www.thelancet.com Vol 370 July 14, 2007 173
Prescribing in Elderly People 1
Appropriate prescribing in elderly people: how well can it be
measured and optimised?
Anne Spinewine, Kenneth E Schmader, Nick Barber, Carmel Hughes, Kate L Lapane, Christian Swine, Joseph T Hanlon
Prescription of medicines is a fundamental component of the care of elderly people, and optimisation of drug prescribing
for this group of patients has become an important public-health issue worldwide. Several characteristics of ageing and
geriatric medicine aff ect medication prescribing for elderly people and render the selection of appropriate pharmacotherapy
a challenging and complex process. In the fi rst paper in this series we aim to defi ne and categorise appropriate prescribing
in elderly people, critically review the instruments that are available to measure it and discuss their predictive validity,
critically review recent randomised controlled intervention studies that assessed the eff ect of optimisation strategies on
the appropriateness of prescribing in elderly people, and suggest directions for future research and practice.
Prescription of medicines is a fundamental component of
the care of elderly people. Several characteristics of ageing
and geriatric medicine aff ect medication prescribing for
these people and render the selection of appropriate
pharmacotherapy a challenging and complex process.
Interindividual variability in health, disease, and disability
increases substantially with ageing, which is a
gerontological principle known as aged heterogeneity.2
This heterogeneity means that the health status of elderly
people ranges widely from those who are fi t to those who
are frail, which makes generalisation of prescribing
decisions diffi cult for clinicians.
Although there are increasing numbers of fi t, healthy
elderly people, there are also increasing numbers of those
who are vulnerable and frail and have limited physiological
reserve, reduced homoeostasis, dysregulations in immune
and infl ammation mechanisms, several comorbidities,
and take many drugs.3,4 These individuals claim a dispro-
por tionate share of medical care and medication use and
make prescribing decisions complex. Some syndromes
related to age, especially cognitive impairment, aff ect the
ability of elderly people to engage with health services. For
example, elderly people with dementia have increased dif-
fi culty with taking drugs, and dementia impedes their
ability to make autonomous decisions about their medi-
cines. Finally, frail elderly people have age-related impair-
ments in the hepatic metabolism and renal clearance of
medications, and enhanced pharma codynamic sensitivity
to specifi c drugs.5
Evidence suggests that the use of drugs in elderly people
is often inappropriate partly because of the complexities of
prescribing as well as other patient, provider, and
health-system factors. Inappropriate prescribing can cause
substantial morbidity, and represents a clinical and
economic burden to patients and society.6–8 Inappropriate
prescribing in elderly people has therefore become an
important public-health issue worldwide.
In this review we aim to defi ne and categorise appropriate
prescribing in elderly people, critically review the instru-
ments that are available to measure it and discuss their
predictive validity, critically review recent randomised
controlled intervention studies that assessed the eff ect of
optimisation strategies on the appropriateness of pres-
cribing in elderly patients, and suggest directions for future
research and practice.
Lancet 2007; 370: 173–84
This is the fi rst in a Series of two
papers about prescribing in
Center for Clinical Pharmacy,
School of Pharmacy, Université
catholique de Louvain,
(A Spinewine PhD); Aging
Center and Department of
Medicine (Geriatrics), School of
Medicine, Duke University
Medical Center, Durham, NC,
USA (K E Schmader MD);
Geriatric Research Education
and Clinical Center, Veterans
Aff airs Medical Center,
Durham, NC, USA
(K E Schmader MD);
Department of Practice and
Policy, School of Pharmacy,
University of London, London,
UK (N Barber PhD); School of
Pharmacy, Queen’s University,
Belfast, UK (C Hughes PhD);
Department of Community
Health, Brown Medical School,
Providence, RI, USA
(K L Lapane PhD); Department
of Geriatric Medicine,
Hospital, Université catholique
de Louvain, Brussels, Belgium
(C Swine MD); Institute on
Aging, and Department of
Medicine (Geriatrics), School of
Medicine and Department of
Pharmacy and Therapeutics,
School of Pharmacy, University
of Pittsburgh, Pittsburgh, PA,
USA (J T Hanlon Pharm D); and
Center for Health Equity
Research and Geriatric Research
Education and Clinical Center,
Veterans Aff airs Pittsburgh
Healthcare System, Pittsburgh,
PA, USA (J T Hanlon)
Anne Spinewine, Centre for
Clinical Pharmacy, Université
catholique de Louvain,
UCL 73.70, Avenue E. Mounier,
73, 1200 Bruxelles, Belgium
Search strategy and selection criteria
We searched Medline (1970–2006), International
Pharmaceutical Abstracts (1970–2006), and the Cochrane
Database. We used the following keywords to identify papers
on measuring appropriate prescribing in elderly people: “aged”,
“frail elderly”, “drug therapy”, “drug utilisation”, “drug
utilisation review”, “elderly”, “measure”, “medication errors”,
“prescription drugs”, “polypharmacy”, “quality indicator”, and
“quality of health care”. Additional publications were identifi ed
by a manual search of references of relevant papers. After
identifi cation of papers on measuring appropriate prescribing
in older people, we reviewed those that examined the
predictive validity of the measures on the basis of the
Donabedian Model that defi nes quality in terms of structure,
processes, and outcomes of health care.1 All studies included
were published in the past decade, measured one or more
appropriate prescribing process measures, measured one or
more patient health outcomes (eg, adverse drug reactions,
death, etc), and involved older people (65 years and older). To
identify articles on interventions to improve prescribing, we
used a combination of the following search terms:
“suboptimal”, “appropriateness”, “underuse”, “misuse”,
“medication”, “drug therapy”, “aged”, “frail elderly”, “trial”,
“randomised controlled trial”, and “intervention”. We also did a
manual search of the reference lists from identifi ed articles and
the author’s article fi les, book chapters, and recent reviews to
identify additional articles. All articles used a randomised
controlled study design, were published in the past decade,
measured change in one or more inappropriate prescribing
practices with either explicit criteria or implicit measures of
inappropriate prescribing in both intervention and control
groups, and involved only older adults (65 years and older).
www.thelancet.com Vol 370 July 14, 2007
Defi nition and categories of appropriate
What is appropriate prescribing and how is it diff erent
for elderly people? Appropriate prescribing is a general
phrase encompassing and compressing a range of values
and behaviours to express in a simple term the quality of
prescribing. Many other words are used to describe
prescribing quality, such as good, poor, appropriate or
inappropriate, optimal or suboptimal, and error.
Additionally, some terms are specifi c to some types of
inappropriateness—eg, underprescribing refers to failure
to prescribe drugs that are needed, overprescribing refers
to prescribing more drugs than are clinically needed, and
misprescribing refers to incorrectly prescribing a drug
that is needed.7,8 We have chosen “appropriate” as a term
that implies the quality is what it should be achieved in
practice, rather than very high (extremely good), or low
(poor or erroneous).
Three of the most important sets of values in judging
appropriateness are what the patient wants; scientifi c,
technical rationalism (including the clinical pharmacology
of the drug); and the general good.9,10 The last value is a
mixture of issues, including societal and family-related
consequences of prescribing. A judgment of appro-
priateness will therefore depend on consideration of the
facts and circumstances in all three domains. Any
measure of appropriateness will inevitably reduce this
complexity; however, much of the published work has
condensed the notion of appropriateness to simply
pharmacological appropriateness–ie, whether a drug was
seen as safe and eff ective, or sometimes cost-eff ective.11
Most performance indicators provide a measurable lower
limit of pharmacological appropriateness, rather than a
continuous scale of prescribing quality.
Appropriate prescribing in elderly people has its own
additional problems, but does not fundamentally change
the domains of decisionmaking. Several factors that are
specifi c to frail elderly people increase the complexity of
prescribing. Furthermore, clinical evidence for the eff ects
of drugs in elderly people is scarce, goals of treatment
might change, and social and economic factors might be
diff erent or more important for these patients than for a
Measures of appropriateness of prescribing
Appropriateness of prescribing can be assessed by
process or outcome measures that are explicit
(criterion-based) or implicit (judgment-based).12 Process
measures assess whether the prescription accords with
accepted standards—they are direct measures of
performance.13,14 However, they might be costly to apply,
and might not have face validity for patients.14 Also, to be
valid, process measures should have causal links to
important outcomes.15 Outcome measures are indicators
of adverse outcomes (eg, adverse drug events and
hospital admissions) that are secondary to inappropriate
Explicit indicators are usually developed from published
reviews, expert opinions, and consensus techniques.
Expert opinion is usually needed in geriatric medicine
because evidence-based aspects of treatments are
frequently absent.16 These measures are usually
drug-orientated or disease-oriented, and can be applied
with little or no clinical judgment. However, explicit
criteria might not take into account all factors that defi ne
high quality health care for the individual.17 They generally
do not address the burden of comorbid disease18,19 and
patients’ preferences. Additionally, consensus approaches
have little evidence of validity and reliability.16 Explicit
measures with little clinical detail can be applied on large
prescribing databases, but with measures that have
increasing amounts of clinical details, valid data from
computerised databases are diffi cult to obtain. In implicit
approaches, a clinician uses information from the patient
and published work to make judgments about
appropriateness. The focus is usually on the patient
rather than on drugs or diseases. These approaches are
potentially the most sensitive and can account for
patients’ preferences, but they are time-consuming,
depend on the user’s knowledge and attitudes, and can
have low reliability. There is no ideal measure, but the
strengths and weaknesses of both approaches should be
considered. Panel 1 provides examples of measures of
Panel 1: Examples of explicit and implicit process and outcome measures of
appropriateness, applied to benzodiazepine prescribing
Prescription of long-acting benzodiazepines is inappropriate (because of extended
sedation and increased risk of falls).20–24 (Process measure based on prescription data).
Prescription of a benzodiazepine is inappropriate if prescribed for insomnia (no valid
indication), in patients with history of fall (contraindication) and no attempt to withdraw
the drug.25 (Process measure based on prescription and clinical data).
If patient is prescribed a long-acting benzodiazepine for insomnia for 5 years, the clinician
identifi es additional risk factors for falls. The patient is open to attempt progressive
discontinuation, and then the clinician assesses that the choice of the drug and the
duration of treatment are inappropriate.*
Patient admitted to hospital for fall and taking a long-acting benzodiazepine indicates
that the benzodiazepine prescription is inappropriate.26–28 (Measure that includes an
adverse outcome component—ie, fall).
If patient admitted to hospital for falls and confusion (ie, outcome), medication history
shows chronic use of benzodiazepine, and use of sedating agents in the previous 3 days
for a cold, then the clinician evaluates that admission was drug-related and preventable
(avoidance of concomitant sedating agents in a patient at risk of falls).
*Some patients on chronic benzodiazepines, who are not willing to undergo substitution treatment and controlled withdrawal,
have benzodiazepine dependency and are at risk of withdrawal symptoms, and discontinuation of benzodiazepines is not
advised. This eff ect can be taken into consideration in the implicit approach, but is not accounted for in the explicit criteria.
www.thelancet.com Vol 370 July 14, 2007 175
Explicit or criterion-based process measures
Explicit criteria used with prescription data alone or with
clinical data are commonly used to detect inappropriate
prescribing. Most criteria constitute a fl oor of quality below
which no patient should go. Panel 2 explores their trans-
ferability between countries. Criteria to detect over-
prescribing consist of a list of invalid indications to
prescribe a specifi c drug or class of drugs. The most
common application has been to detect high amounts of
overprescribing of neuroleptic drugs for patients in
Criteria to detect underprescribing usually state that a
drug should be prescribed to treat or prevent a specifi c con-
dition, unless there is a contraindication. These criteria
have been applied to diff erent areas, such as heart failure36,37
and myocardial infarction,38 osteoporosis and fractures,39
atrial fi brillation,40 pain,41 and depression.42 The prevalence
of underuse is usually high (above 40% of patients). The
main restrictions of present studies are that few have exam-
ined underuse of medicines for several medical conditions
simultaneously,43–45 and criteria do not allow for factors such
as life expectancy and time needed to derive clinical benefi t
as legitimate reasons for underprescribing.46
Misprescribing criteria usually focus on choice of drug,
dose, drug interactions, duration of therapy, duplication,
and follow-up. The drug-to-avoid criteria have been the
most frequently used. They consist of a list of drugs that
should be avoided in elderly people because the risks of
use outweigh benefi ts. These lists were developed and
updated by Beers and co-workers20–22 in the USA and
McLeod and colleagues23 and Naugler and co-workers24 in
Canada. No similar initiative based on expert consensus
has been reported in Europe. The lists include drugs that
should be avoided in any circumstances, doses that should
not be exceeded, and drugs to avoid in patients with specifi c
disorders. These criteria have been frequently used in
aggregate on large databases. A study in Europe29 found
that 20% of elderly patients cared for at home used at least
one inappropriate drug as defi ned by the Beers or McLeod
criteria, but there were substantial diff erences between
There are disadvantages with the use of lists of so-called
bad drugs as a sole measurement for inappropriate
prescribing in elderly people. First, the inclusion of some
drugs is subject to controversy,47 and there is insuffi cient
evidence to support inclusion of several drugs.48
Furthermore, this approach
appropriate prescribing as inappropriate (poor specifi city).
Second, the prescription of drugs that should be avoided is
a relatively minor problem compared with other categories
of inappropriate prescribing such as underuse of
medicines, medication monitoring, or drug disease
interactions.43 Third, the reliability of the process to
generate such lists is not established.
Other misprescribing criteria go beyond this drug-to-
avoid perspective. For example, explicit drug-use-review
criteria were developed to detect dosage, duplication,
sometimes identifi es
interactions, and duration problems for eight classes of
drugs.49 New criteria are being developed to assess the
quality of laboratory monitoring of drug therapy.50 Drug
interaction criteria will be examined in more detail in the
second paper in this series.
Initiatives have attempted to develop and to validate sets
of explicit criteria.25,51,52 These sets consist of criteria of
overprescribing, misprescribing, and underprescribing for
several drugs or diseases, which provides an overview of
appropriateness of prescribing for patients. The most
comprehensive project—the Assessing Care Of the
Vulnerable Elder (ACOVE) project—used systematic
reviews of publications, expert opinion, and the guidance
of expert groups and stakeholders in the USA to develop a
set of quality-of-care indicators that are relevant to
vulnerable elders.52,53 68 (29%) indicators refer to
medication. Higashi and colleagues43 reported a prevalence
of inappropriateness of 3% in the drug-to-avoid domain,
36% in the medication-monitoring domain, and 50% in
the underprescribing domain. The ACOVE indicators have
several merits. First, geriatric conditions (eg, dementia,
falls) are included. Second, indicators pertain to treatment,
prevention, monitoring, education, and documentation,
and they encompass overprescribing, misprescribing, and
underprescribing. Third, most indicators are applicable to
people with advanced dementia and poor prognosis.54 Only
few data on inter-rater reliability have been published with
the ACOVE criteria.14
Implicit or judgment-based process measures
When an individual clinician judges the appropriateness
of a patient’s regimen in the context of research, the
fi ndings might be non-valid, not reproducible, or not
generalisable, which could have been the case in studies
for which no data on the validity or reliability of
measurements were provided.55,56 These limitations are,
nevertheless, remediable—reliability can be improved with
detailed specifi cations, instruments to obtain data, and by
training data collectors,15 as done with the Medication
Appropriateness Index (MAI).57
The MAI is a measure of prescribing appropriateness
that assesses ten elements of prescribing: indication,
eff ectiveness, dose, correct directions, practical directions,
Panel 2: Can explicit indicators be transferred between countries?
Since the development of quality indicators is resource-intensive, explicit indicators
should ideally be generalisable across countries. The Beers criteria show the diffi culty in
achieving this transfer—almost half the drugs on the Beers list are not available in
European countries.29,30 The situation is somewhat diff erent for indicators that do not
exclusively rely on specifi c drugs. For example, a study reported that the ACOVE indicators
in the treatment and follow-up domains were transferable from the USA to the UK.31
Similar fi ndings were reported with other sets of indicators.32,33 However, these studies
emphasise that indicators cannot be transferred from one country to another (or even
from one setting to another) without going through a process of modifi cation and
revalidation, because of contextual diff erences.32,33
www.thelancet.com Vol 370 July 14, 2007
drug-drug interactions, drug-disease interactions, dupli-
cation, duration, and cost. Although clinical judgment is
needed to assess some criteria (which is why the MAI is
classifi ed in implicit measures), the index has operational
defi nitions and explicit instructions, which standardise the
rating process. The ratings generate a weighted score that
serves as a summary
appropriateness.58 Three questions of the MAI (indication,
eff ectiveness, and duplication) can be used to detect
unnecessary polypharmacy,59 and high rates of inap-
propriateness have been detected. For example, 92% of
frail elderly inpatients included in a health-services
intervention study had at least one drug with one or more
inappropriate ratings, and 44% had at least one unnecessary
drug.59,60 The MAI has good intrarater and inter-rater
measure of prescribing
reliability, and face and content validity.57,58,61–66 However, it
is time-consuming and does not assess underprescribing.
Underprescribing can be detected with the Assessment
of Underutilization of Medication. The assessment needs
a health professional to match a list of chronic medical
disorders to the prescribed medications to establish
whether there is an omission of a needed drug.67 A small
study showed good inter-rater reliability,67 and in two
studies,67,68 25–60% of patients had evidence of under-
Is there a link between process measures and adverse
To be valid, process measures should have causal links
with important outcomes (eg, mortality, morbidity, adverse
Gupta et al72
Fick et al73
Fu et al74
Laroche et al75
19932 Medicaid benefi ciaries, USA
2336 managed care patients, USA
2305 community-dwellers (MEPS), USA
2018 patients admitted to the acute
geriatric unit of a teaching hospital, France
444 community-dwellers (MEPS), USA
487 383 community-dwellers, USA
406 Medicare-managed care patients,
1117 residents in 15 Georgia nursing
425 patients admitted to seven nursing
homes and two hospitals, Finland
5152 patients in 81 hospitals, Italy
Beers 1991 (do not use)
Beers 1997 (do not use)
Beers 1997 (do not use)
Beers 1997 (do not use)
No signifi cant diff erence in mortality (p=0·31)
Higher cost and use of health care (p=0·0001)
Poor self-rated health (p=0·006)
No signifi cant increased risk of adverse drug reactions (OR 1·0, 95% CI 0·8–1·3)
Franic et al76
Zuckerman et al77
Rask et al78
Beers 2003 (do not use)
Beers 2003 (do not use)
McLeod and Beers 1997 (do
Beers 1997 (do not use, dose)
No signifi cant diff erence in HRQOL (results not provided)
Increased risk of nursing home admission over the next 2 years (RR 1·31; 99% CI 1·26–1·36)
No signifi cant diff erence of self-reported adverse drug events (OR 1·42, 95% CI 0·90–2·25)
Perri et al79
Higher risk of death/admission/emergency visit (OR 2·34, 95% CI 1·61–3·40)
Raivio et al80
Beers 1997 (do not use, dose)No signifi cant diff erence in mortality (HR 1.02, 95% CI 0·7–1·37) and admissions (0R 1·40,
95% CI 0·93–2·11)
No signifi cant diff erence in mortality (OR 1·05, 95% CI 0·75–1·48), length of stay (OR 1·09,
95% CI 0·95–1·25), and adverse drug reaction (OR 1·20, 95% CI 0·89–1·61)
No signifi cant diff erence in adverse drug event (OR 1·51, 95% CI 0·98–2·35), length of stay (1·03,
0·64–1·63), discharge to higher levels of care (1·39, 0·82–2·34), and in-hospital mortality (1·49,
No signifi cant diff erence in health care use, and activities of daily living (p>0·05)
Onder et al81
Beers 2003 (do not use, dose)
Page et al82
389 admitted to two adult internal
Beers 2003 (do not use, dose)
Aparasu et al83
471 community-dwellers (MEPS) taking a
psychotropic drug, USA
882 patients in outpatient clinics, Taiwan
Beers psychotropic (do not
use, drug-disease interaction)
Beers 1997 (do not use, dose,
Chang et al84
Higher rate of adverse drug reactions (RR 15·3, 95% CI 4·0–58·8)
Lau et al85
3372 nursing home residents (MEPS), USA Beers 1997 (do not use, dose,
(1) DUR criteria and (2) Beers
1997 (do not use)
Higher risk of death (OR 1·21, 95% CI 1·00–1·46) and admission (1·28, 1·10–1·50)
Hanlon et al86
3234 community dwellers (Duke EPESE),
(1) No signifi cant diff erence in mortality (OR 0·85, 95% CI 0·69–1·24) and higher risk of decline
in functional status (2·04, 1·32–3·16) for interactions and basic-self care
(2) No signifi cant diff erence in mortality (1·02, 0·85–1·23), decline in functional status
(1) Increased outpatient visits (β=0·82, 95% CI 0·27–1·37), but no increased time to admission
(HR 1·06, 95% CI 0·90–1·25), or time to nursing home entry (HR 1·06, 95% CI 0·76–1·47)
(2) Increased time to admission (HR 1·20, 95% CI 1·04–1·39), but no increased outpatient visits
(β=0·48, –0·01 to 0·97, or time to nursing home entry (HR 0·93, 95% CI 0·69–1·08)
Higher admission (OR 2·00, 95% CI 1·33–3·00)
No signifi cant diff erence in mortality (HR 0·93, 95% CI 0·67–1·29)
Fillenbaum et al87
3165 community-dwellers (Duke EPESE),
(1) DUR criteria and (2) Beers
1997 (do not use)
Klarin et al88
785 ambulatory and nursing home
patients in a rural area, Sweden
Beers 1997 (high severity do
not use), McLeod
MAI (summed score)
Schmader et al65
208 community-dwellers, USA Higher hospital admission (p=0·07) and unscheduled visit (p=0·05); better blood pressure
β=regression coeffi cient. DUR=drug use review. EPESE=Established Populations for Epidemiologic Studies of the Elderly. HR=hazard ratio. HRQOL=health-related quality-of-life. MAI=medication appropriateness
index. MEPS=Medical Expenditure Panel Survey. OR=odds ratio. RR=relative risk. *For the drug-to-avoid criteria, data in brackets refer to the subtype of criteria used in the study: do not use refers to drugs that
should be avoided in any circumstances, dose refers to doses of drugs that should not be exceeded, and drug-disease interaction refers to drugs to avoid in patients with specifi c conditions. †Risk of adverse
outcomes in patients prescribed inappropriate drugs, as compared with patients not prescribed inappropriate drugs.
Table 1: Association between misprescribing detected by process measures, and adverse patient outcomes
www.thelancet.com Vol 370 July 14, 2007 177
drug events, quality of life).15 To the best of our knowledge
there are no studies linking overprescribing (unnecessary
polypharmacy) with health outcomes. Several studies
reported a link between under use of cardiovascular drugs
and adverse health outcomes such as mortality.38,69 The
restriction of drug use because of cost considerations is
linked to adverse clinical outcomes70 and a decrease in
self-reported health status.71 At least 18 studies have looked
at the predictive validity of process measures with respect
to misprescribing (mainly the drug-to-avoid criteria;
Some studies showed a positive relation between
inappropriate prescribing and mortality, use of health-care
services, adverse drug events, and quality of life, 30,65,73,74,77,79,84,85
whereas others reported
results.72,75,76,78,80,83,86–89 Most studies, however, had important
limitations in the methods—no adjustment for important
confounders (eg, comorbidity, polymedication), temporal
relation between the process and the outcome not
addressed, duration and dose response relation not
addressed, short follow-up, small and select sample, and
clinically meaningless diff erences observed.
In summary, the evidence is mixed and contradictory
that inappropriate prescribing, defi ned by process
measures, is associated with adverse patient outcomes. No
clear conclusions can be made about the predictive validity
of specifi c measures, except for criteria for underuse of
drugs for cardiovascular disease. The important questions,
therefore, are: do existing process measures measure the
wrong things, or just a small subset of the right things, or
is it simply the design of studies that needs to be
strengthened? Should other aspects of appropriateness,
such as measures of continuity of care, patients’
involvement, or of patients’ adherence, be included in the
new models? Future studies that test the predictive validity
of measures of inappropriate prescribing for elderly people
are needed to better inform health policy.
mixed or negative
New measures have been developed that detect in appro-
priate prescriptions which cause harm to the patient.
Juurlink and colleagues90 investigated the association of
hospital admission for drug toxic eff ects and use of
interacting drugs in the preceding week. Other researchers
attempted to develop indicators of preventable drug-related
morbidity.26–28,91 These indicators can be used in epidemio-
logical databases, with linkages via appropriately coded
disorders, medications, and other patient character istics.28
However, their specifi city and sensitivity might not be
satisfactory,92 they could be diffi cult to operationalise,93 and
only a few indicators refer to geriatric conditions.
Perspectives on measuring appropriateness
In summary, diverse process measures are available to
quantify overprescribing, misprescribing, and under-
prescribing in elderly patients. There is no ideal measure,
and the choice should depend on study objectives and
available data. However, assessment of prescribing
appropriateness should go beyond the use of measures
that rely exclusively on drug data, and the use of
appropriateness for patients should be encouraged.
Importantly, the predictive validity of process measures
remains to be proven.
We believe that the needs of individual patients, and
society as a whole, have been overlooked. Most measures
of appropriateness do not extend beyond pharmacological
appropriateness, with the occasional marker of cost
containment, and we believe this approach is inadequate.
The notion of pharmacological appropriateness does not
always coincide with what could be called overall
appropriateness (accounting for the perspectives of
patients, prescribers, and pharmacology).11 However, there
are substantial challenges in going beyond measures based
on scientifi c rationality and available, measurable data.94
Objectives for future research will be to operationalise and
validate instruments that go beyond pharmacological
appropriateness, and to assess the predictive validity of
present and future instruments. Meanwhile, many of the
measures mentioned above have suggested that prescribing
for elderly people is often inappropriate, and have been
used in optimisation studies.
several dimensions of
Approaches for optimisation of prescribing
Approaches for optimisation of prescribing in younger
patients might not be applicable to frail, elderly patients.
Older patients usually have several comorbidities,
associated polymedication, and objectives of treatment that
may diff er from that of younger adults. The application of
guidelines for specifi c chronic disorders is not always
suited to this older population,95,96 and enrolment in several
separate programmes for the management of multiple
disease (eg, diabetes, heart failure) might not be the best
option for caring for elderly patients with several chronic
disorders, since this approach may lead to fragmentation
of care.97 Specifi c adaptations should therefore be
14 studies met our inclusion criteria. Overall, two
studies used an educational type of intervention,98,99 one
used a computerised decision support system,100 three
used pharmacist interventions,101–103 and fi ve used a
geriatric medicine service approach.104–108 Geriatric
medicine service approaches generally consist of a
multidisciplinary team including a geriatrician and other
health-care providers with specialised geriatrics training
(eg, nurses, pharmacists, psychiatrists). The study by
Stranberg and colleagues108 was the only trial to include
only one of these aspects—namely, the input of a geri-
atrician. Finally, two studies used a multidisciplinary
approach without geriatrician medicine services,109,110 and
one used a multifaceted intervention.111 Only three studies
were done in Europe,102,106,108 and the others in North
America or Australia. All studies were undertaken in
ambulatory-care settings except for those by Schmader
www.thelancet.com Vol 370 July 14, 2007
and colleagues105 and Saltvedt and co-workers106(both
hospital settings), and those by Crotty and col leagues103,107
(nursing homes). Table 2 summarises the indi vidual
trials. A Belgian study (a randomised controlled trial) was
released after our search was completed. The investi-
gators reported that pharmaceutical care provided in
addition to acute geriatric care signifi cantly improved
over pres cribing, misprescribing, and underprescribing.112
Several studies showed that geriatric medicine service
approaches, pharmacist involvement in patient care, and
computerised decision support can improve the
appropriateness of prescribing in elderly patients in
diff erent settings. Geriatric medicine services, which are
designed to meet the special needs of elderly people and
are provided by specially trained health-care providers,
have already been cited as a priority for development by the
Setting Unit of
Intervention Duration Results (process measures of appropriate prescribing [P] and patient health
372 family doctors Mailed prescribing feedback and
education materials on the
prescription of benzodiazepines
P: Absolute decrease of 0·7% in prescribing of long-acting benzodiazepines in
intervention group, and increase of 1·1% in control group (p=0·036); no diff erence in
long-term benzodiazepine therapy, and in combination treatment with other
P: Better adherence to guidelines with workshop and decision tree (OR 1·8, 95% CI 1·3-
2·4); weak evidence that workshop plus decision tree is more eff ective than decision
Eight towns [cluster],
249 family doctors
Small-group workshop and
decision tree to manage
Computerised decision support systems
et al100 care, Canada
Ambulatory 107 family doctors Computerised decision support
13 months P: Lower prescription of new inappropriate drugs (Canadian criteria, drug-to-avoid,
drug-drug and drug-disease interactions, duration and duplication) in the intervention
group vs control group (RR 0·82, 95%CI 0·69–0·98); no diff erence in the
discontinuation of inappropriate drugs (1·06, 0·89–1·26)
Aff airs General
208 patients DRR and written drug therapy
recommendations for physician;
patient counselling at each clinic
P: Higher decline in inappropriate prescribing scores (MAI) in intervention vs control
group, at 3 months (24% vs 6% decrease, p=0·0006), and 12 months (28% vs 5%
O: No signifi cant diff erences in adverse drug events, health related quality of life, or
health services use
P: More drug-related problems resolved in intervention than in control group (82·7% vs
O: No diff erence in health related quality of life or health services use
P: Scores of inappropriate prescribing (MAI) at follow-up lower in the intervention than
in control group (2·5 vs 6·5 p=0·006); at follow-up, 22% decrease vs 91% increase,
O: Better pain control and less hospital use; no diff erence in adverse drug events, falls/
332 patients Pharmaceutical care plan
completed and given to family
Transfer medication list to
community pharmacist, DRR by
community pharmacist, and case
conference with doctors and
Geriatric medicine services
nine family doctors,
Chronic care clinic including visit
with geriatrician, nurse, and
24 monthsP: No signifi cant improvements in the prescription of high-risk medications at
12 months (2·94 high-risk medications per patient in the intervention group vs 3·26 in
the control group; p=0·57) and 24 months (1·86 vs 2·54, respectively; p=0·20)
O: No diff erence in selected geriatric syndromes
P: Higher improvements in the number of unnecessary drugs in intervention than in
control patients (–0·6 vs +0·1, p<0·0001), inappropriate prescribing (47% decrease vs
25% increase in MAI score, p<0·0001), and number of conditions with underuse (–0·4 vs
+0·1; p<0·001) in inpatients. Higher improvements in the number of conditions with
underuse in intervention than in control outpatients (–0·2 vs +0·1; p<0·0004)
O: Decreased risk of serious adverse drug reactions in outpatients
P: Lower prevalence of potential drug-drug interactions in intervention than in control
group at discharge (p=0·009, 36% decrease from admission to discharge vs 17%,
respectively), and of anticholinergic medications (p=0·03, 78% vs 10% decrease,
respectively); no diff erence in prescription of Beers’ drugs (p>0·05, 60% vs 33%
P: Higher improvements in prescribing appropriateness in intervention than in control
group (55% decrease vs 10% decrease in MAI scores, p=0·004)
O: No diff erences in resident behaviour
P: Signifi cant increase in the use of evidence-based drugs in the intervention compared
with control group (β blockers p=0·02, ACE-I p=0·0001, ARA p=0·007, statins p<0·0001)
O: Signifi cant improvements in blood pressure and cholesterol levels, but no diff erence
in major cardiovascular events and total mortality
Multidisciplinary geriatric team
care (including a geriatrician) for
inpatients and outpatients
(2×2 factorial design)
254 patientsMultidisciplinary geriatric team
care (including a geriatrician)
Ten facilities [cluster];
Two multidisciplinary case
conference (including a
geriatrician), 6–12 weeks apart
review plus nutritional and
400 patients with
(Continues on next page)
www.thelancet.com Vol 370 July 14, 2007 179
UN.113 There were mixed fi ndings on the eff ect of
educational approaches. Simon and colleagues111 reported
that intervention with physicians via academic detailing
might not enhance computerised decision support
interventions. However, the investigators used a non-
traditional academic detailing approach, in which the main
focus diff ered from appropriate prescribing. Table 3 shows
the advantages and disadvantages of approaches that we
have critically reviewed. In several cases, no or only little
eff ect on appropriateness of prescribing was reported,
which could have been because of no direct interaction
with the main prescriber,98,109 or a low participation rate of
health-care professionals,99,103,109 mainly for educational
interventions and case conferences. Environmental
barriers certainly have an important role and should be
addressed adequately. The data also show that, whenever
possible, the intervention should be provided at the time of
prescribing rather than retrospectively—ie, after an initial
prescription has been issued.
Several weaknesses can be reported in terms of the
process measures used—fi ve studies looked only at
prescription data to assess appropriateness, without taking
into account clinical data;98,100,104,106,111 two studies used explicit
measures that were not fully validated;109,110 and Krska and
co-workers102 used implicit measures without reporting
data on their validity and reliability. In contrast, robust
measures, such as the Medication Appropriateness
Index101,103,105,107 or a combination of implicit and explicit
measures of overprescribing, misprescribing, and
underprescribing,105 were used in other trials.
Nine studies assessed the eff ect on patient health
outcomes, such as adverse drug events, mortality,
morbidity, or quality of life. Most did not fi nd an eff ect
(either positive or negative),102–105,107,108,110,114 which is probably
because most studies were underpowered to detect
diff erences in patient health outcomes or the outcome
measures were not responsive enough to the intervention.
This issue is an important limitation of present studies.
There are some potential restrictions of our review. Some
studies (usually with negative fi ndings) might not have
been published and therefore could not be included. Other
studies of interest could not be included because they did
not use a randomised controlled design115–118 or because
they did not specifi cally use valid measures of appropriate
prescribing in the control and intervention group.119–131 Two
studies had to be excluded because of a lower age limit.132,133
Similarly, we did not look at other intervention types (eg,
regulatory approaches) because they have not been
rigorously studied with a randomised controlled trial. We
were unable to do quantitative synthesis (ie, meta-analysis)
because of the heterogeneity of the interventions, their
settings, and outcome measures.
How do approaches tackle the causes of inappropriate
Inappropriate prescribing has been attributed to several
causes that should be addressed when approaches for
optimisation are considered. Conceptually, prescribing can
be regarded as a function of the patient, prescriber, and
environment. First, the clinical needs of the patient should
be the primary determinant of prescribing decisions.
Appropriate prescribing should aim to promote the use of
evidence-based therapies and keep the use of drugs for
which there is no clinical need or where there is dubious
effi cacy to a minimum. The patients themselves can
infl uence prescribing decisions on the basis of their
expectations.134 Second, prescribing is done mainly by
physicians who will use their own clinical experience and
attitudes to make the fi nal decision. A contributory factor
to inappropriate prescribing is the inadequate training in
(Continued from previous page)
266 patients DRR by single interdisciplinary
team (two physicians, one
pharmacist, and one nurse) and
written recommendations given
to family doctor
DRR by pharmacist and nurse to
identify problems that were then
presented to the physician
12 monthsP: The mean number of potentially inappropriate prescription (Quebec consensus
panel: drug interactions, therapeutic overlapping, drugs of limited use) declined by 0·24
in the intervention group and by 0·15 in the control group (p<0·001 ); 37% of
intervention patients had no team DRR, and those with team DRR were twice as likely
to have fewer potentially inappropriate prescriptions
P: Overall medication use improved for 50% of intervention patients and 38% of control
patients (p=0·051); more duplicative drugs stopped in intervention group (p=0·003)
and more appropriate cardiac drugs (p=0·017); no eff ect on appropriate prescribing of
psychotropic drugs and NSAIDs (p>0·05; DUR criteria)
O: No diff erence in clinical outcomes or health care use
and LA, USA
et al111 maintenance
13 clinics [cluster];
126 doctors, 26 805
decision support with or without
3 months P: 5·7% decrease in prescribing of inappropriate drugs (Beers) with computerised alerts
(p=0·75); academic detailing had no eff ect (p=0·52)
ACE-I=angiontensin-converting enzyme inhibitor. ARA=angiotensin II receptor antagonist. ADEs=adverse drug events. ADRs=adverse drug reactions. CVD=cardiovascular disease. DRR=drug regimen review.
DUR=drug use review. MAI=Medication Appropriateness Index. NSAID=non-steroidal anti-infl ammatory drug. * These studies were specifi cally designed to assess the eff ect of the clinical pharmacist who made
recommendations to prescribers. Clinical pharmacists can also work within geriatric medicine teams, and this was the case in most geriatric medicine service studies included in this review. The diff erence is that
such trials were designed to assess the eff ect of the whole geriatric team, and not of clinical pharmacists themselves.
Table 2: Summary of randomised controlled studies to improve inappropriate prescribing in elderly people
www.thelancet.com Vol 370 July 14, 2007
geriatric pharmacotherapy.135,136 Prescribers might not
prescribe a drug or increase the dose, for example, because
the patient is old (a phenomenon called ageism).137,138
Additionally, inappropriate prescribing can arise from the
absence of communication between doctors practising in
diff erent settings or even between specialists practising in
the same setting.100,138
Third, the environment in which the prescriber operates
can, in turn, aff ect prescribing decisions, as shown by the
following setting-specifi c examples. Although not a
panacea, the regulatory framework by which nursing
homes in the USA operate (which provides disincentives
to nursing homes for extended prescribing of medicines in
the absence of documentation justifying its use)139 has
aff ected prescribing.140 Furthermore, contextual factors (eg,
staffi ng and resources) within nursing homes are
associated with drug use in these settings.141,142 The acute
care environment does not encourage review of chronic
and preventive drugs.138 Finally, environments with no or
few structures to share information relating to drugs
during transitions between settings of care can also
compromise quality. Ultimately, the fi nal prescribing
decision may arise from the interaction of these three
factors (the patient, prescriber, and environment), and in
some cases from the family or caregiver.
Although several studies addressed communication
between diff erent health-care providers through multi-
disciplinary approaches, we believe the issue of
communication between prescribers and their patients
has been overlooked. However, several studies suggest that
this issue is important. For example, Tamblyn and
colleagues100 reported no eff ect of computerised decision
support on the discontinuation of inappropriate drugs,
because physicians were concerned with patients’
resistance to change or felt uncomfortable discontinuing
therapy that another physician had prescribed. In the
future, interventions seeking to improve prescribing
should address these causes, and might need to be
customised to account for diff erences in patient, prescriber,
How should prescribing be optimised in the future?
From a clinical research perspective, further robust
information is urgently needed about the risks and benefi ts
of drugs in elderly patients. The type of evidence that
clinical trials provides is restricted with respect to
generalisability, because trials usually exclude older, frail
patients, and even when a trial is targeted to elderly people,
the population enrolled is usually highly selected.143 Future
trials complemented by evidence from well-designed
non-experimental studies that estimate causal eff ects could
address this inequity.
From an interventional and health-care research
perspective, even though data provide useful insights into
the eff ectiveness of diff erent approaches, several questions
remain unanswered. The eff ect on important health
outcomes and health-care costs still needs to be proven
(some interventions can potentially decrease direct
Can be passive (eg, didactic courses, dissemination of printed
material), or more interactive (eg, academic detailing)
Academic detailing: repeated face-to-face delivery of
educational messages to individual prescribers, by doctors or
Audit and feedback can be added to enhance the eff ect
Support with regard to drug interactions, dosage, choice of
drug, and monitoring
Eff ect of CPOE based on the use of prescription data only,
whereas CDSS uses prescription and clinical data to provide
Provide pharmaceutical care and drug regimen review
Directly addresses the absence of training in geriatric
Can promote changes in prescribing behaviours
Personalised, interactive, and multidisciplinary
approaches most likely to be eff ective
Usually restricted to specifi c drugs or diseases
Passive approaches likely to be ineff ective
Eff ect not sustained without continued
Low participation rate; barriers to implementation
of interactive and multidisciplinary meetings
Challenging to implement
Existing systems are not geriatric-specifi c
High volume of alerts; therapeutic fl ags usually
overridden by physicians; risk of unimportant
warnings. Some prescribers are reluctant to use
Successful interventions require that pharmacists
work in close liaison with the prescriber, and have
access to the full clinical record of the patient
CPOE and CDSS
Potentially powerful tools to prevent adverse drug events
Support at the time of prescribing
All categories of inappropriate prescribing can be
addressed, if prescription data are linked to clinical data
Specialist clinical pharmacists have expertise in geriatric
pharmacology and pharmacotherapy
Drug regimen review can potentially improve all
categories of inappropriate prescribing
Can potentially address most causes of inappropriate
Every team member brings specifi c competences with
regard to drug use
Service is tailored to meet the needs of elderly people,
and criteria to enter the programme are related to frailty
and functional decline
Can address distinct causes of inappropriate prescribing
Every team member brings specifi c competences with
regard to medicines use
Can address distinct causes of inappropriate prescribing
More likely to work than single interventions
Usually an interdisciplinary team composed of geriatricians,
nurses, and other specialised health-care professionals
(sometimes pharmacists) delivers medical care that includes
optimisation of the drug regimen
Comprehensive geriatric assessment is the usual process of
Barriers to implementing multidisciplinary team
meetings in the ambulatory and nursing home
settings (challenge to organise and coordinate a
multidisciplinary group, fi nancial barriers)
Usually a group of health-care professionals undertake drug
regimen review of individual patients
Health-care professionals may not be involved in
patient care and communication of
recommendations to the prescriber
Complex and costly to implementMultifaceted
Interventions that incorporate two or more distinct
strategies (eg, academic detailing and CDSS)
CDSS=computerised decision support system. CPOE=computerised physician order entry.
Table 3: Advantages and disadvantages of approaches to improve prescribing in elderly patients
www.thelancet.com Vol 370 July 14, 2007 181
costs,127,144,145 but there is yet no guarantee that eff ective
strategies will generate economic savings in the long-term).
This process is a challenging task that will need the
implementation of multicentre studies with large samples
and outcome measures that are clinically relevant and
responsive to the intervention (ie, adverse drug events,
therapeutic failure). The eff ect of multifaceted approaches
should also be assessed.
Another important perspective relates to the widespread
diff usion of eff ective approaches. Despite the substantial
resources devoted to developing and testing the
eff ectiveness of interventions to improve prescribing,
widespread diff usion of successful methods has not yet
been achieved. This failure could be because of several
reasons. First, researchers often do little to put together
and disseminate interventions beyond traditional methods
such as publication in academic journals. At the end of a
particular study, researchers generally do not have the
resources to assist others in implementation of successful
approaches. Further, the translation of research into
practice depends on the resources needed to implement
the intervention, as well as the characteristics and resources
of the organisation adopting the approach.146 The issue of
who should meet the cost for such interventions might
prevent diff usion of innovation.
Direct transfer of interventions between diff erent
settings or between the same setting in diff erent countries
might not be possible. The US approach to prescribing in
nursing homes will not necessarily work within other
countries and indeed, other countries have not used this
method.139 A complex pharmaceutical care intervention
tested in US nursing homes needed adaptation before it
could be implemented in nursing homes in Northern
Ireland.147 Diff erences in the practice environment and
culture should be considered if interventions are to be
successfully transferred into diff erent settings and
The involvement of patients or their carers in
decisionmaking relevant to prescribing is a real challenge,
especially in a frail elderly population. However, this
approach seems promising. Evidence suggests that a
patient’s decision to take or not to take drugs might be part
of a negotiation process rather than a fi nal stance,148 and
that changing patients’ behaviour is more likely if patients
are helped to make decisions for themselves rather than
being told what to do.149,150 Encouraging adherence in this
population for whom multiple drug therapy is common
will need careful prescribing, assessment of benefi t, and
avoidance of adverse eff ects. Changes in the attitudes of
prescribers towards sharing prescribing decisions are
needed, in addition to the improvements in communication
that could arise from information technology.
Information technology should improve the use of
drugs. Prescribing in the future will use three interacting
databases—the patient’s drug history, a scientifi c drug
information reference and guideline database, and clinical
information that is patient-specfi c.151 Integrated prescribing
systems off er promise, but tailoring such systems to the
unique concerns of the geriatric patient population is
warranted.152 Improvements in the specifi city of alerting
systems might improve their clinical usefulness.
Finally, prescribing is no longer viewed as a solitary
activity undertaken by physicians. Prescribing authority in
the UK has been extended to other health professions,
notably nursing and pharmacy.153 Continual assessment of
pharmacist prescribing suggests that it has been positively
received by the medical profession.154 There has been very
little objective robust data for the eff ect of prescribing by
pharmacists on patient outcome, so further assessment
will be needed.
Confl ict of interest statement
We declare that we have no confl ict of interest.
Financial support was provided by the National Institute on Health
(JTH: R01 AG027017, P30 AG024827, and K12HD049109;
KES: K24AI051324-01 and R01AG14158), the Belgian Fonds National de la
Recherche Scientifi que (at the time of writing, AS was a research fellow of
the Belgian Fonds National de la Recherche Scientifi que), the Agency for
Health Care Quality (KLL: U18HS016394), the Commonwealth Fund and
the Retirement Research Foundation (KLL), and Research and
Development Offi ce, Northern Ireland (CH).
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