Evidence map›Paper›PMID 28851353›Full record

ArticleBMC health services research2017

Exploring the concurrent validity of the nationwide assessment of permanent nursing home residence in Denmark - A cross-sectional data analysis using two administrative registries.

Anna Bebe, Anni Brit Sternhagen Nielsen, Tora Grauers Willadsen, Jens Søndergaard, Volkert Siersma, Dagný Rós Nicolaisdóttir, Jakob Kragstrup, Frans Boch Waldorff

Abstract readValidation Study
In one paragraph

Article in BMC health services research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

8 authors.

Anna BebeThe Research Unit and Section of General Practice, Institute of Public Health, University of Copenhagen, Øster Farimagsgade 5, Post box 2099, 1014, Copenhagen K, Denmark. anna.bebe@sund.ku.dk.ORCID http://orcid.org/0000-0002-0072-977X
Anni Brit Sternhagen NielsenThe Research Unit and Section of General Practice, Institute of Public Health, University of Copenhagen, Øster Farimagsgade 5, Post box 2099, 1014, Copenhagen K, Denmark.
Tora Grauers WilladsenThe Research Unit and Section of General Practice, Institute of Public Health, University of Copenhagen, Øster Farimagsgade 5, Post box 2099, 1014, Copenhagen K, Denmark.
Jens SøndergaardThe Research Unit and Section of General Practice, Institute of Public Health, University of Copenhagen, Øster Farimagsgade 5, Post box 2099, 1014, Copenhagen K, Denmark.
Volkert SiersmaThe Research Unit and Section of General Practice, Institute of Public Health, University of Copenhagen, Øster Farimagsgade 5, Post box 2099, 1014, Copenhagen K, Denmark.
Dagný Rós NicolaisdóttirThe Research Unit and Section of General Practice, Institute of Public Health, University of Copenhagen, Øster Farimagsgade 5, Post box 2099, 1014, Copenhagen K, Denmark.
Jakob KragstrupThe Research Unit and Section of General Practice, Institute of Public Health, University of Copenhagen, Øster Farimagsgade 5, Post box 2099, 1014, Copenhagen K, Denmark.
Frans Boch WaldorffThe Research Unit and Section of General Practice, Institute of Public Health, University of Copenhagen, Øster Farimagsgade 5, Post box 2099, 1014, Copenhagen K, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany register studies make use of information about permanent nursing home residents. Statistics Denmark (StatD) identifies nursing home residents by two different indirect methods, one based on reports from the municipalities regarding home care in taken place in a nursing home, and the other based on an algorithm created by StatD. The aim of the present study was to validate StatD's nursing home register using dedicated administrative municipality records on individual nursing home residents as gold standard.

methodsIn total, ten Danish municipalities were selected. Within each Danish Region, we randomly selected one municipality reporting to Stat D (Method 1) and one not reporting where instead an algorithm created by StatD was used to discover nursing home residents (Method 2). Method 1 means that municipalities reported to Stat D whether home care has taken place in a nursing home or in a private home. Method 2 is based on an algorithm created by Stat D for the municipalities where Method 1 is not applicable. Our gold standard was the information from the local administrative system in all ten selected municipalities. Each municipality provided a list with all individuals > 65 years living in a nursing home on January 1st, 2013 as well as the central personal number. This was compared to the list of individuals >65 living in nursing home facilities in the same ten municipalities on January 1st, 2013 retrieved from StatD.

resultsAccording to the data received directly from the municipalities, which was used as our gold Standard 3821 individuals were identified as nursing home residents. The StatD register identified 6,141 individuals as residents. Additionally, 556 of the individuals identified by the municipalities were not identified in the StatD register. Overall sensitivity for the ten municipalities in the StatD nursing home register was 0.85 (95% CI 0.84-0.87) and the PPV was 0.53 (95% CI 0.52-0.54). The municipalities for which nursing home status was based on the StatD algorithm (method 2) had a sensitivity of 0.84 (95% CI 0.82-0.86) and PPV of 0.48 (95% CI 0.46-0.50). Both slightly lower than the reporting municipalities (method 1) where the sensitivity was 0.87(95% CI 0.85-0.88) and the PPV was 0.57 (95% CI 0.56-0.59). Additionally, the sensitivity and PPV of the Stat D register varied heavily among the ten municipalities from 0.51 (95% CI 0.43-0.59) to 0.96 (95% CI 0.95-0.98) and PPV correspondingly, from 0.14 (95% CI: 0.11-0.17) to 0.73 (95% CI 0.69-0.77).

conclusionsThe overall PPV of StatD nursing home register was low and differences between municipalities existed. Even in countries with extensive nation-wide registers, validating studies should be conducted for outcomes based on these registers.

Indexed as

AlgorithmsRegistriesAgedAged, 80 and overCross-Sectional StudiesDenmarkFemaleHumansMaleNursing HomesAlgorithmDenmarkEpidemiologyNursing home admittanceNursing home entryNursing home placementNursing home referralNursing homesPopulation registerRegister dataValidationValidity

Identifiers

PMID28851353
PMCPMC5576368

What OpenQuestion holds

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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.