Evidence map›Paper›PMID 26054326›Full record

ArticlePharmacoEconomics2015

Preventing Obesity in the USA: Impact on Health Service Utilization and Costs.

Michele Cecchini, Franco Sassi

Abstract read
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Article in PharmacoEconomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Michele CecchiniInstitute of Global Health Innovation, Imperial College London, London, UK, michele.cecchini@oecd.org.
Franco Sassi

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWith more than two-thirds of the US population overweight or obese, the obesity epidemic is a major threat for population health and the financial sustainability of the healthcare service. Whether, and to what extent, effective prevention interventions may offer the opportunity to 'bend the curve' of rising healthcare costs is still an object of debate.

objectiveThis study evaluates the potential economic impact of a set of prevention programmes, including education, counselling, long-term drug treatment, regulation (e.g. of advertising or labelling) and fiscal measures, on national healthcare expenditure and use of healthcare services in the USA. STUDY DESIGN AND

methodThe study was carried out as a retrospective evaluation of alternative scenarios compared with a 'business as usual' scenario. An advanced econometric approach involving the use of logistic regression and generalized linear models was used to calculate the number of contacts with key healthcare services (inpatient, outpatient, drug prescriptions) and the associated cost. Analyses were carried out on the Medical Expenditure Panel Survey (1997-2010).

resultsIn 2010, prevention interventions had the potential to decrease total healthcare expenditure by up to $US2 billion. This estimate does not include the implementation costs. The largest share of savings is produced by reduced use and costs of inpatient care, followed by reduced use of drugs. Reduction in expenditure for outpatient care would be more limited. Private insurance schemes benefit from the largest savings in absolute terms; however, public insurance schemes benefit from the largest cost reduction per patient. People in the lowest income groups show the largest economic benefits.

conclusionPrevention interventions aimed at tackling obesity and associated risk factors may produce a significant decrease in the use of healthcare services and expenditure. Savings become substantial when a long-term perspective is taken.

Indexed as

Health Care CostsHealth ExpendituresHumansObesityPreventive Health ServicesRetrospective StudiesUnited States

Identifiers

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.