Question · asked by 1 review

Oral-health promotion programs (OHPPs): community-based oral-health education/training, supervised toothbrushing with fluoride toothpaste and topical fluoride, dental screening, and dietary advice vs No oral-health promotion program, or a differing (usual-care) action under similar conditions: Incremental cost‐effectiveness

OHPPs were associated with a lower program cost per DMFT/S in about 97 of 100 programs (OR 0.03, 95% CI 0.01 to 0.11; ungraded, very high heterogeneity I2=99%).

What each review found

Current versions only
FindingEffectStudiesGRADE certainty
Oral-health promotion programs (OHPPs): community-based oral-health education/training, supervised toothbrushing with fluoride toothpaste and topical fluoride, dental screening, and dietary advice vs No oral-health promotion program, or a differing (usual-care) action under similar conditions
Incremental cost-effectiveness per DMFT/S · Children aged 0-12 years (healthy except for dental caries) · Community settings: home visits, telephone contacts, healthcare centers, and primary schools
OHPPs were associated with a lower program cost per DMFT/S in about 97 of 100 programs (OR 0.03, 95% CI 0.01 to 0.11; ungraded, very high heterogeneity I2=99%).
Clinical Effectiveness and Cost-Effectiveness of Oral-Health Promotion in Dental Caries Prevention among… (2019) All outcomes
OR 0.03 [0.01, 0.11]8 studiesGRADE not reported

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Clinical Effectiveness and Cost-Effectiveness of Oral-Health Promotion in Dental Caries Prevention among Children: Systematic Review and…
2019 All outcomes
11 December 2018 (search initiated)29Critically Low / Critically Low

Studies behind the findings

None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.

How reviews are matched to this question

Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.