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Drug Saf. 2019 Jan 8. doi: 10.1007/s40264-018-00785-z. [Epub ahead of print]

Identifying Data Elements to Measure Frailty in a Dutch Nationwide Electronic Medical Record Database for Use in Postmarketing Safety Evaluation: An Exploratory Study.

Author information

1
Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Policlinico Universitario, University of Messina, 1, Via Consolare Valeria, 98125, Messina, Italy. jaysultana@gmail.com.
2
Department of Medical Informatics, Erasmus Medical Centre, s-Gravendijkwal 230, 3015 CE, Rotterdam, The Netherlands. jaysultana@gmail.com.
3
Department of Medical Informatics, Erasmus Medical Centre, s-Gravendijkwal 230, 3015 CE, Rotterdam, The Netherlands.
4
Julius Centre for Global Health, Utrecht University Medical Centre, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands.
5
Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Policlinico Universitario, University of Messina, 1, Via Consolare Valeria, 98125, Messina, Italy.

Abstract

INTRODUCTION:

The role of frailty in postmarketing drug safety is increasingly acknowledged. Few European electronic medical records (EMRs) have been used to explore frailty in observational drug safety research.

OBJECTIVE:

The aim of this study was to identify data elements, beyond multimorbidity and polypharmacy, that could potentially contribute to measuring frailty among older adults in the Dutch nationwide Integrated Primary Care Information (IPCI) database.

METHODS:

Persons aged between 65 and 90 years in the IPCI database were identified from 2008 to 2013. Clinical non-disease, non-drug measurements that could potentially contribute to measuring frailty were identified and selected if they were recorded in > 0.005% of patients and could be included in at least one of three definitions of frailty: the frailty phenotype model, the cumulative deficit model, and direct evaluations of frailty through standardized frailty scores. The frequency of these measures was calculated.

RESULTS:

Overall, 314,191 (17% of the source population) elderly persons were identified. Of these, 7948 (2.53%) had one or more of 12 clinical measurements identified that could potentially contribute to measuring frailty, such as clinical evaluations of cognition, mobility, and cachexia, as well as direct measures of frailty, such as the Groningen Frailty Index. Three of five measurements required for the frailty phenotype were identified in < 0.5% of the population: cachexia, reduced walking speed, and reduced physical activity; weakness and fatigue were not identified. The measurements outlined above may be appropriate for the cumulative deficit definition of frailty, provided that at least 30 deficits, including comorbidities and drug utilization, are evaluated in total. The most commonly recorded item identified that could potentially be used in a cumulative frailty model was the Mini-Mental State Examination score (N= 2850; 0.91%); the only recorded direct measurement of frailty was the Groningen Frailty Index (N = 2382; 0.76%).

CONCLUSION:

Non-disease, non-drug clinical data that could potentially contribute to a frailty model was not commonly recorded in the IPCI; less than 3% of a cohort of elderly persons had these data recorded, suggesting that the use of these data in postmarketing drug safety evaluation may be limited.

PMID:
30617499
DOI:
10.1007/s40264-018-00785-z

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