Evidence map›Paper›PMID 36434583›Full record

ArticleBMC health services research2022

Supporting the implementation of new healthcare technologies by investigating generalisability of pilot studies using area-level statistics.

James Alexander Doorbar, Christopher S Mathews, Karin Denton, Matejka Rebolj, Adam R Brentnall

Abstract read
In one paragraph

Article 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 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

5 authors.

James Alexander DoorbarCancer Prevention Group, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK.
Christopher S MathewsCancer Prevention Group, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK.
Karin DentonSevern Pathology, Southmead Hospital, North Bristol NHS Trust, Bristol, UK.
Matejka Rebolj *Cancer Prevention Group, School of Cancer & Pharmaceutical Sciences, Faculty of Life Sciences & Medicine, King's College London, London, UK. matejka.rebolj@kcl.ac.uk.ORCID http://orcid.org/0000-0001-9597-645X
Adam R Brentnall *Wolfson Institute of Population Health, Queen Mary University of London, London, UK.

Funding

Cancer Research UK 27047Cancer Research UK C8162/A27047
6 · The paper itself

Abstract

backgroundImplementation of new technologies into national health care systems requires careful capacity planning. This is sometimes informed by data from pilot studies that implement the technology on a small scale in selected areas. A critical consideration when using implementation pilot studies for capacity planning in the wider system is generalisability. We studied the feasibility of using publicly available national statistics to determine the degree to which results from a pilot might generalise for non-pilot areas, using the English human papillomavirus (HPV) cervical screening pilot as an exemplar.

methodsFrom a publicly available source on population indicators in England ("Public Health Profiles"), we selected seven area-level indicators associated with cervical cancer incidence, to produce a framework for post-hoc pilot generalisability analysis. We supplemented these data by those from publicly available English Office for National Statistics modules. We compared pilot to non-pilot areas, and pilot regimens (pilot areas using the previous standard of care (cytology) vs. the new screening test (HPV)). For typical process indicators that inform real-world capacity planning in cancer screening, we used standardisation to re-weight the values directly observed in the pilot, to better reflect the wider population. A non-parametric quantile bootstrap was used to calculate 95% confidence intervals (CI) for differences in area-weighted means for indicators.

resultsThe range of area-level statistics in pilot areas covered most of the spectrum observed in the wider population. Pilot areas were on average more deprived than non-pilot areas (average index of multiple deprivation 24.8 vs. 21.3; difference: 3.4, 95% CI: 0.2-6.6). Participants in HPV pilot areas were less deprived than those in cytology pilot areas, matching area-level statistics. Differences in average values of the other six indicators were less pronounced. The observed screening process indicators showed minimal change after standardisation for deprivation.

conclusionsNational statistical sources can be helpful in establishing the degree to which the types of areas outside pilot studies are represented, and the extent to which they match selected characteristics of the rest of the health care system ex-post. Our analysis lends support to extrapolation of process indicators from the HPV screening pilot across England.

Indexed as

Papillomavirus InfectionsUterine Cervical NeoplasmsDelivery of Health CareEarly Detection of CancerFemaleHumansPilot ProjectsGeneralisabilityHuman papillomavirus testingPilot studiesPopulation statisticsProcess indicatorsScreeningTechnology implementation

Identifiers

PMID36434583
PMCPMC9694587

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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.