Nursing Home Team-Care Deprescribing Study
Phase: NA
Conditions: Fall in Nursing Home, Medication Therapy Management
Sponsor: Tan Tock Seng Hospital

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Kua C-H, et al. BMJ Open 2017;7:e015293. doi:10.1136/bmjopen-2016-015293
ABSTRACT 
Introduction  An ageing population has become an 
urgent concern for Asia in recent times. In nursing 
homes, polypharmacy has also become a compounding 
issue. Deprescribing practice is an evidence-based 
strategy to provide a better outcome in this group of 
patients; however, its implementation in nursing homes 
is often challenging, and prospective outcome data on 
deprescribing practice in the elderly is lacking. Our study 
assesses the implementation of team-care deprescribing 
to understand the benefits of this practice in geriatric 
setting and to explore the factors affecting deprescribing 
practice.
Methods and analysis  This multicentre prospective 
study consists of a prestudy interview questionnaire, 
and a preintervention and postintervention study to be 
conducted in the nursing home setting on residents 
at least 65 years old and on five or more medications. 
We will employ a cluster randomised stepped-wedge 
interventional design, based on a five-step (reviewing, 
checking, discussion, communication and documentation) 
team-care deprescribing practice coupled with the 
use of a deprescribing guide (consisting of Beers and 
STOPP criteria, as well as drug interaction checking), to 
assess the health and pharmacoeconomic outcome in 
nursing homes’ practice. Primary outcome measures of 
the intervention will consist of fall risks using a fall risk 
assessment tool. Other outcomes assessed include fall 
rates, pill burden including number of pills per day, number 
of doses per day and number of medications prescribed. 
Cost-related measures will include the use of cost–benefit 
analysis, which is calculated from the medication cost 
savings from deprescribing. For the prestudy interview 
questionnaire, findings will be analysed qualitatively using 
thematic analysis.
Ethics and dissemination  This study is approved by 
the Domain Specific Review Board of National Healthcare 
Group, Singapore (2016/00422) and Monash University 
Human Research Ethics Committee (2016-1430-7791). 
The study findings shall be disseminated in international 
conferences and peer-reviewed publications. The study 
is registered with ​ClinicalTrials.​gov (NCT02863341), Pre-
results
INTRODUCTION
Asia’s population is rapidly ageing, and the 
elderly accounts for more than half of the 
global elderly population in 2015. This popu­
lation is expected to increase by another 
66% to 844.5 million in the next 15 years.1 
This demographic transition in the elderly 
is expected to pose a significant challenge 
for many health authorities worldwide as an 
advancing age is associated with multiple 
chronic diseases. Many of current guidelines 
are based on a healthy adult population, and 
much less information is available for the 
geriatric population. However, prescribing in 
the elderly based on guidelines for younger 
adults can result in several issues, including 
polypharmacy, increase pill burden and thus 
risk of adverse events.2
Nursing homes have one of the highest 
rates of polypharmacy,3 with almost one-half 
of nursing home residents exposed to poten­
tially inappropriate medications, and a likely 
increasing prevalence over time.4 A recent 
study in Malaysia identified an average of 
6.1 medication-related problems per nursing 
home resident.5 In Singapore, a nursing 
Nursing home team-care deprescribing 
study: a stepped-wedge randomised 
controlled trial protocol
Chong-Han Kua,1,2 Cindy Ying Ying Yeo,2 Cheryl Wai Teng Char,3 
Cheryl Wei Yan Tan,3 Poh Ching Tan,3 Vivienne SL Mak,4 Shaun Wen Huey Lee,1 
Ian Yi-Onn Leong2 
To cite: Kua C-H, Yeo CYY, 
Char CWT, et al. Nursing home 
team-care deprescribing 
study: a stepped-wedge 
randomised controlled 
trial protocol. BMJ Open 
2017;7:e015293. doi:10.1136/
bmjopen-2016-015293
►
►Prepublication history 
and additional material are 
available. To view these files 
please visit the journal online 
(http://​dx.​doi.​org/ 10.1136/
bmjopen-2016-015293).
Received 23 November 2016
Revised 17 April 2017
Accepted 17 March 2017
1School of Pharmacy, Monash 
University – Malaysia, Selangor, 
Malaysia
2Continuing and Community 
Care Department, Tan Tock Seng 
Hospital, Singapore
3National Healthcare Group 
Pharmacy, Singapore
4Centre for Medicine Use and 
Safety, Faculty of Pharmacy 
and Pharmaceutical Sciences, 
Monash University, Melbourne, 
Australia
Correspondence to
Mr. Chong-Han Kua; 
​chong.​kua@​monash.​edu
Open Access
Protocol
Strengths and limitations of this study
►
►This is the first deprescribing study in Asia to 
be carried out in the nursing home setting and 
incorporate the investigation of health outcomes 
using a stepped-wedge design.
►
►Our five-step team-care deprescribing practice is 
structured using updated evidence-based 2015 
Beers criteria and 2014 STOPP criteria.
►
►The study entails a novel three-way comparison of 
structured team-based deprescribing practice, with 
existing non-team-based deprescribing practice and 
with deprescribing-naïve nursing home participants.
►
►The main limitation of the study is that by being 
conducted only in one country, the findings may not 
be reflective of all Asian settings.
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home study showed that residents were on more than five 
medications on average. Polypharmacy and inappropriate 
medication use were seen in 58.6% and 70% of residents, 
respectively, and there was significant association between 
polypharmacy and inappropriate medication use.6 
Furthermore, the number of readmission is significantly 
associated with the number of medications prescribed.7 
Thus, the growing problem of polypharmacy in the 
elderly may be addressed through deprescribing.
There is now growing evidence to support that the 
discontinuation of specific medications or deprescribing 
in elderly population does not worsen outcomes while 
decreasing adverse drug events and medication costs.8 9 
Deprescribing is increasingly adopted in many countries 
including Australia, New Zealand, United States, Canada, 
and several European countries, as reflected from a 
recent review,10 but is limited in Asia. The principles 
of deprescribing include reviewing all current medica­
tions, identifying medications to be ceased, substituted 
or reduced, planning a partnership with the patient and 
frequently reviewing and supporting the patient11 and 
should be applied in the nursing home setting as well.12
Deprescribing is important in reducing polypharmacy, 
risk of adverse medication outcome and medical care cost 
while improving compliance.13 However, there is a lack 
of prospective outcome data on deprescribing practice in 
elderly in an Asian population, especially in the nursing 
home settings. Our study will assess a team-based depre­
scribing intervention on falls risk and falls rate, as well 
as pharmacoeconomic outcomes in nursing homes and 
explore the factors affecting deprescribing practice. In 
particular, our primary outcome measure of falls risk and 
falls rate will be important as falls cascade down to other 
medical and related economical issues. Primary outcome 
measures of the intervention will consist of fall risks 
using a fall risk assessment tool (FRAT). Other outcomes 
assessed include fall rates, pill burden including number 
of pills per day, number of doses per day and number 
of medications prescribed and cost-related measures 
including cost–benefit analysis (CBA).
Aims of the study
The aims of this study are to examine: (1) the effective­
ness of a five-step team-care deprescribing intervention 
in a nursing home setting in reducing falls risk, falls rate, 
pill burden and medication cost, and (2) the factors that 
affect the acceptance of deprescribing among healthcare 
professionals. We hypothesise that a team-care depre­
scribing intervention initiated by the pharmacists will 
provide better health (through a reduction in falls risk 
and falls rate) and economic outcomes versus usual care 
in a nursing home setting.
METHODS AND ANALYSIS
Participants and settings
This study will be a longitudinal preinterventional and 
postinterventional study conducted in a nursing home 
setting. The study setting would comprise up to four 
nursing homes in Singapore, with a total capacity of 950 
beds, representing 8% of the total nursing home beds 
in Singapore.14 The nursing home residents are mostly 
aged 60 years and above, with mobility issue and require 
daily skilled nursing care or assistance in activities of daily 
living. The functional status of the residents is deter­
mined from Singapore’s Ministry of Health’s Resident’s 
Assessment Form15 and will be used in the standardisa­
tion during our analysis of fall risks and fall rates.
All residents in the nursing homes will be assessed 
and included if they fulfil the following criteria: (1) 
aged 65 years and above, (2) currently on five or more 
medications and (3) provided informed consent (unless 
cognitive  impaired, with no or uncontactable next of 
kin). Consent from next of kins will be sought for cogni­
tive-impaired participants. Principal investigator will seek 
consent from next of kins and participants. Participants 
will be excluded if they have a life expectancy of less than 
6 months (based on patient’s physician/general practi­
tioner judgement) or staying for respite care. Participants 
will be discontinued from the study if there is admission 
into hospital for longer than 30 days, passed away or on 
discharged back to home or moved to another nursing 
home.
Study design
This study will employ a stepped-wedge design, which 
involves sequential crossover from control to interven­
tion, until all cluster groups receives the intervention.16 
We decided to employ this design due to its pragmatic 
approach, as it does not deprive any participant from 
receiving an evidence-based intervention (figure 1).
Sample size considerations
Sample size was calculated based on the main clinical 
outcome,  which is falls rate reduction. Our literature 
search found that the Asian elderly annual fall rate is 
18%,17 and we expect that the intervention will reduce 
the fall rate by a further 10%. Assuming a 5% significance, 
80% power and an intracluster correlation coefficient of 
0.1, we calculated that we need 54 participants per arm for 
the stepped-wedge trial with four different arms. Allowing 
for a 25% attrition rate, a total of 288 participants will be 
recruited.
Randomisation and blinding
This study will employ a stratified cluster randomised 
design with the cluster groups as the unit of randomis­
ation. The investigator conducting analyses will be using 
coded information of participants located in the nursing 
homes during data analysis. Participants will know what 
medication they are taking, as per usual practice.
Intervention
The intervention will consist of a five-step multidisciplinary 
team-based deprescribing approach using a deprescribing 
guide adapted from the Beers criteria,18 Screening Tool of 
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Older People's Prescriptions (STOPP) criteria,19 as well as 
a review of medication interactions and side effects.
The five-step team-care process consists of reviewing, 
checking, discussion, communication and documentation 
as described in figure 2, initiated by the pharmacists. Each 
nursing home in the study is currently served by one to 
two community-based pharmacists. They have completed 
or are currently undertaking their postgraduate studies 
(Master of Clinical Pharmacy) or Board Certified Geri­
atric Pharmacist training. All pharmacists (minimum 
working experience at aged care homes of 1 year) will 
receive a half-day face-to-face training and familiarisation 
session on the intervention. Our multidisciplinary team-
care approach involves nurses, pharmacists and doctors 
and will be implemented during routine doctor and phar­
macist nursing home review visits. Pharmacists will initiate 
deprescribing in medication review, after discussion with 
ward nurses on the feasibility of deprescribing for each 
appropriate individual patient. The intervention informa­
tion filled-up by the pharmacist will be passed on through 
the ward nurses to the doctor for review during doctor's 
visit. Thereafter, the doctor will make the final decision 
on drugs that will be deprescribed. A copy of the depre­
scribing reference guide (Beers and STOPP criteria) will 
be available to all participating healthcare professionals. 
The Beers and STOPP criteria are intended as a guide 
for educating pharmacists and doctors regarding the 
different types of interventions that they could make. For 
successful deprescribed patients with external institution 
follow-up, a copy of the deprescribing details will be pass 
as memorandum to the external doctor. Additionally, 
multidisciplinary discussion session may be introduced 
as part of the nursing home's standard practice at some 
sites, but implementation depends on case-by-case avail­
ability and agreement of individual doctor, pharmacist 
and nurse at each site during routine care. Non-cognitive 
impaired residents or next of kins of cognitive-impaired 
residents may be contacted in decision  making of the 
intervention where feasible.
Control
All participants in the control arm will continue to receive 
usual care or support that they usually receive from 
their healthcare professionals. In participants who were 
randomised to control, there is a possibility that some 
participants will require a review of their medication. 
These patients will be documented and analysed sepa­
rately at the end of study.
Data collection
Data collection from both intervention and control 
groups will occur at four time points (baseline, month 
3, month 6 and month 12). The data include the FRAT 
scores, fall rate, pill burden, medication intervention 
acceptance and reduction rates as well as costs. Principal 
investigator and study team will be in charge of the data 
monitoring. Data management procedures have been 
reviewed by the ethics board with the frequency of review 
at baseline, 3, 6 and 12 months.
In addition, a prestudy interview questionnaire with 
doctors, pharmacists and nurses will be conducted to 
determine the factors that affect their views and accept­
ability of deprescribing. The anonymous prestudy 
interview questionnaire will consist of 10 open-ended ques­
tions covering knowledge, practice and attitude towards 
deprescribing. The principal investigator will approach 
potential participants at the study sites during routine 
visits by convenience sampling, and the short prestudy 
interview questionnaire will enrol up to 10 doctors, phar­
macists and nurses (total 30 participants) each to collect 
qualitative data on deprescribing. We will provide a quali­
tative analysis of the views of these participants.
Figure 1  The stepped-wedge design for the current study. Baseline population of each home is subclassified into two groups 
(groups A and B). Group As are non-naive (participants whose attending doctor or pharmacist has recently deprescribed 
their medications within 6 months before the study starts), while the group Bs are intervention naive. Intervention will be 
implemented to first half of the participants in 3 months. Each home thus has four clusters, and all clusters will be assessed 
for sustainability of outcomes after 6 months.
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Outcomes and study measures
Primary outcome
Fall risks: Assessments of fall risk will be compared prein­
tervention and postintervention using the FRAT.20 Our 
adapted FRAT will cover additional elements including 
medical conditions, history of falls, contributing medica­
tions, functional status, as well as behavioural issues, as 
recommended by local fall risk assessment guideline. The 
primary outcome is the mean change in FRAT scores at 
baseline, 3, 6 and 12 months.
Secondary outcomes
Fall rate: Actual fall rates will be compared between base­
line preintervention period and the intervention period 
(proportion of participants who experiencing a fall 1 year 
prestudy and 1 year poststudy). A fall was defined as any 
incident reported as a fall in the progress notes.
Pill burden: Number of pills per day, number of doses 
per day and number of medication will be compared 
predeprescribing and postdeprescribing at baseline, 3, 6 
and 12 months.
Medication reduction rate: Percentage of reviewed cases 
where medications are deprescribed will be compared 
between baseline preintervention period and the inter­
vention period. The total number of regular medicines 
comprised all regular and as-needed medicines that is in 
the resident’s medication record. It also includes supple­
ments and complementary or alternative medicine.
Cost related: CBA is constructed from cost savings postde­
prescribing. This will be calculated from medication review 
Figure 2  Five-step team-based deprescribing practice.
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expenditure, utilisation expenditure and medication 
cost. The direct medication cost saved from deprescribing 
is compared with any increment in manpower cost by 
tracking the number of reviews completed by pharma­
cists. The number of reviews completed will be tracked 
monthly.
Factors affecting deprescribing: Findings from thematic 
analysis of data from our exploratory prestudy stan­
dardised interview questionnaire covering factors on 
knowledge, practice and attitude towards deprescribing 
for healthcare professionals (doctors, nurses and phar­
macists) will be presented.
In addition to the outcomes above, we will also be 
assessing the acceptance rate of the deprescribing inter­
vention (number of pharmacist interventions accepted 
by doctor monthly), as well as the type and percentage 
of drug-related problems. Charlson comorbidity index 
and medication regimen complexity index will be tabu­
lated from the collected data. We will also collect data 
on the number of STOPP criteria and Beers criteria 
interventions made. In addition, we will assess any harm 
associated with the intervention by comparing hospital­
isation and mortality rates. These data together with the 
primary outcomes will subsequently be used in our phar­
macoeconomic analysis.
Statistical analysis
All analysis will be performed following intention-to-treat 
principle. The characteristics of the patient population 
will be determined using appropriate descriptive statistics. 
χ2 tests will be used to compare proportions, and analysis 
of variance will be used for comparing continuous data. A 
p value of <0.05 will be considered statistically significant 
for all tests.
The effectiveness of the current study intervention will 
be measured by determining the differences with respect 
to change to activities performed and events data. In 
addition, the presence of significant separate time trends 
within subgroups will be examined, as analytical methods 
employed in stepped-wedge trials are vulnerable to it. 
Confounding of time will be accounted for during data 
analysis by stratified analysis or multiple variable regres­
sion analysis.
Fall risks and fall rates within and between groups will 
be tested for significant difference. Pill burden (number 
of pills per day, number of doses per day and number 
of medication) will be tabulated under descriptive statis­
tics and compared using t-tests. Subgroup analysis will 
be further performed for successfully and unsuccessfully 
deprescribed subjects. Medication deprescribed will be 
further classified based on their primary indication in 
subgroup analysis.
CBA will be conducted to analyse the economic bene­
fits of the deprescribing intervention. Parameters that 
will be examined include medication cost, time spent for 
medication review and utilisation expenditure. CBA will 
be derived from the medication cost divided by the phar­
macist manpower cost, between the intervention and 
control groups. The average hourly cost of pharmacist 
review will be used in the calculation.
The 10 open-ended interview questionnaire involving 
doctors, pharmacists and nurses will be qualitatively anal­
ysed using thematic analysis. The interview questionnaire 
will be transcribed verbatim, and audio-recording is by 
participant's consent. We will use QSR NVivo 11 to assist 
in analysis of the data, and both inductive approach as 
well as deductive approach will be used in our analysis.21 
In conventional content analysis (inductive approach), 
we will conduct a regression analysis to determine the 
various demographic and clinical characteristics of our 
participants that can affect success of deprescribing. 
These will be used to develop themes and subthemes 
for the thematic analysis, as well as to develop a coding 
scheme. Following which, we will also be using directed 
content analysis (deductive approach), using the inter­
view questions to collect qualitative data and the transcript 
data placed into themes or subthemes.
DISCUSSION
Deprescribing is not yet widely practised in Asian settings 
but has been strongly advocated in many countries 
including Singapore.22 We have adopted the pioneering 
principle from Woodward,11 which looks at discontin­
uation, substitution and reduction, as these can also be 
related to our application of the latest Beers criteria. In 
our nursing home settings, a large proportion of partic­
ipants are cognitive  impaired and will not be able to 
engage in some of the published protocols23 24 due to 
communication capabilities. As such, our study will look 
at the deprescribing process that aims to discontinue, 
substitute and reduce medication.
Our multicentre prospective nursing home study will 
encompass an evaluation of a five-step multidisciplinary 
team-based deprescribing intervention on health and 
pharmacoeconomic outcomes in an Asian nursing home 
setting. This is supplemented by a prestudy interview 
questionnaire that will enable the exploration of the views 
of local healthcare professionals towards deprescribing. 
This work will add knowledge in the field of geriatric care 
and address important outcomes applicable for an esca­
lating global ageing population.
By employing an innovative stepped-wedge design, 
our study will allow each study group to act as its own 
control and preserve the internal validity of the study.25 
This design is particularly suited for ethical evaluation of 
service delivery intervention,26 and we expected it to be 
especially applicable in long-term care facilities such as 
nursing homes.
We anticipate a few challenges for the study. In partic­
ipants who were randomised to waitlist control, some 
participants may require an early review of their medica­
tion before crossing over to intervention. These patients 
will be documented and analysed separately at the end 
of study, although this will inevitably dilute down the 
results of the control group. Another challenge in our 
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population is that a large number of residents are cogni­
tive  impaired, and thus may have limited capabilities 
to be involved in decision making, or participate in the 
prestudy interview questionnaire. Their next of kins may 
not be contactable as well.
Acknowledgements  We would like to thank Dr Karla Hemming for sharing her 
insights on our stepped-wedge design. This study protocol is presented according 
to the SPIRIT 2013 checklist (see online supplementary data).
Contributors  C-HK drafted the manuscript and is the principal investigator. C-HK, 
CYYY, SWHL, VSLM and IY-OL participated in the design of the study presented in 
the manuscript. C-HK, CYYY, CWTC, CWYT and PCT will be conducting the study. All 
authors have reviewed and approved the manuscript.
Competing interests  None declared.
Ethics approval  Domain Specific Review Board (DSRB) Singapore and Monash 
University Human Research Ethics Committee.
Provenance and peer review  Not commissioned; externally peer reviewed.
Open Access  This is an Open Access article distributed in accordance with the 
Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which 
permits others to distribute, remix, adapt, build upon this work non-commercially, 
and license their derivative works on different terms, provided the original work is 
properly cited and the use is non-commercial. See: http://​creativecommons.​org/​
licenses/​by-​nc/​4.​0/
© Article author(s) (or their employer(s) unless otherwise stated in the text of the 
article) 2017. All rights reserved. No commercial use is permitted unless otherwise 
expressly granted.
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controlled trial protocol
study: a stepped-wedge randomised 
Nursing home team-care deprescribing
and Ian Yi-Onn Leong
Wei Yan Tan, Poh Ching Tan, Vivienne SL Mak, Shaun Wen Huey Lee 
Chong-Han Kua, Cindy Ying Ying Yeo, Cheryl Wai Teng Char, Cheryl
doi: 10.1136/bmjopen-2016-015293
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