Evidence map›Paper›PMID 35255898›Full record

SynthesisBMC health services research2022

Economic models of community-based falls prevention: a systematic review with subsequent commissioning and methodological recommendations.

Joseph Kwon, Hazel Squires, Matthew Franklin, Yujin Lee, Tracey Young

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in BMC health services research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.9field-weighted citation impact, top 10% of its field
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

9 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Review
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  7. Observational
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  9. Review
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

5 authors at 2 institutions in 1 country.

Joseph KwonSchool of Health and Related Research, University of Sheffield, Regent Court (ScHARR), 30 Regent Street, Sheffield, S1 4DA, England. jkwon6@sheffield.ac.uk.ORCID https://orcid.org/0000-0002-2860-7280
Hazel SquiresSchool of Health and Related Research, University of Sheffield, Regent Court (ScHARR), 30 Regent Street, Sheffield, S1 4DA, England.ORCID https://orcid.org/0000-0001-8467-0471
Matthew FranklinSchool of Health and Related Research, University of Sheffield, Regent Court (ScHARR), 30 Regent Street, Sheffield, S1 4DA, England.ORCID https://orcid.org/0000-0002-2776-4014
Yujin LeeWarwick Medical School, University of Warwick, Gibbet Hill Road, Coventry, CV4 7AL, England.ORCID https://orcid.org/0000-0003-0450-9667
Tracey YoungSchool of Health and Related Research, University of Sheffield, Regent Court (ScHARR), 30 Regent Street, Sheffield, S1 4DA, England.ORCID https://orcid.org/0000-0002-0754-7223
University of Sheffield · GBUniversity of Warwick · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundFalls impose significant health and economic burdens among older populations, making their prevention a priority. Health economic models can inform whether the falls prevention intervention represents a cost-effective use of resources and/or meet additional objectives such as reducing social inequities of health. This study aims to conduct a systematic review (SR) of community-based falls prevention economic models to: (i) systematically identify such models; (ii) synthesise and critically appraise modelling methods/results; and (iii) formulate methodological and commissioning recommendations.

methodsThe SR followed PRISMA 2021 guideline, covering the period 2003-2020, 12 academic databases and grey literature. A study was included if it: targeted community-dwelling persons aged 60 and over and/or aged 50-59 at high falls risk; evaluated intervention(s) designed to reduce falls or fall-related injuries; against any comparator(s); reported outcomes of economic evaluation; used decision modelling; and had English full text. Extracted data fields were grouped by: (A) model and evaluation overview; (B) falls epidemiology features; (C) falls prevention intervention features; and (D) evaluation methods and outcomes. A checklist for falls prevention economic evaluations was used to assess reporting/methodological quality. Extracted fields were narratively synthesised and critically appraised to inform methodological and commissioning recommendations. The SR protocol is registered in the Prospective Register of Systematic Reviews (CRD42021232147).

resultsForty-six models were identified. The most prevalent issue according to the checklist was non-incorporation of all-cause care costs. Based on general population, lifetime models conducting cost-utility analyses, seven interventions produced favourable ICERs relative to no intervention under the cost-effectiveness threshold of US$41,900 (£30,000) per QALY gained; of these, results for (1) combined multifactorial and environmental intervention, (2) physical activity promotion for women, and (3) targeted vitamin D supplementation were from validated models. Decision-makers should explore the transferability and reaches of interventions in their local settings. There was some evidence that exercise and home modification exacerbate existing social inequities of health. Sixteen methodological recommendations were formulated.

conclusionThere is significant methodological heterogeneity across falls prevention models. This SR's appraisals of modelling methods should facilitate the conceptualisation of future falls prevention models. Its synthesis of evaluation outcomes, though limited to published evidence, could inform commissioning.

Indexed as

Accidental FallsModels, EconomicAgedCost-Benefit AnalysisExerciseFemaleHumansIndependent LivingMiddle Aged

Identifiers

PMID35255898
PMCPMC8902781
OpenAlexW4220790082

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.