Sage Journals: Discover world-class research

Abstract

Polypharmacy is common among older adults and is associated with adverse outcomes. Polypharmacy increases the likelihood of receiving a potentially inappropriate medication (PIM). PIMs have traditionally been defined as medications that have either no benefit (e.g. therapeutic duplication) or increased risk (e.g. altered pharmacodynamics/kinetics with aging). A growing literature supports the notion that these represent only a subset of the potential risks of medications prescribed to older adults. Different authors have proposed new sets of criteria for evaluating medication appropriateness. This narrative review had two objectives: 1) to summarize the contents of these criteria in order to obtain preliminary information about where clinical consensus exists regarding appropriateness; 2) The second was to describe studies examining the risks and benefits of medications identified by the criteria to determine the strength of the evidence supporting the derivation of these criteria. We identified 13 articles sharing overlapping criteria for evaluating appropriateness including: (1) delayed time to benefit; (2) altered benefit–harm ratios in the face of competing risks; (3) effects that do not match patients’ goals; and (4) nonadherence. The similarities across the articles suggested strong clinical consensus; however, the articles presented little data directly supporting these criteria. Additional studies provide evidence for the proof of concept that average estimates of benefit and harm derived from randomized controlled trials may differ from the benefits and harms experienced by older persons. However, more data are required to characterize the benefits and harms of medications in the context of the regimen as a whole and the individual’s health status.

Keywords

medication appropriateness multimorbidity polypharmacy

Introduction

The use of multiple medications, commonly referred to as polypharmacy, is steadily increasing among older adults. While there is no firm consensus regarding the number of medications defining polypharmacy,¹ a cutoff point of ⩾5 medications is commonly used.² The proportion of community-dwelling adults in the United States (US) aged ⩾65 years taking more than five medications rose from 24% between 1999 and 2000 to 39% between 2011 and 2012.² In a systematic review of observational studies, polypharmacy, defined using different cutoffs, was associated with multiple adverse health outcomes, including falls, fall-related injury, hospitalizations, mortality, impaired function and cognition, and adverse drug reactions.³

Polypharmacy is strongly associated with the prescription of potentially inappropriate medications (PIMs).⁴ There are several well-established and validated strategies for evaluating the medical regimen and identifying PIMs. One is the Medication Appropriateness Index, which requires implicit medication review using a set of criteria looking for medications without benefit because, for example, they represent therapeutic duplication, and medications with drug–drug or drug–disease interactions.⁵ A second is the use of consensus-based lists of medications that should not^6–11 and should¹⁰ be prescribed to older adults, generally because of altered pharmacokinetics or dynamics or drug–drug/drug–disease interactions.

A growing literature suggests that these established methods for identification of PIMs addresses only a subset of the potential risks imposed by polypharmacy. Clinical practice guidelines do not yet exist for the evaluation of medication appropriateness across an entire medication regimen. Nor are there studies examining the clinical outcomes associated with the use of these expanded criteria. One well-established limitation for the development of guidelines is the lack of data regarding medication outcomes in older adults, who are regularly excluded from randomized controlled trials (RCTs) of the medications they are most likely to be prescribed.^12,13 Even with the inclusion of observational studies, several large systematic reviews also reveal the absence of data.^14,15 For a few individual medications or classes of medications, strong evidence of harms outweighing benefits has supported the development of deprescribing guidelines, including proton-pump inhibitors,¹⁶ benzodiazepine receptor agonists,¹⁷ and psychotropic medications for the treatment of the behavioral symptoms of dementia and insomnia.¹⁸ However, for other medications, such as for antihyperglycemic agents, evidence is not strong, and the guideline developed for deprescribing notes highly variable glycemic targets in different diabetes treatment guidelines.¹⁹ Uncertainty resulting from lack of data is also reflected in the description of the development of STOPPFrail criteria, a consensus-based list of PIMs for frail older adults, and for which consensus could not be achieved for all proposed medications.²⁰

Even beyond the challenge of defining the overall benefits and harms of individual medications, is evaluating the potential for medications with demonstrated benefit for certain disease-specific outcomes to nonetheless fail to have benefit or cause harm among selected groups of older adults, particularly those with multimorbidity or frailty and disability. Several investigators have separately proposed criteria for an expanded assessment of medication appropriateness based on this concept. The purpose of this review was to compare these criteria, an effort that can serve as the beginning of a derivation of expert consensus around these criteria. This review also sought to summarize the studies regarding the benefits and harms of medications that would be identified by these criteria, in order to evaluate the strength of the current evidence underlying these criteria and to identify where additional evidence is most needed.

Methods

The authors began with the articles known to them that presented sets of criteria for the evaluation of medication appropriateness among older adults based on the expert opinion of the author(s). A review of the MeSH headings of these articles revealed a lack of common indexing terms, precluding the conduct of a systematic review. Instead, we used a search strategy consisting of a text search of keywords, title, and abstract in Ovid MEDLINE for the following terms: ‘polypharmacy’ and ‘drug-related side effects and adverse reactions’ and ‘inappropriate prescribing’ (66 results) or ‘deprescri* and polypharmacy’ (153 results). The abstracts of the search results were reviewed to identify additional articles presenting sets of criteria, and then the references for these articles were examined for further relevant articles. We included only articles that were written specifically to provide a description of processes for conducting an appropriateness review. We did not include articles addressing medication appropriateness at the end of life or among individuals with a specific condition, such as cancer, or providing general principles regarding appropriateness rather than a set of specific review criteria. A total of 13 articles were identified. In a second round of review, we examined the citations provided by these articles as empirical evidence supporting the criteria. We supplemented these citations with additional studies presenting supporting evidence.

Results

The criteria across the 13 articles are presented in Table 1.^21–33 Virtually all articles include PIMs as traditionally defined and described above. Because the methods for identifying these PIMs are well established, they are not further discussed. We present four additional criteria expanding the dimensions of medications that may be inappropriate for the older patient.

Table 1.

Criteria for the evaluation of medication appropriateness included in the frameworks.^a

Author	PIMs	Time to benefit	Harm versus benefit	Goals of care	Adherence
Barnett and colleagues²¹		X	X	X	X
Drenth-van Maanen and colleagues²²		X
Frank and Weir²³		X		X	X
Garfinkel and colleagues²⁴		X	X	X
Haque²⁵			X
Hilmer and colleagues²⁶	X	X		X
Holmes and colleagues²⁷		X		X
Jetha²⁸		X	X	X
Lee and colleagues²⁹
Scott and colleagues³⁰		X	X
Scott and colleagues³¹		X	X	X
Steinman and colleagues³²		X
Woodward³³

The shaded boxes indicate primary literature provided to support the criterion.

PIM, potentially inappropriate medication.

Medications with a delayed time to benefit

A total of nine articles present the criterion of evaluating the time to benefit (TTB). A PIM is defined as one providing benefit in a timeframe exceeding the patient’s life expectancy. Only two provide citations to support examples of such medications. Scott and colleagues cite a review article of bisphosphonate therapy concluding that fracture risk reduction requires more than 12 months of therapy;³⁴ however, the review does not provide primary literature reporting the TTB. This article also cites a review article to support the assertion that the TTB for statins is 12 months.³⁵ Within this review article is a meta-analysis presenting the TTB for different outcomes ranging from 3 months to 2–3 years.³⁶ Steinman and colleagues cite the American Geriatrics Society (AGS) Diabetes Guidelines, which state that the TTB for glucose control is approximately 8 years to reduce the risk of microvascular complications and 2–3 years for blood pressure control to reduce the risk of macrovascular changes. It is challenging to verify these statements in the articles cited by the guideline.³⁷

Medications whose likelihood of harm outweighs the benefit because of competing risks

In eight articles, there is a description of the criterion of the likelihood of harm outweighing the likelihood of benefit. Most of these articles include a discussion suggesting that patient-specific factors can alter the likelihood of benefit and harm, including frailty/disability, quality of life (QOL), chronic conditions, and age. While each of the articles recommends assessing some combination of these factors and considering the medications in their context, only three provide specific examples of inappropriate medications based on citations of the literature for hypertension (HTN) and diabetes mellitus (DM).

Scott and colleagues discuss the potentially inappropriate treatment of HTN based on the evidence for an increased risk of mortality among older persons for whom systolic blood pressure control is achieved only with low diastolic readings. This article cites an observational prospective cohort study of persons with a mean age of 72 years, 75% of whom were being treated for HTN, in which lower diastolic blood pressures were associated with a higher mortality risk.³⁸ Included in that cohort study is a reference to a review summarizing the findings of multiple observational studies of cohorts of people aged ⩾85 years, demonstrating an association between higher systolic or diastolic blood pressure and lower mortality.³⁹ This review also presented a subgroup meta-analysis of RCTs of antihypertensive treatment including patients aged ⩾80 years and older, demonstrating that, while treatment was associated with reductions in stroke and heart failure, it was also associated with an increased mortality risk.⁴⁰

Scott and colleagues and Steinman and colleagues discuss the potentially inappropriate treatment of DM. Scott and colleagues cite a decision analysis demonstrating that the benefits of intensive control decline as multimorbidity increases and function decreases.⁴¹ Steinman and colleagues cite an observational cohort study demonstrating that patients with DM and high comorbidity did not achieve a reduction in cardiovascular risk with more intensive glucose control.⁴² Steinman and colleagues also cite the 2003 AGS Diabetes Guidelines, which states ‘the risks of intensive control…may significantly alter the risk–benefit equation’ without providing supporting citations.³⁷ The AGS subsequently published updated guidelines citing the American Diabetes Association (ADA) 2013 guideline recommending ‘a less stringent target such as 8.0%’ for ‘persons with limited life expectancy or extensive comorbid conditions, and others in whom the risks of intensive glycemic control appear to outweigh the potential benefits.’⁴³ The ADA guidelines cite expert consensus or clinical experience as the source for this recommendation. Updated ADA 2017 guidelines upgrade the source of evidence to well-conducted observational studies, but do not provide specific citations.⁴⁴

There is additional evidence regarding altered benefits and harms of treatment in HTN, DM, and end-stage renal disease (ESRD) among older persons. An observational study of a nationally representative sample of community-living Medicare beneficiaries aged >70 years with HTN found that individuals who received moderate or high-intensity antihypertensive therapy had an increased risk of serious fall injury compared with antihypertensive nonusers.⁴⁵ In a second observational cohort study examining a nationally representative cohort aged ⩾65 years, the association between HTN and mortality varied by gait speed. HTN was not associated with a higher mortality risk among those with a slow gait speed, and a higher systolic blood pressure was associated with a lower risk of death among participants who did not complete the walk test, suggesting that these patients might not derive a mortality benefit from treatment.⁴⁶

A cohort study utilizing a large claims database of individuals enrolled in private and Medicare Advantage plans demonstrated that, among patients receiving intensive treatment, those with high clinical complexity, defined as aged >75 years, dementia or ESRD, or more than three chronic conditions, had nearly double the risk of severe hypoglycemia as compared with patients with low complexity.⁴⁷ In a cohort study of nursing home residents with DM, there was no difference in the likelihood of functional decline or death over 24 months across the strata of baseline HbA1c.⁴⁸ Among patients with ESRD, in one RCT of patients undergoing hemodialysis and a second RCT of patients with DM undergoing hemodialysis, statins did not decrease the risk of a composite endpoint of cardiovascular death, nonfatal stroke, and nonfatal myocardial infarction.^49,50

Medications inconsistent with patient’s goals of care

A total of nine articles present the criterion of a mismatch between the medication and the patient’s treatment goals. Among these nine, three refer to patients’ goals or preferences without further elaboration, and one discusses goals in terms of cure versus palliation. The other five refer to goals in terms of health outcomes including prolonging life, maximizing function and QOL, reducing symptoms, avoiding medication adverse effects, and avoiding disease progression, and one also included minimizing the pill burden and reducing medication costs. The evaluation of medications in the context of patients’ goals is closely related to the evaluation of benefits and harms. The articles recognize that the process of weighing the likelihood of benefit versus harm requires an assessment of how the patient or family values these outcomes. For example, medications prescribed with the objective of reducing the likelihood of disease-specific outcomes, such as myocardial infarction or stroke, or of mortality, may also have adverse effects on patients’ function or QOL, and the patient may more highly value the latter than the former.⁵¹

Although the articles did not include references providing data on potentially competing outcomes, the authors identified several relevant studies. A narrative review summarized 19 observational and intervention design studies which assessed the relationship between specific medications and functional decline. The review concluded that the use of certain individual medications, specifically benzodiazepines and medications with a higher load of anticholinergic effects, are associated with functional decline.⁵² In an observational cohort study of community-living men aged 65 years and older, those who began statin therapy had a steeper rate of decline in physical activity compared with nonusers and chronic users.⁵³

Nonadherence to medications

While eight articles state that patients’ adherence to their medications should be assessed, only three assert that poor adherence is a criterion for PIMs. These three recommend that medications with poor adherence be evaluated according to the criteria stated elsewhere in the articles, implying that a medication with poor adherence is one with a limited TTB, risk outweighing benefit, or failing to meet patients’ goals.

Discussion

The similarities in criteria for evaluation of appropriateness across the articles summarized in this review provide evidence for a strong consensus of expert opinion. Further supporting this consensus are the recommendations provided by several practice guidelines. However, evaluation of the evidence base underlying these recommendations reveals the limited data available to inform the question of how aging alters the benefits and harms of medications beyond the consideration of drug–drug and drug–disease interactions. Even when moving beyond the literature cited by the articles, it is challenging to find evidence regarding how the benefits and harms of medications may be affected by aging and its effects on health status, such as multimorbidity, frailty, and limitations in life expectancy.

Time to benefit

The inclusion of TTB in so many of the criteria attests to the strong clinical belief that many medications prescribed for primary or secondary prevention may not benefit patients with limited life expectancy. However, a recent review points out that the methodology for calculating the TTB is in its infancy.⁵⁴ Most RCTs only report cumulative outcomes at the end of the study period, so that the time to a given event is unknown. Even if time to events are measured and reported in a Kaplan–Meier curve, a visual inspection of the separation in curves cannot determine the statistical significance of any differences seen. In addition, the TTB depends upon the sample size of the study, the effect size being examined, and the study outcome (e.g. a single versus composite endpoint). One recent innovation to address the methodological issues with calculating the TTB has been the application of the statistical process control method, a statistical method used in healthcare improvement research to identify significant variations in clinical outcomes.⁵⁵ However, in addition to these methodological considerations, the TTB, as determined by RCTs, suffers from being a population-level outcome. This has the same limitation as other findings from RCTs when applied to older persons with multiple conditions, since such patients are rarely included in the trials and may have outcomes substantially different from study participants.⁵⁶ The ideal TTB would be calculated on an individual level, using patient-specific factors that could modify the TTB.

Competing risks and patients’ goals

The limited existing studies summarized in this review provide proof of concept that the average estimates of benefit and harm derived from standard RCTs may be very different from the benefits and harms that individual older persons, with different combinations of impairments, conditions, and other risk factors, will obtain from a given medication or combination of medications.⁵⁷ They also demonstrate that medications which improve one outcome may worsen another. While the evidence base is small, and, particularly in the case of diabetes treatment, does not seem to provide direct support for guidelines, it provides strong justification for additional investigation. Observational studies with adequate control of confounding variables can yield data regarding the benefits and harms of medications as prescribed in diverse patient cohorts according to different sets of risk factors. Such studies can generate the information necessary to calculate patient-specific outcomes and the TTB rather than the population average results resulting from RCTs that frequently exclude patients at a highest risk for adverse events or the lowest likelihood of benefit. This limitation in RCTs can be addressed by enrolling more diverse samples combined with multivariable risk-stratified analysis to identify patient subgroups at a higher or lower likelihood of a given outcome.⁵⁸

Consideration of global benefit versus harm

While the articles included in this review expand the criteria to assess the appropriateness of medications, these criteria are all based on a process of evaluating the benefits and harms of individual medications. This approach does not address the most challenging issue related to polypharmacy; namely, evaluating the appropriateness of a medication regimen considered as a whole. In a landmark study, Boyd and colleagues demonstrated the potential harms associated with the application of guideline-directed medication management to an older patient with multiple chronic conditions.⁵⁹ In addition to the many drug–drug and drug–disease interactions, the resulting regimen is highly complex and potentially burdensome. In order to address this issue of potentially inappropriate regimens, a comprehensive framework for medication appropriateness will need to include two additional domains: (1) medication regimens that are not feasible for the patient to manage; and (2) medication regimens in which overall harm outweighs the overall benefit.

As acknowledged by the articles in this review, the regimen needs to be evaluated in the context of the patient’s ability to adhere. Medication nonadherence is common, and impaired cognitive function is a risk factor for nonadherence.⁶⁰ Even among patients without cognitive impairments, there have been few effective interventions to improve adherence.^61,62 Older patients with multiple medical conditions may have indications for more medications than they can feasibly manage given their cognition and available social support. The reviewed articles stipulate that, when nonadherence is detected, medications that meet additional criteria for inappropriateness be discontinued. However, this may not be sufficient. It is possible that, to achieve feasibility, even medications that would otherwise not be considered inappropriate will need to be discontinued. While this principle is likely to be controversial, it achieved consensus support in a Delphi panel examining recommendations for deprescribing.¹

Perhaps the most important unresolved question regarding polypharmacy is whether the overall medication load confers a risk beyond each medication considered individually. There is not yet an established methodology available to calculate the overall benefits and harms of a given regimen. One approach that begins to address this issue is the use of a utility function to combine the probabilities of benefits and harms across individual medications.⁶³ While this method provides a prototype for evaluating the medication regimen as a whole, it is limited by the absence of data on the marginal benefits and harms of medications when they are part of a large regimen and potentially interacting with many different other medications and conditions.⁶⁴

Growing the evidence base for deprescribing

It may seem hopelessly complex to try to tease out the ‘signal’ from the ‘noise’ of the many possible combinations of conditions, medications, and risk factors that may interact with one another. One approach that may be well suited to this challenge is machine learning, with its ability to look at a large number of predictors and combined them in highly interactive ways.⁶⁵ For example, a machine-learning model has been built that identifies treatment response to a specific medication in the treatment of depression.⁶⁶ There are also several large trials underway that are developing new algorithms for identifying PIMs and evaluating the effects of deprescribing on clinically meaningful outcomes.^67,68 Ultimately, addressing the question of whether fewer medications are better than more will require RCTs of deprescribing, targeting not only medications with known adverse effects but medications that may have adverse effects as the sixth or seventh medication for a patient whose comorbidities or frailty may increase vulnerability to harms.

Conclusion

There is strong expert consensus that the approach to evaluating appropriateness of medications among older persons needs to incorporate considerations of the TTB for medications prescribed for primary or secondary prevention, the potential for an altered benefit–harm ratio, and a patient’s most highly valued outcomes. However, data to inform these considerations are lacking. In addition, even medications that are appropriate when considered individually may be part of regimens that are inappropriate because their complexity makes them unfeasible or changes marginal benefits and harms. Deprescribing trials that include a broad range of outcomes will be critical to obtaining the data necessary to optimize medication management in older persons.

Footnotes

Acknowledgements

This material is the result of work supported with resources and the use of facilities at the VA Connecticut Healthcare System. The contents do not represent the views of the US Department of Veterans Affairs or the US Government.

Funding

This work was supported by the Donaghue Foundation Program for Research Leadership (DF11-303); the Claude D. Pepper Older Americans Independence Center at Yale University School of Medicine (P30AG2134); and the Health Resources and Services Administration Geriatric Workforce Enhancement Program (U1QHP28745).

Conflict of interest statement

The authors declare that there is no conflict of interest.

References

Fried

Niehoff

Tjia

et al . A Delphi process to address medication appropriateness for older persons with multiple chronic conditions. BMC Geriatr 2016; 16: 67.

Kantor

Rehm

Haas

et al . Trends in prescription drug use among adults in the united states from 1999–2012. JAMA 2015; 314: 1818–1830.

Fried

O’Leary

Towle

et al . Health outcomes associated with polypharmacy in community-dwelling older adults: a systematic review. J Am Geriatr Soc 2014; 62: 2261–2272.

Steinman

Landefeld

Rosenthal

et al . Polypharmacy and prescribing quality in older people. J Am Geriatr Soc 2006; 54: 1516–1523.

Hanlon

Schmader

Samsa

et al . A method for assessing drug therapy appropriateness. J Clin Epidemiol 1992; 45: 1045–1051.

Laroche

Charmes

Merle

Potentially inappropriate medications in the elderly: a French consensus panel list. Eur J Clin Pharmacol 2007; 63: 725–731.

McLeod

Huang

Tamblyn

et al . Defining inappropriate practices in prescribing for elderly people: a national consensus panel. CMAJ 1997; 156: 385–391.

Holt

Schmiedl

Thurmann

PA.

Potentially inappropriate medications in the elderly: the PRISCUS list. Dtsch Arztebl Int 2010; 107: 543–551.

By the American Geriatrics Society 2015 Beers Criteria Update Expert Panel. American Geriatrics Society 2015 Updated Beers Criteria for Potentially Inappropriate Medication Use in Older Adults. J Am Geriatr Soc 2015; 63: 2227–2246.

10.

O’Mahony

O’Sullivan

Byrne

et al . STOPP/START criteria for potentially inappropriate prescribing in older people: version 2. Age Ageing 2015; 44: 213–218.

11.

Chang

C-B

Chen

J-H

Wen

C-J

et al . Potentially inappropriate medications in geriatric outpatients with polypharmacy: application of six sets of published explicit criteria. Br J Clin Pharmacol 2011; 72: 482–489.

12.

Konrat

Boutron

Trinquart

et al . Underrepresentation of elderly people in randomised controlled trials. The example of trials of 4 widely prescribed drugs. PLoS One 2012; 7: e33559.

13.

Cherubini

Oristrell

Pla

et al . The persistent exclusion of older patients from ongoing clinical trials regarding heart failure. Arch Intern Med 2011; 171: 550–556.

14.

Schott

Martinez

Ediriweera de Silva

et al . Effectiveness and safety of dipeptidyl peptidase 4 inhibitors in the management of type 2 diabetes in older adults: a systematic review and development of recommendations to reduce inappropriate prescribing. BMC Geriatr 2017; 17: 226.

15.

Meinshausen

Rieckert

Renom-Guiteras

et al . Effectiveness and patient safety of platelet aggregation inhibitors in the prevention of cardiovascular disease and ischemic stroke in older adults–a systematic review. BMC Geriatr 2017; 17: 225.

16.

Farrell

Pottie

Thompson

et al . Deprescribing proton pump inhibitors: evidence-based clinical practice guideline. Can Fam Physician 2017; 63: 354–364.

17.

Pottie

Thompson

Davies

et al . Deprescribing benzodiazepine receptor agonists: Evidence-based clinical practice guideline. Can Fam Physician 2018; 64: 339–351.

18.

Bjerre

Farrell

Hogel

et al . Deprescribing antipsychotics for behavioural and psychological symptoms of dementia and insomnia: evidence-based clinical practice guideline. Can Fam Physician 2018; 64: 17–27.

19.

Farrell

Black

Thompson

et al . Deprescribing antihyperglycemic agents in older persons: Evidence-based clinical practice guideline. Can Fam Physician 2017; 63: 832–843.

20.

Lavan

Gallagher

Parsons

et al . STOPPFrail (Screening Tool of Older Persons Prescriptions in Frail adults with limited life expectancy): consensus validation. Age Ageing 2017; 46: 600–607.

21.

Barnett

Oboh

Smith

Patient-centred management of polypharmacy: a process for practice. Eur J Hosp Pharm 2015; 23: 113–117.

22.

Drenth-van Maanen

van Marum

Knol

et al . Prescribing optimization method for improving prescribing in elderly patients receiving polypharmacy: results of application to case histories by general practitioners. Drugs Aging 2009; 26: 687–701.

23.

Frank

Weir

Deprescribing for older patients. CMAJ 2014; 186: 1369–1376.

24.

Garfinkel

Zur-Gil

Ben-Israel

The war against polypharmacy: a new cost-effective geriatric-palliative approach for improving drug therapy in disabled elderly people. Isr Med Assoc J 2007; 9: 430–434.

25.

Haque

. ARMOR: a tool to evaluate polypharmacy in elderly persons. Ann Longterm Care 2009: 26–30.

26.

Hilmer

Gnjidic

Le Couteur

DG.

Thinking through the medication list - appropriate prescribing and deprescribing in robust and frail older patients. Aust Fam Physician 2012; 41: 924–928.

27.

Holmes

Hayley

Alexander

et al . Reconsidering medication appropriateness for patients late in life. Arch Intern Med 2006; 166: 605–609.

28.

Jetha

Polypharmacy, the elderly, and deprescribing. Consult Pharm 2015; 30: 527–532.

29.

Lee

Schwemm

Reist

et al . Pharmacists’ and pharmacy students’ ability to identify drug-related problems using TIMER (Tool to Improve Medications in the Elderly via Review). Am J Pharm Educ 2009; 73: 52.

30.

Scott

Gray

Martin

et al . Minimizing inappropriate medications in older populations: a 10-step conceptual framework. Am J Med 2012; 125: 529–537.

31.

Scott

Hilmer

Reeve

et al . Reducing inappropriate polypharmacy: the process of deprescribing. JAMA Intern Med 2015; 175: 827–834.

32.

Steinman

Hanlon

JT.

Managing medications in clinically complex elders: “There’s got to be a happy medium”. JAMA 2010; 304: 1592–1601.

33.

Woodward

MC.

Deprescribing: achieving better health outcomes for older people through reducing medications. J Pharm Pract 2003; 33: 323–328.

34.

Schmidt

Horner

McDanel

et al . Risks and benefits of long-term bisphosphonate therapy. Am J Health Syst Pharm 2010; 67: 994–1001.

35.

Berthold

Gouni-Berthold

Lipid-lowering drug therapy in elderly patients. Curr Pharm Des 2011; 17: 877–893.

36.

Roberts

Guallar

Rodriguez

Efficacy and safety of statin monotherapy in older adults: a meta-analysis. J Gerontol A Biol Sci Med Sci 2007; 62: 879–887.

37.

Brown

Mangione

Saliba

et al . Guidelines for improving the care of the older person with diabetes mellitus. J Am Geriatr Soc 2003; 51: S265–S280.

38.

Ungar

Pepe

Lambertucci

et al . Low diastolic ambulatory blood pressure is associated with greater all-cause mortality in older patients with hypertension. J Am Geriatr Soc 2009; 57: 291–296.

39.

Goodwin

JS.

Embracing complexity: a consideration of hypertension in the very old. The J Gerontol A Biol Sci Med Sci 2003; 58: M653–M658.

40.

Gueyffier

Bulpitt

Boissel

J-P

et al . Antihypertensive drugs in very old people: a subgroup meta-analysis of randomised controlled trials. Lancet 1999; 353: 793–796.

41.

Huang

Zhang

Gandra

et al . The effect of comorbid illness and functional status on the expected benefits of intensive glucose control in older patients with type 2 diabetes: a decision analysis. Ann Intern Med 2008; 149: 11–19.

42.

Greenfield

Billimek

Pellegrini

et al . Comorbidity affects the relationship between glycemic control and cardiovascular outcomes in diabetes: a cohort study. Ann Intern Med 2009; 151: 854–860.

43.

American Diabetes Association. Standards of medical care in diabetes—2013. Diabetes Care 2013; 36(Suppl. 1): S11–S66.

44.

American Diabetes Association. Glycemic targets. Sec. 6. diabetes – 2017. Diabetes Care 2017; 40(Suppl. 1): S48–S56.

45.

Tinetti

Han

Lee

et al . Antihypertensive medications and serious fall injuries in a nationally representative sample of older adults. JAMA Intern Med 2014; 174: 588–595.

46.

Odden

Peralta

Haan

et al . Rethinking the association of high blood pressure with mortality in elderly adults: the impact of frailty. Arch Intern Med 2012; 172: 1162–1168.

47.

McCoy

Lipska

Yao

et al . Intensive treatment and severe hypoglycemia among adults with type 2 diabetes. JAMA Intern Med 2016; 176: 969–978.

48.

Hsu

Gan

Cenzer-Stijacic

et al . Glycemic control and functional decline in nursing home residents with diabetes. JAMA Intern Med 2017; 177: 130–132.

49.

Fellström

Jardine

Schmieder

et al . Rosuvastatin and cardiovascular events in patients undergoing hemodialysis. N Engl J Med 2009; 360: 1395–1407.

50.

Wanner

Krane

Marz

et al . Atorvastatin in patients with type 2 diabetes mellitus undergoing hemodialysis. N Engl J Med 2005; 353: 238–248.

51.

Fried

Tinetti

Iannone

et al . Health outcome prioritization as a tool for decision making among older persons with multiple chronic conditions. Arch Intern Med 2011; 171: 1854–1856.

52.

Peron

Gray

Hanlon

JT.

Medication use and functional status decline in older adults: a narrative review. Am J Geriatr Pharmacother 2011; 9: 378–391.

53.

Lee

Markwardt

Goeres

et al . Statins and physical activity in older men: the osteoporotic fractures in men study. JAMA Intern Med 2014; 174: 1263–1270.

54.

Holmes

Min

Yee

et al . Rationalizing prescribing for older patients with multimorbidity: considering time to benefit. Drugs Aging 2013; 30: 655–666.

55.

van de Glind

Willems

Eslami

et al . Estimating the time to benefit for preventive drugs with the statistical process control method: an example with alendronate. Drugs Aging 2016; 33: 347–353.

56.

Tinetti

Fried

Boyd

CM.

Designing health care for the most common chronic condition–multimorbidity. JAMA 2012; 307: 2493–2494.

57.

Fraenkel

Fried

TR.

Individualized medical decision making: necessary, achievable, but not yet attainable. Arch Intern Med 2010; 170: 566–569.

58.

Hayward

Kent

Vijan

et al . Multivariable risk prediction can greatly enhance the statistical power of clinical trial subgroup analysis. BMC Med Res Methodol 2006; 6: 18.

59.

Boyd

Darer

Boult

et al . Clinical practice guidelines and quality of care for older patients with multiple comorbid diseases: implications for pay for performance. JAMA 2005; 294: 716–724.

60.

Salas

In’t Veld

van der Linden

et al . Impaired cognitive function and compliance with antihypertensive drugs in elderly: the Rotterdam Study. Clin Pharmacol Ther 2001; 70: 561–566.

61.

Kripalani

Yao

Haynes

RB.

Interventions to enhance medication adherence in chronic medical conditions: a systematic review. Arch Intern Med 2007; 167: 540–550.

62.

Nieuwlaat

Wilczynski

Navarro

et al . Interventions for enhancing medication adherence. Cochrane Database Syst Rev 2014;: CD000011.

63.

Murphy

Agostini

Van Ness

et al . Assessing multiple medication use with probabilities of benefits and harms. J Aging Health 2008; 20: 694–709.

64.

Tinetti

Bogardus

Jr. Agostini

JV.

Potential pitfalls of disease-specific guidelines for patients with multiple conditions. N Engl J Med 2004; 351: 2870–2874.

65.

Obermeyer

Emanuel

EJ.

Predicting the future — big data, machine learning, and clinical medicine. N Engl J Med 2016; 375: 1216–1219.

66.

Chekroud

Zotti

Shehzad

et al . Cross-trial prediction of treatment outcome in depression: a machine learning approach. Lancet Psychiatr 2016; 3: 243–250.

67.

Soiza

Subbarayan

Antonio

et al . The SENATOR project: developing and trialling a novel software engine to optimize medications and nonpharmacological therapy in older people with multimorbidity and polypharmacy. Ther Adv Drug Saf 2017; 8: 81–85.

68.

PRIMA-EDS. Polypharmacy in chronic diseases: reduction of inappropriate medication and adverse drug events in elderly populations by electronic decision support, https://www.prima-eds.eu/ (2018, accessed 10 October 2018).

Medication appropriateness criteria for older adults: a narrative review of criteria and supporting studies

Abstract

Keywords

Introduction

Methods

Results

Medications with a delayed time to benefit

Medications whose likelihood of harm outweighs the benefit because of competing risks

Medications inconsistent with patient’s goals of care

Nonadherence to medications

Discussion

Time to benefit

Competing risks and patients’ goals

Consideration of global benefit versus harm

Growing the evidence base for deprescribing

Conclusion

Footnotes

Acknowledgements

Funding

Conflict of interest statement

References