HTA (public) Flashcards

1
Q

what is hta

A

multidisciplinary process that uses explicit methods
to determine the value of a health technology at different points in its lifecycle

.

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2
Q

dimensions of value to be assessed

A

clinical effectiveness, safety, costs, and economic implications

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3
Q

additional dimensions of value that may be assessed

A

ethical, social, cultural, legal and organisational and environmental aspects.

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4
Q

how to do hta

A

Globalise the evidence
Localise the decision

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5
Q

how to localise the decision to sg?

A
  1. Selection of relevant comparator
  2. Cost-effectiveness in local context/health system
  3. Ethical issues
  4. Access issues
  5. Consumer preferences
  6. Workforce planning
  7. Training/credentialing users of technology
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6
Q

what does pico stand for

A

patient/population
intervention
comparator
outcome

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7
Q

what is CMA

A

If there is no significant difference in efficacy and safety, the cheapest option is
preferred i.e. cost minimisation analysis (CMA)

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8
Q

what is CEA

A

If a new technology is superior in outcomes but is likely to result in additional cost to
the health system, cost effectiveness analysis (CEA) is conducted.

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9
Q

what is ICER

A

Incremental cost-effectiveness ratio (ICER) – incremental change in costs divided by
incremental change in health outcomes of a new technology compared to the current
standard of care over a period of time

ICER =
CostA − CostB/EffectA − EffectB (incremental cost per unit outcome)

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10
Q

what outcome should be considered in hta?
1. Safety profile
2. Delays in progression
3. Improved compliance with the new technology
4. Lengthening of life
5. New mechanism of action

A

1,2,4

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11
Q

what are indirect treatment comparisons

A

making use of RCTs that have a common comparator
eg. RCT1: A and B
RCT2: B and C
to determine effectiveness between A and C

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12
Q

transitivity assumption

A

no systematic differences between available comparisons, control groups are sufficiently similar

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13
Q

minimal clinically important difference

A

smallest difference in score in domain of interest which patients perceive as beneficial

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14
Q

what is the health outcome of CUA

A

QALY

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15
Q

what does CEA consider

A

cost and health outcomes

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16
Q

2 components of CMA

A

equieffective doses (proposed medicine and comparator),
direct medicine cost (cost of proposed medicine vs cost of comparator)

17
Q

what is bill size

A

patients out of pocket payment after subsidies

18
Q

what is cost

A

Price at which the public healthcare institution (PHI) procures from manufacturer or distributor

19
Q

what is charge

A

Price which includes any profit margins applied by the PHI (‘cost-plus’ model) and reflected on
patients’ bill
* This price is before any deductions for government subsidies, insurance payouts,

20
Q

are societal costs included in CEA?

21
Q

markov model assumption

A

future state depends only on the present state, ‘memoryless’

22
Q

long time horizon benefit vs disadvantage

A

benefit: captures all health effects and costs
disadvantage: increases uncertainty

23
Q

short cycle length benefit vs disadvantage

A

benefit: increases precision
disadvantage: reduces efficiency

24
Q

what are utility weights

A

incorporates no. of life years and QOL

25
what are vignettes for measuring health
qualitative descriptions of health state to be valued
26
ways to measure health
1. direct patient elicitation 2. generic preference based measures of health 3. disease specific measures of health 4. vignettes/scenarios
27
price volume agreement benefit
payment back in rebates for spending above pre-negotiated caps
28
problems when countries uphold explicit CE threshold
- drugs with supposedly lower ICER get raised by companies to maximise profit - lack of long term data to determine ICER - ignores budget constraints
29
major criteria in decision making of drug subsidies
- clinical need - overall benefit - cost effectiveness - cost of technology and estimated number of patients to benefit
30
characteristics of rwd
- observational - unstructured and inconsistent due to variations in data entry - large volume of data - lack key endpoints for analysis - subject to bias and measurement errors
31