Swiss Frailty Network and Repository: protocol of a Swiss Personalized Health Network's driver project observational study

Michael Gagesch, Karin Edler, Patricia O Chocano-Bedoya, Lauren A Abderhalden, Laurence Seematter-Bagnoud, Tobias Meyer, Dominic Bertschi, Dina Zekry, Christophe J Büla, Gabriel Gold, Reto W Kressig, Andreas E Stuck, Heike A Bischoff-Ferrari, Michael Gagesch, Karin Edler, Patricia O Chocano-Bedoya, Lauren A Abderhalden, Laurence Seematter-Bagnoud, Tobias Meyer, Dominic Bertschi, Dina Zekry, Christophe J Büla, Gabriel Gold, Reto W Kressig, Andreas E Stuck, Heike A Bischoff-Ferrari

Abstract

Introduction: Early identification of frailty by clinical instruments or accumulation of deficit indexes can contribute to improve healthcare for older adults, including the prevention of negative outcomes in acute care. However, conflicting evidence exists on how to best capture frailty in this setting. Simultaneously, the increasing utilisation of electronic health records (EHRs) opens up new possibilities for research and patient care, including frailty.

Methods and analysis: The Swiss Frailty Network and Repository (SFNR) primarily aims to develop an electronic Frailty Index (eFI) from routinely available EHR data in order to investigate its predictive value against length of stay and in-hospital mortality as two important clinical outcomes in a study sample of 1000-1500 hospital patients aged 65 years and older. In addition, we will examine the correlation between the eFI and a test-based clinical Frailty Instrument to compare both concepts in Swiss older adults in acute care settings. As a Swiss Personalized Health Network (SPHN) driver project, our study will report on the characteristics and usability of the first nationwide eFI in Switzerland connecting all five Swiss University Hospitals' Geriatric Departments with a representative sample of patients aged 65 years and older admitted to acute care.

Ethics and dissemination: The study protocol was approved by the competent ethics committee of the Canton of Zurich (BASEC-ID 2019-00445). All acquired data will be handled according to SPHN's ethical framework for responsible data processing in personalised health research. Analyses will be performed within the secure BioMedIT environment, a national infrastructure to enable secure biomedical data processing, an integral part of SPHN.

Trial registration number: NCT04516642.

Keywords: epidemiology; geriatric medicine; health informatics.

Conflict of interest statement

Competing interests: None declared.

© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

References

    1. Newman AB. Comorbidity and multimorbidity. In: Newman A, Cauley J, eds. The epidemiology of aging. Dordrecht: Springer, 2012.
    1. Clegg A, Young J, Iliffe S, et al. . Frailty in elderly people. Lancet 2013;381:752–62. 10.1016/S0140-6736(12)62167-9
    1. Vermeiren S, Vella-Azzopardi R, Beckwée D, et al. . Frailty and the prediction of negative health outcomes: a meta-analysis. J Am Med Dir Assoc 2016;17:1163.e1–17. 10.1016/j.jamda.2016.09.010
    1. Lin H-S, Watts JN, Peel NM, et al. . Frailty and post-operative outcomes in older surgical patients: a systematic review. BMC Geriatr 2016;16:157. 10.1186/s12877-016-0329-8
    1. Turner G, Clegg A, British Geriatrics Society, et al. . Best practice guidelines for the management of frailty: a British geriatrics Society, age UK and Royal College of general practitioners report. Age Ageing 2014;43:744–7. 10.1093/ageing/afu138
    1. Theou O, Squires E, Mallery K, et al. . What do we know about frailty in the acute care setting? A scoping review. BMC Geriatr 2018;18:139. 10.1186/s12877-018-0823-2
    1. Morley JE, Vellas B, van Kan GA, et al. . Frailty consensus: a call to action. J Am Med Dir Assoc 2013;14:392–7. 10.1016/j.jamda.2013.03.022
    1. Rodríguez-Mañas L, Féart C, Mann G, et al. . Searching for an operational definition of frailty: a Delphi method based consensus statement: the frailty operative definition-consensus conference project. J Gerontol A Biol Sci Med Sci 2013;68:62–7. 10.1093/gerona/gls119
    1. Dent E, Kowal P, Hoogendijk EO. Frailty measurement in research and clinical practice: a review. Eur J Intern Med 2016;31:3–10. 10.1016/j.ejim.2016.03.007
    1. Dent E, Martin FC, Bergman H, et al. . Management of frailty: opportunities, challenges, and future directions. Lancet 2019;394:1376–86. 10.1016/S0140-6736(19)31785-4
    1. Walston J, Bandeen-Roche K, Buta B, et al. . Moving frailty toward clinical practice: NIa intramural frailty science symposium summary. J Am Geriatr Soc 2019;67:1559–64. 10.1111/jgs.15928
    1. Fried LP, Tangen CM, Walston J, et al. . Frailty in older adults: evidence for a phenotype. J Gerontol A Biol Sci Med Sci 2001;56:M146–57. 10.1093/gerona/56.3.M146
    1. Mitnitski AB, Mogilner AJ, Rockwood K. Accumulation of deficits as a proxy measure of aging. ScientificWorldJournal 2001;1:323–36. 10.1100/tsw.2001.58
    1. Buta BJ, Walston JD, Godino JG, et al. . Frailty assessment instruments: systematic characterization of the uses and contexts of highly-cited instruments. Ageing Res Rev 2016;26:53–61. 10.1016/j.arr.2015.12.003
    1. Clegg A, Bates C, Young J, et al. . Development and validation of an electronic frailty index using routine primary care electronic health record data. Age Ageing 2016;45:353–60. 10.1093/ageing/afw039
    1. Cesari M, Franchi C, Cortesi L, et al. . Implementation of the frailty index in hospitalized older patients: results from the REPOSI register. Eur J Intern Med 2018;56:11–18. 10.1016/j.ejim.2018.06.001
    1. Avila-Funes JA, Amieva H, Barberger-Gateau P, et al. . Cognitive impairment improves the predictive validity of the phenotype of frailty for adverse health outcomes: the three-city study. J Am Geriatr Soc 2009;57:453–61. 10.1111/j.1532-5415.2008.02136.x
    1. Boyle PA, Buchman AS, Wilson RS, et al. . Physical frailty is associated with incident mild cognitive impairment in community-based older persons. J Am Geriatr Soc 2010;58:248–55. 10.1111/j.1532-5415.2009.02671.x
    1. Swiss Personalized Health Network . Swiss personalized health network (SPHN), 2017. Available: [Accessed 25 Jul 2019].
    1. Hope AA, Adeoye O, Chuang EH, et al. . Pre-hospital frailty and hospital outcomes in adults with acute respiratory failure requiring mechanical ventilation. J Crit Care 2018;44:212–6. 10.1016/j.jcrc.2017.11.017
    1. Wan X, Wang W, Liu J, et al. . Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol 2014;14:135. 10.1186/1471-2288-14-135
    1. Evans SJ, Sayers M, Mitnitski A, et al. . The risk of adverse outcomes in hospitalized older patients in relation to a frailty index based on a comprehensive geriatric assessment. Age Ageing 2014;43:127–32. 10.1093/ageing/aft156
    1. Hewitt J, Long S, Carter B, et al. . The prevalence of frailty and its association with clinical outcomes in general surgery: a systematic review and meta-analysis. Age Ageing 2018;47:793–800. 10.1093/ageing/afy110
    1. Hogan DB, Maxwell CJ, Afilalo J, et al. . A scoping review of frailty and acute care in middle-aged and older individuals with recommendations for future research. Can Geriatr J 2017;20:22–37. 10.5770/cgj.20.240
    1. Song X, Mitnitski A, Rockwood K. Prevalence and 10-year outcomes of frailty in older adults in relation to deficit accumulation. J Am Geriatr Soc 2010;58:681–7. 10.1111/j.1532-5415.2010.02764.x
    1. Rockwood K, Song X, Mitnitski A. Changes in relative fitness and frailty across the adult lifespan: evidence from the Canadian national population health survey. CMAJ 2011;183:E487–94. 10.1503/cmaj.101271
    1. Rockwood K, Andrew M, Mitnitski A. A comparison of two approaches to measuring frailty in elderly people. J Gerontol A Biol Sci Med Sci 2007;62:738–43. 10.1093/gerona/62.7.738
    1. Gaudet-Blavignac C, Raisaro JL, Touré V, et al. . A National, Semantic-Driven, Three-Pillar Strategy to EnableHealth Data Secondary Usage Interoperability for Research Withinthe Swiss Personalized Health Network: Methodological Study. JMIR Med Inform 2021;9:e27591. 10.2196/27591
    1. Meier-Abt PJ, Lawrence AK, Selter L. The Swiss approach to precision medicine. Swiss Med Wkly 2018.
    1. Swiss Institute of Bioinformatics . Personalized health informatics group. 2018, 2019. Available: [Accessed 25 Jul 2019].
    1. D'Ath P, Katona P, Mullan E, et al. . Screening, detection and management of depression in elderly primary care attenders. I: the acceptability and performance of the 15 item geriatric depression scale (GDS15) and the development of short versions. Fam Pract 1994;11:260–6. 10.1093/fampra/11.3.260
    1. Shah A, Herbert R, Lewis S, et al. . Screening for depression among acutely ill geriatric inpatients with a short geriatric depression scale. Age Ageing 1997;26:217–21. 10.1093/ageing/26.3.217
    1. Bischoff-Ferrari HA, de Godoi Rezende Costa Molino C, Rival S, et al. . DO-HEALTH: Vitamin D3 - Omega-3 - Home exercise - Healthy aging and longevity trial - Design of a multinational clinical trial on healthy aging among European seniors. Contemp Clin Trials 2021;100:106124. 10.1016/j.cct.2020.106124
    1. Bischoff-Ferrari HA, Vellas B, Rizzoli R, et al. . Effect of vitamin D supplementation, omega-3 fatty acid supplementation, or a Strength-Training exercise program on clinical outcomes in older adults: the DO-HEALTH randomized clinical trial. JAMA 2020;324:1855–68. 10.1001/jama.2020.16909
    1. Gagesch M, Abderhalden L, Kressig RW. Threshold definition for grip strength to identify relevant weakness in Swiss DO-HEALTH participants. International Conference on Frailty and Sarcopenia Research; February 20-22, 2019, Miami Beach, FL, 2019.
    1. Börsch-Supan A, Brugiavini A. Health, Ageing and Retirement in Europe - First Results from the Survey of Health, Ageing and Retirement in Europe. Mannheim Research Institute for the Economics of Aging (MEA), 2008.

Source: PubMed

Sponsoren und Mitarbeiter

Krankheiten

Drogeninterventionen

3
Abonnieren