Drug Methods And Process Guide

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DRUG EVALUATION METHODS AND PROCESS GUIDE
Version 1.0 February 2018

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Table of Contents
Foreword................................................................................................................................................ 1
1.

Introduction .................................................................................................................................... 2

Topic Selection ............................................................................................................................. 2

2.1

Call for drug topics .................................................................................................. 2

2.2

Filtering of topics ..................................................................................................... 3

2.3

Selection of topics ................................................................................................... 4

Technology Evaluation ................................................................................................................ 5
3.1

Type of evaluation................................................................................................... 5

3.2

Evaluation processes .............................................................................................. 6

3.3

Defining the evaluation framework .......................................................................... 9

Scoping .......................................................................................................................................... 9
4.1

Developing the scope ............................................................................................. 9

4.2

Stakeholder Workshop .......................................................................................... 10

4.3

Final scope ........................................................................................................... 10

Evidence Generation and Critical Appraisal ........................................................................... 11
5.1

General principles ................................................................................................. 11

5.2

Types of evidence ................................................................................................. 11

5.3

Evidence submissions from manufacturers ........................................................... 12

The Reference Case .................................................................................................................. 13
6.1

Perspective of the evaluation ................................................................................ 15

6.2

Target population and subgroups.......................................................................... 16

6.3

Comparators ......................................................................................................... 16

6.4

Systematic review of clinical evidence .................................................................. 17

6.4.1

Pairwise meta-analysis .................................................................................. 18

6.4.2

Indirect comparisons and network meta-analyses .......................................... 19

6.5

Economic evaluation ......................................................................................... 20

6.5.1

Type of economic evaluation ......................................................................... 20

6.5.2

Choice of modelling approach ........................................................................ 21

6.5.3

Transformation of evidence............................................................................ 22

6.5.4

Precision of model structure and hypotheses ................................................. 22

6.6

Measuring and valuing health effects .................................................................... 24

6.7

Measurement of costs........................................................................................... 27

6.8

Time horizon ......................................................................................................... 28

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6.9

Discount rate......................................................................................................... 28

6.10

Calibration, face-validity and cross-validation of a model ...................................... 29

6.11

Handling uncertainty and testing robustness of results ......................................... 29

6.12

Budget impact ....................................................................................................... 31

Independent Evidence Review Centres (IERC)..................................................................... 32

Value-Based Pricing................................................................................................................... 32

8.1

Request for Proposal (RFP) .................................................................................. 34

8.2

Notification of Outcome ......................................................................................... 34

8.3

Letter of Acceptance ............................................................................................. 34

8.4

Resubmission of price proposal in response to negative recommendations .......... 35

8.5

Consideration of “me-too” drugs............................................................................ 35

8.6

Consideration of biosimilars .................................................................................. 36

Decision-making ......................................................................................................................... 36
9.1

MOH Drug Advisory Committee (DAC) ................................................................. 36

9.2

Factors informing subsidy decisions ..................................................................... 36

10. Guidance Development and Implementation ......................................................................... 39
10.1

Drafting of guidance .............................................................................................. 39

10.2

Implementation of guidance .................................................................................. 39

10.3

Review of guidance and subsidy recommendations .............................................. 40

Annex 1: Company evidence submission template for full evaluations ........................................ i
Annex 2: Company evidence submission template for expedited evaluations .......................... ix
Annex 3: Proposal for Subsidy Listing (RFP template, Form A) .................................................. xi

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Foreword
The Agency for Care Effectiveness (ACE) is the national health technology assessment (HTA)
agency in Singapore residing within the Ministry of Health. It conducts technical evaluations
to inform subsidy decisions for treatments, and produces guidance on the appropriate use of
treatments for public hospitals and institutions in Singapore.
The ACE Drug Evaluation Methods & Process Guide outlines the core technical methodology
and processes underpinning the assessment of clinical and economic evidence for drugs
which are being considered for government subsidy. This guide is not intended to be a
comprehensive academic document or to describe all technical details relating to health
economic analyses. Rather, the intention of this guide is to standardise and document the
methods that ACE follows for drug evaluations, and increase transparency of our processes
and decision-making frameworks.
While this document forms an important part of the Ministry of Health Drug Advisory
Committee’s (DAC) decision-making processes for drug subsidy, it is only a guide – ACE and
DAC are not bound to adhere to it in every detail, or in every case.
Information in this guide may also be useful for healthcare professionals and pharmaceutical
manufacturers who provide evidence and advice to support ACE’s evaluations. ACE will
continue to review and update this guide to ensure that it remains a useful resource for the
Singapore healthcare system.
Find out more about ACE at www.ace-hta.gov.sg/about

ACE would like to thank the following experts for their comments during the development of
this guide:
 Prof Jonathan Craig, Professor of Clinical Epidemiology, School of Public Health,
University of Sydney, Australia
 Prof Ron Goeree, Professor Emeritus, Department of Health Research Methods,
Evidence and Impact, McMaster University, Canada
 Prof Carole Longson, Director of the Centre for Health Technology Evaluation,
National Institute for Health and Care Excellence (NICE), United Kingdom
 Prof Paul Scuffham, Director, Centre for Applied Health Economics (CAHE), Griffith
University, Australia
 Prof Mark Sculpher, Centre for Health Economics, University of York, United Kingdom
 Prof Robyn Ward, Deputy Vice-Chancellor (Research), The University of Queensland,
Australia

© Agency for Care Effectiveness, Ministry of Health, Republic of Singapore
All rights reserved. Reproduction of this publication in whole or in part in any material form is prohibited without the prior written permission
of the copyright holder. Application to reproduce any part of this publication should be addressed to:
Head (Evaluation)
Agency for Care Effectiveness
Email: ACE_HTA@moh.gov.sg
In citation, please credit the Ministry of Health when you extract and use the information or data from the publication.

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1. Introduction
Health technology assessment (HTA) is an established scientific research methodology to
inform policy and clinical decision-making on the relative value of new health technologies,
such as drugs, devices and medical services, compared to existing standards of care. It is
conducted using analytical frameworks, drawing on clinical, epidemiological and health
economic information, to determine how to best allocate limited healthcare resources.
This document provides an overview of ACE’s HTA methods and processes for the evaluation
of new and existing drugs available in Singapore. It introduces the general methodological
concepts underlying each stage of the evaluation process and outlines the key information
required from manufacturers who submit evidence to inform ACE’s evaluations.
Each core step in the evaluation process is described in sequence, from the selection of the
topics for evaluation, through to evidence generation, value-based pricing, decision-making
then the development of ACE’s guidance (Figure 1).
Figure 1. Overview of drug evaluation process

Specific templates which manufacturers may be asked to complete at various points in the
process are also provided in the Annexes for information.

2. Topic Selection
Topic selection is the process for deciding which drugs and indications (drug topics) are
appropriate for evaluation by ACE. The process has been designed to ensure that the drugs
chosen address priority issues and therapeutic gaps, which will help improve the health of the
population, and will support healthcare professionals to provide appropriate care.

2.1

Call for drug topics

Potential drug topics for technology evaluation are identified predominantly through
applications by individual public healthcare professionals. New and emerging drugs that might
be suitable for evaluation are also identified through literature searches and horizon scanning
by the ACE technical team.

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Public healthcare institutions are invited to submit applications for the inclusion of drug
preparations into the MOH List of Subsidised Drugs on an annual basis (during January to
March). The annual invitation for drug applications is sent to the Chairman of the Medical
Board (or equivalent body) of each institution at the start of each application cycle by the MOH
Drug Advisory Committee (DAC) Secretariat within ACE. All applications should be submitted
to the Chairman of the Medical Board (or equivalent body) for endorsement and collation
before submission to the MOH DAC Secretariat.

2.2

Filtering of topics

Topic selection decisions are based on the consideration of each potential topic against
elimination and prioritisation criteria. The elimination criteria filter out topics which are
unsuitable for evaluation. A topic will not be considered for evaluation by ACE if:




the drug is not registered for use in Singapore by the Health Sciences Authority (HSA)
or
the drug topic is identical to a topic that has been evaluated by ACE within the last
year and guidance is already in development or
there is insufficient evidence available to conduct an evaluation.

The following topic areas are also currently outside the remit of ACE drug evaluations:










Vaccinations (including therapeutic vaccines)
HIV therapy
Blood products
Nutritional products (enteral or parenteral)
Dialysis solutions
Wound dressings
Fertility drugs
Lifestyle drugs
General Sales List (GSL) medications

Off-label use of HSA-registered drugs will only be considered for evaluation on a case-bycase basis if all of the following conditions apply:



the off-label use of the drug is the current standard of care in local clinical practice and
also in line with international best practice;



there is a lack of affordable and cost-effective treatment alternatives to the off-label
drug, and



there is sufficient evidence available to assess the safety, efficacy, and costeffectiveness of the off-label use of the drug.

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2.3

Selection of topics

The need to evaluate each remaining topic is then considered against specific selection
criteria, which seek to measure the population size and disease severity, clinical need for the
new treatment, claimed therapeutic benefit over alternative treatments, and value that ACE
could add in conducting a technology evaluation (Table 1).
Scores are assigned for each criterion to generate a total “need score”. Topics are more likely
to receive a moderate to high need score and be selected for evaluation if the drug represents
a therapeutic gap which is expected to be of significant benefit to patients in terms of clinical
efficacy or improved side-effect profile, and there is sufficient evidence to support an
evaluation.
Table 1. ACE topic selection criteria
No.
1.

Criterion
Type of gap that drug will fill
in clinical practice

Unmet clinical need

Disease severity
a Impact on mortality

4.
5.
6.
7.

b Impact on morbidity and
quality of life
Size of affected population in
Singapore
Comparative clinical
effectiveness (from
published literature)
Relative safety (from
published literature)
Cost-effectiveness (from
published literature)

Definition
Chemical gap: Alternative treatment for the condition of interest
is already subsidised but from a different drug class to the new
treatment.
Therapeutic gap: No treatment for condition of interest is
currently subsidised.
Extent to which condition is currently being adequately treated in
local clinical practice.
Survival or mortality associated with the underlying health
condition
Impact of underlying health condition on morbidity, health related
quality of life or both.
The estimated size of the patient population that is affected by the
underlying health condition and which may be eligible for the new
treatment.
Added or reduced clinical benefit of the new technology
compared to alternatives
Safety of the new technology compared to alternatives.
Dominance or incremental cost-effectiveness of new technology
compared to alternatives.

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3. Technology Evaluation
3.1

Type of evaluation

Topics with moderate to high need scores (following the topic selection process) are prioritised
for evaluation by the DAC. All evaluations are conducted internally by the ACE technical team
with supporting evidence provided by local healthcare professionals from public institutions
and pharmaceutical manufacturers, where required.
Evaluations are conducted at two levels - expedited or full – depending on the estimated
budget impact and uncertainty around the clinical and cost parameters for each drug:





High cost drugs (estimated budget impact >$2 million per year) or drugs which are
expected to have high impact on population health due to superior outcomes relative
to current standard of care are typically subject to full evaluation
Drugs with a lower budget impact (<$1 million per year) or which are already available
as a generic formulation, are subject to expedited evaluation
Drugs with a moderate budget impact (between $1 million to $2 million per year) are
considered for expedited or full evaluation on a case by case basis depending on the
uncertainty around the clinical and cost estimates. Drugs with uncertain estimates are
likely to be subject to full evaluation.

In addition, the extent of information available for evaluation and the availability of ACE
technical resources to conduct the evaluation within the required timeframe is taken into
account when deciding the type of evaluation required.
A summary of the evidence sourced for each evaluation type, the analyses undertaken by
ACE and the average resource required is shown in Table 2.

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Table 2. Evidence and analyses included in expedited and full evaluations
Type of evaluation
Expedited evaluation

Full evaluation

Types of evidence and analyses included in evaluation
 Qualitative written survey of clinical experts to inform local
treatment algorithm, define comparator(s), and describe
current use of drug(s) in local practice and patients’ clinical
need for drug subsidy
 Literature search of published clinical and economic
evidence (local and international studies) and review of
retrieved studies
 Review of previous assessments by international HTA
agencies
 Value-based pricing proposal from manufacturer
 Budget impact analysis, including estimated annual cost to
government for listing drug(s) on SDL or MAF
 Stakeholder workshop with local healthcare professionals
to define the scope of the evaluation
 Systematic review of published clinical evidence (local and
international studies). Indirect comparisons, pairwise metaanalyses and network meta-analyses undertaken if
required.
 Literature search of published economic evidence (local
and international studies) and review of retrieved studies
 Development of economic model (cost-effectiveness
analysis (CEA) or cost-utility analysis (CUA) as
appropriate), using local data inputs where available.
Scenario and sensitivity analyses also undertaken to model
the uncertainty of key model parameters. Cost
minimisation analyses (CMA) may also be undertaken for
class reviews if all drugs are considered clinically
comparable.
 Review of previous assessments by international HTA
agencies
 Value-based pricing proposal from manufacturer
 Budget impact analysis, including estimated annual cost to
government for listing drug(s) on SDL or MAF

FTE Required
2 to 3 months

6 to 9 months

FTE: full-time equivalent. Timelines are indicative. Actual timelines vary depending on the complexity of the topic and the
number of drugs/indications included in each evaluation.

3.2

Evaluation processes

Overviews of the processes for expedited and full evaluations are shown in Figures 2 and 3
respectively.

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Figure 2. Overview of expedited evaluation process for drug topics

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Figure 3. Overview of full evaluation process for drug topics

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3.3

Defining the evaluation framework

Before a technology evaluation commences, the ACE technical team use the PICO framework
(population, intervention, comparators, and health outcome measures) to define the key
elements of interest and the research question that the evaluation is intended to address. This
serves to clearly define the purpose and boundaries of the evaluation, and to assist the ACE
technical team formulate clear search terms (MESH headings) and yield more precise search
results (Table 3).
Table 3. PICO evaluation framework
P
Patient/Population
 Patient or
population
characteristics
 Condition/disease
of interest

I
Intervention/Exposure
Drug(s) under evaluation

C
Comparator
Alternative treatment
option(s) to the
intervention used in
routine clinical practice

O
Outcome
Clinically meaningful health
outcomes of interest

For expedited evaluations, the framework is defined by the ACE technical team in line with the
indication requested for evaluation by healthcare professionals (see Section 2 for topic
selection process).
For full evaluations, the evaluation framework is defined through the scoping process in
consultation with local clinical experts through a stakeholder workshop (Section 4.2).

4. Scoping
4.1

Developing the scope

The scope provides a framework for topics which are subject to full evaluation. Using the
PICO framework, it defines the population, intervention, comparators, and health outcome
measures of interest to inform the economic modelling approach, and sets the boundaries for
the work undertaken by the ACE technical team. A scope is not drafted for topics undergoing
expedited evaluation (because economic modelling is not required), however, PICO elements
are still used to ensure that the research question is properly defined and considered within
the evaluation report.
The issues for consideration in the evaluation that are described in the scope include:




the disease or health condition and the population(s) for whom treatment with the drug
is being evaluated
use of the drug in local clinical practice (and the setting for its use; for example, hospital
[inpatient and outpatient] or community if relevant)
the relevant comparator treatments, which reflect the treatments used in current clinical
practice in Singapore to manage the disease or condition (this may include off-label
alternatives if they constitute routine care)

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


the principal health outcome measures appropriate for the analysis, including the
length of time over which the benefits and costs will be considered
consideration of patient subgroups for whom the drug might be particularly clinically
and/or cost effective.

A draft scope is developed by the ACE technical team. Two healthcare professionals who
have expertise in the disease area under evaluation are invited to review the draft scope and
provide their views on the use of the drug in relation to current local clinical practice. The draft
scope is then revised by the ACE technical team in line with comments received, and is sent
to all stakeholders who have confirmed their attendance at the stakeholder workshop.

4.2

Stakeholder Workshop

To ensure that the evaluation framework for the full evaluation is appropriately defined with
relevance to local clinical practice and patient need, ACE holds a roundtable workshop with
healthcare professionals with expertise in the disease area or the use of the drug under
evaluation.
The aims of the workshop are to:



ensure that the scope is appropriately defined
seek further advice from healthcare professionals on:
 variations between groups of patients, in particular, differential baseline risk of the
condition and potential for different subgroups of patients to benefit
 appropriate outcomes and surrogate outcome measures
 significance of side effects or adverse reactions and the clinical benefits expected
(from clinical trials) or realised in local practice (if drug is already in use in
Singapore)
 relevant potential comparators
 requirements to implement any guidance on the use of the drug, including need for
extra staff or equipment; education and training requirements for hospital staff
before using the drug; and ways in which adherence to treatment can be improved.
 how response to treatment is assessed in clinical practice, and the circumstances
in which treatment might be discontinued.

Additional details about the proposed economic modelling approach, input parameters and
assumptions, may also be shared by the ACE technical team at the workshop to elicit feedback
from the stakeholders.

4.3

Final scope

After the stakeholder workshop, the ACE technical team finalises the scope, taking into
account the discussions at the workshop. The final scope is shared with the manufacturer of
the drug under evaluation if they intend to provide clinical and/or cost information to support
ACE’s evaluation.

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5. Evidence Generation and Critical Appraisal
5.1

General principles

Consideration of a comprehensive evidence base is fundamental to the evaluation process.
While information from multiple sources may inform the evaluation, ACE’s preference for
different types of evidence to determine comparative treatment effectiveness is influenced by
the hierarchy of scientific literature (Table 4).
Table 4. Hierarchy of scientific literature
1.
2.
3.
4.
5.
6.
7.

Systematic reviews or meta-analysis
Randomised controlled trials (RCTs)
Non-randomised controlled trials
Cohort studies
Case-control studies
Descriptive studies, limited series
Anecdotal evidence, position papers, non-systematic reviews, expert opinion

When sourcing information, secondary studies, such as systematic reviews and assessments
of published information (including HTA reports and clinical guidelines) are typically retrieved
first, before primary studies (individual trials). Among primary studies, randomised controlled
trials (RCTs) are generally considered to provide the highest standard of evidence on
comparative treatment effectiveness. Data from non-randomised studies may also be required
to supplement RCT data and inform other evaluation parameters such as costs and utility
values.

5.2

Types of evidence

A summary of the different types of evidence used to inform ACE’s drug evaluations, and the
considerations made by ACE when using each type of evidence are shown in Table 5.
Table 5. Types of evidence considered in ACE evaluations
Evidence type
Randomised
controlled trials

Considerations
 Randomised controlled trials (RCTs) are considered to be appropriate for measures
of relative and absolute treatment effects. If randomisation is conducted properly,
observed and unobserved characteristics should be balanced between the
randomised groups, so the effect of treatment versus the control on the observed
outcomes can be inferred.
 The relevance of RCT evidence to the evaluation depends on both the external and
internal validity of each trial:


Internal validity is assessed according to the design and conduct of a trial
and includes blinding (when appropriate), the method of randomisation
and concealment of allocation, and the completeness of follow-up. Other
important considerations are the size and power of the trial, the selection
and measurement of outcomes and analysis by intention to treat.

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

Non-randomised
evidence




Real world data




Qualitative
research



Economic
evaluations




Unpublished
evidence



5.3

External validity is assessed according to the generalisability of the trial
evidence; that is, whether the results apply to wider patient groups (and
over a longer follow-up), Asian populations, and to routine clinical practice
in the local context.
In non-randomised studies (such as observational or epidemiological studies), the
treatment assignment is non-random, and the mechanism of assigning patients to
alternative treatments is usually unknown. Hence, the estimated effects of treatment
on outcomes are subject to treatment selection bias, and this should be recognised
in the interpretation of the results.
Inferences will necessarily be more cautious about relative treatment effects drawn
from studies without randomisation or control groups than those from RCTs. The
potential biases of non-randomised studies should be identified, and ideally
quantified and adjusted for.
Evidence from non-randomised sources is often used to obtain non-clinical model
parameters such costs and utility values. As study quality can vary, critical appraisal
and sensitivity analyses are important for review of these data.
In its broad definition, real world data encompasses all non-randomised evidence
and can include data generated as part of pragmatic controlled trials; however, in
HTA, it typically presents as observational data from patient registries,
administrative databases, electronic medical records and surveys.
The quality of real world data can vary across different data types and sources. To
mitigate potential bias, careful study design is needed and an analysis plan should
be created prior to retrieving and analysing real world data.
Qualitative research, in the form of questionnaire or survey responses from clinical
professionals, is often used to explore areas such as patients' experiences of having
a disease and/or specific treatment, and clinicians’ views on the role of different
types of treatment in local clinical practice.
Evidence on the cost effectiveness of the drug under evaluation may be obtained
from new analyses conducted by the ACE technical team (for full evaluations);
however, a comprehensive search of published, relevant evidence on the cost
effectiveness of the drug is also conducted to inform the evaluation.
Economic evaluations should quantify how the treatments under comparison affect
disease progression and patients' health-related quality of life, and value those
effects to reflect the preferences of the general population.
To ensure that the evaluation does not miss important relevant evidence, attempts
are made to identify evidence that is not in the public domain. Such evidence
includes unpublished clinical trial data such as those in clinical study reports (which
is preferred over data in poster or abstract form only).
If unpublished evidence is used to populate an economic model, such information
should be critically appraised and, when appropriate, sensitivity analysis conducted
to examine the effects of its inclusion or exclusion.

Evidence submissions from manufacturers

For topics which are subject to full evaluation, concise evidence submissions (up to 35
pages) are invited from the manufacturer of the drug under evaluation as supplementary
evidence to ACE’s assessment. The information in the submission should be in line with the
evaluation framework set out in the final scope, and provided within the company evidence
submission template for full evaluations (Annex 1). A separate Excel workbook to summarise
cost information (Costing template for manufacturers) should also be included alongside
evidence submissions for full evaluations. Manufacturers who express interest in submitting
evidence to inform a full evaluation, will be given 8 weeks to complete the templates.

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For topics which are subject to expedited evaluation, a brief summary (up to 5 pages) of key
clinical evidence may be submitted by manufacturers with their Call for Proposal for Subsidy
Listing (see section 8.1). Evidence should be submitted within the company evidence
submission template for expedited evaluations (Annex 2) within the required timelines
(typically 6-8 weeks).
It is not mandatory for manufacturers to complete an evidence submission for full or expedited
evaluations. The topic will still be evaluated by the ACE technical team and presented to the
DAC to inform subsidy considerations, irrespective of manufacturer involvement.

6. The Reference Case
The DAC has to make subsidy decisions across different drugs and disease areas. It is
therefore crucial that analyses of clinical and cost effectiveness undertaken to inform the
evaluation adopt a consistent approach. To allow this, ACE has defined a 'reference case' with
an aim to promote high-quality analysis and encourage consistency in analytical approaches.
Although the reference case specifies the preferred methods followed by ACE, it does not
preclude the DAC's consideration of non-reference-case analyses if appropriate. The key
elements of analysis using the reference case are summarised in Table 6.
Table 6. ACE's reference case for drug evaluations
Component of drug
evaluation
Perspective of the
evaluation

Reference Case






Target population and
subgroups





Comparators




Only direct health-care costs from the perspective of the
health-care payer should be included in reference case
analyses; this includes payments out of the government’s
health-care or insurance budget as well as patients’ copayments including Medisave and out of pocket expenses
Health outcomes measured in patients and valued from a
healthcare payer perspective
If characteristics of treatments have a value to people
independent of any direct effect on health, the nature of
these characteristics should be clearly explained and if
possible the value of the additional benefit should be
quantified
Productivity costs may be presented as secondary
analyses (not in the reference case)
Consistent with the patient population defined in evaluation
framework
Subgroup analyses if appropriate (statistical) justification is
provided
Epidemiological data for Singapore presented for the entire
target population and relevant subgroups
Comparator(s) should be used to allow a robust
assessment of relative clinical and cost effectiveness
Comparator(s) should reflect either the treatment that is
most likely to be replaced by the new treatment or, in case
of add-on treatments, the current treatment without the addon product

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

Systematic review



Economic evaluation















Calculation of costs



Measuring and valuing
health effects




Comparisons with treatments which are used off-label for
the indication under evaluation are allowed only if they
reflect common practice in the local setting
Systematic review of the existing clinical studies on the
intervention and comprehensive search of published
economic studies: best available up-to-date evidence for
clinical effectiveness of the technology and its costeffectiveness relative to its comparator(s); ongoing studies
should be mentioned
Reproducible search strategy
Transparent selection criteria and selection procedures
Critical appraisal and quality assessment of the evidence
For treatments which are non-inferior (comparable
effectiveness and safety) to the comparator(s), a costminimisation analysis (CMA) should be undertaken
Cost-effectiveness analysis (CEA) should only be carried
out for full evaluations if the technology is clinically superior
to, and more costly than the main comparator. CEA is not
conducted for expedited evaluations.
CEA should be undertaken for full evaluations to establish
whether differences in expected costs between treatment
options can be justified in terms of changes in expected
health effects
Cost-utility analysis (CUA) should be used in full
evaluations if the treatment has an impact on health-related
quality of life that is significant to the patient or if there are
multiple patient-relevant clinical outcome parameters
expressed in different units
Results expressed as incremental cost-effectiveness or
cost–utility ratios with their associated upper and lower
limits
If an incremental cost–utility ratio is presented as a base
case result, corresponding cost per life-year gained should
also be presented (if mortality benefits are shown)
Economic models should be based on data from clinical
studies comparing the study treatment and the comparator,
on data from validated databases and/or data from
literature
Justification of model structural assumptions and data
inputs should be provided. When there are alternative
plausible assumptions and inputs, sensitivity analyses of
their effects on model outputs should be undertaken.
The identification, measurement and valuation of costs
should be consistent with the perspective of the Singapore
health-care payer (government, insurance provider and
patient health costs)
Non–healthcare costs or unrelated healthcare costs should
not be included in the reference case analysis, but are
permitted in secondary analyses
Final, clinically meaningful outcomes, preferably clearly
defined outcome measures, for which there is little debate
about the measurement methods
CEA: life years gained for chronic conditions and acute
conditions with long-term sequelae or a relevant short-term
outcome for acute conditions with no long term
consequences
CUA: QALYs gained
Life expectancy estimates based on Singapore age-specific
life tables

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

Time horizon



Discount rate




Handling uncertainty





Budget impact analysis






6.1

Health-related quality of life weights based on empirical
data either from the literature or ideally from a
representative sample of the general public in Singapore
Quality of life weights derived with generic instrument (e.g.
EQ-5D)
The time horizon for estimating clinical and cost
effectiveness should be sufficiently long to reflect all
important differences in costs or outcomes between the
treatments being compared
Costs and benefits are discounted at 3%
Other scenarios can be presented to test sensitivity of
results to discount rate applied
Explore all relevant structural, parameter source, and
parameter precision uncertainty
One way deterministic sensitivity analysis should be
presented for all uncertain parameters
Multivariate probabilistic sensitivity analysis may also be
performed to address simultaneous impact of all uncertain
parameters
Budget impact analyses conducted for full evaluations
should follow these principles:
Target population: The analysis should estimate the
potential size of the target population and its potential
evolution over time (e.g. shifts in incidence, prevalence,
disease severity). The methods used to estimate the
population size should be described and justified. The
degree of penetration of the intervention in the targeted
population (e.g. detection rate, compliance, market share
etc.) needs to be considered and justified.
Comparator: The analysis should calculate the predicted
financial impact of subsidising an intervention compared to
the current situation
Costs and outcomes: Tariffs and prices should be kept
constant over the years (i.e. not inflated). The cost
consequences of the treatment effect, side effects and
other short and long-term consequences (e.g. follow-up
treatment) should be included in the analysis
Time horizon: The time horizon depends on the time
needed to reach a steady state. It is recommended to
present the budget impact up to the steady state, with a
time horizon of three to five years.
Discount rate: Future costs and savings should not be
discounted

Perspective of the evaluation

The reference case analysis should only include direct healthcare costs from the
perspective of the healthcare payer. This includes payments out of the government’s
and insurance providers’ healthcare budget as well as patients’ co-payments. Health
outcomes should also be valued from a healthcare payer perspective.

Costs and outcomes should be relevant for the patient population involved in the treatment
and valued from a healthcare payer perspective. This includes costs paid out of the
government’s and insurance providers’ healthcare budget and patients’ co-payments for
healthcare, including Medisave and out-of-pocket expenses.

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The reference-case perspective on health outcomes aims to maximise health gain from
available healthcare resources. If characteristics of a treatment have a value to people
independent of any direct effect on health (for example, important reductions in the absence
for work or productivity costs), the nature of these characteristics should be clearly explained
and if possible the value of the additional benefit should be quantified (for consideration as
secondary analyses only).

6.2

Target population and subgroups

The patient population should be consistent with that which is defined in the
evaluation framework. If the clinical and/or cost-effectiveness of treatment differs
between subgroups, separate subgroup analyses should be performed, provided that
appropriate (statistical) justification is given.
The target population should be consistent with the population described in the evaluation
framework (and/or scope) and in line with the population in the registered indication for the
drug under evaluation unless off-label use is being considered (see section 2.2).
For many drugs, the capacity to benefit from treatment will differ for patients depending on
their characteristics. This should be explored as part of the reference-case analysis by
providing estimates of clinical and cost effectiveness separately for each relevant subgroup of
patients. The characteristics of patients in the subgroup should be clearly defined and should
preferably be identified on the basis of an expectation of differential clinical or cost
effectiveness because of known, biologically plausible mechanisms, social characteristics or
other clearly justified factors. When possible, potentially relevant subgroups will be identified
when the evaluation framework is defined with consideration being given to the rationale for
expecting a subgroup effect. However, this does not preclude the identification of subgroups
later in the process.

6.3

Comparators

The drug should be compared with the most relevant alternative treatment for the
condition under evaluation. This is either the treatment that is most likely to be
replaced by the new treatment in local clinical practice or, in the case of add-on
treatments, the current treatment without the add-on treatment. In some cases,
multiple treatments will have to be included as comparators.
Comparisons with treatments which are used off-label for the indication under
evaluation are allowed only if they reflect common practice in the local setting. The
choice of the comparator(s) should always be justified.

Comparator(s) defined in the evaluation framework (and/or scope) should be used to allow a
robust assessment of relative clinical and cost effectiveness.

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The comparator can be another medical treatment, best supportive care, watchful waiting or
doing nothing (no intervention).
When the comparator is a medical treatment, it should represent a treatment with proven
efficacy that is used in established clinical practice in Singapore for the target indication. It
may not necessarily be the comparator in the pivotal clinical trials. It is the treatment that most
prescribers would replace with the new treatment if it became subsidised. Multiple
comparators can be considered if relevant to local clinical practice.
In the case of an add-on treatment, the comparator is the current standard treatment in clinical
practice without the add-on treatment.
The choice of the comparator should always be justified. Treatments which are used off-label
in routine clinical practice in Singapore for the indication under evaluation can be considered
as valid comparators in the economic evaluation.

6.4

Systematic review of clinical evidence

Each evaluation should include a systematic review of the existing clinical studies
on the intervention. The search strategy should be reproducible and selection criteria
and procedures clearly presented. The review should reveal the best available up-todate evidence for clinical effectiveness of the drug relative to its comparator(s). The
evidence should be critically appraised and its quality assessed.
Estimates of the mean clinical effectiveness of the treatments being compared must
be based on data from all relevant studies of the best available quality and should
consider the range of typical patients, normal clinical circumstances, clinically
relevant outcomes, comparison with relevant comparators, and measures of both
relative and absolute effectiveness with appropriate measures of uncertainty.
For a full overview of the clinical effectiveness of a drug, a systematic literature review should
be conducted.
A systematic approach to literature searching ensures that:




the literature is identified in accordance with an explicit search strategy
the literature is selected on the basis of defined inclusion and exclusion criteria
the literature is assessed using recognised methodological standards.

The methodology used for the literature search should be clear and reproducible. The search
algorithm should be presented, including search terms used for each database and the study
selection criteria. The search strategy should be developed in line with the evaluation
framework and/or final scope.
Once the search strategy has been developed and literature searching undertaken, a list of
possible studies should be compiled. Each study must be assessed to determine whether it

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meets the inclusion criteria of the review. A list of ineligible studies should be produced with
the justification for why studies were included or excluded. A flow diagram, specifying the yield
and exclusions (with the reason for exclusion) should be presented. Each study meeting the
criteria for inclusion should be critically appraised and have its quality assessed.
Randomised controlled trials (RCT) directly comparing the drug under evaluation with relevant
comparators provide the most valid evidence of relative efficacy and safety. However, such
evidence may not always be available and may not be sufficient to quantify the effect of
treatment over the course of the disease. Therefore, data from non-randomised studies may
be required to supplement RCT data. Any potential bias arising from the design of the studies
used in the assessment should be explored and documented. The external validity of study
results included in the review, and their applicability to local clinical practice in Singapore
should be assessed.
Many factors can affect the overall estimate of relative treatment effects obtained from a
systematic review. Some differences between studies occur by chance, others from
differences in the characteristics of patients (such as age, sex, severity of disease, choice and
measurement of outcomes), care setting, additional routine care and the year of the study.
Such potential treatment effect modifiers should be identified before data analysis, either by a
thorough review of the subject area, extrapolation from relevant studies, or discussion with
experts in the clinical discipline.
6.4.1

Pairwise meta-analysis

Synthesis of outcome data through meta-analysis is appropriate provided there are sufficient
relevant and valid data using measures of outcome that are comparable.
The characteristics and possible limitations of the data (that is, population, intervention,
setting, sample size and validity of the evidence) should be fully reported for each study
included in the analysis and a forest plot included.
Statistical pooling of study results should be accompanied by an assessment of heterogeneity
(that is, any variability in addition to that accounted for by chance) which can, to some extent,
be taken into account using a random (as opposed to fixed) effects model. However, the
degree of, and the reasons for clinical and methodological heterogeneity should be explored
as fully as possible. Known clinical heterogeneity (for example, because of patient
characteristics) may be explored using subgroup analyses and meta-regression. If the risk of
an event differs substantially between the control groups of the studies in a meta-analysis, an
assessment of whether the measure of relative treatment effect is constant over different
baseline risks should be carried out. This is especially important when the measure of relative
treatment effect is to be used in an economic model and the baseline rate of events in the
comparator arm of the model is very different to the corresponding rates in the studies in the
meta-analysis.

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6.4.2

Indirect comparisons and network meta-analyses

Data from head-to-head RCTs should be presented in the reference-case analysis. When
treatments are being compared that have not been evaluated within a single RCT, data from
a series of pairwise head-to-head RCTs should be presented together with a network metaanalysis if appropriate. The DAC will take into account the additional uncertainty associated
with the lack of direct evidence when considering estimates of relative effectiveness derived
from indirect sources only. Transitivity (consistency between direct and indirect evidence) is
also examined. The principles of good practice for standard pairwise meta-analyses should
also be followed in adjusted indirect treatment comparisons and network meta-analyses.
Heterogeneity between results of pairwise comparisons and inconsistencies between the
direct and indirect evidence on the technologies should be reported. If inconsistencies within
a network meta-analysis are found, then attempts should be made to explain and resolve
them.
In all cases when evidence is combined using adjusted indirect comparisons or network metaanalysis frameworks, trial randomisation must be preserved, that is, it is not acceptable to
compare results from single treatment arms from different randomised trials (also known as
naïve indirect comparison). If this type of comparison is presented, the data will be treated as
observational in nature and associated with increased uncertainty.
When sufficient relevant and valid data are not available to include in pairwise or network
meta-analyses, the analysis may have to be restricted to a narrative overview that critically
appraises individual studies and presents their results. In these circumstances, the DAC will
be particularly cautious when reviewing the results and in drawing conclusions about the
relative clinical effectiveness of the treatment options.

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6.5

Economic evaluation

For treatments which are non-inferior (comparable effectiveness and safety) to their
comparator(s), a cost-minimisation analysis (CMA) should be undertaken.
A cost-effectiveness analysis (CEA) should only be carried out for full evaluations if
the technology is clinically superior to the main comparator. It should be undertaken
to establish whether differences in expected costs between treatment options can be
justified in terms of changes in expected health effects.
Cost-utility analysis (CUA) should be used if the treatment has an impact on healthrelated quality of life that is significant to the patient or if there are multiple patientrelevant clinical outcome parameters expressed in different units.
Results should be expressed as incremental cost-effectiveness or cost-utility ratios
with their associated upper and lower limits. If an incremental cost-utility ratio is
presented as a reference case analysis result, the corresponding cost per life-year
gained should also be presented, if appropriate.
Economic models should be based as much as possible on data from clinical studies
comparing the study treatment and the comparator, on data from validated databases
and/or data from literature. Model inputs and outputs should be consistent with
existing data and have face validity. Justification of model structural assumptions
and data inputs should be provided. When there are alternative plausible
assumptions and inputs, sensitivity analyses of their effects on model outputs should
be undertaken.
6.5.1

Type of economic evaluation

For topics subject to expedited evaluation, the cost-effectiveness of the intervention relative
to its comparator(s) is determined based on a comprehensive review of published literature.
Cost minimisation analysis (CMA) is conducted by the ACE technical team for both expedited
and full evaluations when relevant:


Cost-minimisation analysis (CMA)
Cost minimisation analyses are used if the effects of two treatments are comparable.
It considers that there is no net health change involved in moving from one treatment
to another; hence cost-effectiveness decisions can be made on the basis of the
difference in the total cost alone, i.e. the treatment with the lowest cost is considered
the most cost effective option.
In addition to CMA, other evaluations, including CEA or CUA may be conducted by the
ACE technical team for full evaluations.



Cost-effectiveness analysis (CEA)
In cost-effectiveness analyses the outcome should be expressed in terms of life years
gained, unless there are compelling arguments to use another physical or clinical
outcome variable (e.g. in case of acute diseases without long-term sequelae). The
result of a cost-effectiveness analysis is expressed as an incremental cost-

Driving better decision-making in healthcare

effectiveness ratio (ICER). The ICER reflects the additional (incremental) cost per
additional unit of outcome achieved.


Cost-utility analysis (CUA)
Cost-utility analysis is used for economic evaluations that include health-related quality
of life in the assessment of treatment outcome. They should be undertaken if the
treatment has an impact on health-related quality of life that is significant to patients or
the treatment is associated with multiple clinical outcomes that are expressed in
different units (e.g. side effects versus survival). Cost-utility is not relevant in all disease
areas or treatment situations. For instance, very serious infections associated with a
high short-term mortality rate but little quality of life consequences in survivors (e.g.
pneumonia), it is more important to look at survival than to health-related quality of life
and hence a cost-effectiveness analysis may be more appropriate.
Currently, the quality-adjusted life year (QALY) is considered to be the most
appropriate generic measure of health benefit that reflects both mortality and healthrelated quality of life effects.
ICERs reported must be the ratio of expected additional total cost to the expected
additional QALYs compared with alternative treatment(s).

6.5.2

Choice of modelling approach

Modelling provides an important framework for synthesising available evidence and
generating estimates of clinical and cost effectiveness in a format relevant to the DAC's
decision-making process (see section 9). Situations when modelling is likely to be required
include those when:







all the relevant evidence is not contained in a single trial
patients participating in trials do not represent the typical patients likely to use the
treatment in Singapore
intermediate outcome measures are used rather than effect on health-related quality
of life and survival
relevant comparators have not been used or trials do not include evidence on relevant
populations
clinical trial design includes crossover (treatment switching) that would not occur in
clinical practice
costs and benefits of the treatment and comparator(s) extend beyond the trial followup period.

Different types of models can be used, the major categories being decision trees, Markov
models, partitioned survival models and discrete event simulation models. The main principle
is that a model should be kept as simple as possible while reflecting sufficient clinical reality,
and that its internal structure should be consistent with proven or generally accepted
relationships between parameters and health states. The more complex the model, the less
likely it is that sufficient data are available to populate it.

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Guidelines for good modelling practices have been developed by the modelling task force of
ISPOR (http://www.ispor.org/workpaper/healthscience/tfmodeling.asp), which are followed by
the ACE technical team whenever a model is required. Key considerations relating to the
development of models are summarised below (sections 6.5.3 and 6.5.4).
6.5.3

Transformation of evidence

Economic evaluations should ideally be based on studies that report clinically important
outcome measures. Surrogate measures should only be used where no alternative health
outcome data are available. Caution should be used when using surrogate measures, as they
may not necessarily translate into clinically relevant and effective outcomes. If there is
uncertainty about the clinical significance of endpoints or the correlation between surrogate
measure and clinical outcomes, conservative assumptions should be applied in the evaluation
regarding their impact (short and/or long term) on survival and/or health-related quality of life.
Where possible, clinical trials demonstrating superiority should be analysed using data from
the intention-to-treat (ITT) population, rather than per protocol (PP), in order to take account
of outcomes from all patients irrespective of whether they received treatment.
All statistically significant clinical events (p<0.05) should typically be included in the economic
evaluation. In some cases, clinical events that are considered statistically non-significant (with
a p value larger than 0.05), may still be clinically significant and should be incorporated into
the economic model because the magnitude of clinical relevance overrides the statistical
aspects. Likewise, in some cases, a result considered to be statistically significant should not
be used if it has no meaningful clinical effects.
The exclusion of any statistically significant event from the evaluation should be justified and
the impact of including or excluding certain parameters should be tested in sensitivity
analyses.
Data from clinical trials and other sources need to be translated into an appropriate form for
incorporation into a model. Modelling may require:





extrapolating data beyond the trial period to the longer term
translating surrogate endpoints to obtain final outcomes affecting disease progression,
overall survival and/or quality of life
generalising results from clinical trials to the Singapore clinical setting
using indirect comparisons where the relevant head to head trials do not exist.

The methodology, limitations, and any possible biases associated with extrapolating and
incorporating data should be clearly described and explored through sensitivity analysis. In
the absence of conclusive data, conservative assumptions should be applied in the economic
evaluation and tested through sensitivity analyses.
6.5.4

Precision of model structure and hypotheses

The methods of quality assurance used in the development of the model should be described
and the methods and results of model validation should be provided. All assumptions made in

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the model should be documented and justified, and tested in the sensitivity analysis to show
the robustness of the results.
The population for which outcomes are modelled should be specified. This may be a
hypothetical population, but should be consistent with the target population for the drug and
the sources used for valuing the modelling input parameters. All variables in the model and
their sources must be documented.
Clinical trial data generated to estimate treatment effects may not sufficiently quantify the risk
of some health outcomes or events for the population of interest or may not provide estimates
over a sufficient duration for the economic evaluation. The methods used to identify and
critically appraise sources of data for economic models should be stated and the choice of
particular data sets should be justified with reference to their suitability to the population of
interest in the evaluation. Preference is given to peer-reviewed publications or primary data
as the source for the input parameters’ values.
Sources used for valuation of costs and assessment of probabilities should also be presented
and described in detail.
If no published evidence is available, expert panel consultation is an acceptable source of
input; however the need for using expert opinion should be well justified, and the number of
experts consulted and their field of expertise should be documented.
Abstracts and oral presentations usually provide insufficient information to assess the quality
of their contents. They should be avoided as a source for input values.
For models that extrapolate to longer time periods, such as for chronic conditions or diseases
with long-term sequelae, the assumptions used to extrapolate the impact of treatment over
the relevant time horizon should have both external and internal validity and be reported
transparently. The external validity of the extrapolation should be assessed by considering
both clinical and biological plausibility of the inferred outcome as well as its coherence with
external data sources such as historical cohort data sets or other relevant clinical trials.
Internal validity should be explored and when statistical measures are used to assess the
internal validity of alternative models of extrapolation based on their relative fit to the observed
trial data, the limitations of these statistical measures should be documented. Alternative
scenarios should also be routinely presented to compare the implications of different
extrapolation approaches on the results.
The scenarios should all be presented as part of the reference case analysis. By presenting
different, sometimes extreme, scenarios, the uncertainty related to the effectiveness of the
treatment in the extended period can be assessed. The presentation of scenarios is the most
transparent way to show how robust the results are to the extrapolation approach used. Each
scenario should be accompanied by appropriate sensitivity analyses on uncertain parameters.
In randomised controlled trials, participants randomised to the control group are sometimes
allowed to switch treatment group and receive the active intervention. In these circumstances,
when intention-to-treat analysis is considered inappropriate, statistical methods that adjust for
treatment switching can also be presented. Simple adjustment methods such as censoring or
excluding data from patients who crossover should be avoided because they are very

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susceptible to selection bias. The relative merits and limitations of the methods chosen to
explore the impact of switching treatments should be explored and justified with respect to the
method chosen and in relation to the specific characteristics of the data set in question. These
characteristics include the mechanism of crossover used in the trial, the availability of data on
baseline and time-dependent characteristics, and expectations around the treatment effect if
the patients had remained on the treatment to which they were allocated.

6.6

Measuring and valuing health effects

The measure of health outcome should capture positive and negative effects on
length of life and quality of life and should be generalisable across disease states.
For cost-utility analyses, health effects should be expressed in quality adjusted life
years (QALYs). The measurement of changes in health-related quality of life should
be reported directly from patients and the utility of these changes should be based
on public preferences using a generic instrument, such as EQ-5D.
For cost-effectiveness analyses, outcomes should be expressed in terms of life years gained
for chronic conditions and acute conditions with long-term sequelae or a relevant short-term
outcome for acute conditions with no long-term consequences.
For cost-utility analyses, quality adjusted life years (QALYs) should be calculated. A QALY
combines both quality of life and life expectancy into a single index. The valuation methods
for health-related quality of life should be equal for all comparators. In calculating QALYs, each
of the health states experienced within the time horizon of the model is given a utility reflecting
the health-related quality of life associated with that health state. The duration of time spent in
each health state is multiplied by the utility. Deriving the utility for a particular health state
usually comprises 2 elements: measuring health-related quality of life in people who are in the
relevant health state and valuing it according to preferences for that health state relative to
other states (usually perfect health [=1] and death [=0]). When it is not possible to obtain
measurements of health-related quality of life directly from patients, data should be obtained
from the person who acts as their carer in preference to healthcare professionals. The
valuation of health-related quality of life (which leads to the calculation of utility values) should
be based on empirical data, obtained with a descriptive system for health status for which
corresponding preference values exist from the general public. The use of Singaporean
preference values is preferred if available.
Utility values should be derived with a generic instrument (such as EQ-5D). A summary of
valid and reliable instruments which are used widely in economic evaluations is shown in Table
7.

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Table 7. Generic instruments as measures of utility
Instrument Overview
EQ-5D-5L Description: The EQ-5D classification system comprises 5 dimensions (mobility, self-care,
usual activities, pain/discomfort and anxiety/depression), with each dimension being subdivided
into 5 levels (no problems, slight problems, moderate problem, severe problems and extreme
problems); the profile system comprises 3125 possible health states. In the EQ-5D
questionnaire, the patient describes his or her own current health status in relation to the 5
dimensions and then on a visual analogue scale (VAS) with endpoints of 0 (worst health state)
and 100 (best health state); the information can be compared over time for the same patient
before and after treatment, with data from other patients or from the general population.
Index score: Where EQ-5D is used as a utility measure, patients’ responses about their own
health over time are collected and then each health state is assigned an index score using
population based preference values for the 3125 possible health states. Preference values are
based on time trade-off and VAS rating methods.
Use: EQ-5D is self-completed by the patient and takes only a few minutes to complete. The
instrument is recommended for cost-effectiveness analysis in both the USA (Washington Panel
on Cost Effectiveness in Health & Medicine) and the UK (National Institute for Health and Care
Excellence, NICE). There is no copyright on EQ-5D, but users are expected to register their
study on the EuroQol Group’s website, which also provides information on the instrument’s use,
alternative versions (e.g. telephone/proxy versions, translations, child version) and publications;
http://www.euroqol.org.
SF-36

Description: SF-36 was developed as a profile measure and comprises 36 items, which are
subdivided into 8 dimensions: physical function, role limitation due to physical problems, bodily
pain, general health perception, energy/vitality, social functioning, role limitation due to
emotional problems, and mental health. The answers to the questions in the original version
vary from dichotomous (yes/no) to 6-point Likert scales. Scores are calculated for each of the 8
dimensions, and they can be transformed on a scale from 0 to 100 by summing the answers
under each dimension; a higher score indicates a better health status. Scores on the 8
dimensions can be further summed as a physical (PCS, Physical Component Summary) and a
mental (MCS, Mental Component Summary) component.
Index score: An index measure (SF-6D) has been developed using standard gamble values to
describe health status on the basis of six of the original dimensions.
Use: SF-36 is self-completed by the patient and takes about 10 minutes. There is copyright on
the use of the SF instruments; see http://www.qualitymetric.com.

HUI Mark 3 Description: The 8 dimensions in HUI3 are vision, hearing, speech, ambulation, dexterity,
emotion, cognition and pain; in total, 972,000 health states are described.
Index score: HUI3 can be used as a utility measure. The scoring system uses multiplicative
multi-attribute utility functions (MAUFs), where preference values based on the standard
gamble method have been generated among the general population in Hamilton, Ontario.
Use: HUI3 has been included in all major health studies of the Canadian population since 1990.
There is copyright on the use of the HUI instruments; see http://www.fhs.mcmaster.ca/hug/.
AQoL

Description: The Assessment of Quality of Life (AQoL) instruments (4D, 6D, 7D, 8D) are multiattribute tools covering 4, 6, 7 or 8 dimensions from the following: independent living, mental
health, relationships, senses, coping, pain, happiness, self-worth, and visual impairment.

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Scores from the dimensions provide a health profile, but the primary purpose of the instrument
is to provide a utility index for quality of life.
Index score: AQoL preference values are calculated without the “illness” dimension and are
based on multi-attribute utility theory. Within each dimension, each level is assigned a
preference value, which is obtained from a random sample taken from the general (Australian)
population; these values are then combined in dimension scores, which are also combined.
Use: As AQoL is relatively new, experience with the instrument is limited. Nevertheless, there
have been a number of comparative studies of AQoL and other utility measures. Use of AQoL
is free of charge; users are asked to register their study; see
http://www.psychiatry.unimelb.edu.au/qol/aqol/use_aqol.html

Scenarios with validated disease-specific measures for health-related quality of life can be
presented as supplementary analyses. A disease-specific measure limits the ability of the DAC
to make reasoned trade-offs between competing investments in different disease states, and
can undermine comparability and consistency in decision-making, therefore it should not be
used in the reference case.
Life expectancy estimates should be based on age-specific life tables for Singapore. These
data are available at the Department of Statistics Singapore (https://www.singstat.gov.sg).
If not available in the relevant clinical trials, utility data can be sourced from the literature.
When obtained from the literature, the methods of identification of the data should be
systematic and transparent. The justification for choosing a particular data set should be
clearly explained. When more than 1 plausible set of utility data is available, sensitivity
analyses should be carried out to show the impact of the alternative utility values.
Mapping valuations from other health-related quality of life instruments (e.g. disease-specific
instruments or another generic instrument) to EQ-5D public preference values is only
recommended if mapping functions are based on and validated with empirical data. The
mapping function chosen should be based on data sets containing both health-related quality
of life measures and its statistical properties should be fully described, its choice justified, and
it should be adequately demonstrated how well the function fits the data. Sensitivity analyses
to explore variation in the use of the mapping algorithms on the outputs should be presented.

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6.7

Measurement of costs

The identification, measurement and valuation of costs should be consistent with
the perspective of the Singapore healthcare payer (government, insurance provider
and patient). Non-healthcare costs or unrelated health care costs should not be
included in the reference case analysis.
Validated sources should be used for the unit costs. Evidence should be presented
to demonstrate that resource use and cost data have been identified systematically.

The perspective for the cost calculation is that of the healthcare payer (government, insurance
provider and patient). Valuation of resource use in monetary units must be consistent with the
perspective of the analysis and should only include costs from Singapore. The types of direct
costs that are included in ACE’s economic evaluations are shown in Table 8.
All differences between the intervention and the comparator in expected resource use for the
target population(s) should be incorporated in the evaluation. Costs that are the same in both
treatment arms can be validly excluded if there is no significant differences in mortality rates
or time periods between treatments.
Table 8. Direct costs included in ACE's evaluations
Type of costs
Drug/Treatment
Hospital inpatient
Hospital outpatient

Direct patient healthcare (in
primary healthcare setting)

Resource consumption
Community and hospital medicines
Diagnosis, treatment and/or procedures, hospital capital costs,
depreciation and overheads (collectively captured through DRGs)1
Laboratory services and diagnostics; healthcare professional
consultations, hospice visits, treatment administration costs, costs of
managing adverse events
General practitioner visits, pharmaceutical co-payments, home or
continuing care

The selling price to patient (before any subsidy or insurance coverage is applied) for
treatments based on the registered dose should be used in the reference-case analysis. In
cases where the registered dose does not reflect current clinical practice in Singapore, the
dose should be based on that which is used in routine clinical practice, providing there is
evidence of efficacy at the proposed dose.
Importance should be placed on the transparency, reasonableness and reproducibility of cost
estimates so that the DAC can assess whether the costs reflect local resource use.
Costs to non-healthcare sectors and indirect healthcare costs should not be included in the
evaluations. Indirect patient costs, which relate to lost productivity of the patient due to
1

Diagnostic Related Groups (DRGs) are a hospital patient classification system that provide data
relating to the number and types of patients treated in a hospital to the resources required by the
hospital.

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treatment, illness or death, of that of family members due to time off work for caring, should
not be included in the reference–case analysis, but can be considered as supplementary
evidence, if justifiable.

6.8

Time horizon

The time horizon for estimating clinical and cost effectiveness should be sufficiently
long to reflect all important differences in costs or outcomes between the treatments
being compared.

The time horizon of the economic evaluation should be in concordance with the period over
which the main differences in costs and health consequences between the treatment and the
comparator are expected. Health consequences include intended as well as unintended
consequences (e.g. side effects).
A lifetime time horizon is required when alternative treatments lead to differences in survival
or benefits that persist for the remainder of a person's life. For a lifetime time horizon, it is often
necessary to extrapolate data beyond the duration of the clinical trials and to consider the
associated uncertainty. When the impact of treatment beyond the results of the clinical trials
is estimated, analyses that compare several alternative scenarios reflecting different
assumptions about future treatment effects using different statistical models are desirable.
These should include assuming that the treatment does not provide further benefit beyond the
treatment period as well as more optimistic assumptions. In addition, sensitivity analyses
should be conducted to evaluate the extent to which changes to the length of the time horizon
impact the base case ICER.
Sometimes a shorter time horizon may be justified, for example, when evaluating very acute
diseases with no differential mortality or long-term morbidity effect between treatment options
and the differences in costs and health-related quality of life relate to a relatively short period.
If a shorter time horizon is chosen, this should be substantiated with clear arguments.
The time horizon should never be determined by the length of time for which evidence is
available. Where data are not available to inform an appropriate time period, some projection
of costs and outcomes into the future will be required.

6.9

Discount rate

Future costs and benefits should be discounted at a rate of 3%. To assess the
sensitivity of the results to the discount rate applied, different scenarios can be
presented in sensitivity analyses.

Incremental cost-effectiveness ratios (ICERs) should be presented in present values. This
means that future costs and benefits should be discounted to reflect the lower value given to
future costs and benefits. The choice of the discount rate for costs and benefits is based on
the return on risk-free government bonds, which are currently about 3% in Singapore. Rates

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of 0% and 5% should be used in sensitivity analyses to test the impact of the chosen discount
rate on the ICER.

6.10

Calibration, face-validity and cross-validation of a model

The results of the model should be logically consistent with real-life observations and data
(calibration). For example, if age-specific incidences of a disease are used in a model, the
total incidence generated by the model should not considerably be higher or lower than the
observed incidence in the population, unless the difference can be explained by differences
in the population structure. In other words, there must be a logical connection between inputs
and outputs of a model.
The results of the model should be intuitively correct, that is, the model should have facevalidity. The model description should be transparent enough to allow an explanation of the
differences with other models for the same interventions (cross-validation).
The presentation of the results of an economic model as a point estimate together with its
appropriate uncertainty range is an absolute prerequisite. An economic model is by definition
subject to uncertainty. The results are conditional upon the input data and the assumptions
applied in the model. Both the uncertainty about the input data and the assumptions generate
uncertainty in the outputs. This uncertainty should be appropriately presented, as the level of
uncertainty might be an element in the decision-making process.

6.11

Handling uncertainty and testing robustness of results

All economic evaluations reflect a degree of uncertainty and it is important that all
types of uncertainty are appropriately described. These include uncertainty about the
source of parameters used in the economic evaluation, the precision of the
parameters, and whether models accurately simulate the cost and effects of the
intervention and comparators.
Uncertainty surrounding cost-effectiveness estimates should be analysed using
appropriate statistical techniques. At a minimum, one-way sensitivity analysis should
be presented for each uncertain parameter in the economic evaluation.
Multivariate probabilistic sensitivity analysis may also be performed to address
simultaneous impact of all uncertain parameters.

Results and conclusions from economic evaluations are subject to various degrees of
uncertainty, which typically is divided into three broad areas:



Model uncertainty – which includes structural and methodological uncertainty due to
the analytical methods chosen to perform the evaluation
Parameter uncertainty, which includes data uncertainty due to variability in sample
data or from uncertainty ranges chosen for non-sample data and uncertainty relating
to the variability between patients (heterogeneity) and the generalisability of the study
results to other populations and/or other contexts.

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

Stochastic uncertainty – which includes the random variability in outcomes between
identical patients.

A summary of possible forms of uncertainty in economic evaluations and appropriate methods
to address them is presented in the table below (Table 9).
Table 9. Summary of types of uncertainty encountered in economic evaluations

Parameter Uncertainty

Data inputs

Sample data
Extrapolation

Model Uncertainty

Generalisability
Analytical
methods

Model structure

Do the point estimates reflect the true values of the parameters? Data
uncertainty applies to trial-based economic evaluations as well as to models. In
trial-based economic evaluations, statistical analyses can be used to estimate
the uncertainty around individual cost and effects data due to choice of data
sources and sampling variability. Detailed descriptive statistics, showing the
distribution and variability of costs and effects data, should be presented.
Variability of sample data can increase uncertainty. Various samples taken from
the same population can result in different data for resource consumption and
outcomes.
Uncertainty caused by extrapolation from intermediate to final outcomes and
uncertainty from extrapolation beyond the study’s time horizon.
Can the results from the study population and the geographical location(s) of the
study be applied generally to other populations and locations? Are the results
from the study generalisable to daily clinical practice in the local Singapore
context?
Choice of different analytical methods can lead to uncertainty about the results
and conclusions. Methodological uncertainty should be tested using scenario
analysis.
Uncertainty relating to the structural assumptions used in the analysis should be
clearly documented and the evidence and rationale to support them provided.
Examples of structural uncertainty may include how different health states are
categorised and how different pathways of care are represented in the model.
The impact of the structural uncertainty on cost effectiveness estimates should
be explored by separate analyses of a representative range of plausible
scenarios.

Despite such uncertainties in the evidence base, decisions still have to be made about the
use of treatments. Sensitivity analysis is the process by which the robustness of an evaluation
is assessed by examining changes in the results when key parameters are varied. If the result
does not change when assumptions, parameters, etc. are varied, the result is said to be robust
and reliable. The characterisation of uncertainty enables the DAC to make a judgement based
not only on a likely estimate of the incremental costs and effects of an intervention, but on the
confidence that those costs and effects represent reality.
One-way sensitivity analysis should be conducted for all economic evaluations, to help
determine the importance of the different assumptions and modelling parameters (such as
price of the drug and the discount rate for costs and outcomes) on the results. Probabilistic
sensitivity analyses may be conducted but are not a mandatory requirement to inform DAC’s
decision-making.

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6.12

Budget impact

The following principles apply to budget impact analyses conducted for full evaluations:
Target population: The analysis should estimate the potential size of the target population
and its potential evolution over time (e.g. shifts in incidence, prevalence, disease severity).
The methods used to estimate the population size should be described and justified. The
degree of penetration of the intervention in the targeted population (e.g. detection rate,
compliance, market share etc.) needs to be considered and justified.
Comparator: The analysis should calculate the predicted financial impact of subsidising an
intervention compared to the current situation.
Costs and outcomes: Tariffs and prices should be kept constant over the years (i.e. not
inflated). The cost consequences of the treatment effect, side effects and other short and
long-term consequences (e.g. follow-up treatment) should be included.
Time horizon: The time horizon depends on the time needed to reach a steady state. It is
recommended to present the budget impact up to the steady state, with a minimum time
horizon of three years.
Discount rate: Future costs and savings should not be discounted.

Budget impact analyses are conducted from the healthcare payer perspective for full and
expedited evaluations to determine the affordability of the drug under evaluation (for
government, insurance provider and patients). For topics subject to expedited evaluation,
the projected cost to government for subsidising the drug on SDL or MAF is estimated based
on current and projected drug utilisation volumes from public healthcare institutions, sales data
projections from manufacturers, and clinical expert opinion. Where a price discount is offered
by the manufacturer through the value-based pricing process (see section 8), multiple budget
impact scenarios, using current and discounted prices, may be presented to DAC to inform
their subsidy deliberations.
For topics subject to full evaluation, budget impact models are developed by the ACE team,
using either an epidemiological or market share approach depending on the robustness of the
prevalence and/or utilisation data available to inform the analysis. An epidemiological
approach is usually preferred for generating utilisation and financial estimates if the evaluation
indicates a superior therapeutic conclusion. A market share approach is often used if the
evaluation suggests a non-inferior therapeutic conclusion. The aim of the analysis is to
provide the most likely uptake of the drug in clinical practice if subsidy is recommended, and
the cost impact to the government budget. Typically budget impact analyses are conducted
over a 3-5 year period and take the following considerations into account (Table 10).

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Table 10. Parameters considered in budget impact analyses for full evaluations
Parameter
Target population

Comparators

Costs

Handling
uncertainty
Discount rate

Considerations
 Population should be consistent with that defined in the evaluation framework
and/or scope. Subgroup analyses can be performed if there is appropriate
justification.
 The potential population size should be specified and the estimation method
described and justified. Attention should be paid to the evolution of the size of the
target population over time with and without subsidy of the drug.
 Diagnosis rates in line with local clinical practice should also be taken into account
when defining the proportion of patients who are likely to receive treatment.
 Comparator treatments should be consistent with those defined in the evaluation
framework and/or scope.
 Changes in comparator market share over time following subsidy of the drug under
evaluation should be modelled and varied in sensitivity analyses.
 Only direct healthcare costs should be considered. Indirect costs should not be
included.
 The cost consequences of the treatment effect, side effects and other short and
long term consequences (e.g. follow-up treatment) should be included.
 Any resource costs related to the use of the drug (including staff training, need for
companion diagnostics etc) should be included.
Sensitivity analyses should be performed on key parameters to model their impact on
the results.
No discount rate should be applied

In instances where manufacturers choose to submit costing information as part of their
evidence submission (for full evaluations) to ACE, relevant information will be incorporated
into ACE’s budget impact analyses.

7. Independent Evidence Review Centres (IERC)
Independent academic centres from overseas institutions which have experience in
conducting and appraising HTAs for drug subsidy decision-making are consulted to review
and critique ACE’s evaluation report and accompanying economic model for full evaluations.
Expedited evaluations (which do not require economic modelling), are not subject to external
review. Review centres are typically given 4-6 weeks to critique ACE’s evaluations, depending
on the complexity of the evaluation, and their comments and suggested amendments are
incorporated into the final report for DAC’s consideration.

8. Value-Based Pricing
Value-based pricing (VBP) is conducted in parallel with drug evaluations to ensure that the
price of patented drugs recommended for subsidy is commensurate with the drugs’ value in
Singapore’s context. The process enables ACE to engage in discussions with manufacturers
to determine the price at which the drug best represents a cost-effective use of healthcare
resources. VBP is conducted for all drugs, including biosimilars, evaluated by ACE, unless

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there are generic formulations registered in Singapore. An overview of the VBP process is
shown in Figure 4.

Figure 4. Value-based pricing process

DAC selects the drugs for evaluation

ACE schedules drugs into evaluation work plan

ACE arranges meetings/phone calls with all manufacturers for drugs scheduled for the
upcoming DAC meeting
within 3 working days
ACE issues Call for Proposal for Subsidy Listing
8 weeks
Manufacturers submit price proposal to ACE

ACE presents drug evaluation report, including VBP prices to DAC

DAC makes subsidy recommendation to MOH

1 month
ACE sends Notification of Outcome to manufacturers who submitted price proposals
3 months
MOH issues Letter of Acceptance

within 3 months
Recommended drugs listed on SDL or MAF

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8.1

Request for Proposal (RFP)

The ‘Call for Proposal for Subsidy Listing’ (Annex 3) invites manufacturers to submit their best
cost prices (i.e. the prices at which the manufacturers sell to the hospitals) for their drugs
which are being evaluated for subsidy consideration. Manufacturers are also required to
provide additional sales information, such as the current cost prices of their drug to each public
healthcare institution, the number of units sold in the last 12 months to public patients, and
details of any existing patient access programmes operated in Singapore.
The deadline for submission of the RFP is 8 weeks. Any request for an extension, is
considered exceptional, and is subject to approval by Head of Evaluation, ACE on a case by
case basis. The tenure of the RFP validity is 12 months, on balance of acceptability to
manufacturers, as well as the meeting schedule of the Committee.
Proposed prices from the RFP are used to inform ACE’s drug evaluation including costeffectiveness analyses (where applicable) and budget impact assessments. In instances
where a manufacturer is required to submit more than one RFP during the course of the
evaluation, any new proposal submitted shall supersede previous proposals.

8.2

Notification of Outcome

The Notification of Outcome (NOO) email provides early notice of the DAC’s
recommendations, within 1 month after each DAC meeting, to allow time for downstream stock
supply and inventory management.
It is sent to all manufacturers who submitted price proposals. Each manufacturer is only
informed of the outcome for their drug. This notification is strictly confidential in nature.
Manufacturers are not allowed to disseminate the information until the subsidy implementation
date.

8.3

Letter of Acceptance

The Letter of Acceptance, that specifies the price and conditions of listing on SDL or MAF, is
issued 4 months after the NOO to the manufacturers of drugs with positive subsidy
decisions.
This is a legally binding agreement, signed by the Permanent Secretary (Health), for and on
behalf of the Government of the Republic of Singapore, represented by the Ministry of Health,
whereby:




The manufacturer undertakes to sell the drug at a price not exceeding the VBP
negotiated price agreed upon for subsidy listing when supplying the drug to the public
healthcare institutions, and
MOH lists the drug on SDL or MAF.

This agreement sets the cost-effective price for subsidy listing, and provides traction against
price increases for a subsidised drug. Any drugs listed on SDL or MAF may be reviewed

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periodically, whereupon MOH may revoke or extend the listing, or vary the conditions of listing,
at its discretion.

8.4
Resubmission of price proposal in response to negative
recommendations
Manufacturers are expected to provide their best and final prices for subsidy consideration of
their drug in the RFP. Immediate resubmission of a price proposal for drugs which have not
been recommended for subsidy is not allowed.
To provide a platform for manufacturers who wish to resubmit prices for DAC’s consideration
following negative recommendations made on the basis of uncertain or unacceptable costeffectiveness or budget impact, a resubmission form will be sent to all manufacturers that
have partaken in the VBP process but have not been successful in securing an SDL or MAF
listing for their drugs. The resubmission period is aligned to the annual drug application cycle
(January to March each year. See section 2.1). Manufacturers will only be given one
opportunity to submit a revised pricing proposal for their drugs which received negative
recommendations during the previous year. Revised pricing proposals will be scheduled for
DAC’s consideration depending on the timing of existing procurement agreements between
manufacturers and public healthcare institutions for the drug under evaluation and/or its
comparators.

8.5

Consideration of “me-too” drugs

Once the first drug in a class is listed on SDL or MAF, one additional me-too drug (with same
formulation and indication as first drug) may be added, no earlier than 12 months after the
first drug was listed if its price is considered reasonable by DAC and there is sufficient clinical
need for an additional drug to be subsidised. A third drug within the class will only be
considered for subsidy on an exceptional basis if it offers substantial benefits over existing
subsidised drugs within the class.
If the first drug within a class is currently listed on SDL or MAF but has not been subject to a
formal ACE technical evaluation previously, and a me-too drug is scheduled for evaluation,
ACE will conduct a class review which includes the requested drug as well as the drug(s)
which is already subsidised from the same class. All manufacturers included in the class
review will be invited to submit a price proposal (section 8.1) to seek listing or to retain listing
of their products. In the event that the existing drug(s) on SDL or MAF is not considered costeffective on the basis of ACE’s evaluation, and offers no additional clinical benefit over other
drugs within the class, the DAC may recommend replacing it with other me-too drugs. Drugs
which are no longer listed on SDL or MAF for a particular indication will not be considered for
re-listing for at least 3 years.

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8.6

Consideration of biosimilars

Biosimilars will not automatically be subsidised even if their reference products are already on
SDL or MAF. All biosimilars are expected to lead to better patient affordability and access and
will be subject to a technical evaluation by ACE which will be presented to the DAC to inform
their subsidy deliberations. As part of the evaluation, the manufacturers will be invited to
submit a price proposal.
On the basis of evidence presented, the DAC may recommend listing no more than one
molecule (reference biologic or biosimilar) on a case by case basis. Public healthcare
institutions will be informed and given sufficient time to implement the required changes.

9. Decision-making
9.1

MOH Drug Advisory Committee (DAC)

The DAC is an expert committee comprising of 13 senior clinicians from public healthcare
institutions, and 1 senior healthcare finance representative from MOH. It is chaired by the
MOH Director of Medical Services (DMS). Members are appointed for a 3-year term by the
Chairman and may be re-appointed to serve for more than one term.
The DAC is responsible for providing evidence-based advice to MOH so that decisions for
public funding of drugs are made in an equitable, efficient and sustainable manner.
The terms of reference of the DAC are:




To prioritise drug applications, which hold potential for driving significant improvement
in health outcomes
To appraise the effectiveness of drugs based on specific therapeutic, clinical and
pharmacoeconomic evidence
To provide drug listing recommendations to the Ministry of Health, including conditions
and/or criteria for subsidy

The DAC meets 3 times a year; additional meetings may be called by the Chairman where
necessary. A minimum of two-thirds attendance is required for a quorum. ACE drug evaluation
reports and pertinent information for the meeting discussion are provided to DAC members at
least 2 weeks before the meeting date.

9.2

Factors informing subsidy decisions

The DAC makes subsidy recommendations informed by ACE’s drug evaluations. When
forming recommendations, four core decision-making criteria are considered for each
evaluation:



Clinical need of patients and nature of the condition
Clinical effectiveness and safety of the technology

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


Cost-effectiveness (value for money) – the incremental benefit and cost of the
technology compared to existing alternatives
Estimated annual drug cost and the number of patients likely to benefit from treatment

Specific factors and judgments which should be deliberated when considering each criterion
are described in Table 11.
Table 11. MOH Drug Advisory Committee decision-making framework
Core Criteria
Clinical need of
patients and nature of
the condition

Impact of the new
technology

Value for money
(Cost effectiveness)
Cost of the
technology and the
estimated number of
patients likely to
benefit

Factors considered
 Disease morbidity and patient
clinical disability with current
standard of care
 Impact of the disease on patients’
quality of life
 Extent and nature of current
treatment options
 Comparative clinical effectiveness
and safety of the technology
 Overall magnitude of health
benefits to patients
 Heterogeneity of health benefits
within the population
 Relevance of new technology to
current clinical practice
 Robustness of the current
evidence and the contribution the
guidance might make to strengthen
it
 Technical efficiency (the
incremental benefit of the new
technology compared to current
treatment)
 Projected cost to healthcare payer
(Singapore government, insurance
provider and patient)

Judgement will also take account of:
 The nature and quality of the evidence
and the views expressed by clinical
specialists on the experiences of
patients with the condition and those
who have used the technology.
 Uncertainty generated by the evidence
and differences between the evidence
submitted for licensing (from clinical
trials) and that relating to effectiveness
in clinical practice.
 The possible differential benefits or
adverse outcomes in different groups
of patients.
 The balance of clinical benefits and
risks associated with the technology.
 The position of the technology in the
overall pathway of care and the
alternative treatments that are
established in clinical practice
 Robustness of costing and budget
impact information
 Out of pocket expenses to patients
 Key drivers of cost-effectiveness
 Uncertainties around and plausibility of
assumptions and inputs in the
economic model
 Any specific groups of people for
whom the technology is particularly
cost effective
 Any identified potentially significant
and substantial health-related benefits
that were not included in the economic
model
 Existing or proposed value-based
pricing arrangements

Additional factors, including social and value judgments, may also inform the DAC’s subsidy
considerations.
The DAC has the discretion to take account of the full range of clinical and economic evidence
available, including RCTs, non-randomised studies and qualitative evidence related to the

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experiences of healthcare professionals who have used the drug or are familiar with the
condition under evaluation.
The impact of the various types of evidence on decision-making depends on the quality of the
evidence, its generalisability to Singapore clinical practice, the level of uncertainty surrounding
the clinical and cost estimates, and the suitability of the evidence to address the drug topic
under evaluation. In general, the DAC places greater importance on evidence derived from
high-quality studies with methodologies designed to minimise bias.
The DAC does not use a precise maximum acceptable ICER above which a drug would
automatically be defined as not cost effective or below which it would (i.e. an ICER threshold).
ICERs are not precise values and are associated with a degree of uncertainty. Therefore, the
DAC considers the upper and lower limits of the ICER range, in addition to the base-case point
estimate when determining whether a drug represents good value for money.
On the basis of the available evidence, the DAC recommends whether a drug should receive
subsidy through listing on the Standard Drug List (SDL) or the Medication Assistance Fund
(MAF) (Table 12). It may recommend the use of a drug in line with the full indication under
evaluation, or for a subgroup of the population, if:



there is clear evidence that the drug is likely to be more clinically and/or cost effective
in the subgroup, and
the characteristics defining the subgroup are easily identifiable or routinely measured
in clinical practice.

Table 12. Types of recommendations made by DAC
Decision
Drug provides similar or greater benefits at a similar or lower cost
than the comparator(s)
Drug provides less health benefit at a similar or greater cost that
the comparator(s) OR
Drug provides similar health benefits at a greater cost than the
comparator(s)

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Type of Recommendation
Recommended
Not Recommended

10. Guidance Development and Implementation
10.1

Drafting of guidance

Following the DAC meeting, the ACE technical team draft a guidance document for each topic
to outline the subsidy recommendation(s), DAC’s rationale for the decision, and a brief
summary of the key clinical and economic evidence which informed the DAC’s deliberations.
For full evaluations, where an economic model is developed by ACE, actual base case ICERs
are not reported in the guidance due to commercial sensitivities regarding pricing information.
Instead a range is described as follows:






Below $15,000/QALY gained
$15,000 to <$45,000/QALY gained
$45,000 to <$75,000/QALY gained
$75,000 to $105,000/QALY gained
Above $105,000/QALY gained

The annual cost to government for subsidising the drug under evaluation is also presented in
ranges, as follows:





<$1 million
$1 million to <$3million
$3 million to <$5 million
>$5 million

The guidances are typically published on ACE’s website (www.ace-hta.gov.sg) three times
per year, when subsidy is implemented.

10.2 Implementation of guidance
Subsidy implementation for recommended drugs typically occurs within 4 to 6 months after
each DAC meeting once financing is approved by the Ministry of Health. To assist with the
smooth adoption of the recommendations, ACE communicates subsidy decisions to public
healthcare institutions after each DAC meeting to allow sufficient time for them to prepare for
implementation, including making changes to their hospital formularies and procurement
processes, if necessary.
For subsidy decisions which are contingent on specific drug prices agreed with the
manufacturer through the value-based pricing process, public healthcare institutions will be
instructed to purchase the drug through the SingHealth Group Procurement Office (GPO), and
adhere to a recommended maximum selling price. This ensures that the savings generated
from price discounts offered by the manufacturer are passed onto the patients.
To monitor the impact of ACE guidance, MOH will track the utilisation of subsidised drugs, in
addition to procurement and selling prices at each institution. Where required, educational

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audits will be conducted in the institutions by MOH to improve adherence to the guidance
recommendations.

10.3

Review of guidance and subsidy recommendations

Each guidance will be considered for review 3 years after publication. At that time, the ACE
technical team will undertake a literature search to determine whether any new clinical
evidence or cost information have been published which are likely to have a material effect on
the subsidy decision and guidance recommendations.
Where considerable clinical and/or cost information has been published, the topic will be
scheduled into the ACE work plan for re-evaluation as a full or expedited topic, depending on
the amount of new evidence that has become available. The process for full or expedited
evaluations will be followed for all topics subject to re-evaluation. Following DAC’s
consideration of the new evidence, the existing guidance may remain the same, or be revised,
depending on the DAC’s recommendations.
For topics where a drug has not been recommended for subsidy due to cost-effectiveness or
budget impact considerations, and negative guidance has been published, manufacturers are
able to request for the DAC to reconsider their product at a revised price during the annual
resubmission period (see section 8.4 for information on price proposal resubmissions). If the
DAC recommends a drug for subsidy on the basis of the revised pricing proposal, existing
ACE guidance will be updated to include the new recommendations.

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Annex 1: Company evidence submission template
evaluations

for full

Instructions for companies
This is the template for submission of evidence to the Agency for Care Effectiveness (ACE)
as part of the full evaluation process for drugs. It is not mandatory for companies to complete
an evidence submission. The topic will still be evaluated by the ACE technical team and
presented to the MOH Drug Advisory Committee (DAC) to inform subsidy considerations,
irrespective of company involvement. Any evidence provided by the company will be
incorporated into ACE’s evaluation. Following appraisal by the MOH Drug Advisory
Committee, in most instances for patented drugs, subsidy through the Medication Assistance
Fund (MAF) is considered. Less often, a patented drug may be considered for listing on the
Standard Drug List (SDL).
Text highlighted in grey is intended to inform companies about the type of information to
include in each section and can be removed from final submission. Additional or less
information can be included at the company’s discretion. The information provided in the
evidence submission should be in line with the evaluation framework set out in the final scope.
The submission should be as brief and informative as possible. The main body of the
submission must not exceed 35 pages, excluding appendices and the pages covered by this
template. Font size for text within the body of the submission should not be smaller than Arial
size 11. Smaller font sizes may be used in tables. Companies are not required to provide an
economic model.
The submission should be sent to ACE electronically in Word or PDF format. The submission
must be a stand-alone document. Additional appendices may only be used for supplementary
explanatory information that exceeds the level of detail requested in the template, but that is
considered to be relevant to the submission. A separate Excel workbook to summarise cost
information (“Costing template for manufacturers”) should also be included alongside the
evidence submission.
When making an evidence submission, companies must ensure that all confidential
information is highlighted and underlined.

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AGENCY FOR CARE EFFECTIVENESS
Full Technology Evaluation
[Evaluation title]
Company evidence submission
Contains confidential information

Date of submission

Yes / No

Section 1: The technology
HSA approved name and brand name
Registered indication(s) and any
restrictions as described in the
Package Insert.
Date of patent expiration

1.1

Administration and costs of the technology

[Provide details of the treatment regimen, including the method of administration, and costs
associated with the technology by completing the table below. Please add additional columns
if more than 2 formulations or strengths are being considered in this evaluation. Specify the
sources of information and data used to complete the table, for example Package Insert or
trial data].

Table X: Administration and costs of the technology being evaluated
Parameter

Pharmaceutical
formulation/strength:
XXX

Source

Method of administration
Dose
Dosing frequency
Average length of a
course of treatment
Average cost of a course
of treatment
Anticipated average
interval between courses
of treatments

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Anticipated number of
repeat courses of
treatments
Dose adjustments
Anticipated care setting
Number of units sold in
the last 12 months to
public healthcare
institutions
Current net** cost price
(excluding GST) to public
healthcare institutions*
Revised cost price for
subsidy consideration***
* When the registered indication recommends the intervention in combination with other treatments, the cost price of
each intervention should be presented.
** Cost price to public healthcare institutions after bonusing arrangements or discounts have been applied
***Revised cost price should be in line with price discount(s) outlined in value-based pricing request for proposal
template (Call for Proposal for Subsidy Listing)

1.2

Changes in service provision and management

[State whether additional tests or investigations are needed (for example, diagnostic tests to
identify the population for whom the technology is licenced, or regular monitoring requirements
once a patient begins treatment). Describe whether there are particular administration
requirements for the technology and the associated costs or additional infrastructure involved.

1.3

Overseas regulatory status

[Provide a summary of the regulatory status of the technology in other countries, including
Australia, New Zealand, UK and Malaysia (and preferably other Asian countries including
Taiwan and South Korea) is also required. If the technology is already reimbursed in other
countries, please provide details of the level of subsidy and the indications covered.]

Section 2: Clinical need
2.1

Health condition and position of the drug in the treatment pathway

[Provide a brief overview of the disease or condition for which the technology is being used.
Include details of the underlying course of the disease.
Provide information about the life expectancy of people with the disease or condition in
Singapore and the source of the data. Please provide information on the number of people in
Singapore with the particular therapeutic indication for which the technology is being
evaluated.

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iii

Describe current clinical practice to manage the condition and list the clinical guidelines (both
local and international) which are most commonly used by clinicians in Singapore. If
applicable, describe results from any surveys which have been conducted with local clinicians
about current clinical practice. Describe any issues relating to current clinical practice,
including variations or uncertainty about established practice.
Explain how the technology under evaluation may change the existing treatment pathway if it
is subsidised.]

2.2

Proposed criteria for listing technology on the Medication Assistance

Fund (MAF)
Based on the proposed position of the drug in the existing clinical treatment pathway for the
condition under evaluation (as per section 2.1), suggest specific eligibility criteria to target the
use of the drug to patients who are most likely to benefit from treatment and in whom the drug
is most likely to be cost-effective, assuming it is listed on the MAF [this population should
correspond with the eligible patient population described in the accompanying costing
template].

Section 3: Clinical effectiveness
Section 3 provides guidance on the level of information that should be included in the evidence
submission template about the clinical effectiveness of the drug under evaluation.

3.1

List of relevant trials

[ACE prefers randomised controlled trials (RCTs) that directly compare the technology with
one or more relevant comparators. Provide details of the RCTs that provide evidence on the
clinical benefits of the technology at its licensed dosage within the indication being evaluated.
There is no need to conduct a systematic review, network meta-analysis, indirect or mixed
treatment comparison as part of your evidence submission.
a. In a table, present the list of relevant RCTs comparing the intervention with other
therapies (including placebo) in the relevant patient group. Highlight which studies
compare the intervention directly with the appropriate comparator(s) with reference to
the final scope. If there are none, state this.
b. All outcome measures listed in the trial protocol, should be identified and completely
defined. When outcomes are assessed at several time points after randomisation,
indicate the pre-specified time point of primary interest. Indicate which outcomes were
specified in the trial protocol as primary or secondary, and whether they are relevant
to the final scope. This should include therapeutic outcomes, as well as patient-related
outcomes such as assessment of health-related quality of life (HRQoL), and any
arrangements to measure adherence. When appropriate, also provide evidence of
reliability or validity, and current status of the measure (such as use within Singapore

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clinical practice). A suggested table format is presented below. The table can be
presented in landscape format.].

Table X: List of relevant RCTs
Trial number
(acronym)
Trial 1
Trial 2
[Add more
rows as
needed]

3.2

Population

Intervention

Comparator

Outcomes

Primary study
reference

Clinical effectiveness results of the relevant trials

[Provide the results for all relevant outcome measures pertinent to the evaluation objective in
line with the final scope. For each outcome, provide the following information from each study:


The unit of measurement.



The size of the effect; for dichotomous outcomes, the results ideally should be
expressed both as relative risks (or odds ratios) and risk (or rate) differences. For timeto-event analysis, the hazard ratio is an equivalent statistic. Both absolute and relative
data should be presented.



A 95% confidence interval.



The number of people in each group included in each analysis and whether the
analysis was intention to treat. State the results in absolute numbers when feasible.



When interim data are quoted, this should be clearly stated, along with the point at
which data were taken and the time remaining until completion of the trial. Analytical
adjustments should be described to cater for the interim nature of the data.



Other relevant data that may help interpret the results may be included, such as
adherence to medication or study protocol.



Discuss and justify any clinically important differences in the results between the
different arms of a trial and between trials.



Specify whether unadjusted and adjusted analyses were performed, and whether the
results were consistent.]

3.3

Non-randomised and non-controlled evidence

[Provide details of the non-randomised and non-controlled studies, including real world data
that provide additional evidence to supplement RCT data. Provide a list of the relevant sources
and summarise the patient characteristics, methodology and quality assessment for each.
Briefly summarise the results.]

3.4

Safety

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[Provide details of all adverse reactions experienced with the technology in relation to the
indication(s) under evaluation. For each intervention group, give the number with the adverse
reaction and the frequency, the total number in the group, and the percentage with the
reaction. Then present the relative risk and risk difference and associated 95% confidence
intervals for each adverse reaction.
Evidence from comparative RCTs and regulatory summaries is preferred, but findings from
non-comparative trials may sometimes be relevant. For example, post-marketing surveillance
data may demonstrate that the technology shows a relative lack of adverse reactions
commonly associated with the comparator, or that the occurrence of adverse reactions is not
statistically significantly different to those associated with other treatments.
Highlight any safety warnings issued by HSA or international regulatory agencies (e.g. FDA,
EMA) related to the use of the technology.
Describe any ongoing studies specifically relating to safety outcomes and the anticipated date
of completion. If any interim results are available from ongoing studies, please summarise
them in a table.]

3.5

Interpretation of clinical effectiveness & safety evidence

[Briefly conclude the clinical effectiveness and safety of the technology against the
comparators specified in the final scope issued by ACE, including any subgroups. Please
indicate whether results show superiority or non-inferiority to comparators for both clinical
effectiveness and safety outcomes].

3.6

Ongoing studies

[Provide details of all completed and ongoing studies from which additional clinical
effectiveness evidence is likely to be available in the next 12 months for the indication being
evaluated.]

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Section 4: Cost effectiveness
Companies are not required to submit a cost-effectiveness model as part of their evidence
submission. All economic models will be produced by the ACE technical team to inform the
Committee’s cost-effectiveness considerations.

4.1

Published cost-effectiveness studies

[Describe and compare the methods and results of any published cost-effectiveness analyses
available for the technology and/or the comparator technologies (relevant to the technology
evaluation). If more than one study is identified, please present the information in a table as
suggested below. The table can be presented in landscape format.]
Table X: Summary list of published cost-effectiveness studies
Study

Year

Perspective

Summary

Time

Patient

QALYs

Costs

ICER

of analysis

of model

horizon

population

(intervention,

(currency)

(per

(average

comparator)

(intervention,

QALY

comparator)

gained)

age in
years)
Study 1
Study 2
[Add
more
rows as
needed]
QALYs, quality-adjusted life years; ICER, incremental cost-effectiveness ratio

Section 5: Budget Impact
[Section 5 should present budget impact calculations, over a 5 year period, to provide the most
likely extent of use of the technology and financial estimates. This section is important for
estimating the likely uptake of the proposed technology in clinical practice if subsidy is
recommended, and the cost impact on the Singapore Government budget. Any proposed price
discounts should be consistent with prices included in the value-based pricing Request for
Proposal. The information provided will be used to inform ACE’s budget impact analyses.
Epidemiological and market-share analyses are the two broad approaches for developing
utilisation and financial estimates, although their use is not mutually exclusive. An
epidemiological approach is usually preferred for generating utilisation and financial estimates
if the submission indicates a superior therapeutic conclusion. However, a market-share
approach might be preferred if the submission indicates a non-inferior therapeutic conclusion.
Justify the approach taken. Demonstrate concordance across both approaches where data
inputs from one approach (epidemiological or market share) are uncertain.

Driving better decision-making in healthcare

vii

Ensure that any estimates of the extent of use of the technology in the Singapore setting are
consistent with evidence presented throughout. Ensure that uptake of the technology is
consistent with its expected use in clinical practice (at appropriate point in local treatment
algorithm).
Please complete the Excel workbook (“Costing template for manufacturers”) and ensure that
all calculations, assumptions and data sources are clearly described. The workbook follows
an epidemiological approach, however it can be modified by the user to capture any other
information that is considered important to include to support the submission.
Briefly summarise the results in a table to show 5-year budget impact to the Singapore
government (for all clinically eligible patients in line with defined clinical criteria, irrespective
of financial eligibility for MAF)].

Section 6: Patient access programs
[Describe any existing patient access programs (PAPs) in Singapore (by institution) that are
currently in place for the technology under evaluation, including patient eligibility criteria and
the bonusing or discount arrangements offered. If the PAPs differ between public healthcare
institutions, please describe these differences and the number of patients who are currently
receiving treatment under each program.
Please indicate whether there is a proposed end date for the PAP(s) and/or whether the
program will no longer be offered if the treatment is subsidised under SDL/MAF].

References
[Use a recognised referencing style, such as Harvard or Vancouver.]

Appendices

Driving better decision-making in healthcare

viii

Annex 2: Company evidence submission template for expedited
evaluations
Instructions for companies
This is the template for submission of evidence to the Agency for Care Effectiveness (ACE)
as part of the expedited evaluation process for drugs. It is not mandatory for companies to
complete an evidence submission. The topic will still be evaluated by the ACE technical team
and presented to the MOH Drug Advisory Committee (DAC) to inform subsidy considerations,
irrespective of company involvement. Any evidence provided by the company will be
incorporated into ACE’s evaluation.
Text highlighted in grey is intended to inform companies about the type of information they
may choose to include in each section and can be removed from final submission. Additional
or less information can be included at the company’s discretion.
The submission should not exceed 5 pages. Additional appendices are not permitted.
Companies are not required to provide an economic model or budget impact analysis. Font
size for text within the body of the submission should not be smaller than Arial size 11. Smaller
font sizes may be used in tables.
The submission should be sent to ACE electronically in Word or PDF format. When making
an evidence submission, companies must ensure that all confidential information is highlighted
and underlined.

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AGENCY FOR CARE EFFECTIVENESS
Expedited Technology Evaluation
[Evaluation title]
Company evidence submission
Contains confidential information

Date of submission

Yes / No

Technology
HSA approved name and brand
name
Formulations commercially
available in Singapore
Date of patent expiration

Clinical need
[Describe the expected place of the technology in the local treatment pathway for the
indication(s) under evaluation. Explain how the technology may change the existing treatment
pathway if it is subsidised (listed on SDL or MAF).]

Summary of clinical effectiveness and safety evidence
[ACE prefers randomised controlled trials (RCTs) that directly compare the technology with
one or more relevant comparators. Provide a brief overview of the pivotal clinical trials which
demonstrate the clinical effectiveness of the technology at its licenced dosage within the
indication being evaluated. Include a summary of any adverse reactions, and safety evidence.
There is no need to conduct a systematic review, network meta-analysis, indirect or mixed
treatment comparison as part of your evidence submission. Results can be presented as a
table or as text.]
[A brief summary of key results from non-randomised evidence sources (including real world
data) that provide additional evidence to supplement RCT data can be included].
[Provide details of all ongoing studies from which additional clinical effectiveness evidence is
likely to be available in the next 12 months for the indication being evaluated.]

Concluding remarks
[Company can include brief concluding remarks at the end of the evidence submission]

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Annex 3: Proposal for Subsidy Listing (RFP template, Form A)
Section 1: Technical Specifications and Costs
We, [name of company in block letters] hereby offer and undertake, on the acceptance
of this Proposal, to offer the following drugs with the following specifications for sale to Public
Healthcare Institutions and Polyclinics at the following price, in accordance with the Terms
and Conditions in Section 2:

Table A1: Price proposals for subsidy listing
Item
No.
Indication(s)

[name of drug, strength
and pharmaceutical
form]
2.
[name of drug, strength
and pharmaceutical
form]
(insert more rows as necessary)

Subsidy
tier

Cost price
per unit,
excluding
GST (SGD)

Select

/ [specify
units]

Select

/ [specify
units]

Percentage
discount
on usual
cost price
(%)

2
To assist the Government of the Republic of Singapore, represented by the Agency for
Care Effectiveness (“the Authority”) of the Ministry of Health, in assessing this Proposal, we
have duly completed and hereby submit the tables in the Appendix for the Authority’s
consideration. We confirm and warrant that the information set out in the Appendix is
complete, up-to-date and accurate.
3
This Proposal is valid for twelve (12) calendar months from [deadline for submission
of the Proposal].
4
We warrant, represent and declare that we are duly authorised to submit and sign this
Proposal, receive any instruction, give any information, accept any contract and act for and
on behalf of [name of company in block letters].
Dated this [date] day of [month], 20yy
Respondent’s Company or Business
Registration No:

Respondent’s official
Stamp:

Authorised Signature:
Name:
Designation:

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Section 2: Terms and Conditions
1

ACCEPTANCE OF PROPOSAL

1.1

The issue by the Authority of a Letter of Acceptance accepting this Proposal shall create
a contract (“Contract”) binding the Respondent to offer for sale to all Public Healthcare
Institutions and Polyclinics the drugs specified in the Letter of Acceptance (“Drugs”) at a
price not exceeding the price set out in this Proposal, for the duration the Drugs are
listed for subsidy on the Standard Drug List or Medication Assistance Fund. Where the
Respondent has existing agreement(s) of sale of the Drugs with any of the Public
Healthcare Institutions and Polyclinics as at the date of the Letter of Acceptance, the
Respondent undertakes to take all reasonable steps to vary such agreement(s) so that
the cost price of the Drugs to each Public Healthcare Institution and Polyclinic does not
exceed the price set out in this Proposal.

1.2

For the purpose of this Proposal, and any Contract formed upon the Authority’s
acceptance of this Proposal, “Public Healthcare Institutions and Polyclinics” shall refer
to the entities listed in Table A2. The Authority may from time to time vary the list in
Table A2 at its absolute discretion, and shall notify the Respondent of any such variation
in writing.

1.3

In consideration of the above, the Authority shall list the Drugs for subsidy on the
Standard Drug List or Medication Assistance Fund within 3 months from the issue of the
Letter of Acceptance.

1.4

Save that the Authority may disclose to all Public Healthcare Institutions and Polyclinics
the prices at which the Respondent sells the Drugs to all Public Healthcare Institutions
and Polyclinics, the Authority shall not otherwise make publicly available the prices at
which the Respondent sells the Drugs to all Public Healthcare Institutions and
Polyclinics.

SUSPENSION AND TERMINATION OF THE CONTRACT

2.1

The Authority shall, after giving seven (7) days prior written notice to the Respondent,
have the right to suspend or terminate the Contract if the Authority is affected by any
state of war, acts of God or other circumstances seriously disrupting public safety, peace
or good order of the Republic of Singapore.

2.2

If the Respondent defaults in his performance of this Contract, the Authority may issue
a notice of default to the Respondent informing the Respondent of its default. The
Respondent shall, within thirty (30) days of the date of the notice of default, remedy the
default. If the Respondent fails to remedy the default, the Authority shall have the right
to immediately revoke the listing of the drugs for subsidies and terminate the Contract
by way of a written notice to the Respondent without the Authority being liable therefor
in damages or compensation.

OTHERS

3.1

The Authority may terminate the Contract and recover from the Respondent the amount
of any loss resulting from such termination, if the Respondent shall have offered or given
or agreed to give to any person any gift or consideration of any kind as an inducement
or reward for doing or forbearing to do or for having done or forborne to do any action in
relation to the obtaining or execution of the Contract with the Authority or for showing or
forbearing to show favour to any person in relation to any contract with the Authority, or
if the like acts shall have been done by any person employed by the Respondent or

Driving better decision-making in healthcare

xii

acting on his behalf (whether with or without the knowledge of the Respondent) or if in
relation to any Contract with the Authority the Respondent or any person employed by
him or acting on his behalf shall have committed any offence under Chapter IX of the
Penal Code (Cap. 224) or the Prevention of Corruption Act (Cap. 231) or shall have
abetted or attempted to commit such an offence or shall have given any fee or reward
the receipt of which is an offence under Chapter IX of the Penal Code or the Prevention
of Corruption Act.
3.2

Except with the prior consent in writing of the Authority, the Respondent shall not
disclose this Proposal, the Contract or any part thereof.

3.3

This Proposal and the Contract shall be subject to, governed by and interpreted in
accordance with the laws of the Republic of Singapore for every purpose.

3.4

The Respondent and the Authority hereby submit to the exclusive jurisdiction of the
Singapore Courts for all purposes relating to this Proposal and the Contract.

3.5

A person who is not a party to this Contract shall have no right under the Contracts
(Rights of Third Parties) Act (Cap. 53B) to enforce any of its terms.

3.6

No variation whether oral or otherwise in the terms of this Proposal or the Contract shall
apply thereto unless such variation shall have first been expressly accepted in writing
by the Respondent and the authorised contract signatory of the Authority.

3.7

The right and remedies of the parties under this Contract are cumulative and are in
addition and without prejudice to any rights or remedies a party may have at law or in
equity. Further, no exercise by a party of any one right or remedy under this Contract
shall operate so as to hinder or prevent the exercise by it of any other right or remedy
under the Contract, or any other right existing at law or in equity.

3.8

In no event shall any delay, failure or omission on the part of either of the Parties in
enforcing or exercising any right, power, privilege, claim or remedy, which is conferred
by this Agreement, at law or in equity, or which arises from any breach by either Party,
be deemed to be or be construed as, (i) a waiver thereof, or of any other such right,
power, privilege, claim or remedy, in respect of the particular circumstances in question,
or (ii) operate so as to bar the enforcement or exercise thereof, or of any other such
right, power, privilege, claim or remedy, in any other instance at any time or times
thereafter.

3.9

The Contract contains the entire and whole agreement between the parties and
supersedes all prior written or oral commitments, representations, arrangements,
understandings or agreements between them. Each party warrants to the other that it
has not entered into this Contract on the basis of any prior written or oral commitments,
representations, arrangements, understandings or agreements between them.

Driving better decision-making in healthcare

xiii

Table A2. List of Public Healthcare Institutions and Polyclinics
1

Alexandra Hospital

Ang Mo Kio – Thye Hua Kwan Hospital

Bright Vision Hospital

Changi General Hospital

Institute of Mental Health/Woodbridge Hospital

Jurong Community Hospital

Khoo Teck Puat Hospital

KK Women’s and Children’s Hospital

National Cancer Centre Singapore

National Dental Centre Singapore

National Heart Centre Singapore

National Healthcare Group Pharmacy

National Healthcare Group Polyclinics

National Neuroscience Institute

National Skin Centre

National University Hospital

Ng Teng Fong General Hospital

Ren Ci Community Hospital

St Andrew’s Community Hospital

Singapore General Hospital

Sengkang General Hospital

Sengkang Community Hospital

St Luke’s Hospital

Singapore National Eye Centre

SingHealth Polyclinics

Tan Tock Seng Hospital

Woodlands General Hospital

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xiv

Appendix
1. Volume and current cost price
Number of units sold in the last
12 months
[MM YYYY to MM YYYY] to
public healthcare institutions
[name of drug, strength
and pharmaceutical form]

[specify units]

[name of drug, strength
and pharmaceutical form]

[specify units]

Usual cost price per
[unit], excluding GST
(SGD)

2. Patient Access Programs (PAPs) currently in place (if applicable)
Please provide details
(eligibility criteria, level of subsidy, differences among
public healthcare institutions and patient numbers)
[name of drug, strength
and pharmaceutical form]
[name of drug, strength
and pharmaceutical form]
Will existing PAPs still be valid at the prices offered for subsidy consideration?

Select

3. Existing agreements to sell the Drugs to Public Healthcare Institutions
and Polyclinics (if applicable)
Contracting Party

Date of expiry of
agreement

[name of drug, strength
and pharmaceutical form]
[name of drug, strength
and pharmaceutical form]

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Agency for Care Effectiveness
College of Medicine Building
16 College Road Singapore 169854
Tel
Fax
Web

(65) 6325 7335
(65) 6225 9747
www.ace-hta.gov.sg

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