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.

Highlights

  • Many register studies make use of information about permanent nursing home residents

  • Since all people in Denmark have a Central Personal Register (CPR) identification number and all people are registered in their municipality to be able to receive health care, pay taxes, get pension and so on, the administrative records of the municipalities can identify all individuals living in nursing homes

  • Based on the data retrieved directly from the 10 municipalities a total of 3,821 individuals were identified as permanent nursing home residents while The Statistics Denmark (StatD) register identified 6,141 as residents

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Summary

Introduction

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. Permanent nursing home placement may be a determining factor or an outcome in epidemiological studies [4,5,6,7]. Residency at a permanent nursing home may be an important confounder to consider, and nursing home admission is already being used as a confounding variable in many research studies in the field of public health and medicine [5, 8]. Reviews have addressed nursing home residence as a relevant outcome/proxy [8, 10, 11]

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