of poor quality. Systematic reviews in the area of prevention seldom give information on cost or cost-effectiveness. When they do, they generally point to the poor quality of the information and the analysis. Ethics is another important area not often the subject of detailed assessment. Ethics are seldom mentioned in the literature concerning prevention (with a few exceptions such as prenatal screening and screening for familial breast cancer). And systematic reviews, despite acknowledging the importance of ethical issues in assessment, seldom mention this area.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,100
score de la tête « metaresearch » (Gemma)0,062
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,100
Score d'incertitude au seuil0,529

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,1000,062
Méta-épidémiologie (sens strict)0,0030,001
Méta-épidémiologie (sens large)0,0020,002
Bibliométrie0,0080,004
Études des sciences et des technologies0,0020,002
Communication savante0,0060,006
Science ouverte0,0050,012
Intégrité de la recherche0,0050,004
Charge utile insuffisante (le modèle a refusé de juger)0,0100,006

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.

Tête enseignante Opus0,109
Tête enseignante GPT0,386
Écart entre enseignants0,277 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2002
Routes d'admission1
Résumé présentoui

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