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

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A Commentary to this article was published on 19 January 2019

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.

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Author information

Authors and Affiliations

  1. Department of Biomedical and Dental Sciences and Morphofunctional Imaging, Policlinico Universitario, University of Messina, 1, Via Consolare Valeria, 98125, Messina, Italy

    Janet Sultana & Gianluca Trifiro’

  2. Department of Medical Informatics, Erasmus Medical Centre, s-Gravendijkwal 230, 3015 CE, Rotterdam, The Netherlands

    Janet Sultana, Ingrid Leal, Marcel de Wilde, Maria de Ridder, Johan van der Lei & Gianluca Trifiro’

  3. Julius Centre for Global Health, Utrecht University Medical Centre, Heidelberglaan 100, 3584 CX, Utrecht, The Netherlands

    Miriam Sturkenboom

Authors
  1. Janet Sultana
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  2. Ingrid Leal
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  3. Marcel de Wilde
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  4. Maria de Ridder
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  5. Johan van der Lei
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  7. Gianluca Trifiro’
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Corresponding author

Correspondence to Janet Sultana.

Ethics declarations

Review board approval

This study was approved by the IPCI Review Board (IPCI Raad van Toezicht).

Funding

This work was supported by the Italian Health Ministry (Grant number GR-2009-1607316: Assessment of the Safety of Antipsychotic Drugs in Elderly with Dementia: An International, Population-Based Study Using Healthcare Databases).

Conflicts of interest

Janet Sultana, Ingrid Leal, Marcel de Wilde, Maria de Ridder, Johan van der Lei, Miriam Sturkenboom and Gianluca Trifiro have no conflicts of interest that are directly relevant to the content of this study.

Author contributions

All authors contributed to this study. GT conceived the study; GT and JS designed the study; MS provided the data; IL, MdR and MdW carried out the data extraction and analysis; and JS, IL, MdR, MdW, JvdL, MS and GT contributed to the data interpretation and drafting of the paper.

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Sultana, J., Leal, I., de Wilde, M. et al. Identifying Data Elements to Measure Frailty in a Dutch Nationwide Electronic Medical Record Database for Use in Postmarketing Safety Evaluation: An Exploratory Study. Drug Saf 42, 713–719 (2019). https://doi.org/10.1007/s40264-018-00785-z

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