Skip to main content
SpringerLink
Log in

Classifying Polypharmacy According to Pharmacotherapeutic and Clinical Risks in Older Adults: A Latent Class Analysis in Quebec, Canada

  • Original Research Article
  • Published:
Drugs & Aging Aims and scope Submit manuscript

Abstract

Introduction

The simplistic definition of polypharmacy, often designated as the concomitant use of five medications or more, does not distinguish appropriate from inappropriate polypharmacy. Classifying polypharmacy according to varying levels of health risk would help optimise medication use.

Objective

We aimed to characterise different types of polypharmacy among older adults and evaluate their association with mortality and institutionalisation.

Methods

Using healthcare databases from the Quebec Integrated Chronic Disease Surveillance System, we selected a community-based random sample of the population ≥ 66 years old covered by the public drug plan. Categorical indicators used to describe polypharmacy included number of medications, potentially inappropriate medications (PIMs), drug–drug interactions, enhanced surveillance medications, complex route of administration medications, anticholinergic cognitive burden (ACB) score and use of blister cards. We used a latent class analysis to subdivide participants into distinct groups of polypharmacy. Their association with 3-year mortality and institutionalisation was assessed with adjusted Cox models.

Results

In total, 93,516 individuals were included. A four-class model was selected with groups described as (1) no polypharmacy (46% of our sample), (2) high-medium number of medications, low risk (33%), (3) medium number of medications, PIM use with or without high ACB score (8%) and (4) hyperpolypharmacy, complex use, high risk (13%). Using the class without polypharmacy as the reference, all polypharmacy classes were associated with 3-year mortality and institutionalisation, with the most complex/inappropriate classes denoting the highest risk (hazard ratio [HR] [95% confidence interval]: class 3, 70-year-old point estimate for mortality 1.52 [1.30–1.78] and institutionalisation 1.86 [1.52–2.29]; class 4, 70-year-old point estimate for mortality 2.74 [2.44–3.08] and institutionalisation 3.11 [2.60–3.70]).

Conclusions

We distinguished three types of polypharmacy with varying pharmacotherapeutic and clinical appropriateness. Our results highlight the value of looking beyond the number of medications to assess polypharmacy.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Lancet T. Making more of multimorbidity: an emerging priority. Lancet. 2018;391:1637. https://doi.org/10.1016/S0140-6736(18)30941-3.

    Article  Google Scholar 

  2. Gosselin E, Simard M, Dubé M, Sirois C. Portrait de la polypharmacie chez les aînés québécois entre 2000 et 2016. Gouvernement du Québec: Institut national de santé publique du Québec; 2020.

    Google Scholar 

  3. Sirois C, Domingues NS, Laroche ML, et al. Polypharmacy definitions for multimorbid older adults need stronger foundations to guide research, clinical practice and public health. Pharmacy. 2019;7(3):126. https://doi.org/10.3390/pharmacy7030126.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Maher RL, Hanlon J, Hajjar ER. Clinical consequences of polypharmacy in elderly. Expert Opin Drug Saf. 2014;13(1):57–65. https://doi.org/10.1517/14740338.2013.827660.

    Article  PubMed  Google Scholar 

  5. Assiri GA, Shebl NA, Mahmoud MA, et al. What is the epidemiology of medication errors, error-related adverse events and risk factors for errors in adults managed in community care contexts? A systematic review of the international literature. BMJ Open. 2018;8(5): e019101. https://doi.org/10.1136/bmjopen-2017-019101.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Li Y, Zhang X, Yang L, et al. Association between polypharmacy and mortality in the older adults: a systematic review and meta-analysis. Arch Gerontol Geriatr. 2022;100: 104630. https://doi.org/10.1016/j.archger.2022.104630.

    Article  PubMed  Google Scholar 

  7. Bushardt RL, Massey EB, Simpson TW, Ariail JC, Simpson KN. Polypharmacy: misleading, but manageable. Clin Interv Aging. 2008;3(2):383–9. https://doi.org/10.2147/CIA.S2468.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Lisibach A, Benelli V, Ceppi MG, Waldner-Knogler K, Csajka C, Lutters M. Quality of anticholinergic burden scales and their impact on clinical outcomes: a systematic review. Eur J Clin Pharmacol. 2021;77(2):147–62. https://doi.org/10.1007/s00228-020-02994-x.

    Article  PubMed  Google Scholar 

  9. Masnoon N, Kalisch Ellett L, Shakib S, Caughey GE. Predictors of mortality in the older population: the role of polypharmacy and other medication and chronic disease-related factors. Drugs Aging. 2020;37(10):767–76. https://doi.org/10.1007/s40266-020-00794-7.

    Article  PubMed  Google Scholar 

  10. Roux B, Sirois C, Simard M, Gagnon M-E, Laroche M-L. Potentially inappropriate medications in older adults: a population-based cohort study. Fam Pract. 2019;37(2):173–9. https://doi.org/10.1093/fampra/cmz060.

    Article  Google Scholar 

  11. Walsh CA, Cahir C, Tecklenborg S, Byrne C, Culbertson MA, Bennett KE. The association between medication non-adherence and adverse health outcomes in ageing populations: a systematic review and meta-analysis. Br J Clin Pharmacol. 2019;85(11):2464–78. https://doi.org/10.1111/bcp.14075.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Carr E, Federman A, Dzahini O, Dobson RJ, Bendayan R. A multidimensional measure of polypharmacy for older adults using the Health and Retirement Study. Sci Rep. 2021;11(1):8783. https://doi.org/10.1038/s41598-021-86331-x.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Akpan A, Roberts C, Bandeen-Roche K, et al. Standard set of health outcome measures for older persons. BMC Geriatr. 2018;18(1):36. https://doi.org/10.1186/s12877-017-0701-3.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Blais C, Jean S, Sirois C, et al. Quebec Integrated Chronic Disease Surveillance System (QICDSS), an innovative approach. Chronic Dis Inj Can. 2014;34(4):226–35.

    Article  CAS  PubMed  Google Scholar 

  15. Tamblyn R, Lavoie G, Petrella L, Monette J. The use of prescription claims databases in pharmacoepidemiological research: the accuracy and comprehensiveness of the prescription claims database in Québec. J Clin Epidemiol. 1995;48(8):999–1009. https://doi.org/10.1016/0895-4356(94)00234-H.

    Article  CAS  PubMed  Google Scholar 

  16. Collins LM, Lanza ST. Latent class and latent transition analysis with applications in the social, behavioral, and health sciences. Pennsylvania: Wiley; 2010. p. 3–5.

    Google Scholar 

  17. Lanza ST, Collins LM, Lemmon DR, Schafer JL. PROC LCA: a SAS procedure for latent class analysis. Struct Equ Model. 2007;14(4):671–94. https://doi.org/10.1080/10705510701575602.

    Article  Google Scholar 

  18. Nylund-Gibson K, Choi AY. Ten frequently asked questions about latent class analysis. Transl Issues Psychol Sci. 2018;4(4):440. https://doi.org/10.1037/met0000486.

    Article  Google Scholar 

  19. Bakoyannis G, Touloumi G. Practical methods for competing risks data: a review. Stat Methods Med Res. 2012;21(3):257–72. https://doi.org/10.1177/0962280210394479.

    Article  PubMed  Google Scholar 

  20. American Geriatrics Society Beers Criteria® Update Expert Panel. American Geriatrics Society 2019 updated AGS Beers criteria® for potentially inappropriate medication use in older adults. J Am Geriatr Soc. 2019;67(4):674–94. https://doi.org/10.1111/jgs.15767

  21. IBM Micromedex. Drug interactions. IBM Corporation. 2022. https://www.micromedexsolutions.com/home/dispatch. Accessed Dec 2021.

  22. Boustani M, Campbell N, Munger S, Maidment I, Fox C. Impact of anticholinergics on the aging brain: a review and practical application. Aging Health. 2008;4(3):311–20.

    Article  CAS  Google Scholar 

  23. Blix HS, Viktil KK, Moger TA, Reikvam A. Drugs with narrow therapeutic index as indicators in the risk management of hospitalised patients. Pharm Pract (Granada). 2010;8(1):50–5. https://doi.org/10.4321/s1886-36552010000100006.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Institute for Safe Medication Practices. High-Alert Medications in Community/Ambulatory Care Settings. 2021. https://www.ismp.org/recommendations/high-alert-medications-community-ambulatory-list. Accessed Dec 2021.

  25. Simard M, Sirois C, Candas B. Validation of the combined comorbidity index of Charlson and Elixhauser to predict 30-day mortality across ICD-9 and ICD-10. Med Care. 2018;56(5):441–7. https://doi.org/10.1097/MLR.0000000000000905.

    Article  PubMed  Google Scholar 

  26. Spiegl K, Luttenberger K, Graessel E, Becker L, Scheel J, Pendergrass A. Predictors of institutionalization in users of day care facilities with mild cognitive impairment to moderate dementia. BMC Health Serv Res. 2021;21(1):1009. https://doi.org/10.1186/s12913-021-07017-8.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Wolff J, Reißner P, Hefner G, et al. Pharmacotherapy, drug-drug interactions and potentially inappropriate medication in depressive disorders. PLoS ONE. 2021;16(7): e0255192. https://doi.org/10.1371/journal.pone.0255192.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. George J, Phun Y-T, Bailey MJ, Kong DC, Stewart K. Development and validation of the medication regimen complexity index. Ann Pharmacother. 2004;38(9):1369–76. https://doi.org/10.1345/aph.1D479.

    Article  PubMed  Google Scholar 

  29. Cross AJ, George J, Woodward MC, et al. Potentially inappropriate medications and anticholinergic burden in older people attending memory clinics in Australia. Drugs Aging. 2016;33(1):37–44. https://doi.org/10.1007/s40266-015-0332-3.

    Article  CAS  PubMed  Google Scholar 

  30. Jang S, Jeong S, Jang S. Patient- and prescriber-related factors associated with potentially inappropriate medications and drug-drug interactions in older adults. J Clin Med. 2021;10(11):2305. https://doi.org/10.3390/jcm10112305.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Al-Azayzih A, Alamoori R, Altawalbeh SM. Potentially inappropriate medications prescribing according to Beers criteria among elderly outpatients in Jordan: a cross sectional study. Pharm Pract (Granada). 2019;17(2):1439. https://doi.org/10.18549/PharmPract.2019.2.1439.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Squires P, Pahor M, Manini TM, Vouri S, Brown JD. Impact of anticholinergic medication burden on mobility and falls in the Lifestyle Interventions for Elders (LIFE) study. J Clin Med. 2020;9(9):2989. https://doi.org/10.3390/jcm9092989.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Lockery JE, Broder JC, Ryan J, et al. A cohort study of anticholinergic medication burden and incident dementia and stroke in older adults. J Gen Intern Med. 2021;36(6):1629–37. https://doi.org/10.1007/s11606-020-06550-2.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Campbell NL, Perkins AJ, Bradt P, et al. Association of anticholinergic burden with cognitive impairment and health care utilization among a diverse ambulatory older adult population. Pharmacotherapy. 2016;36(11):1123–31. https://doi.org/10.1002/phar.1843.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. de Araújo NC, Silveira EA, Mota BG, et al. Potentially inappropriate medications for the elderly: Incidence and impact on mortality in a cohort ten-year follow-up. PLoS ONE. 2020;15(10): e0240104. https://doi.org/10.1371/journal.pone.0240104.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Huang CH, Umegaki H, Watanabe Y, et al. Potentially inappropriate medications according to STOPP-J criteria and risks of hospitalization and mortality in elderly patients receiving home-based medical services. PLoS ONE. 2019;14(2): e0211947. https://doi.org/10.1371/journal.pone.0211947.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Parekh N, Ali K, Davies JG, Rajkumar C. Do the 2015 Beers Criteria predict medication-related harm in older adults? Analysis from a multicentre prospective study in the United Kingdom. Pharmacoepidemiol Drug Saf. 2019;28(11):1464–9. https://doi.org/10.1002/pds.4849.

    Article  CAS  PubMed  Google Scholar 

  38. Xing XX, Zhu C, Liang HY, et al. Associations between potentially inappropriate medications and adverse health outcomes in the elderly: a systematic review and meta-analysis. Ann Pharmacother. 2019;53(10):1005–19. https://doi.org/10.1177/1060028019853069.

    Article  PubMed  Google Scholar 

  39. Muhlack DC, Hoppe LK, Weberpals J, Brenner H, Schöttker B. The association of potentially inappropriate medication at older age with cardiovascular events and overall mortality: a systematic review and meta-analysis of cohort studies. J Am Med Dir Assoc. 2017;18(3):211–20. https://doi.org/10.1016/j.jamda.2016.11.025.

    Article  PubMed  Google Scholar 

  40. Fox C, Smith T, Maidment I, et al. Effect of medications with anti-cholinergic properties on cognitive function, delirium, physical function and mortality: a systematic review. Age Ageing. 2014;43(5):604–15. https://doi.org/10.1093/ageing/afu096.

    Article  PubMed  Google Scholar 

  41. Ali S, Peterson GM, Bereznicki LR, Salahudeen MS. Association between anticholinergic drug burden and mortality in older people: a systematic review. Eur J Clin Pharmacol. 2020;76(3):319–35. https://doi.org/10.1007/s00228-019-02795-x.

    Article  PubMed  Google Scholar 

  42. Salminen M, Laine J, Vahlberg T, et al. Factors associated with institutionalization among home-dwelling patients of Urgent Geriatric Outpatient Clinic: a 3-year follow-up study. Eur Geriatr Med. 2020;11(5):745–51. https://doi.org/10.1007/s41999-020-00338-7.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Wauters M, Elseviers M, Vaes B, et al. Mortality, hospitalisation, institutionalisation in community-dwelling oldest old: the impact of medication. Arch Gerontol Geriatr. 2016;65:9–16. https://doi.org/10.1016/j.archger.2016.02.009.

    Article  PubMed  Google Scholar 

  44. Rosenberg T, Montgomery P, Hay V, Lattimer R. Using frailty and quality of life measures in clinical care of the elderly in Canada to predict death, nursing home transfer and hospitalisation - the frailty and ageing cohort study. BMJ Open. 2019;9(11): e032712. https://doi.org/10.1136/bmjopen-2019-032712.

    Article  PubMed  PubMed Central  Google Scholar 

  45. De Buyser SL, Petrovic M, Taes YE, Vetrano DL, Onder G. A multicomponent approach to identify predictors of hospital outcomes in older in-patients: a multicentre, observational study. PLoS ONE. 2014;9(12):e115413-e. https://doi.org/10.1371/journal.pone.0115413.

    Article  CAS  Google Scholar 

  46. Joling KJ, Janssen O, Francke AL, et al. Time from diagnosis to institutionalization and death in people with dementia. Alzheimers Dement. 2020;16(4):662–71. https://doi.org/10.1002/alz.12063.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Luppa M, Luck T, Weyerer S, König H-H, Brähler E, Riedel-Heller SG. Prediction of institutionalization in the elderly. A systematic review. Age Ageing. 2009;39(1):31–8. https://doi.org/10.1093/ageing/afp202.

    Article  PubMed  Google Scholar 

  48. Taylor-Rowan M, Edwards S, Noel-Storr AH, et al. Anticholinergic burden (prognostic factor) for prediction of dementia or cognitive decline in older adults with no known cognitive syndrome. Cochrane Database Syst Rev. 2021;5(5):CD013540. https://doi.org/10.1002/14651858.CD013540.pub2.

  49. Manias E, Kabir MZ, Maier AB. Inappropriate medications and physical function: a systematic review. Ther Adv Drug Saf. 2021;12:20420986211030372. https://doi.org/10.1177/2042098621103037.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Franchi C, Marcucci M, Mannucci PM, et al. Changes in clinical outcomes for community-dwelling older people exposed to incident chronic polypharmacy: a comparison between 2001 and 2009. Pharmacoepidemiol Drug Saf. 2016;25(2):204–11. https://doi.org/10.1002/pds.3938.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Social and Preventive Medicine, Faculty of medicine, Université Laval, Québec, Canada

    M. Gosselin, D. Talbot, M. Simard & M. Mésidor

  2. Centre d’excellence sur le vieillissement de Québec, Québec, Canada

    M. Gosselin, M. Simard, P.-H. Carmichael & C. Sirois

  3. VITAM, Centre de recherche en santé durable, Québec, Canada

    M. Gosselin, M. Simard, Y. M. Chiu & C. Sirois

  4. CHU de Québec- Université Laval Research Centre, Québec, Canada

    M. Gosselin, D. Talbot, M. Simard, M. Mésidor & C. Sirois

  5. Institut national de santé publique du Québec, Québec, Canada

    M. Simard, Y. M. Chiu, M. Mésidor, V. Boiteau & C. Sirois

  6. Faculty of pharmacy, Université Laval, Québec, Canada

    Y. M. Chiu & C. Sirois

Authors
  1. M. Gosselin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. D. Talbot
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. M. Simard
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Y. M. Chiu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. M. Mésidor
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. V. Boiteau
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. P.-H. Carmichael
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. C. Sirois
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to C. Sirois.

Ethics declarations

Funding

This work was supported by the Canadian Institute of Health Research (CIHR) and the Natural Sciences and Engineering Research Council of Canada (grant number CPG—170621); a scholarship from the Centre d’excellence sur le vieillissement de Québec to Maude Gosselin and Marc Simard; a Fond de Recherche du Québec—Santé (FRQS) Junior 2 award to Caroline Sirois and Denis Talbot; a postdoctoral CIHR scholarship to Yohann Chiu; and a postdoctoral FRQS scholarship to Miceline Mésidor.

Conflict of interest

All authors declare that they have no conflict of interest.

Ethics approval

The use of the QICDSS for surveillance purposes has been approved by the provincial Public Health Research Ethics Board and the Quebec Commision d’accès à l’information. No written consent is needed from the participants. Data are deidentified and protected by privacy safeguards. The Université Laval Ethics Committee has approved the conduct of this study (#2021-245/30-08-3021).

Consent to participate

Not applicable.

Consent for publication

Not applicable.

Data availability

The datasets generated and analysed during the current study are not publicly available due to individual privacy stakes.

Code availability

The code created for this study is available from the corresponding author on request.

Author contributions

MG and VB had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. VB created the cohort from the QICDSS. MG participated in the conceptualisation of the project, conducted the statistical analyses and wrote the manuscript. CS (director), DT (co-director), MS, YC, MM and P-HC also participated in the conceptualisation of the project and the interpretation of the results. All authors critically reviewed the manuscript and approved its final version. Everyone who contributed significantly to the work are listed as authors.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (PDF 550 KB)

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Gosselin, M., Talbot, D., Simard, M. et al. Classifying Polypharmacy According to Pharmacotherapeutic and Clinical Risks in Older Adults: A Latent Class Analysis in Quebec, Canada. Drugs Aging 40, 573–583 (2023). https://doi.org/10.1007/s40266-023-01028-2

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40266-023-01028-2

Search

Navigation