Evidence map›Paper›PMID 34583685›Full record

ArticleBMC health services research2021

Qualitative research to inform economic modelling: a case study in older people's views on implementing the NICE falls prevention guideline.

Joseph Kwon, Yujin Lee, Tracey Young, Hazel Squires, Janet Harris

Abstract read
In one paragraph

Article in BMC health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  8. 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.

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

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHigh prevalence of falls among older persons makes falls prevention a public health priority. Yet community-based falls prevention face complexity in implementation and any commissioning strategy should be subject to economic evaluation to ensure cost-effective use of healthcare resources. The study aims to capture the views of older people on implementing the National Institute for Health and Care Excellence (NICE) guideline on community-based falls prevention and explore how the qualitative data can be used to inform commissioning strategies and conceptual modelling of falls prevention economic evaluation in the local area of Sheffield.

methodsFocus group and interview participants (n = 27) were recruited from Sheffield, England, and comprised falls prevention service users and eligible non-users of varying falls risks. Topics concerned key components of the NICE-recommended falls prevention pathway, including falls risk screening, multifactorial risk assessment and treatment uptake and adherence. Views on other topics concerning falls prevention were also invited. Framework analysis was applied for data analysis, involving data familiarisation, identifying themes, indexing, charting and mapping and interpretation. The qualitative data were mapped to three frameworks: (1) facilitators and barriers to implementing the NICE-recommended pathway and contextual factors; (2) intervention-related causal mechanisms for formulating commissioning strategies spanning context, priority setting, need, supply and demand; and (3) methodological and evaluative challenges for public health economic modelling.

resultsTwo cross-component factors were identified: health motives of older persons; and professional competence. Participants highlighted the need for intersectoral approaches and prioritising the vulnerable groups. The local commissioning strategy should consider the socioeconomic, linguistic, geographical, legal and cultural contexts, priority setting challenges, supply-side mechanisms spanning provider, organisation, funding and policy (including intersectoral) and health and non-health demand motives. Methodological and evaluative challenges identified included: incorporating non-health outcomes and societal intervention costs; considering dynamic complexity; considering social determinants of health; and conducting equity analyses.

conclusionsHolistic qualitative research can inform how commissioned falls prevention pathways can be feasible and effective. Qualitative data can inform commissioning strategies and conceptual modelling for economic evaluations of falls prevention and other geriatric interventions. This would improve the structural validity of quantitative models used to inform geriatric public health policies.

Indexed as

Accidental FallsMotivationAgedAged, 80 and overFocus GroupsHumansQualitative ResearchRisk AssessmentEconomic modelFacilitators and barriersFallsFalls preventionFalls riskImplementationNational Institute for health and care excellence guidelinePublic healthQualitative research

Identifiers

PMID34583685
PMCPMC8479997

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LicenceCC BY
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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.