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Rules to Identify Persons with Frailty in Administrative Health Databases*

Published online by Cambridge University Press:  04 October 2017

Robin Urquhart ,
Anik M.C. Giguere ,
Beverley Lawson ,
Cynthia Kendell ,
Jayna M. Holroyd-Leduc ,
Joseph H. Puyat ,
Arminee Kazanjian ,
Sharon Straus  and
Grace M. Johnston
Robin Urquhart*
Affiliation:
Department of Surgery, Dalhousie University Department of Community Health and Epidemiology, Dalhousie University
Anik M.C. Giguere
Affiliation:
Office of Education and Continuing Professional Development, Department of Family and Emergency Medicine, Pavillon Ferdinand-Vandry, Laval University Quebec Research Centre for Excellence in Aging, Research Centre of the CHU de Quebec, St. Sacrement Hospital
Beverley Lawson
Affiliation:
Department of Family Medicine, Dalhousie University
Cynthia Kendell
Affiliation:
Department of Surgery, Dalhousie University
Jayna M. Holroyd-Leduc
Affiliation:
Departments of Medicine and Community Health Sciences, University of Calgary
Joseph H. Puyat
Affiliation:
School of Population and Public Health, University of British Columbia
Arminee Kazanjian
Affiliation:
School of Population and Public Health, University of British Columbia
Sharon Straus
Affiliation:
Li Ka Shing Knowledge Institute, St. Michael’s Hospital Department of Medicine, University of Toronto
Grace M. Johnston
Affiliation:
School of Health Administration, Dalhousie University
*
† Correspondence and requests for reprints should be sent to / La correspondance et les demandes de tirés à part doivent être adressées à : Robin Urquhart, Ph.D. Room 8-032, Centennial Building QEII Health Sciences Centre 1276 South Park Street Halifax, NS B3H 2Y9 <robin.urquhart@nshealth.ca>
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Abstract

This study sought to develop frailty “identification rules” using population-based health administrative data that can be readily applied across jurisdictions for living and deceased persons. Three frailty identification rules were developed based on accepted definitions of frailty, markers of service utilization, and expert consultation, and were limited to variables within two common population-based administrative health databases: hospital discharge abstracts and physician claims data. These rules were used to identify persons with frailty from both decedent and living populations across five Canadian provinces. Participants included persons who had died and were aged 66 years or older at the time of death (British Columbia, Alberta, Ontario, Quebec, and Nova Scotia) and living persons 65 years or older (British Columbia, Alberta, Ontario, and Quebec). Descriptive statistics were computed for persons identified using each rule. The proportion of persons identified as frail ranged from 58.2-78.1 per cent (decedents) and 5.1-14.7 per cent (living persons).

Résumé

Cette étude avait pour objectif le développement de règles d’identification de la fragilité par l’utilisation de données administratives populationnelles sur la santé qui peuvent être appliquées dans différentes juridictions, en lien avec les personnes vivantes ou décédées. Trois règles d’identification de la fragilité ont été élaborées sur la base de définitions reconnues pour la fragilité, de marqueurs associés à l’utilisation de services, de la consultation d’experts. Ces règles ont été limitées aux variables retrouvées dans deux bases de données administratives communes en santé démographiques : les registres de congé des hôpitaux et les données sur les réclamations des médecins. Ces règles ont été utilisées pour identifier les personnes avec fragilité, qu’elles soient décédées ou en vie, dans cinq provinces canadiennes. Les données des participants provenaient de personnes décédées à l’âge de 66 ans ou plus (provinces : Colombie-Britannique, Alberta, Ontario, Québec, Nouvelle-Écosse) et de personnes vivantes âgées de 65 ans ou plus (provinces : Colombie-Britannique, Alberta, Ontario, Québec). Des statistiques descriptives ont été calculées pour ces personnes en utilisant chacune des règles. La proportion de personnes identifiées comme frêles se situait entre 58,2 et 78,1 % chez les personnes décédées, et entre 5,1 à 14,7 % chez les personnes en vie.

Keywords

agingfrailtyidentificationalgorithmadministrative health datavieillissmentfragilitéidentificationalgorithmedonnées administratives sur la santé
Type
Research Notes / Notes de recherché
Information
Canadian Journal on Aging / La Revue canadienne du vieillissement , Volume 36 , Issue 4 , December 2017 , pp. 514 - 521
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Copyright
Copyright © Canadian Association on Gerontology 2017 

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Footnotes

*

We gratefully acknowledge Sharon Zhang, Jim Si, Refik Saskin, Alejandro Gonzalez, and Louis Rochette for carrying out the analyses in Alberta, Ontario, and Quebec, and Sonia Jean, Serge Dumont, André Tourigny, and René Verreault for their valuable input on this study. This work was supported by the Canadian Frailty Network of the Networks of Centres of Excellence. The funder had no role in the design, methods, data collection, analysis, or preparation of this article.

References

Armstrong, J. J., Stolee, P., Hirdes, J. P., & Poss, J. W. (2010). Examining three frailty conceptualizations in their ability to predict negative outcomes for home-care clients. Age and Ageing, 39(6), 755–758.Google Scholar
Bronskill, S. E., Carter, M. W., & Costa, A. P. (2010). Aging in Ontario: An ICES Chartbook of Health Service Use by Older Adults - Technical Report. Toronto, ON: Institute for Clinical Evaluative Sciences.Google Scholar
Campitelli, M. A., Bronskill, S. E., Hogan, D. B., Diong, C., Amuah, J. E., Gill, S., … Maxwell, C. J. (2016). The prevalence and health consequences of frailty in a population-based older home care cohort: A comparison of different measures. BMC Geriatrics, 16, 133.Google Scholar
Clegg, A., Bates, C., Young, J., Ryan, R., Nichols, L., Ann Teale, E., … Marshall, T. (2016). Development and validation of an electronic frailty index using routine primary care electronic health record data. Age and Ageing, 45(3), 353–360.Google Scholar
Collard, R. M., Boter, H., Schoevers, R. A., & Oude Voshaar, R. C. (2012). Prevalence of frailty in community-dwelling older persons: A systematic review. Journal of the American Geriatrics Society, 60(8), 1487–1492.CrossRefGoogle ScholarPubMed
Davidoff, A. J., Zuckerman, I. H., Pandya, N., Hendrick, F., Ke, X., Hurria, A., … Edelman, M. J. (2013). A novel approach to improve health status measurement in observational claims-based studies of cancer treatment and outcomes. Journal of Geriatric Oncology, 4(2), 157–165.Google Scholar
Earle, C. C., Park, E. R., Lai, B., Weeks, J. C., Ayanian, J. Z., & Block, S. (2003). Identifying potential indicators of the quality of end-of-life cancer care from administrative data. Journal of Clinical Oncology, 21(6), 1133–1138.CrossRefGoogle ScholarPubMed
Fassbender, K., Fainsinger, R. L., Carson, M., & Finegan, B. A. (2009). Cost trajectories at the end of life: The Canadian experience. Journal of Pain and Symptom Management, 38(1), 75–80.CrossRefGoogle ScholarPubMed
Fried, L. P., Tangen, C. M., Walston, J., Newman, A. B., Hirsch, C., Gottdiener, J., … Cardiovascular Health Study Collaborative Research, G. (2001). Frailty in older adults: evidence for a phenotype. Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, 56(3), M146–156.Google Scholar
Gobbens, R. J., Luijkx, K. G., Wijnen-Sponselee, M. T., & Schols, J. M. (2010). Towards an integral conceptual model of frailty. Journal of Nutrition, Health & Aging, 14(3), 175–181.CrossRefGoogle ScholarPubMed
Hirdes, J. P., Frijters, D. H., & Teare, G. F. (2003). The MDS-CHESS scale: A new measure to predict mortality in institutionalized older people. Journal of the American Geriatrics Society, 51(1), 96–100.CrossRefGoogle Scholar
Hoover, M., Rotermann, M., Sanmartin, C., & Bernier, J. (2013). Validation of an index to estimate the prevalence of frailty among community-dwelling seniors. Health Reports, 24(9), 10–17.Google ScholarPubMed
Hubbard, R. E., Peel, N. M., Samanta, M., Gray, L. C., Fries, B. E., Mitnitski, A., & Rockwood, K. (2015). Derivation of a frailty index from the interRAI acute care instrument. BMC Geriatrics, 15, 27.CrossRefGoogle ScholarPubMed
Iezzoni, L. I. (1997). Assessing quality using administrative data. Annals of Internal Medicine, 127(8 Part 2), 666–674.Google Scholar
Kim, D. H., & Schneeweiss, S. (2014). Measuring frailty using claims data for pharmacoepidemiologic studies of mortality in older adults: Evidence and recommendations. Pharmacoepidemiology and Drug Safety, 23(9), 891–901.Google Scholar
Kojima, G. (2015). Prevalence of frailty in nursing homes: A systematic review and meta-analysis. Journal of the American Medical Directors Association, 16(11), 940–945.Google Scholar
Mitnitski, A. B., Mogilner, A. J., & Rockwood, K. (2001). Accumulation of deficits as a proxy measure of aging. The Scientific World Journal, 1, 323–336.Google Scholar
Organisation for Economic Co-operation and Development (OECD). (2017). The Next Generation of Health Reforms: OECD Health Ministerial Meeting. Paris, FRA: Author.Google Scholar
Rockwood, K., & Mitnitski, A. (2007). Frailty in relation to the accumulation of deficits. Journals of Gerontology, Series A: Biological Sciences and Medical Sciences, 62(7), 722–727.CrossRefGoogle Scholar
Rockwood, K., Song, X., MacKnight, C., Bergman, H., Hogan, D. B., McDowell, I., & Mitnitski, A. (2005). A global clinical measure of fitness and frailty in elderly people. Canadian Medical Association Journal, 173(5), 489–495.CrossRefGoogle ScholarPubMed
Rockwood, K., Stadnyk, K., MacKnight, C., McDowell, I., Hebert, R., & Hogan, D. B. (1999). A brief clinical instrument to classify frailty in elderly people. Lancet, 353(9148), 205–206.Google Scholar
Rolfson, D. B., Majumdar, S. R., Tsuyuki, R. T., Tahir, A., & Rockwood, K. (2006). Validity and reliability of the Edmonton Frail Scale. Age and Ageing, 35(5), 526–529.Google Scholar
Rosen, A., Wu, J., Chang, B. H., Berlowitz, D., Rakovski, C., Ash, A., & Moskowitz, M. (2001). Risk adjustment for measuring health outcomes: An application in VA long-term care. American Journal of Medical Quality, 16(4), 118–127.Google Scholar
Sieliwonczyk, E., Perkisas, S., & Vandewoude, M. (2014). Frailty indexes, screening instruments and their application in Belgian primary care. Acta Clinica Belgica, 69(4), 233–239.Google Scholar
The John Hopkins University. (2014). The Johns Hopkins ACG® System − Excerpt from Version 11.0 Technical Reference Guide. Available at https://www.healthpartners.com/ucm/groups/public/@hp/@public/documents/documents/cntrb_035024.pdf Google Scholar
World Health Organization. (2011). Global health and aging. Washington, DC: National Institute on Aging, National Institutes of Health.Google Scholar