The influence of primary care quality on nursing home admissions in a multimorbid population with and without dementia in Germany: a retrospective cohort study using health insurance claims data

Identifying Predictors of Nursing Home Admission by Using Electronic Health Records and Administrative Data: Scoping Review

Background

Among older adults, nursing home admissions (NHAs) are considered a significant adverse outcome and have been extensively studied. Although the volume and significance of electronic data sources are expanding, it is unclear what predictors of NHA have been systematically identified in the literature via electronic health records (EHRs) and administrative data.

Objective

This study synthesizes findings of recent literature on identifying predictors of NHA that are collected from administrative data or EHRs.

Methods

The PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines were used for study selection. The PubMed and CINAHL databases were used to retrieve the studies. Articles published between January 1, 2012, and March 31, 2023, were included.

Results

A total of 34 papers were selected for final inclusion in this review. In addition to NHA, all-cause mortality, hospitalization, and rehospitalization were frequently used as outcome measures. The most frequently used models for predicting NHAs were Cox proportional hazards models (studies: n=12, 35%), logistic regression models (studies: n=9, 26%), and a combination of both (studies: n=6, 18%). Several predictors were used in the NHA prediction models, which were further categorized into sociodemographic, caregiver support, health status, health use, and social service use factors. Only 5 (15%) studies used a validated frailty measure in their NHA prediction models.

Conclusions

NHA prediction tools based on EHRs or administrative data may assist clinicians, patients, and policy makers in making informed decisions and allocating public health resources. More research is needed to assess the value of various predictors and data sources in predicting NHAs and validating NHA prediction models externally.

The impact of study factors in the association of periodontal disease and cognitive disorders: systematic review and meta-analysis

AIM

The aim was to assess study factors that impact the association of cognitive disorders in people with periodontal disease (PD).

METHOD

Medline, EMBASE and Cochrane databases were searched until February 2022 using keywords and MeSH: (periodon* OR tooth loss OR missing teeth) AND (dementia OR Alzheimer's Disease OR cognitive*). Observational studies reporting prevalence or risk of cognitive decline, dementia or Alzheimer's disease (AD) in people with PD compared with healthy controls were included. Meta-analysis quantified the prevalence and risk (relative risk[RR]) of cognitive decline, dementia/AD, respectively. Meta-regression/subgroup analysis explored the impact of study factors including PD severity and classification type, and gender.

RESULTS

Overall, 39 studies were eligible for meta-analysis: 13 cross-sectional and 26 longitudinal studies. PD demonstrated increased risks of cognitive disorders (cognitive decline-RR = 1.33, 95% CI = 1.13-1.55; dementia/AD-RR = 1.22, 95% CI = 1.14-1.31). Risk of cognitive decline increased with PD severity (moderate-[RR] = 1.14, 95% confidence interval [CI] = 1.07-1.22; severe-RR = 1.25, 95% CI = 1.18-1.32). For every 10% population increase in females, the risk of cognitive decline increased by 34% (RR = 1.34, 95% CI = 1.16-1.55). Self-reported PD showed a lower risk of cognitive disorders compared with clinical classification (cognitive decline-RR = 0.77, 95% CI = 0.65-0.91; dementia/AD-RR = 0.86, 95% CI = 0.77-0.96).

CONCLUSION

The prevalence and risk estimates of cognitive disorders in association with PD can be influenced by gender, the disease classification of PD and its severity. Further homologous evidence taking these study factors into consideration is needed to form robust conclusions.

Data linkage of German statutory health insurance claims data and care needs assessments preceding a population-based cohort study on nursing home admission

OBJECTIVES

We perform and evaluate record linkage of German Care Needs Assessment (CNA) data to Statutory Health Insurance (SHI) claims data. The resulting dataset should enable the identification of factors in healthcare predicting the time between the onset of long-term care dependency and the admission to a nursing home in Germany in subsequent analyses.

DESIGN

A deterministic record linkage was conducted using the key variables region, sex, date of birth and care level. In further steps, the underlying cause of care dependency (International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10)) was added for a higher level of distinction. Before linkage, the suitability of the two datasets for these procedures was assessed. After linkage, the results of each stage were analysed and the resulting dataset was evaluated cross-sectionally with respect to bias generated through this process.

SETTING

The study comprises data from the German SHI and Statutory Long-Term Care Insurance.

PARTICIPANTS

The study cohort comprised 158 069 individuals who became care dependent in 2006. We obtained CNA data for the year 2006 including 188 935 individuals.

RESULTS

We could link CNAs to 66 310 individuals of the original study cohort, corresponding to 42.0%. Records from two federal states could not be matched due to missing data. Linkage rates were lower where more people shared the same attributes. The resulting dataset showed minor differences regarding age, sex and care level compared to the original cohort.

CONCLUSIONS

Data linkage between German SHI claims data and CNA data is feasible. Failure to link was mostly attributable to a lack of distinction between individuals using available identifiers. The resulting dataset contains relevant information from both health services provision and functional status of care dependent people and is suitable for further analyses with critical reflection of representativity.