Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Emerging approaches to polypharmacy among older adults

Nature Aging volume 1, pages 347–356 (2021)Cite this article

Subjects

Abstract

Polypharmacy is a major health issue for older adults. Entangled with several geriatric syndromes, including frailty, falls and cognitive decline, research focused on polypharmacy has been challenged by heterogeneity in its definition, confounding by comorbidities and limited prospective data. In this Review, we discuss varying definitions for polypharmacy and highlight the need for a uniform definition for future studies. We critically appraise strategies for reducing medication prescriptions and implementing deprescribing as a mechanism to reduce the potential harmful effects of polypharmacy. As we look to the future, we assess the role of novel analytics and high-throughput technology, including multiomics profiling, to advance research in polypharmacy and the development of new strategies for risk stratification in the age of precision medicine.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Theoretical model of the proposed subgroups of older adults.
Fig. 2: Adverse outcomes of polypharmacy.
Fig. 3: Process of deprescribing.
Fig. 4: The future of polypharmacy.

Similar content being viewed by others

References

  1. Ogden, D. Magic, Witchcraft, and Ghosts in the Greek and Roman Worlds: A Sourcebook (Oxford Univ. Press, 2002).

  2. Rollason, V. & Vogt, N. Reduction of polypharmacy in the elderly: a systematic review of the role of the pharmacist. Drugs Aging 20, 817–832 (2003).

    Article  PubMed  Google Scholar 

  3. Medication Safety in Polypharmacy: Technical Report (World Health Organization, 2019); https://apps.who.int/iris/rest/bitstreams/1235792/retrieve

  4. Jokanovic, N., Tan, E. C. K., Dooley, M. J., Kirkpatrick, C. M. & Bell, J. S. Prevalence and factors associated with polypharmacy in long-term care facilities: a systematic review. J. Am. Med. Dir. Assoc. 16, 535.e1–535.e12 (2015).

    Article  Google Scholar 

  5. Kantor, E. D., Rehm, C. D., Haas, J. S., Chan, A. T. & Giovannucci, E. L. Trends in prescription drug use among adults in the United States from 1999–2012. J. Am. Med. Assoc. 314, 1818–1831 (2015).

    Article  CAS  Google Scholar 

  6. Qato, D. M., Wilder, J., Schumm, L. P., Gillet, V. & Alexander, G. C. Changes in prescription and over-the-counter medication and dietary supplement use among older adults in the United States, 2005 vs 2011. JAMA Intern. Med. 176, 473–482 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Maher, R. L., Hanlon, J. & Hajjar, E. R. Clinical consequences of polypharmacy in elderly. Expert Opin. Drug Saf. 13, 57–65 (2014).

    Article  PubMed  Google Scholar 

  8. Morin, L., Johnell, K., Laroche, M.-L., Fastbom, J. & Wastesson, J. W. The epidemiology of polypharmacy in older adults: register-based prospective cohort study. Clin. Epidemiol. 10, 289–298 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Kojima, T. et al. Association of polypharmacy with fall risk among geriatric outpatients. Geriatr. Gerontol. Int. 11, 438–444 (2011).

    Article  PubMed  Google Scholar 

  10. Arauna, D. et al. Polypharmacy is associated with frailty, nutritional risk and chronic disease in Chilean older adults: remarks from PIEI-ES study. Clin. Interv. Aging 15, 1013–1022 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Li, J.-W., Hsieh, H.-M., Weng, S.-F. & Lee, I.-C. Polypharmacy and utilization of health care services: a cohort study of people aged over 50 years in Taiwan. Asia-Pac. J. Public Health 31, 257–266 (2019).

    Article  PubMed  Google Scholar 

  12. Flaherty, J. H., Perry, H. M., Lynchard, G. S. & Morley, J. E. Polypharmacy and hospitalization among older home care patients. J. Gerontol. A Biol. Sci. Med. Sci. 55, M554–M559 (2000).

    Article  CAS  PubMed  Google Scholar 

  13. Brockhattingen, K. K., Anru, P. L., Masud, T., Petrovic, M. & Ryg, J. Association between number of medications and mortality in geriatric inpatients: a Danish nationwide register-based cohort study. Eur. Geriatr. Med. 11, 1063–1071 (2020).

    Article  PubMed  Google Scholar 

  14. Veehof, L., Stewart, R., Haaijer-Ruskamp, F. & Jong, B. M. The development of polypharmacy. A longitudinal study. Fam. Pract. 17, 261–267 (2000).

    Article  CAS  PubMed  Google Scholar 

  15. Viktil, K. K., Blix, H. S., Moger, T. A. & Reikvam, A. Polypharmacy as commonly defined is an indicator of limited value in the assessment of drug-related problems. Br. J. Clin. Pharm. 63, 187–195 (2007).

    Article  Google Scholar 

  16. Lai, S.-W. & Liao, K.-F.Optimal cutoff of polypharmacy and outcomes. J. Clin. Epidemiol. 66, 465–466 (2013).

    Article  PubMed  Google Scholar 

  17. Langeard, A. et al. Polypharmacy cut-off for gait and cognitive impairments. Front. Pharmacol. 7, 296 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  18. Gnjidic, D., Le Couteur, D. G., Kouladjian, L. & Hilmer, S. N. Deprescribing trials: methods to reduce polypharmacy and the impact on prescribing and clinical outcomes. Clin. Geriatr. Med. 28, 237–253 (2012).

    Article  PubMed  Google Scholar 

  19. Masnoon, N., Shakib, S., Kalisch-Ellett, L. & Caughey, G. E.What is polypharmacy? A systematic review of definitions. BMC Geriatr. 17, 230 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  20. Kuijpers, M. A. J., van Marum, R. J., Egberts, A. C. G. & Jansen, P. A. F. Relationship between polypharmacy and underprescribing. Br. J. Clin. Pharm. 65, 130–133 (2008).

    Article  Google Scholar 

  21. 2019 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. 67, 674–694 (2019).

    Article  Google Scholar 

  22. O’Mahony, D. et al. STOPP/START criteria for potentially inappropriate prescribing in older people: version 2. Age Ageing 44, 213–218 (2015).

    Article  PubMed  Google Scholar 

  23. Hamilton, H., Gallagher, P., Ryan, C., Byrne, S. & O’Mahony, D. Potentially inappropriate medications defined by STOPP criteria and the risk of adverse drug events in older hospitalized patients. Arch. Intern. Med. 171, 1013–1019 (2011).

    Article  PubMed  Google Scholar 

  24. Osei, E. K., Berry-Cabán, C. S., Haley, C. L. & Rhodes-Pope, H.Prevalence of Beers criteria medications among elderly patients in a military hospital. Gerontol. Geriatr. Med. 2, 1–6 (2016).

    Google Scholar 

  25. Hill-Taylor, B. et al. Application of the STOPP/START criteria: a systematic review of the prevalence of potentially inappropriate prescribing in older adults, and evidence of clinical, humanistic and economic impact. J. Clin. Pharm. Ther. 38, 360–372 (2013).

    Article  CAS  PubMed  Google Scholar 

  26. Hanlon, J. T. et al. A method for assessing drug therapy appropriateness. J. Clin. Epidemiol. 45, 1045–1051 (1992).

    Article  CAS  PubMed  Google Scholar 

  27. Kuhn-Thiel, A. M., Weiß, C. & Wehling, M. & FORTA authors/expert panel members. Consensus validation of the FORTA (Fit fOR The Aged) List: a clinical tool for increasing the appropriateness of pharmacotherapy in the elderly. Drugs Aging 31, 131–140 (2014).

    Article  CAS  PubMed  Google Scholar 

  28. Pazan, F., Weiss, C. & Wehling, M. & FORTA. The EURO-FORTA (Fit fOR The Aged) List: international consensus validation of a clinical tool for improved drug treatment in older people. Drugs Aging 35, 61–71 (2018).

    Article  PubMed  Google Scholar 

  29. Rudolph, J. L.The Anticholinergic Risk Scale and anticholinergic adverse effects in older persons. Arch. Intern. Med. 168, 508–513 (2008).

    Article  PubMed  Google Scholar 

  30. Boustani, M., Campbell, N., Munger, S., Maidment, I. & Fox, C. Impact of anticholinergics on the aging brain: a review and practical application. Aging Health 4, 311–320 (2008).

    Article  CAS  Google Scholar 

  31. Hilmer, S. N.A drug burden index to define the functional burden of medications in older people. Arch. Intern. Med. 167, 781–787 (2007).

    Article  PubMed  Google Scholar 

  32. Fox, C. et al. Effect of medications with anti-cholinergic properties on cognitive function, delirium, physical function and mortality: a systematic review. Age Ageing 43, 604–615 (2014).

    Article  PubMed  Google Scholar 

  33. Carnahan, R. M., Lund, B. C., Perry, P. J., Pollock, B. G. & Culp, K. R. The Anticholinergic Drug Scale as a measure of drug-related anticholinergic burden: associations with serum anticholinergic activity. J. Clin. Pharm. 46, 1481–1486 (2006).

    Article  CAS  Google Scholar 

  34. Khera, A. V. et al. Genetic risk, adherence to a healthy lifestyle, and coronary disease. N. Engl. J. Med. 375, 2349–2358 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Michel, J.-P., Dreux, C. & Vacheron, A. Healthy ageing: evidence that improvement is possible at every age. Eur. Geriatr. Med. 7, 298–305 (2016).

    Article  Google Scholar 

  36. Stone Neil, J. et al. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults. J. Am. Coll. Cardiol. 63, 2889–2934 (2014).

    Article  CAS  PubMed  Google Scholar 

  37. Doan, J., Zakrzewski-Jakubiak, H., Roy, J., Turgeon, J. & Tannenbaum, C. Prevalence and risk of potential cytochrome P450-mediated drug–drug interactions in older hospitalized patients with polypharmacy. Ann. Pharmacother. 47, 324–332 (2013).

    Article  PubMed  Google Scholar 

  38. Vik, S. A., Maxwell, C. J. & Hogan, D. B. Measurement, correlates, and health outcomes of medication adherence among seniors. Ann. Pharmacother. 38, 303–312 (2004).

    Article  PubMed  Google Scholar 

  39. Leelakanok, N., Holcombe, A. L., Lund, B. C., Gu, X. & Schweizer, M. L. Association between polypharmacy and death: a systematic review and meta-analysis. J. Am. Pharm. Assoc. 57, 729–738.e10 (2017).

    Article  Google Scholar 

  40. Jyrkkä, J., Mursu, J., Enlund, H. & Lönnroos, E. Polypharmacy and nutritional status in elderly people. Curr. Opin. Clin. Nutr. Metab. Care 15, 1–6 (2012).

    Article  PubMed  Google Scholar 

  41. Kojima, T. et al. Association of polypharmacy with fall risk among geriatric outpatients. Geriatr. Gerontol. Int. 11, 438–444 (2011).

    Article  PubMed  Google Scholar 

  42. Crentsil, V., Ricks, M. O., Xue, Q.-L. & Fried, L. P. A pharmacoepidemiologic study of community-dwelling, disabled older women: factors associated with medication use. Am. J. Geriatr. Pharmacother. 8, 215–224 (2010).

    Article  PubMed  Google Scholar 

  43. Staller, K. et al. Menopausal hormone therapy is associated with increased risk of fecal incontinence in women after menopause. Gastroenterology 152, 1915–1921 (2017).

    Article  CAS  PubMed  Google Scholar 

  44. Nuotio, M., Jylhä, M., Luukkaala, T. & Tammela, T. L. J. Health problems associated with lower urinary tract symptoms in older women. A population-based survey. Scand. J. Prim. Health Care 23, 209–214 (2005).

    Article  PubMed  Google Scholar 

  45. Rochon, P. A. & Gurwitz, J. H. Optimising drug treatment for elderly people: the prescribing cascade. Br. Med. J. 315, 1096–1099 (1997).

    Article  CAS  Google Scholar 

  46. Savage, R. D. et al. Evaluation of a common prescribing cascade of calcium channel blockers and diuretics in older adults with hypertension. JAMA Intern. Med. 180, 643–651 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Gutiérrez‐Valencia, M. et al. The relationship between frailty and polypharmacy in older people: a systematic review. Br. J. Clin. Pharmacol. 84, 1432–1444 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  48. Green, J. L., Hawley, J. N. & Rask, K. J. Is the number of prescribing physicians an independent risk factor for adverse drug events in an elderly outpatient population? Am. J. Geriatr. Pharmacother. 5, 31–39 (2007).

    Article  PubMed  Google Scholar 

  49. Hutchinson, T. A., Flegel, K. M., Kramer, M. S., Leduc, D. G. & Kong, H. H. Frequency, severity and risk factors for adverse drug reactions in adult out-patients: a prospective study. J. Chronic Dis. 39, 533–542 (1986).

    Article  CAS  PubMed  Google Scholar 

  50. Gandhi, T. K. et al. Drug complications in outpatients. J. Gen. Intern. Med. 15, 149–154 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Shah, R. R. & Smith, R. L. Addressing phenoconversion: the Achilles’ heel of personalized medicine. Br. J. Clin. Pharm. 79, 222–240 (2015).

    Article  Google Scholar 

  52. Agbabiaka, T. B., Spencer, N. H., Khanom, S. & Goodman, C. Prevalence of drug–herb and drug–supplement interactions in older adults: a cross-sectional survey. Br. J. Gen. Pract. 68, e711–e717 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  53. Jou, J. & Johnson, P. J. Nondisclosure of complementary and alternative medicine use to primary care physicians: findings from the 2012 National Health Interview Survey. JAMA Intern. Med. 176, 545–546 (2016).

    Article  PubMed  Google Scholar 

  54. Tesfamariam, S. et al. Self-medication with over the counter drugs, prevalence of risky practice and its associated factors in pharmacy outlets of Asmara, Eritrea. BMC Public Health 19, 159 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  55. Stone, J. A. et al. A preliminary examination of over-the-counter medication misuse rates in older adults. Res. Soc. Admin. Pharm. 13, 187–192 (2017).

    Article  Google Scholar 

  56. Armanious, M. & Vender, R. A review of drug–drug interactions for biologic drugs used in the treatment of psoriasis. J. Cutan. Med. Surg. https://doi.org/10.1177/1203475420952423 (2020)

  57. Earl, T. R., Katapodis, N. D., Schneiderman, S. R. & Shoemaker-Hunt, S. J. Using deprescribing practices and the screening tool of older persons’ potentially inappropriate prescriptions criteria to reduce harm and preventable adverse drug events in older adults. J. Patient Saf. 16, S23–S35 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  58. May, F. W., Rowett, D. S., Gilbert, A. L., McNeece, J. I. & Hurley, E. Outcomes of an educational-outreach service for community medical practitioners: non-steroidal anti-inflammatory drugs. Med. J. Aust. 170, 471–474 (1999).

    Article  CAS  PubMed  Google Scholar 

  59. Woodward, M. C. Deprescribing: achieving better health outcomes for older people through reducing medications. J. Pharm. Pract. Res. 33, 323–328 (2003).

    Article  Google Scholar 

  60. Reeve, E., Gnjidic, D., Long, J. & Hilmer, S. A systematic review of the emerging definition of ‘deprescribing’ with network analysis: implications for future research and clinical practice. Br. J. Clin. Pharm. 80, 1254–1268 (2015).

    Article  Google Scholar 

  61. Scott, I. A. et al. Reducing inappropriate polypharmacy: the process of deprescribing. JAMA Intern. Med. 175, 827–834 (2015).

    Article  PubMed  Google Scholar 

  62. Kutner, J. S. et al. Safety and benefit of discontinuing statin therapy in the setting of advanced, life-limiting illness: a randomized clinical trial. JAMA Intern. Med. 175, 691–700 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  63. Olry de Labry Lima, A. et al. Evidence for deprescription in primary care through an umbrella review. BMC Fam. Pract. 21, 100 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  64. Page, A. T., Clifford, R. M., Potter, K., Schwartz, D. & Etherton-Beer, C. D. The feasibility and effect of deprescribing in older adults on mortality and health: a systematic review and meta-analysis. Br. J. Clin. Pharm. 82, 583–623 (2016).

    Article  Google Scholar 

  65. Sheppard, J. P. et al. Effect of antihypertensive medication reduction vs usual care on short-term blood pressure control in patients with hypertension aged 80 years and older: the OPTIMISE randomized clinical trial. J. Am. Med. Assoc. 323, 2039–2051 (2020).

    Article  CAS  Google Scholar 

  66. Salanitro, A. H. et al. Rationale and design of the multicenter medication reconciliation quality improvement study (MARQUIS). BMC Health Serv. Res. 13, 230 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  67. Gleason, K. M. et al. Results of the Medications at Transitions and Clinical Handoffs (MATCH) study: an analysis of medication reconciliation errors and risk factors at hospital admission. J. Gen. Intern. Med. 25, 441–447 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  68. Petrov, K., Varadarajan, R., Healy, M., Darvish, E. & Cowden, C. Improving medication history at admission utilizing pharmacy students and technicians: a pharmacy-driven improvement initiative. Pharmacy Ther. 43, 676–684 (2018).

    Google Scholar 

  69. Van der Cammen, T. J. M., Rajkumar, C., Onder, G., Sterke, C. S. & Petrovic, M. Drug cessation in complex older adults: time for action. Age Ageing 43, 20–25 (2014).

    Article  PubMed  Google Scholar 

  70. Declercq, T. et al. Withdrawal versus continuation of chronic antipsychotic drugs for behavioural and psychological symptoms in older people with dementia. Cochrane Database Syst. Rev. 28, CD007726 (2013).

    Google Scholar 

  71. Linsky, A. & Zimmerman, K. M. Provider and system-level barriers to deprescribing: interconnected problems and solutions. Public Policy Aging Rep. 28, 129–133 (2018).

    Article  Google Scholar 

  72. Doherty, A. J. et al. Barriers and facilitators to deprescribing in primary care: a systematic review. BJGP Open https://doi.org/10.3399/bjgpopen20X101096 (2020).

  73. Zechmann, S. et al. Barriers and enablers for deprescribing among older, multimorbid patients with polypharmacy: an explorative study from Switzerland. BMC Fam. Pract. 20, 64 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  74. Wallis, K. A., Andrews, A. & Henderson, M.Swimming against the tide: primary care physicians’ views on deprescribing in everyday practice. Ann. Fam. Med. 15, 341–346 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Jubraj, B. et al. A pilot survey of junior doctors’ attitudes and awareness around medication review: time to change our educational approach? Eur. J. Hosp. Pharm. 22, 243–248 (2015).

    Article  PubMed  Google Scholar 

  76. Lee, J., Negm, A., Wong, E. & Holbrook, A. Does deprescribing fall-associated drugs reduce falls and its complications?: a systematic review. Innov. Aging 1, 268 (2017).

    Article  PubMed Central  Google Scholar 

  77. Thompson, W. & Farrell, B. Deprescribing: what is it and what does the evidence tell us? Can. J. Hosp. Pharm. 66, 201–202 (2013).

    PubMed  PubMed Central  Google Scholar 

  78. Farrell, B. et al. Deprescribing proton pump inhibitors: evidence-based clinical practice guideline. Can. Fam. Physician 63, 354–364 (2017).

    PubMed  PubMed Central  Google Scholar 

  79. Gazarin, M. et al. Evaluating an inpatient deprescribing initiative at a rural community hospital in Ontario. Can. Pharm. J. (Ott.) 153, 224–231 (2020).

    Article  Google Scholar 

  80. Vasilevskis, E. E. et al. A patient-centered deprescribing intervention for hospitalized older patients with polypharmacy: rationale and design of the Shed-MEDS randomized controlled trial. BMC Health Serv. Res. 19, 165 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  81. Fried, L. P. et al. Frailty in older adults: evidence for a phenotype. J. Gerontol. A Biol. Sci. Med. Sci. 56, M146–M156 (2001).

    Article  CAS  PubMed  Google Scholar 

  82. Gaziano, J. M. et al. Million Veteran Program: a mega-biobank to study genetic influences on health and disease. J. Clin. Epidemiol. 70, 214–223 (2016).

    Article  PubMed  Google Scholar 

  83. Psaty, B. M. et al. Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: design of prospective meta-analyses of genome-wide association studies from five cohorts. Circ. Cardiovasc. Genet. 2, 73–80 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Ngiam, K. Y. & Khor, I. W. Big data and machine learning algorithms for health-care delivery. Lancet Oncol. 20, e262–e273 (2019).

    Article  PubMed  Google Scholar 

  85. Gulshan, V. et al. Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. J. Am. Med. Assoc. 316, 2402–2410 (2016).

    Article  Google Scholar 

  86. Chan, M., Nicklason, F. & Vial, J. H. Adverse drug events as a cause of hospital admission in the elderly. Intern. Med. J. 31, 199–205 (2001).

    Article  CAS  PubMed  Google Scholar 

  87. Stevenson, J. M. et al. Predicting adverse drug reactions in older adults; a systematic review of the risk prediction models. Clin. Inter. Aging 9, 1581–1593 (2014).

    Article  Google Scholar 

  88. Sharif-Askari, F. S., Syed Sulaiman, S. A., Saheb Sharif-Askari, N. & Al Sayed Hussain, A.Development of an adverse drug reaction risk assessment score among hospitalized patients with chronic kidney disease. PLoS ONE 9, e95991 (2014).

    Article  PubMed  Google Scholar 

  89. Rozenblum, R. et al. Using a machine learning system to identify and prevent medication prescribing errors: a clinical and cost analysis evaluation. Jt. Comm. J. Qual. Patient Saf. 46, 3–10 (2020).

    PubMed  Google Scholar 

  90. Lin, H.-H., Zhang, L.-L., Yan, R., Lu, J.-J. & Hu, Y. Network analysis of drug–target interactions: a study on FDA-approved new molecular entities between 2000 to 2015. Sci. Rep. 7, 12230 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  91. Burkhardt, H. A., Subramanian, D., Mower, J. & Cohen, T. Predicting adverse drug–drug interactions with neural embedding of semantic predications. AMIA Annu. Symp. Proc. 2019, 992–1001 (2020).

    PubMed  PubMed Central  Google Scholar 

  92. Fick, D. M. et al. Updating the Beers criteria for potentially inappropriate medication use in older adults: results of a US consensus panel of experts. Arch. Intern. Med. 163, 2716–2724 (2003).

    Article  PubMed  Google Scholar 

  93. Bjerrum, L., Søgaard, J., Hallas, J. & Kragstrup, J. Polypharmacy: correlations with sex, age and drug regimen. A prescription database study. Eur. J. Clin. Pharmacol. 54, 197–202 (1998).

    Article  CAS  PubMed  Google Scholar 

  94. Kocbek, S. et al. Building interpretable models for polypharmacy prediction in older chronic patients based on drug prescription records. PeerJ 6, e5765 (2018).

    Article  PubMed  PubMed Central  Google Scholar 

  95. Levy, A. E. et al. Applications of machine learning in decision analysis for dose management for dofetilide. PLoS ONE 14, e0227324 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  96. Schwartz, J. B. et al. Pharmacotherapy in older adults with cardiovascular disease: report from an American College of Cardiology, American Geriatrics Society, and National Institute on Aging workshop. J. Am. Geriatr. Soc. 67, 371–380 (2019).

    PubMed  Google Scholar 

  97. Claesson, M. J. et al. Gut microbiota composition correlates with diet and health in the elderly. Nature 488, 178–184 (2012).

    Article  CAS  PubMed  Google Scholar 

  98. Falony, G. et al. Population-level analysis of gut microbiome variation. Science 352, 560–564 (2016).

    Article  CAS  PubMed  Google Scholar 

  99. Maier, L. et al. Extensive impact of non-antibiotic drugs on human gut bacteria. Nature 555, 623–628 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Vich Vila, A. et al. Impact of commonly used drugs on the composition and metabolic function of the gut microbiota. Nat. Commun. 11, 362 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R. & Goodman, A. L. Mapping human microbiome drug metabolism by gut bacteria and their genes. Nature 570, 462–467 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Haiser, H. J. et al. Predicting and manipulating cardiac drug inactivation by the human gut bacterium Eggerthella lenta. Science 341, 295–298 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Haiser, H. J., Seim, K. L., Balskus, E. P. & Turnbaugh, P. J. Mechanistic insight into digoxin inactivation by Eggerthella lenta augments our understanding of its pharmacokinetics. Gut Microbes 5, 233–238 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  104. Schwab, R. S., England, A. C., Poskanzer, D. C. & Young, R. R. Amantadine in the treatment of Parkinson’s disease. J. Am. Med. Assoc. 208, 1168–1170 (1969).

    Article  CAS  Google Scholar 

  105. Ianiro, G. et al. Faecal microbiota transplantation for the treatment of diarrhoea induced by tyrosine-kinase inhibitors in patients with metastatic renal cell carcinoma. Nat. Commun. 11, 4333 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  106. Zadak, Z., Hyspler, R., Ticha, A. & Vlcek, J. Polypharmacy and malnutrition. Curr. Opin. Clin. Nutr. Metab. Care 16, 50–55 (2013).

    Article  CAS  PubMed  Google Scholar 

  107. Chen, R. Y. et al. Duodenal microbiota in stunted undernourished children with enteropathy. N. Engl. J. Med. 383, 321–333 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  108. Cavallari, L. H. et al. Multi-site investigation of outcomes with implementation of CYP2C19 genotype-guided antiplatelet therapy after percutaneous coronary intervention. JACC Cardiovasc. Interv. 11, 181–191 (2018).

    Article  PubMed  Google Scholar 

  109. Kim, D. et al. Targeted therapy guided by single-cell transcriptomic analysis in drug-induced hypersensitivity syndrome: a case report. Nat. Med. 26, 236–243 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Finkelstein, J., Friedman, C., Hripcsak, G. & Cabrera, M. Potential utility of precision medicine for older adults with polypharmacy: a case series study. Pharmgenomics Pers. Med. 9, 31–45 (2016).

    PubMed  PubMed Central  Google Scholar 

  111. Liu, J., Friedman, C. & Finkelstein, J. Pharmacogenomic approaches for automated medication risk assessment in people with polypharmacy. AMIA Jt Summits Transl. Sci. Proc. 2018, 142–151 (2018).

    PubMed Central  Google Scholar 

  112. Jiang, Y. et al. Predicting putative adverse drug reaction related proteins based on network topological properties. Anal. Methods 6, 2692–2698 (2014).

    Article  CAS  Google Scholar 

  113. Boland, M. R. et al. Systems biology approaches for identifying adverse drug reactions and elucidating their underlying biological mechanisms. Wiley Interdiscip. Rev. Syst. Biol. Med. 8, 104–122 (2016).

    Article  PubMed  Google Scholar 

  114. Levine, D. M., Lipsitz, S. R. & Linder, J. A. Trends in seniors’ use of digital health technology in the United States, 2011–2014. J. Am. Med. Assoc. 316, 538–540 (2016).

    Article  Google Scholar 

  115. Cross, A. J., Elliott, R. A., Petrie, K., Kuruvilla, L. & George, J.Interventions for improving medication‐taking ability and adherence in older adults prescribed multiple medications. Cochrane Database Syst. Rev. 5, CD012419 (2020).

    PubMed  Google Scholar 

  116. Patel, T. et al. A prospective study of usability and workload of electronic medication adherence products by older adults, caregivers, and health care providers. J. Med. Internet Res. 22, e18073 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  117. Zárate-Bravo, E. et al. Supporting the medication adherence of older Mexican adults through external cues provided with ambient displays: feasibility randomized controlled trial. JMIR mHealth uHealth 8, e14680 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  118. Huizer-Pajkos, A. et al. Adverse geriatric outcomes secondary to polypharmacy in a mouse model: the influence of aging. J. Gerontol. A Biol. Sci. Med. Sci. 71, 571–577 (2016).

    Article  CAS  PubMed  Google Scholar 

  119. Saka, B., Kaya, O., Ozturk, G. B., Erten, N. & Karan, M. A. Malnutrition in the elderly and its relationship with other geriatric syndromes. Clin. Nutr. 29, 745–748 (2010).

    Article  PubMed  Google Scholar 

  120. Lanhers, C. et al. Long-term cost reduction of routine medications following a residential programme combining physical activity and nutrition in the treatment of type 2 diabetes: a prospective cohort study. BMJ Open 7, e013763 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  121. Kreuter, M. W., Scharff, D. P., Brennan, L. K. & Lukwago, S. N. Physician recommendations for diet and physical activity. Preventive Med. 26, 825–833 (1997).

    Article  CAS  Google Scholar 

  122. Dietary Guidelines for Americans (USDA Food and Nutrition Service, 2021); https://www.fns.usda.gov/cnpp/dietary-guidelines-americans

  123. Burton, D. G. A., Wilmot, C. & Griffiths, H. R. Personalising nutrition for older adults: the InCluSilver project. Nutr. Bull. 43, 442–455 (2018).

    Article  Google Scholar 

  124. Gibson, A. et al. Effect of fruit and vegetable consumption on immune function in older people: a randomized controlled trial. Am. J. Clin. Nutr. 96, 1429–1436 (2012).

    Article  CAS  PubMed  Google Scholar 

  125. Ong, G.-J. et al. Clinician agreement and influence of medication-related characteristics on assessment of polypharmacy. Pharm. Res. Perspect. 5, e00321 (2017).

    Article  Google Scholar 

Download references

Acknowledgements

M.E.E. and A.T.C. received funding from the U.S. Department of Health & Human Services, National Institutes of Health (grant nos. RF1 AG067744 and U19 AG062682 to M.E.E., and nos. R35 CA253185, U19 AG062682 and RF1 AG067744 to A.T.C.).

Author information

Authors and Affiliations

  1. Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Raaj S. Mehta, Bharati D. Kochar & Andrew T. Chan

  2. Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

    Raaj S. Mehta, Bharati D. Kochar & Andrew T. Chan

  3. Department of Pharmacy Practice and Science, College of Pharmacy, University of Iowa, Iowa City, IA, USA

    Korey Kennelty & Michael E. Ernst

  4. Department of Family Medicine, Carver College of Medicine, University of Iowa, Iowa City, IA, USA

    Korey Kennelty & Michael E. Ernst

Authors
  1. Raaj S. Mehta
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Bharati D. Kochar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Korey Kennelty
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Michael E. Ernst
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Andrew T. Chan
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors conceived of the idea, discussed the concepts and contributed to the final manuscript. R.S.M. led the writing of the manuscript with input from K.K. and B.D.K. M.E.E. and A.T.C. supervised the project.

Corresponding author

Correspondence to Andrew T. Chan.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Aging thanks Rohan Elliott and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mehta, R.S., Kochar, B.D., Kennelty, K. et al. Emerging approaches to polypharmacy among older adults. Nat Aging 1, 347–356 (2021). https://doi.org/10.1038/s43587-021-00045-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s43587-021-00045-3

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing