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

Overview of attention for article published in BMC Health Services Research, August 2017
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Title
Exploring the concurrent validity of the nationwide assessment of permanent nursing home residence in Denmark - A cross-sectional data analysis using two administrative registries
Published in
BMC Health Services Research, August 2017
DOI 10.1186/s12913-017-2535-2
Pubmed ID
Authors

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

Abstract

Many 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. In 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. According 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). The 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.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 18 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 22%
Professor 2 11%
Lecturer 2 11%
Researcher 2 11%
Student > Master 2 11%
Other 4 22%
Unknown 2 11%
Readers by discipline Count As %
Medicine and Dentistry 10 56%
Nursing and Health Professions 4 22%
Neuroscience 1 6%
Unknown 3 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 October 2017.
All research outputs
#18,820,431
of 23,323,574 outputs
Outputs from BMC Health Services Research
#6,644
of 7,806 outputs
Outputs of similar age
#243,224
of 316,706 outputs
Outputs of similar age from BMC Health Services Research
#123
of 142 outputs
Altmetric has tracked 23,323,574 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,806 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one is in the 6th percentile – i.e., 6% of its peers scored the same or lower than it.
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We're also able to compare this research output to 142 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.