Evidence map›Paper›PMID 33890864›Full record

ReviewJMIR aging2021

The Value of Routinely Collected Data in Evaluating Home Assessment and Modification Interventions to Prevent Falls in Older People: Systematic Literature Review.

Helen Daniels, Joe Hollinghurst, Richard Fry, Andrew Clegg, Sarah Hillcoat-Nallétamby, Silviya Nikolova, Sarah E Rodgers, Neil Williams, Ashley Akbari

Open access · goldAbstract readReview
In one paragraph

Review in JMIR aging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact, top 95% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Observational
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

9 authors at 4 institutions in 1 country.

Helen DanielsPopulation Data Science, Swansea University, Swansea, United Kingdom.ORCID https://orcid.org/0000-0001-8899-0333
Joe HollinghurstPopulation Data Science, Swansea University, Swansea, United Kingdom.ORCID https://orcid.org/0000-0002-3556-2017
Richard FryPopulation Data Science, Swansea University, Swansea, United Kingdom.ORCID https://orcid.org/0000-0002-7968-6679
Andrew CleggAcademic Unit of Elderly Care and Rehabilitation, University of Leeds, Leeds, United Kingdom.ORCID https://orcid.org/0000-0001-5972-1097
Sarah Hillcoat-NallétambyCentre for Ageing and Dementia Research, Swansea University, Swansea, United Kingdom.ORCID https://orcid.org/0000-0003-2554-076X
Silviya NikolovaLeeds Institute of Health Sciences, Swansea University, Leeds, United Kingdom.ORCID https://orcid.org/0000-0002-6922-5115
Sarah E RodgersPublic Health, Policy & Systems, University of Liverpool, Liverpool, United Kingdom.ORCID https://orcid.org/0000-0002-4483-0845
Neil WilliamsCare and Repair Cymru, Cardiff, United Kingdom.ORCID https://orcid.org/0000-0001-5960-8262
Ashley AkbariPopulation Data Science, Swansea University, Swansea, United Kingdom.ORCID https://orcid.org/0000-0003-0814-0801
Swansea University · GBUniversity of Leeds · GBNational Health Service Wales · GBUniversity of Liverpool · GB

Funding

HCRW_ SCF-18-1504Wellcome Trust
6 · The paper itself

Abstract

backgroundFalls in older people commonly occur at home. Home assessment and modification (HAM) interventions can be effective in reducing falls; however, there are some concerns over the validity of evaluation findings. Routinely collected data could improve the quality of HAM evaluations and strengthen their evidence base.

objectiveThe aim of this study is to conduct a systematic review of the evidence of the use of routinely collected data in the evaluations of HAM interventions.

methodsWe searched the following databases from inception until January 31, 2020: PubMed, Ovid, CINAHL, OpenGrey, CENTRAL, LILACS, and Web of Knowledge. Eligible studies were those evaluating HAMs designed to reduce falls involving participants aged 60 years or more. We included study protocols and full reports. Bias was assessed using the Risk Of Bias In Non-Randomized Studies of Interventions (ROBINS-I) tool.

resultsA total of 7 eligible studies were identified in 8 papers. Government organizations provided the majority of data across studies, with health care providers and third-sector organizations also providing data. Studies used a range of demographic, clinical and health, and administrative data. The purpose of using routinely collected data spanned recruiting and creating a sample, stratification, generating independent variables or covariates, and measuring key study-related outcomes. Nonhome-based modification interventions (eg, in nursing homes) using routinely collected data were not included in this study. We included two protocols, which meant that the results of those studies were not available. MeSH headings were excluded from the PubMed search because of a reduction in specificity. This means that some studies that met the inclusion criteria may not have been identified.

conclusionsRoutine data can be used successfully in many aspects of HAM evaluations and can reduce biases and improve other important design considerations. However, the use of these data in these studies is currently not widespread. There are a number of governance barriers to be overcome to allow these types of linkage and to ensure that the use of routinely collected data in evaluations of HAM interventions is exploited to its full potential.

Indexed as

agedevaluation researchfallsroutinely collected datasystematic review

Identifiers

PMID33890864
PMCPMC8105762
OpenAlexW3134030402

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.