Table of Contents 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 468

Bastiaan Sallevelt

Medication optimisation in hospitalised older people with polypharmacy and multimorbidity Bastiaan Sallevelt

Medication optimisation in hospitalised older people with polypharmacy and multimorbidity Bastiaan Sallevelt

Colofon Cover concept: Bastiaan Sallevelt Cover design and artwork: Charlotte van den Bosch Provided by thesis specialist Ridderprint, ridderprint.nl Printing: Ridderprint Layout and design: Dagmar van Schaik, persoonlijkproefschrift.nl Printing: Ridderprint ISBN: 978-94-6458-480-6 Publication of this thesis was financially supported by: Nederlands Bijwerkingen Fonds Stichting Fondsen Koninklijke Nederlandse Maatschappij ter bevordering der Pharmacie (KNMP) The work presented in this thesis was performed at the Department of Clinical Pharmacy and the Department of Geriatric Medicine at the University Medical Center Utrecht, Utrecht, The Netherlands. © 2022 B.T.G.M. Sallevelt All rights reserved. No parts of this thesis may be reproduced or transmitted in any form or by any means without permission in writing by the author, or when appropriate, by the publishers of the publications.

Medication optimisation in hospitalised older people with polypharmacy and multimorbidity Medicatie-optimalisatie bij klinisch opgenomen ouderen met polyfarmacie en multimorbiditeit (met een samenvatting in het Nederlands) Proefschrift ter verkrijging van de graad van doctor aan de Universiteit Utrecht op gezag van de rector magnificus, prof.dr. H.R.B.M. Kummeling, ingevolge het besluit van het college voor promoties in het openbaar te verdedigen op donderdag 20 oktober 2022 des middags te 2.15 uur door Bastiaan Theodoor Gerard Marie Sallevelt geboren op 31 maart 1991 te Boxmeer

Promotoren: Prof. dr. A.C.G. Egberts Prof. dr. E.P. van Puijenbroek Co-promotoren: Dr. I. Wilting Dr. W. Knol Beoordelingscommissie: Prof. dr. M.H. Emmelot-Vonk (voorzitter) Prof. dr. M.L. Bouvy Dr. D.L.M. Zwart Prof. dr. C. Kramers Prof. dr. P.M.L.A. van den Bemt

‘Diep peinsde hij, als in een diep water liet hij zich tot op de bodem van dit gevoel zakken, tot waar de oorzaken liggen, want weten wat de oorzaak is, zo kwam het hem voor, is denken, en daardoor alleen worden gevoelens tot kennis en gaan niet verloren, maar ze worden wezenlijk en beginnen uit te stralen wat ze in zich hebben.’ ~ Uit: Siddhartha, een Indiase vertelling door Hermann Hesse (1922)

Table of contents Chapter 1 General Introduction 9 Chapter 2 Applicability of tools for medication optimisation in hospitalised older people 31 2.1 Performance of a trigger tool for detecting adverse drug reactions in patients with polypharmacy acutely admitted to the geriatric ward 33 2.2 Evaluation of clarity of the STOPP/START criteria for clinical applicability in prescribing for older people: A quality appraisal study 59 2.3 Conversion of STOPP/START version 2 into coded algorithms for software implementation: A multidisciplinary consensus procedure 111 Chapter 3 Process development and clinical outcomes of in-hospital medication reviews 193 3.1 Intervention protocol: OPtimising thERapy to prevent avoidable hospital Admission in theMulti-morbid elderly (OPERAM): a structuredmedication review with support of a computerised decision support system 195 3.2 Optimizing therapy to prevent avoidable hospital admissions in multimorbid older adults (OPERAM): cluster randomised controlled trial 219 Chapter 4 Evaluation of the in-hospital medication review process 273 4.1 Frequency and acceptance of clinical decision support systemgenerated STOPP/START signals for hospitalised older patients with polypharmacy and multimorbidity 275 4.2 Hospital physicians' and older patients' agreement with individualised STOPP/START-based medication optimisation recommendations in a clinical trial setting 325 4.3 Detectability of medication errors with a STOPP/START-based medication review in older people in the year prior to a potentially preventable drug-related admission 349 Chapter 5 General Discussion 389 Chapter 6 Summary 427 Chapter 7 Nederlandse samenvatting 435 Chapter 8 Appendices 447 Chapter 9 Dankwoord 459

Chapter 1

General introduction

10 CHAPTER 1 Risk of drug-related harm in older people Reducing drug-related harm is a continuous challenge for health care professionals who aim to maintain a positive benefit-risk balance of pharmacotherapy to treat patients [1–3]. Older age, multimorbidity and polypharmacy are important risk factors for negative health outcomes related to medication use, such as adverse drug events and drug-related hospital admissions (Figure 1) [1,4,5]. This thesis focuses on the applicability of tools for medication optimisation, the effectiveness of a medication review on clinical outcomes, and the evaluation of the medication review process in hospitalised older people with polypharmacy and multimorbidity. Pharmacotherapy aims to optimise patients’ health outcomes and quality of life and to minimise drug-related harm [6,7]. Risks are inherent to medication use and can be accepted as long as the benefit-risk balance is positive [8–10], requiring considering, monitoring and evaluating the risk-benefit balance of pharmacotherapy for and together with the individual patient. In contrast, medication errors may cause potentially preventable patient harm and should be minimised. The report ‘To Err Is Human: Building a Safer Health System’ by the American Institute of Medicine in 1999 refuelled the awareness that preventable medication errors are a serious problem in health care requiring efforts to improve patient safety [11]. Subsequent research has drawn attention to the population of older patients with multimorbidity and polypharmacy, who are particularly vulnerable to potentially preventable drug-related harm. 8.6 million unplanned hospital admissions are caused by adverse drug events in Europe each year 50% of drug-related hospital admissions in older people are potentially preventable 75% of preventable drug-related hospital admission are from patients ≥ 65 years of age and on ≥ 5 drugs Figure 1. Drug-related harm in Europe [1,4,5].

11 General Introduction In 2008, two important Dutch observational studies on drug-related harm were published. A retrospective study (IPCI) found that 5% of all acute hospital admissions in adults (n = 2,238) were drug-related, which increased to almost 10% in the older population over 75 years of age [12]. In older patients, 40% of these hospitalisations were judged as potentially preventable compared to 16% in adults under 55 [12]. Similarly, the prospective Hospital Admissions Related to Medication (HARM) study concluded that 5.6% of the included 13,000 unplanned hospital admissions in adults were drug-related, of which about half were considered potentially preventable [4]. Older age, multimorbidity, polypharmacy, impaired cognition, dependent living situation, impaired renal function and non-adherence to medication regimens were identified as independent risk factors for drug-related hospital admissions [4]. These independent risk factors continue to cluster in the growing ageing population, explaining why older patients are particularly vulnerable to drug-related harm. In Europe, 20% of the total population is currently over 65 years of age, increasing to an estimated 30% by 2050 [13]. Life expectancy has risen by more than two years per decade since the 1960s. Improvements in the effectiveness of (pharmaco) therapy and healthcare coverage are key factors in these gained life-years [13– 15]. However, with ageing, the susceptibility to developing chronic diseases and multimorbidity – the co-existence of multiple chronic diseases in an individual – increases [16–18]. Multimorbidity impacts the quality of life and frequently results in polypharmacy [19,20], usually defined as the concomitant use of five or more regularly prescribed medications [21,22]. In line with ageing population’s demographic shift, polypharmacy’s prevalence has increased over the past decades (Figure 2) [23]. Figure 2. Trends in polypharmacy prevalence in older adults in the United States, Europe and New Zealand. Adopted from Wastesson et al. [23] 1

12 CHAPTER 1 Although the combination of ageing, multimorbidity and polypharmacy are wellknown important risk factors for drug-related harm, many other factors contribute to an increased vulnerability in this population. Frailty, age-related pharmacokinetic and pharmacodynamic changes, drug-disease interactions, drug-drug interactions, inadequate medication use and health care transitions (e.g. hospital admissions) are examples of such attributable risk factors (Figure 3) [24–26]. Therefore, reducing risk factors associated with drug-related harm requires a multidimensional approach on the levels of healthcare providers, patients, healthcare work environments and primary-secondary care interfaces, as addressed by the World Health Organization (WHO) [2,3,27]. Thus, complex interventions targeting multiple levels in healthcare are needed to enable the best possible outcomes and reduce healthcare expenditures in the growing older population with multimorbidity and polypharmacy. In 2009, the Dutch Ministry of Health, Welfare and Sport initiated a multidisciplinary task force to develop specific recommendations for the reduction of potentially preventable drug-related hospital admissions, which resulted in the HARMWrestling report [28,29]. However, the absolute number of drug-related admissions increased from an estimated 39,000 in 2008 to 49,000 in 2013. Similar to the results in 2008, 10% of hospital admissions in older patients were drug-related, half of which were considered potentially preventable. These findings confirmed that implementing of medication optimisation strategies and the evaluation thereof in clinical practice requires continuous effort [30].

13 General Introduction Figure 3. Examples of risk factors for drug-related harm in older people with polypharmacy and multimorbidity admitted to the hospital. 1

14 CHAPTER 1 Prescribing in older people Appropriate prescribing Although polypharmacy is an independent and important risk factor for drugrelated hospital admissions, the assumption that polypharmacy in itself is harmful to individual patients would be too simplistic. Indicated polypharmacy in multimorbid patients can also positively affect health outcomes, and withholding pharmacotherapy can have negative health consequences [31–33]. Underprescribing (i.e. the lack of an indicated drug without a valid reason for not prescribing it) is remarkably common in older people, especially in patients with polypharmacy [33–35]. For example, cardiovascular drug underuse in older patients has been associated with hospital admissions due to heart failure exacerbation [32,36]. Therefore, increasing ‘medication appropriateness’ is critical, not just reducing the number of drugs. Medication appropriateness is generally defined as the quality of prescribing pharmacotherapy related to the individual patient and refers to a continuous process of pharmacotherapeutic decision-making that maximises individual health gains [37,38]. The WHO six-step model is a validated method to promote appropriate prescribing (Figure 4) [39–41]. However, challenges in all steps of the prescribing process may be encountered in older patients with multimorbidity and polypharmacy compared to younger patients. For instance, the patient’s problem may be less obvious in multimorbid patients, and the misinterpretation of adverse drug reactions can lead to prescribing cascades (i.e. prescription of a subsequent drug to treat a drug-induced adverse event) [42]. In addition, patient-specific therapeutic objectives may be different (e.g. life prolongation vs quality of life). Figure 4. WHO 6-step model of appropriate prescribing [39–41].

15 General Introduction Moreover, the risk-benefit balance in older multimorbid patients is often uncertain, which can complicate treatment choices [43,44]. Evidence-based guidelines for older patients with multimorbidity and polypharmacy are often lacking since they are largely underrepresented in clinical trials [45–48]. Although regulatory agencies are developing strategies to cover existing knowledge gaps in pharmaceutical patient care and drug product design for older people, the most currently available clinical practice guidelines are still single-disease oriented [45,49]. As a result, guideline recommendations are usually drawn from results in younger adults without multimorbidity or polypharmacy. In addition, difficulties may arise in communicating with older patients (e.g. due to cognitive impairment or hearing problems), impeding clear patient information, instruction for medication use and shared decision-making throughout the prescribing process. Lastly, frequent changes in medical conditions and co-medication make appropriate prescribing subject to highly dynamic factors in older patients over time, requiring close monitoring of pharmacotherapy. Monitoring is further compromised by involving multiple prescribers in patients with polypharmacy, which requires intensive collaboration between healthcare professionals to ensure adequate follow-up. Explicit tools for appropriate prescribing in older patients Due to the knowledge gap in single-disease-oriented clinical practice guidelines about optimal pharmacotherapy in older patients, several explicit tools have been developed to facilitate appropriate prescribing in this population [50]. Most explicit screening tools provide lists of drugs – often concerning concomitant diseases or medical conditions – frequently involved in drug-related harm in older people [51–53]. Although explicit screening tools are based on the best available evidence for the benefit-risk balance in older people, they do not consider individual patients’ needs and preferences and require clinical consideration. Therefore, these drugs are often referred to as ‘potentially’ inappropriate in older people. The Beers Criteria were the first list of explicit criteria developed to detect potential inappropriate prescribing in older people [54]. However, the Beers Criteria have several limitations that impede their use outside the United States [55]. For this reason, the Screening Tool of Older Person’s Prescriptions (STOPP) and the Screening Tool to Alert to Right Treatment (START) criteria were developed in Ireland (2008). This version was updated in 2015 by a European expert team resulting in STOPP/ START version 2 comprising 114 explicit criteria [56,57]. In contrast to other explicit screening tools, STOPP/START also includes potential drug omissions to detect under-prescribing. Hence, the STOPP/START criteria are the most widely used and extensively studied explicit screening tool for older patients in Europe [58]. Applying the STOPP/START criteria has been shown to reduce potentially inappropriate prescribing and adverse drug reactions while lowering healthcare costs in older 1

16 CHAPTER 1 patients in previous trials. However, their effects on other clinical outcomes, such as drug-related hospitalisations, remain to be established [56,59–62]. European geriatric clinical practice guidelines – including the Dutch geriatric guideline on polypharmacy – endorse considering using STOPP/START to facilitate medication reviews in older people [63,64]. Medication review in older people A medication review can be defined as ‘a structured, critical examination of a person’s medicines with the objective of reaching an agreement with the person about treatment, optimising the impact of medicines, minimising the number of medicationrelated problems and reducing waste’ [63]. A medication review aims to optimise a patient’s existing pharmacotherapy to prevent worsening medical conditions or complications (related to pharmacotherapy) while individualising pharmacotherapy to a patient’s needs to promote medication self-management. This purpose differs from regular medication safety monitoring, usually performed when preparing and dispensing (new) medication to ensure safe and effective pharmaceutical products related to co-medication or patient characteristics while limiting the likelihood of harm from the products’ use [65]. The STRIP method for medication review The Systematic Tool to Reduce Inappropriate Prescribing (STRIP) is a medication review method that combines implicit (judgement-based) questions with explicit screening tools (e.g. STOPP/START criteria) to increase appropriate prescribing in older people [64–67]. The STRIP method consists of five steps: 1. Medication reconciliation: Obtaining information about thepatient’smedicationhistory and actual medication use while understanding wishes, experiences and beliefs about medications; 2. Pharmacotherapy analysis: Identifying potential drug-related problems (e.g. underuse, overuse, misuse, potential adverse drug reactions, drug-drug interactions, drug-disease interactions, practical intake issues); 3. Pharmaceutical care plan: Agreeing about therapeutic aims between the physician and pharmacist and how these aims could be achieved;

17 General Introduction 4. Shared decision-making: Collaborating between patients and healthcare professionals to jointly decide therapeutic aims and pharmacotherapy; 5. Follow-up and monitoring: Determining patient outcomes based on the desired goals of pharmacotherapy. The steps of a medication review according to the STRIP method and tools to facilitate this process appear in Figure 5. Medication reconciliation is the first step in the medication review process and aims to obtain and maintain a complete and accurate list of a patient’s current medication use – both prescription and non-prescription drugs – particularly at care transitions [68]. The Structured History-taking of Medication (SHiM) tool was developed to reduce the number of unintentional medication discrepancies [69]. This implicit screening tool revealed unintentional discrepancies in medication lists of 92% of patients admitted to the geriatric ward, of which one-fifth had clinical consequences [69]. Unintentional discrepancies in medication lists at hospital discharge to the less controlled primary care environment pose an even higher risk for patient harm [70,71]. Van der Linden et al. found that more than a quarter (27%) of discontinued drugs during hospitalisation because of an adverse drug reaction were represcribed after discharge from geriatric wards [72]. Medication reconciliation effectively decreases admission and discharge order discrepancies, possibly reducing preventable medication harm [73,74]. Hence, the integration of medication reconciliation by pharmacy technicians at transitions of care has been implemented as a standard of care for several years in Dutch hospitals [75,76]. However, performing a complete medication review using the STRIP method is time-consuming. Therefore, computerised interventions have been suggested to increase the efficacy and quality of the medication review process in older people [55]. Explicit screening tools, such as STOPP/START, have the potential to be implemented as algorithms in clinical decision support systems (CDSS), thereby facilitating the pharmacotherapy analysis (step 2) of themedication reviewprocess [77]. The STRIP Assistant (STRIPA) is a Dutch software-based CDSS first developed in 2015 to assist healthcare professionals in performing a pharmacotherapy analysis during a medication review. This prototype of STRIPA included STOPP/START criteria version 1, intended for use in primary care [78]. Its performance was tested in a validation study among general practitioners and pharmacists. STRIPA increased correct decisions from 58% to 76% (p < 0.01) and reduced incorrect decisions 1

18 CHAPTER 1 from 42% to 24% (P<0.01) compared to a pharmacotherapy analysis without clinical decision support [79]. However, unlike the aimed improvement in efficacy, participants spent more time using STRIPA attributed to the prototypical design of the software’s user interface, and the users’ unfamiliarity with the application. Further development of STRIPA aimed to improve usability, incorporate the updated STOPP/START criteria version 2 and make the tool suitable for application in a hospital setting [80]. Effectiveness of medication review on clinical outcomes Although the aforementioned explicit screening tools have been shown to improve medication appropriateness in older people, the effect of medication reviews as a multicomponent intervention on clinical outcomes remains uncertain [81,82]. The low quality of currently available studies (e.g. short follow-up, small sample sizes, high risk of bias) impedes drawing firm conclusions [81,82]. In addition, heterogeneity in study designs, settings and outcomes also hamper comparing studies investigating the effectiveness of medication review [83,84]. Knowledge gap and thesis rationale Although geriatric-specific clinical practice guidelines have been developed to guide safe and effective pharmacotherapy, drug-related adverse outcomes in older patients remain a major problem. Thus, healthcare professionals and older patients still need evidence-based strategies to reduce potentially preventable drug-related harm. The question arises whether the existing tools for medication optimisation recommended by clinical practice guidelines are suitable for implementation in clinical practice or how their applicability can be improved. Hence, the uncertainty of the effectiveness of medication reviews in older people with polypharmacy and multimorbidity on clinical outcomes was the rationale to design a large, randomised controlled trial explicitly addressing the limitations of previous trials. The aim of the OPtimising thERapy to prevent Avoidable hospital admissions in Multimorbid older people (OPERAM) trial assessed the effectiveness of an in-hospital structured medication review compared to usual care on drugrelated hospital admissions and other clinical outcomes, using a core outcome set previously developed by European healthcare professionals and patients [85,86]. A detailed evaluation of the different steps of this in-hospital medication review could provide relevant insights to optimise this complex process.

19 General Introduction Figure 5. The five-step Systematic Tool to Reduce Inappropriate Prescribing (STRIP) method and tools to facilitate the medication review process. 1

20 CHAPTER 1 Objectives of this thesis The general aim of this thesis is to investigate strategies for medication optimisation in hospitalised older people with polypharmacy and multimorbidity. This aim was divided into the following objectives: 1. To evaluate the applicability of medication optimisation tools recommended by clinical practice guidelines; 2. To develop a process for in-hospital medication review using implicit and explicit medication optimisation tools; 3. To investigate the effect of an in-hospital medication review in older people with multimorbidity and polypharmacy on clinical outcomes; 4. To evaluate the process of the in-hospital medication review to formulate recommendations for future refinement of the medication review process.

21 General Introduction Thesis outline Chapter 2 describes the applicability of medication optimisation tools recommended by clinical practice guidelines. In Chapter 2.1, the performance of a trigger tool for detecting adverse drug reactions is evaluated. This ADR trigger tool has been recommended for use in all acutely admitted older patients with polypharmacy by the Dutch geriatric guideline on ‘polypharmacy optimisation in hospitalised older people’. In Chapter 2.2, the clarity of STOPP/START version 2 as a clinical practice guideline for applicability in daily patient care is evaluated. The conversion of STOPP/START criteria version 2 into software algorithms to enable their incorporation into a CDSS is described in Chapter 2.3. Chapter 3 focuses on the process development of a CDSS-assisted in-hospital medication review (Chapter 3.1) and its effect on clinical outcomes in hospitalised older people with multimorbidity and polypharmacy (Chapter 3.2). This research is part of the OPERAM trial, a European cluster-randomised controlled multicentre trial investigating the effect of a STOPP/START-based in-hospital medication review on drug-related readmissions in older (≥ 70 years) patients with multimorbidity (≥3 chronic conditions) and polypharmacy (≥5 regular medication use). Secondary outcomes are based on the aforementioned core outcome set [85]. The in-hospital medication review is performed according to the STRIP method supported by STRIPA software with incorporated STOPP/START version 2. Chapter 4 evaluates the process of in-hospital medication reviews performed in the OPERAM trial on three levels. In Chapter 4.1, the clinical applicability of CDSS-generated STOPP/START signals in a hospital setting is evaluated. Second, the patients’ and physicians’ agreement with STOPP/START-based individualised medication optimisation recommendations are assessed in Chapter 4.2. In Chapter 4.3, the detectability of medication errors with the in-hospital medication review in the year prior to a potentially preventable drug-related hospital admission is assessed. The thesis outline is graphically summarised in Figure 6. 1

22 CHAPTER 1 Figure 6. Graphical summary of the outline of this thesis. CPG = clinical practice guidelines; CDSS = clinical decision support system.

23 General Introduction Declarations Authors’ contributions Bastiaan Sallevelt wrote the general introduction of this thesis. His supervisors Wilma Knol, Ingeborg Wilting, Eugène van Puijenbroek and Toine Egberts reviewed the manuscript critically for important intellectual content and approved the final version. Acknowledgement Bastiaan would also like to thank his parents, who reviewed the general introduction on comprehensibility for people not professionally involved in the field of medicine. Competing interests The author(s) declare that they have no competing interests. 1

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26 CHAPTER 1 33. Lombardi F, Paoletti L, Carrieri B, Dell’Aquila G, Fedecostante M, Di Muzio M, et al. Underprescription of medications in older adults: causes, consequences and solutions—a narrative review. Eur Geriatr Med 2021;12:453–62. https://doi.org/10.1007/ s41999-021-00471-x. 34. Kuijpers MAJ, Van Marum RJ, Egberts ACG, Jansen PAF. Relationship between polypharmacy and underprescribing. Br J Clin Pharmacol 2008;65:130–3. https://doi. org/10.1111/j.1365-2125.2007.02961.x. 35. Cherubini A, Corsonello A, Lattanzio F. Underprescription of beneficial medicines in older people: Causes, consequences and prevention. Drugs and Aging 2012;29:463–75. https://doi.org/10.2165/11631750-000000000-00000. 36. Márquez PHP, Torres OH, San-José A, Vidal X, Agustí A, Formiga F, et al. Potentially Inappropriate Antihypertensive Prescriptions to Elderly Patients: Results of a Prospective, Observational Study. Drugs and Aging 2017;34:453–66. https://doi. org/10.1007/s40266-017-0452-z. 37. Spinewine A, Schmader KE, Barber N, Hughes C, Lapane KL, Swine C, et al. Appropriate prescribing in elderly people: how well can it be measured and optimised? Lancet 2007;370:173–84. https://doi.org/10.1016/S0140-6736(07)61091-5. 38. Buetow SA, Sibbald B, Cantrill JA, Halliwell S. Appropriateness in health care: Application to prescribing. Soc Sci Med 1997;45:261–71. https://doi.org/10.1016/S02779536(96)00342-5. 39. De Vries T, Henning R, Hogerzeil H, Fresle D. Guide to Good Prescribing. World Health Organization (WHO). 1995:1–142. https://apps.who.int/iris/handle/10665/59001 (accessed May 30, 2022). 40. Keijsers CJPW, Segers WS, De Wildt DJ, Brouwers JRBJ, Keijsers L, Jansen PAF. Implementation of the WHO-6-step method in the medical curriculum to improve pharmacology knowledge and pharmacotherapy skills. Br J Clin Pharmacol 2015;79:896– 906. https://doi.org/10.1111/bcp.12575. 41. Tichelaar J, Richir MC, Garner S, Hogerzeil H, de Vries TPGM. WHO guide to good prescribing is 25 years old: quo vadis? Eur J Clin Pharmacol 2020;76:507–13. https:// doi.org/10.1007/s00228-019-02823-w. 42. Rochon PA, Gurwitz JH. The prescribing cascade revisited. Lancet 2017;389(1008:1778– 80. https://doi.org/10.1016/S0140-6736(17)31188-1. 43. Payne RA. The epidemiology of polypharmacy. Clin Med J R Coll Physicians London 2016;16:465–9. https://doi.org/10.7861/clinmedicine.16-5-465. 44. Hughes LD, McMurdo MET, Guthrie B. Guidelines for people not for diseases: The challenges of applying UK clinical guidelines to people with multimorbidity. Age Ageing 2013;42:62–9. https://doi.org/10.1093/ageing/afs100. 45. Cerreta F, Eichler H-G, Rasi G. Drug Policy for an Aging Population — The European Medicines Agency’s Geriatric Medicines Strategy. N Engl J Med 2012;367(21):1972–4. https://doi.org/10.1056/nejmp1209034. 46. Konrat C, Boutron I, Trinquart L, Auleley GR, Ricordeau P, Ravaud P. Underrepresentation of elderly people in randomised controlled trials. The example of trials of 4 widely prescribed drugs. PLoS One 2012;7. https://doi.org/10.1371/journal.pone.0033559. 47. Nanna MG, Chen ST, Nelson AJ, Navar AM, Peterson ED. Representation of Older Adults in Cardiovascular Disease Trials since the Inclusion across the Lifespan Policy. JAMA Intern Med 2020;180(11):1531–3. https://doi.org/10.1001/jamainternmed.2020.2750. 48. Jadad AR, To MJ, Emara M, Jones J. Consideration of multiple chronic diseases in randomized controlled trials. JAMA - J Am Med Assoc 2011;306(24):2670–2. https:// doi.org/10.1001/jama.2011.1886.

27 General Introduction 49. van Riet-Nales DA, Sundberg K, de Boer A, Hirschlérova B. Developing patient-centric medicines for older people: Reflections from the draft EMA paper on the pharmaceutical development of medicines for use in the older population. Br J Clin Pharmacol 2020;86(10):2008–13. https://doi.org/10.1111/bcp.14530. 50. Lavan AH, Gallagher PF, O’Mahony D. Methods to reduce prescribing errors in elderly patients with multimorbidity. Clin Interv Aging 2016;11:857–66. https://doi.org/10.2147/ CIA.S80280. 51. Motter FR, Fritzen JS, Hilmer SN, Paniz ÉV, Paniz VMV. Potentially inappropriate medication in the elderly: a systematic review of validated explicit criteria. Eur J Clin Pharmacol 2018;74(6):679–700. https://doi.org/10.1007/s00228-018-2446-0. 52. Denis Curtin PFG and DO. Explicit criteria as clinical tools to minimize inappropriate medication use and its consequences. Ther Adv Drug Saf 2019;10:1–10. https://doi. org/10.1177/https. 53. Howard RL, Avery AJ, Slavenburg S, Royal S, Pipe G, Lucassen P, et al. Which drugs cause preventable admissions to hospital? A systematic review. Br J Clin Pharmacol 2007;63:136–47. https://doi.org/10.1111/j.1365-2125.2006.02698.x. 54. Fick DM, Semla TP, Steinman M, Beizer J, Brandt N, Dombrowski R, et al. American Geriatrics Society 2019 Updated AGS Beers Criteria® for Potentially Inappropriate Medication Use in Older Adults. J Am Geriatr Soc 2019;67:674–94. https://doi. org/10.1111/jgs.15767. 55. O’Connor MN, Gallagher P, O’Mahony D. Inappropriate Prescribing. Drugs Aging 2012;29:437–52. https://doi.org/10.2165/11632610-000000000-00000. 56. O’Mahony D. STOPP/START criteria for potentially inappropriate medications/potential prescribing omissions in older people: origin and progress. Expert Rev Clin Pharmacol 2020;13:15–22. https://doi.org/10.1080/17512433.2020.1697676. 57. O’Mahony D, O’Sullivan D, Byrne S, O’Connor MN, Ryan C, Gallagher P. STOPP/START criteria for potentially inappropriate prescribing in older people: Version 2. Age Ageing 2015;44:213–8. https://doi.org/10.1093/ageing/afu145. 58. Alshammari H, Al-Saeed E, Ahmed Z, Aslanpour Z. Reviewing potentially inappropriate medication in hospitalized patients over 65 using explicit criteria: A systematic literature review. Drug Healthc Patient Saf 2021;13:183–210. https://doi.org/10.2147/DHPS.S303101. 59. Curtin D, Gallagher PF, O’Mahony D. Explicit criteria as clinical tools to minimize inappropriate medication use and its consequences. Ther Adv Drug Saf 2019;10:2042098. https://doi.org/10.1177/2042098619829431. 60. Masnoon N, Shakib S, Kalisch-Ellett L, Caughey GE. Tools for Assessment of the Appropriateness of Prescribing and Association with Patient-Related Outcomes: A Systematic Review. Drugs Aging 2018;35:43–60. https://doi.org/10.1007/s40266018-0516-8. 61. Hill-Taylor B, Walsh KA, Stewart SA, Hayden J, Byrne S, Sketris IS. Effectiveness of the STOPP/START (Screening Tool of Older Persons’ potentially inappropriate Prescriptions/ Screening Tool to Alert doctors to the Right Treatment) criteria: Systematic review and meta-analysis of randomized controlled studies. J Clin Pharm Ther 2016;41:158–69. https://doi.org/10.1111/jcpt.12372. 62. O’Connor MN, O’Sullivan D, Gallagher PF, Eustace J, Byrne S, O’Mahony D. Prevention of Hospital-Acquired Adverse Drug Reactions in Older People Using Screening Tool of Older Persons’ Prescriptions and Screening Tool to Alert to Right Treatment Criteria: A Cluster Randomized Controlled Trial. J Am Geriatr Soc 2016;64(8):1558–66. https:// doi.org/10.1111/jgs.14312. 1

28 CHAPTER 1 63. NICE, Medicines and CUP. Medicines optimisation: the safe and effective use of medicines to enable the best possible outcomes. NICE Guidel 2015. https://www.nice. org.uk/guidance/ng5 (accessed May 30, 2022). 64. Dutch Society for Geriatric Medicine. Multidisciplinary Guideline for Polpharmacy in older people. 2020. https://richtlijnendatabase.nl/richtlijn/polyfarmacie_bij_ouderen/ polyfarmacie_bij_ouderen_2e_lijn.html (accessed May 30, 2022). 65. Royal Dutch Pharmacists Association. KNMP-Richtlijn Medicatiebeoordeling [Dutch guideline on medication review] 2013:22. https://www.knmp.nl/richtlijnen/ medicatiebeoordeling (accessed May 12, 2022). 66. Drenth-van Maanen AC, Leendertse AJ, Jansen PAF, Knol W, Keijsers CJPW, Meulendijk MC, et al. The Systematic Tool to Reduce Inappropriate Prescribing (STRIP): Combining implicit and explicit prescribing tools to improve appropriate prescribing. J Eval Clin Pract 2018;24:317–22. https://doi.org/10.1111/jep.12787. 67. Keijsers CJPW, Van Doorn ABD, Van Kalles A, De Wildt DJ, Brouwers JRBJ, Van De Kamp HJ, et al. Structured pharmaceutical analysis of the systematic tool to reduce inappropriate prescribing is an effective method for final-year medical students to improve polypharmacy skills: A randomized controlled trial. J Am Geriatr Soc 2014;62:1353–9. https://doi.org/10.1111/jgs.12884. 68. Karapinar-Çarkit F, Borgsteede SD, Zoer J, Smit HJ, Egberts ACG, Van Den Bemt PMLA. Effect of medication reconciliation with and without patient counseling on the number of pharmaceutical interventions among patients discharged from the hospital. Ann Pharmacother 2009;43(6):1001–10. https://doi.org/10.1345/aph.1L597. 69. Drenth-Van Maanen AC, Spee J, Van Marum RJ, Egberts TCG. Structured history taking of medication use reveals iatrogenic harm due to discrepancies in medication histories in hospital and pharmacy records. J Am Geriatr Soc 2011;59(10):1976–7. https://doi. org/10.1111/j.1532-5415.2011.03610_11.x. 70. Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med 2003;138:161–7. https://doi.org/10.7326/0003-4819-138-3-200302040-00007. 71. Pippins JR, Gandhi TK, Hamann C, Ndumele CD, Labonville SA, Diedrichsen EK, et al. Classifying and predicting errors of inpatient medication reconciliation. J Gen Intern Med 2008;23:1414–22. https://doi.org/10.1007/s11606-008-0687-9. 72. Van Der Linden CMJ, Kerskes MCH, Bijl AMH, Maas HAAM, Egberts ACG, Jansen PAF. Represcription after adverse drug reaction in the elderly: A descriptive study. Arch Intern Med 2006;166(15):1666–7. https://doi.org/10.1001/archinte.166.15.1666. 73. Schnipper JL, Reyes Nieva H, Mallouk M, Mixon A, Rennke S, Chu E, et al. Effects of a refined evidence-based toolkit and mentored implementation on medication reconciliation at 18 hospitals: Results of the MARQUIS2 study. BMJ Qual Saf 2021:1–9. https://doi.org/10.1136/bmjqs-2020-012709. 74. Ciapponi A, Fernandez Nievas SE, Seijo M, Rodríguez MB, Vietto V, García-Perdomo HA, et al. Reducing medication errors for adults in hospital settings. Cochrane Database Syst Rev 2021;11(11):CD009985. https://doi.org/10.1002/14651858.CD009985.pub2. 75. Schnipper JL. Medication Reconciliation - Too Much or Not Enough? JAMA Netw Open 2021;4(9):e2125272. https://doi.org/10.1001/jamanetworkopen.2021.25272. 76. Dutch Ministry of Health Welfare and Sports [Ministerie van Volksgezondheid Welzijn en Sport]. Richtlijn Overdracht van Medicatiegegevens in de keten 2019:1–11. https://www. zorginzicht.nl/kwaliteitsinstrumenten/medicatieoverdracht (accessed May 30, 2022). 77. Dalton K, O’Brien G, O’Mahony D, Byrne S. Computerised interventions designed to reduce potentially inappropriate prescribing in hospitalised older adults: A systematic review and meta-analysis. Age Ageing 2018;47:670–8. https://doi.org/10.1093/ageing/afy086.

29 General Introduction 78. Meulendijk MC, Spruit MR, Jansen PAF. STRIPA : A Rule-Based Decision Support System for Medication Reviews in Primary Care. ECIS 2015 Res. Pap., 2015. 79. Meulendijk MC, Spruit MR, Drenth-van Maanen AC, Numans ME, Brinkkemper S, Jansen PAF, et al. Computerized Decision Support Improves Medication Review Effectiveness: An Experiment Evaluating the STRIP Assistant’s Usability. Drugs Aging 2015;32:495–503. https://doi.org/10.1007/s40266-015-0270-0. 80. Shen Z, Meulendijk M, Spruit M. A federated information architecture for multinational clinical trials: Stripa revisited. 24th Eur. Conf. Inf. Syst. ECIS 2016, 2016. 81. Christensen M, Lundh A. Medication review in hospitalised patients to reduce morbidity and mortality (Review). Cochrane Database Syst Rev 2016;2(2):CD008986. https://doi. org/10.1002/14651858.CD008986.pub3.www.cochranelibrary.com. 82. Rankin A, Cadogan CA, Patterson SM, Kerse N, Cardwell CR, Bradley MC, et al. Interventions to improve the appropriate use of polypharmacy for older people. Cochrane Database Syst Rev 2018;9(9):CD008165. https://doi.org/10.1002/14651858. CD008165.pub4. 83. Dautzenberg L, Bretagne L, Koek HL, Tsokani S, Zevgiti S, Rodondi N, et al. Medication review interventions to reduce hospital readmissions in older people. J Am Geriatr Soc 2021;69:1646–58. https://doi.org/10.1111/jgs.17041. 84. Beuscart JB, Pont LG, Thevelin S, Boland B, Dalleur O, Rutjes AWS, Westbrook JI SA. A systematic review of the outcomes reported in trials of medication review in older patients : the need for a core outcome set. Br J Clin Pharmacol 2017;83:942–52. https:// doi.org/10.1111/bcp.13197. 85. Beuscart J, Knol W, Cullinan S, Schneider C, Dalleur O, Boland B, et al. International core outcome set for clinical trials of medication review in multi-morbid older patients with polypharmacy. BMC Med 2018;21:1–9. https://doi.org/10.1186/s12916-018-1007-9. 86. Adam L, Moutzouri E, Baumgartner C, Loewe AL, Feller M, M’Rabet-Bensalah K, et al. Rationale and design of OPtimising thERapy to prevent Avoidable hospital admissions in Multimorbid older people (OPERAM): A cluster randomised controlled trial. BMJ Open 2019;9:1–9. https://doi.org/10.1136/bmjopen-2018-026769. 1

Chapter 2

Applicability of tools for medication optimisation in hospitalised older people

2.1

Chapter 2.1 Performance of a trigger tool for detecting adverse drug reactions in patients with polypharmacy acutely admitted to the geriatric ward Nikki MF Noorda*, Bastiaan TGM Sallevelt*, Wivien L Langendijk, Toine CG Egberts, Eugène P van Puijenbroek, Ingeborg Wilting, Wilma Knol (*) denotes shared first co-authorship Eur Geriatr Med. 2022;13: 837–847. Published as open access article (CC-BY 4.0)

34 CHAPTER 2.1 Abstract Introduction Adverse drug reactions (ADRs) account for 10% of acute hospital admissions in older people, often under-recognised by physicians. The Dutch geriatric guideline recommends screening all acutely admitted older patients with polypharmacy with an ADR trigger tool comprising ten triggers and associated drugs frequently causing ADRs. This study investigated the performance of this tool and the recognition by usual care of ADRs detected with the tool. Methods A cross-sectional study was performed in patients ≥70 years with polypharmacy acutely admitted to the geriatric ward of the University Medical Centre Utrecht. Electronic health records (EHRs) were screened for trigger-drug combinations listed in the ADR trigger tool. Two independent appraisers assessed causal probability with the WHO-UMC algorithm and screened EHRs for recognition of ADRs by attending physicians. Performance of the tool was defined as the positive predictive value (PPV) for ADRs with a possible, probable or certain causal relation. Results In total, 941 trigger-drug combinations were present in 73% (n = 253/345) of the patients. The triggers fall, delirium, renal insufficiency and hyponatraemia covered 86% (n = 810/941) of all trigger-drug combinations. The overall PPV was 41.8% (n = 393/941), but the PPV for individual triggers was highly variable ranging from 0–100%. Usual care recognised the majority of ADRs (83.5%), increasing to 97.1% when restricted to possible and certain ADRs. Conclusion The ADR trigger tool has predictive value; however, its implementation is unlikely to improve the detection of unrecognised ADRs in older patients acutely admitted to our geriatric ward. Future research is needed to investigate the tool’s clinical value when applied to older patients acutely admitted to non-geriatric wards.

35 Performance of a trigger tool for detecting adverse drug reactions Introduction Older people are more susceptible to adverse drug reactions (ADRs) due to comorbidity, polypharmacy, frailty and age-related changes in pharmacokinetics and -dynamics [1–3]. It is estimated that ADRs account for approximately 10% of all acute hospital admissions in older people [4,5]. Despite this high frequency of hospital admissions due to ADRs in older people, studies show that drug related problems, including ADRs, are missed or misdiagnosed by physicians at the emergency department in approximately 40–60% of the cases [6–8]. Consequently, methods to improve detection and management of ADRs are needed [9]. Polypharmacy is one of the most important risk factors for developing ADRs [10]. It is known that a few commonly used drug classes account for the majority of ADRs leading to or developed during hospital admission in the older population [1,3–5,9]. A meta-analysis found that ADR-induced hospital admissions were most frequently related to nonsteroidal anti-inflammatory drugs (NSAIDs) causing upper gastrointestinal bleeding, hypertension, coronary events and renal failure. Other ADRs frequently associated with hospitalisations were hypotension due to betablockers, angiotensin-converting enzyme (ACE) inhibitors or calcium antagonists; hypoglycaemia due to oral antidiabetics; bleeding due to oral anticoagulants and bradycardia due to digoxin [4]. The use of a trigger tool focusing on clinical events and drugs frequently associated with such events may therefore reduce the problem of undiagnosed ADRs. Several trigger tools have been developed to increase ADR detection in patient care. The most commonly known trigger tool is the Global Trigger Tool [11,12], but other trigger tools targeting ADR detection, especially in the older population, have been investigated [13–15]. These trigger tools have in common that they comprise lists of either clinical events (e.g. ‘hypotension’), the use of specific drugs or antidotes (e.g. ‘naloxone use’) or abnormal drug or laboratory values (e.g. ‘potassium <2.9 mEq/L’, ‘digoxin level >2 ng/L’). However, the positive predictive values (PPVs) of such triggers were generally low, which impedes their implementation in clinical practice to improve ADR detection in older people [12–15]. Consequently, no ‘gold standard’ to improve ADR detection in older people has yet been established. The performance of trigger tools in detecting clinically relevant ADRs in older people may be improved by combining clinical events with drug classes frequently associated with such events. The Dutch national geriatric guideline on ‘polypharmacy optimisation in hospitalised older people’ provides a consensus-based trigger tool listing combinations of certain clinical events and associated drugs that frequently result in ADR-related hospital admissions in older people [16]. The guideline strongly recommends screening each patient aged 70 years and older with polypharmacy (≥5 2

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