BIM Question

Description

Make a Budget Impact Model on excel.

Unformatted Attachment Preview

Budget Impact Models
Day 2
January 2024
Confidential
REVIEW
what & why | examples | sections of a BIM
Confidential
2
Our Agenda for Yesterday
01
02
Conceptual
Overview
03
Sections of a BIM
Build-A-BIM
Our Agenda for Today
01
02
Results, Sensitivity &
Other Important BIM
Components
03
Visualization, Pretty
Factor and Reporting
Review & Working
Session
Quick Review
True or False?
• The purpose of a BIA is to estimate the
financial consequences of adoption of a
new intervention.
• In particular, a BIA predicts how a
change in the mix of drugs and other
therapies used to treat a particular
health condition will impact the
trajectory of spending on that condition.
Quick Review
Give me a number
• Typical time horizon for a BIM for a payer
for a diabetes drug
Quick Review
Give me an example
• Name a good source for population
estimates
Quick Review
Give me some ideas
• What other costs (other than direct
treatment costs) might you include in a
BIM?
Review Results – Sections of a ‘Simple’ BIM
These sheets are not exhaustive or always included
Welcome with disclaimer*
Overview of model (like a table of contents)*
Population
Treatment mix (market share)
Treatment costs†
Results‡
*May include selection of time horizon and perspective
†May include clinical outcomes and costs, or these factors may be on a separate sheet
‡May include simple, detailed and sensitivity/scenario analysis
Results
• Summary and detailed sheets
• Present annual outcomes
•
•
•
•
Drug costs
Re-hospitalization costs
Total costs
Number of hospitalizations
• Incremental change from year to
year
• Increase in drug budget
• Decrease in other medical cost
budget
• Change in total cost budget
• Hospitalization avoided
• Display user selections and inputs
Per member per
month
÷
÷
ℎ
PPPY, PMPM
An Illustrative Example
• A new medication, GLP-Drug, is approaching FDA approval for
Condition X, which affects 1 in 100,000 patients in the United States.
• After considering all costs associated with GLP-Drug (eg, medication
cost, cost of administration, cost of managing toxicities, medical cost
offsets), GLP-Drug has an incremental additive cost of $100,000 per
patient per year (PPPY) treated.
• Analysts expect that GLP-Drug will have 50% market uptake in year 1.
• A BIA was conducted for this new drug with 50% market uptake for a
hypothetical third-party payer with 1 million members.
How many patients
are estimated to
receive GLP-Drug?
What is the per
member per month
(PMPM) impact?
Review Results – Sections of a ‘Simple’ BIM
Assumptions & Limitations
Sensitivity and Scenario Analysis
Documentation
Data Visualization
Model Appearance & Interactivity
Validation
Types of Assumptions & Limitations
Spoiler: a BIA ALWAYS has assumptions and limitations
Include a table of assumptions. Listing the major assumptions in tabular form can improve the
transparency of the model, particularly to the relatively inexperienced user and should be included
with the model description.
60-MINUTE BREAKOUT
Decide on what results to show, -generally- how to show them, what
inputs to show / allow modification to, do the calculations.
• PMPM
• PMPY
• Total Budget by
Scenario
• Detailed
calculations and
results
• High-level results
page
What results
will you
show?
Do you want
to have a
simple and
detailed page
16
Review Results – Sections of a ‘Simple’ BIM
Assumptions & Limitations
Sensitivity and Scenario Analysis
Documentation
Data Visualization
Model Appearance & Interactivity
Validation
What If
parameter
uncertainty
in the input values
used and
structural
uncertainty
introduced by the
methods of the BIA
Parameter Uncertainty
There is considerable uncertainty in a BIA. Therefore, a single “best estimate” is not a
sufficient outcome.
• Various forms of sensitivity analysis (univariate, multivariate, probabilistic, etc.) may be carried
out. Their usefulness depends on the amount and quality of available data and the needs of the
decision-maker.
• There is little point to an extensive probabilistic sensitivity analysis when little is known about
the degree of variability and the extent of correlation among parameters.
Variable
LB
UB
HR, CKD Progression from Stage 4 per 10 ng/ml
($23,512,127)
increase in 25(OH)D
$2,824,493
HR, CKD Progression from Stage 3 per 10 ng/ml
($20,761,277)
increase in 25(OH)D$302,069
Annual Cost of CKD Stage 5/ESRD
($2,943,034)
($20,896,484)
Annual Cost of ERC
($16,801,215)
($7,038,306)
Efficacy of Paricalcitol on 25(OH)D outcomes ($9,494,620)
($14,380,329)
RR, CV Event per 10 ng/ml increase in 25(OH)D
($9,469,735)
($13,600,585)
Annual Cost of Paricalcitol
($10,066,204)
($13,773,317)
Cost per CV Event
($10,895,698)
($12,943,823)
Efficacy of ERC on 25(OH)D outcomes
($11,588,571)
($12,176,392)
Cost per Fracture
($11,873,847)
($11,965,674)
19
Scenario Analysis – Structural Uncertainty
While a sensitivity analysis is based on the modification of clinical and economic estimates of input
variables over a plausible range of values, a scenario analysis is based on the modification of the
underlying strategies of the model: e.g. society perspective, time horizon, comparator therapies.
• The selection of these additional scenario analyses remains subjective, in contrast to standard
sensitivity analyses, which are based on statistical distributions
• Generally, consider any assumptions that are not well-backed by data or are prone to
controversy
20
Scenarios for Plan Size
RECALL:
• A new medication, GLP-Drug, is approaching FDA approval for Condition X, which
affects 1 in 100,000 patients in the United States.
• After considering all costs associated with GLP-Drug (eg, medication cost, cost of
administration, cost of managing toxicities, medical cost offsets), GLP-Drug has an
incremental additive cost of $100,000 per patient per year (PPPY) treated.
• Analysts expect that GLP-Drug will have 50% market uptake in year 1.
• A BIA was conducted for this new drug with 50% market uptake for a hypothetical
third-party payer with 1 million members.
What if?
• A health plan of 5000 members had 1 patient requiring GLP-Drug . . .
• A health plan of 15,000 members with 1 patient requiring GLP-Drug would have an
increase in spend of $0.56 PMPM. A health plan of 50,000 members with 1 patient
requiring GLP-Drug would have an increase in spend of $0.17 PMPM.
Sampling of Input parameters in a BIM
BIA
Input parameters
Probabilities
Cost per patient
Treatment patterns
Costing information: resource utilisation and prices and tariffs
Prevalence
Incidence
Proportion of identified patients
Proportion of eligible patients
Proportion of patients in clinical trials
Number of patients
Annual growth rate for utilisation of the technology
Existing mix of available treatment modalities
Information on dosing
Treatment sequencing
Diffusion (uptake)
Substitution effects
Off-label use
Time horizon
As demanded by the research question at hand
60-MINUTE BREAKOUT
Build in a sensitivity analysis, including a tornado diagram
• Sensitivity analysis
table (inputs and
variability)
• Find sources for
variability
• Describe and include
at least one scenario
analysis
What
inputs
should you
include?
• Include a tornado
diagram
Visualize
the
model’s
sensitivity
23
Review Results – Sections of a ‘Simple’ BIM
Assumptions & Limitations
Sensitivity and Scenario Analysis
Documentation
Data Visualization
Model Appearance & Interactivity
Validation
Documenting Design, Methods and Sources
What to include in your notes and technical report
Note: this section reviews documentation for internal purposes; reporting for
dissemination (either to the payer, client, journal publication, congress) is more extensive
Model description:
Patient
population:
Technology mix:
Time horizon:
Perspective and
target audience:
Input data:
Data sources:
Analyses:
• Describe the structure of the BIM, including a figure of the model.
• identify and justify approach (epidemiological, literature, internal data) and maybe
differences between the clinical trial populations and the BIA population
• The choice of the technology mix is often based on the local treatment patterns and
clinical guidelines and this choice should be justified.
• The time horizon(s) for the study should be presented and its choice justified. The
choice for the study period should be appropriate to the budget holder.
• Clearly identify the perspective(s) from which the analysis is performed.
• The parameter values assumed for all the clinical and cost data items for all the
scenarios modeled should be presented.
• The sources of model inputs should be described in detail. The strengths,
weaknesses, and possible sources of bias, that may be inherent in the data sources
used in the analysis, should be described.
• A description of the methods used to perform budget total and incremental analyses
should be provided. The choice of all of the scenarios presented in the results should
be documented and justified.
Methods of Rolling Documentation
Excel Notes
(Comments)
Excel Data
Validation
Excel Pop
Ups
Running
Word
Document
Multiple ways
(choose one to
primarily use) of
documenting in
the model
Ultimately,
always have a
separate
document,
external from
your actual
model
Excel Comments v Data Validation
Notes
Shows a message when a cell is hovered over
& shows comment flag
Data Validation Input Message
Shows a message when a cell is selected
Excel Notes & Comments – How To
Notes (Legacy Comments)
Comments
Right-click a cell
and select which
option you prefer
• Copy notes to other cells
• Respond to comments (thread)
• Change the font, shape, color, picture
• Date, time, and cell stamp
28
Backend Inputs Sheet(s)
pretty in the front, party in the back
include default input parameter values and text
description of each parameter and reference to the
data source
29
Review Results – Sections of a ‘Simple’ BIM
Documentation
Assumptions & Limitations
Sensitivity and Scenario Analysis
Data Visualization
Model Appearance & Interactivity
Validation
30
Data Visualization
The graphical representation of information and data. By using visual elements like charts, graphs,
and maps, data visualization tools provide an accessible way to see and understand trends,
outliers, and patterns in data.
Words don’t always paint the clearest picture. Raw data
doesn’t always tell the most compelling story.
• Excel is often viewed as a spreadsheet
31
“Above all else,
show the data.”
— Edward Tufte
“ T h e r e a r e
t w o g o a l s
w h e n
p r e s e n t i n g
d a t a : c o n v e y
y o u r s t o r y
a n d e s t a b l i s h
c r e d i b i l i t y . ”
— E d w a r d
T u f t e
Some (not all) Data Viz Principles
Keep your
Audience in
Mind
Choose the
Chart Wisely
Think Beyond
the
PowerPoint
Templates
Form follows
Function
Direct
Attention to
the Important
Details
Use Tables and
Graphs
Appropriately
Provide
Context
Align the Data
and the
Displays Right
Choose the
Right Colors
Pay Careful
Attention to
Titles
Use Clear Axis
Labels and
Numbers
Leverage
Interactivity
When
Appropriate
34
What is a Chart?
A chart is a graphical representation of data, in which “the data
is represented by symbols, such as bars in a bar chart, lines in a
line chart, or slices in a pie chart”.
– Cary Jensen, Loy Anderson (1992). Harvard graphics 3: the complete
reference. Osborne McGraw-Hill ISBN 0-07-881749-8 p.413
Often used to ease understanding of large quantities of data and the relationships between
parts of the data
Can usually be read more quickly than the raw data
Used in a wide variety of fields and can be created by hand (often on graph paper) or by
computer using a charting application
Certain types of charts are more useful or common for presenting a given data set than others
35
Chart Elements Review
All of these elements are optional: yes, you can create a chart that contains no chart
elements
36
Create a Chart
1. Select the range B4:E10
OR
Select a cell in the range of cells
B4:E10
2. On the Insert tab, in the Charts
group, click the Line symbol
3. Click Line with Markers
4. Check result
5. Change the title to Chart #1
37
Change the Chart Type
1. Select and copy the original
chart
2. Select the new chart (chart #2)
3. On the Design tab, in the Type
group, click Change Chart Type
4. On the left side, click Column
5. Check results
6. Change the chart title to “Chart
#2”
38
Selecting a Chart
Choosing the correct chart type is often a key factor in the effectiveness of the message.
“data visualization selector”
39
Lunch
Enjoy!
40
Review Results – Sections of a ‘Simple’ BIM
Documentation
Assumptions & Limitations
Sensitivity and Scenario Analysis
Data Visualization
Model Appearance & Interactivity
Validation
41
From Raw to Pretty
42
Principles of Model Polish
LOGIC ABOVE ALL
Logically sequenced worksheets
• e.g. welcome > overview > population > treatment mix . . .
Formatted sheets
• Column widths, fonts, colors, cell organization, gridlines
Interactivity
• Which sheets, which variables, data validation
Hiding sheets
• Backend sheets, data sheets
Visualizations
• Charts, number boxes
Zoom and resolution
• Across different computers
Pressure testing
• Test different inputs, different computers, any macros
43
Interactive Models
Static Inputs
Results
User Modifiable Inputs
Population
Treatment mix
Market uptake
Treatment costs
Clinical effects
44
Methods of Interaction
Direct input
(continuous,
unknown)
Sliders
(continuous, lower
and upper
bounds)
Radio boxes
(discrete, mutually
exclusive, known
options)
Dropdown menu
(discrete, mutually
exclusive, known
options)
Check boxes
(discrete, not
mutually
exclusive)
45
60-MINUTE BREAKOUT
Build results charts and make your model interactive
• Include at least one
visualization in your
results section
• Consider adding
other charts / viz to
sections like the
population
Results &
other
charts
• Make sure your
sheets connect
• Certain inputs
should be dynamic
and usermodifiable
Add
interactivity
46
Review Results – Sections of a ‘Simple’ BIM
Documentation
Assumptions & Limitations
Sensitivity and Scenario Analysis
Data Visualization
Model Appearance & Interactivity
Validation
47
Is your model credible?
Determine face validity through agreement with relevant
decision makers on the computing framework, aspects
included, and how they are addressed (e.g. market share and
time horizon)
Verification of the cost calculator or model implementation,
including all formulas.
When possible, the observed costs in a health plan with the
current interventions should be compared with the initialyear estimates from a BIA.
48
Steps to Validate
Face Validity
• Rough
calculations
• Comparable
BIMS
• Literature
• Experts
Computational
Validity
Retrospective
Validity
• Robustness of
results (does
your model
break)
• Cross check
with face
validity
• Separate audit
• Rare
• May
retrospectively
check your
prospective
results
49
30-MINUTE BREAKOUT
Validate your model
• Find at least two
sources that
validate your
results
• Document
validation in your
model (comments,
separate tab)
and/or in your
Word document
Sources
Documentation
50
PPT Sections
01
Overview
02
Methods
03
Results
04 Conclusions,
Recommendatio
ns, Follow-Up
Objectives
Approach
High-level, tables,
charts
Review of the
therapy, the
context
Inputs & sources
Sensitivity and
scenario analyses
Validation,
executive
summary
Next steps,
additional analyses
Principles of PPT Design
Keep Your PowerPoint Slides
Simple
Principles of PPT Design
Content first, design
second
Principles of PPT Design
Core Design Principles
Contrast
Repetition
Alignment
Proximity
PowerPoint presentation should have no more than 10
slides, never last longer than 20 minutes, and should use
a minimum point size of 30 for the font
F or each slide in you r p resent ation, you
shou ld use no m ore than: 7 lines ( or bullets)
per slide. 7 ( or f ew er) words p er line.
Working Session:
Finishing Touches &
PPT Presentation
90-minutes.
1) Clean up your workbook
2) Clean up your sheets
3) Develop a PPT presentation
57
Review of Materials and Assignment
Mid-Point Assignment: Budget Impact Model Build Assignment
Final Draft Due Date: 03/08/2024
Submit on Blackboard: Each individual needs to submit their own excel workbook
Output (what you need to complete): Microsoft Excel BIM Workbook
This assignment is worth 20 percent of your grade.
What to do:
1.) Build a Budget Impact Model based on the Case Scenario provided – See Rubric
Included below for grading
To accomplish this you must:
a. Define the target population and build a population funnel
b. Establish key cost inputs
c. Conduct the budget impact analysis and develop a output worksheet
highlighting the results of your BIM
d. Define your key assumptions and limitations of your model
e. Add data visualization to improve visual
The workbook should include each of the following worksheets:
1. Model Introduction/Welcome Sheet
2. Model Overview – Including key assumptions and limitations reported
3. Population
4. Treatment Mix
5. Treatment Cost
6. Budget Impact – Results Page
7. 1-way Sensitivity Analysis
You can use personal preference and judgement as you setup the workbook and submit
your final draft; however, you need to be sure that the model functions properly, is fully
dynamic, and intuitive to work within.
See Rubric for more details on how workbook submissions will be graded.
Budget Impact Models
Day 1
January 2024
Confidential
INTRODUCTIONS
m a t t he w g i t l i n | s o p h i e s n y d e r
OVERVIEW
relevance | goals | agenda
Confidential
3
The
MODEL
a simplified representation of reality
4
WHAT IS A BIM?
Traditional budget impact models are built to estimate a
payer’s financial consequences from a new drug or
technology entering the market.
What say you, Google Generative AI?
▰
The difference
between the costs
of two scenarios is
called the “net
budget impact”. If
the total costs for
the scenario where
the new health
technology is
reimbursed are
lower than the total
costs for the
scenario where the
technology is not
reimbursed, then
the net budget
impact is negative.
▰
BIMs are a type of
health economic
decision modeling
tool that calculates
the potential costoffsets and extra
budget after a new
healthcare
technology is
introduced.
▰
BIMs are standard
deliverables for
HEOR teams and
can estimate the
costs of adding a
drug to a formulary
for a health system
or payer.
The What and Why of Budget Impact Models
What
• BIA provides a computing framework
that allows users to see how different
assumptions about the diffusion of a
new technology in the health plan or
institution will result in:
• Changes in the mix of treatments used
for a specific condition
• Changes in the cost of treating a specific
condition
• BIMs are part of a comprehensive
economic assessment of a health care
technology.
• BIMs are not a measure of value.
Why
• BIMs are used for budget planning and
forecasting.
• Healthcare payer and provider budgets
are limited.
• Manufacturers, payers, and providers are
under pressure from increasing demand,
treatment costs, and innovations.
• BIMs are often required, along with costeffectiveness analyses (CEA), prior to
formulary approval, reimbursement or
otherwise getting a product/service paid
for in the market.
• Help estimate the impact of health
technology changes on health
insurance premiums
Goal & Objectives
GOAL
OBJECTIVES
Creatively build a BIM from
scratch, given a therapy and
rough guidelines
Fully understand what a BIA
is, including structure and
components
•••
Build from a blank
workbook in Excel
•••
Know how to source, clean,
prepare and work with data
Our Agenda for Today
01
02
Conceptual
Overview
03
Sections of a BIM
Build-A-BIM
Our Agenda for Tomorrow
01
02
Results, Sensitivity &
Other Important BIM
Components
03
Visualization, Pretty
Factor and Reporting
Review & Working
Session
Conceptual Framework
Budget im pa ct schemat ic
Adapted from Brosa et al.
Key Elements in a Budget-Impact Model
Factors to consider before you start building
Model structure: use the simplest model structure that will
provide credible estimates of the budget impact of adding the
new drug to the formulary
• Cost calculator (steady state)
• Decision tree
• Markov
• Discrete-event simulation
Population Size and Characteristics: population size and
mix of disease severity or other characteristics such as the age
and sex of patients currently being treated for the disease and
who will be eligible for treatment with the new drug
• Current and projected eligible population (prevalent & incident)
• Currently untreated
Time Horizon: generally chosen based on the financial
information requirements of the budget holder and is not
related to the duration of the disease for which the new drug
is indicated
• Typically short, from 3 to 5 years
• Costs are presented for each year of the model time horizon
separately and are not discounted
Treatment Mix: mix of treatments currently used for the
indicated and eligible population, and the predicted change in
the treatment mix if the new drug is added to the formulary
Treatment Costs: may include acquisition, administration,
monitoring, and adverse event costs
Disease-Related Costs: not always included in budgetimpact analyses
Uncertainty Analysis: decision makers might vary in their
agreement with the model assumptions and in their
perception of the input parameter values
• Uptake of the new drug each year over the model time horizon
• Whether the new drug is added to current treatments or
replaces them
• Uptake from generic or branded
• Include all of the cost categories and present them separately
• Allow discounts, co-insurance, and co-payments to be subtracted
from the drug acquisition costs
• Not included if the impact on disease-related costs will not occur
during the model time horizon
• If included, should be based on clinical trial or observational data
• Series of one-way sensitivity analyses and/or scenario analyses
• Alternative values for inputs that might vary across health plans
• Alternative values for inputs for which the values are not known
Comprehensive Elements of a BIA
For Reference
Use and cost of interventions
Features of the health care
system
Perspective
• Eligible population
• Current interventions
• Uptake & market effects
• Off-label uses
Impact on other costs
• Condition-related costs
• Indirect costs
Choice of computing
framework
Time horizon
Time dependencies and
discounting
Uncertainty and scenario
analysis
Validation
Model Conceptualization
Good model conceptualization begins with
understanding the problem that is being analyzed
Conceptualizing the Problem
Before constructing a model, it is important to be clear about the nature of the problem under
consideration and the project objectives
The modeling team should consult with subject experts and stakeholders
A clear, written statement of the decision problem, modeling objective, and scope should be developed
The analytic perspective should be stated and defined. Outcomes modeled should be consistent with the
perspective
The target population should be defined in terms of features relevant to the decision
Health outcomes or other measures important to stakeholders should be directly relevant to the question
being asked
Although data are essential to a model, the conceptual structure should be driven by the decision problem
or research question
The choice of comparators crucially affects results and should be determined by the problem, not by data
availability or quality
The time horizon of the model should be long enough to capture relevant differences in outcomes across
strategies
The problem conceptualization should be used to identify key uncertainties in model structure
17
Conceptualizing the Model
Best Practices
An explicit process (expert consultations, influence diagrams, concept mapping, or
similar method) should be used to convert the problem conceptualization into an
appropriate model structure
Several model types may be suitable. Some problems are more naturally represented
in some types than others
For some problems, combinations of model types, hybrid models, and other modeling
methodologies are appropriate
Model simplicity is desirable for transparency, ease of analysis, validation and
description; however, the model must be complex enough to ensure that differences
in value (e.g. health or cost) across the strategies considered are faithfully represented
18
Example Model Conceptualization Table
Effects of mammography screening under different screening schedules
Decision problem/decision
objective
Policy context
Funding source
Disease
Perspective
To evaluate US breast cancer screening strategies.
This analysis was used to inform the 2009 US Preventive Services Task Force
recommendations on breast cancer screening.
AHRQ, NCI
Breast cancer: Four models included ductal carcinoma in situ, two did not; cancer was
characterized by estrogen receptor status, tumor size, and stage in all models and by calendar
year in three.
Stated as societal. Health outcomes are breast cancer outcomes for patients. Limited
modeling of resources used (see below). The US Preventive Services Task Force does not
consider costs in making its recommendations.
Target population
Cohort of US women born in 1960.
Subgroups were defined by age and the disease characteristics noted above. Subgroups
mentioned in the report but not analyzed: BRCA1 and BRCA2, black, comorbidities, HRT, obese.
Health outcomes
Resources/costs
Reduction in breast cancer deaths and life-years gained, false-positive results, overdiagnosis.
Explicitly not included: morbidity from unnecessary biopsies or from treatment.
Screening: Twenty mammography screening strategies defined by frequency (annual or
biennial), starting age (40, 45, 50, 55, or 60 y), and stopping age (69, 74, 79, or 84 y); no
screening. Assumed 100% compliance.
Follow-up treatment: ideal and observed patterns.
Number of mammograms, unnecessary biopsies
Time horizon
Remaining lifetime of women
Strategies/comparators
19
Sections of a ‘Simple’ BIM
These sheets are not exhaustive or always included
Welcome with disclaimer*
Overview of model (like a table of contents)*
Population
Treatment mix (market share)
Treatment costs†
Results‡
*May include selection of time horizon and perspective
†May include clinical outcomes and costs, or these factors may be on a separate sheet
‡May include simple, detailed and sensitivity/scenario analysis
Example BIM
Cost calculator including drug costs only, payer perspective
Home button
Navigation bar
Sections visible as
tabs (under Admin
Mode)
Disclaimer text
Sections of a ‘Simple’ BIM
These sheets are not exhaustive or always included
Welcome with disclaimer*
Overview of model (like a table of contents)*
Population
Treatment mix (market share)
Treatment costs†
Results‡
*May include selection of time horizon and perspective
†May include clinical outcomes and costs, or these factors may be on a separate sheet
‡May include simple, detailed and sensitivity/scenario analysis
Perspective & Time Horizon
Who might be using the results and what timeframe is relevant to them?
The perspective needs to be flexible
The time horizon needs to be relevant
The ‘budget
holder’ may be
• A single payer covering an entire health care system
• A private or government health plan
• A pharmacy controller
• A single patient or family
What does the
budget holder
care about?
• Time horizon
• e.g. the pharmacy budget holder may be concerned
only with the expenses for drugs
Sections of a ‘Simple’ BIM
These sheets are not exhaustive or always included
Welcome with disclaimer*
Overview of model (like a table of contents)*
Population
Treatment mix (market share)
Treatment costs†
Results‡
*May include selection of time horizon and perspective
†May include clinical outcomes and costs, or these factors may be on a separate sheet
‡May include simple, detailed and sensitivity/scenario analysis
Population
Estimate the eligible population for the new technology, typically done using a population funnel
Include all patients eligible for the new intervention during the time horizon of interest, given any
access restrictions
Typically set at 1M, but should be user modifiable
These larger populations are more familiar
Align the technology label, e.g. rates of relapse,
events, stage, comorbidities, age, sex, ethnicity
Optional but sometimes important if low
Consider if your technology increases / decreases
% treated (i.e. due to improved outcomes, safety)
Population Stock and Flow
The eligible population MAY change in the sense that individuals enter or leave depending on
whether they meet the criteria for inclusion (e.g., by developing the indication, meeting the
restrictions, no longer having symptoms, and dying).
Also consider incorporating general
population growth (~0.5% / year).
Note: Prevalence refers to proportion of persons who have a condition at or during a particular time period, whereas incidence refers to the proportion or rate of persons who develop
a condition during a particular time period.
*Restricted to patients who are still alive in that year. Mortality is factored in based on the clinical data from the trial by treatment comparator.
†The prevalent population in years subsequent to year 1 comprises the year 1 prevalent population less mortality in each year plus the incident population from subsequent years (i).
HF: heart failure; i: index year
Population Data Sources
Cancer:
Surveillance,
Epidemiology, and
End Results (SEER)
Program
Centers for
Disease
Control and
Prevention
Also consider availability of internal data and allow for user modification
90-MINUTE BREAKOUT
Conceptualizing and Building:
Perspective, Time Horizon, Population
• Payer – Commercial,
Medicare
• IDN
• Provider
• Pharmacy controller
What perspective
do you plan to take?
• Will you allow the user
to choose a range of
years or keep the
timeframe set?
• Justify your choices
What time horizon
do you think is
relevant to this
perspective and the
therapy?
• Document methods to
arrive at estimates for
each level of the funnel
• Document your sources
• Show your ‘funnel’
graphically – with
numbers and labels
Estimate the
eligible population,
starting at the top
of the funnel and
going all the way to
your estimated
treated population.
LUNCH BREAK
60 MINUTES
30
Sections of a ‘Simple’ BIM
These sheets are not exhaustive or always included
Welcome with disclaimer*
Overview of model (like a table of contents)*
Population
Treatment mix (market share)
Treatment costs†
Results‡
*May include selection of time horizon and perspective
†May include clinical outcomes and costs, or these factors may be on a separate sheet
‡May include simple, detailed and sensitivity/scenario analysis
Treatment Mix – Current Interventions + New
Usually compare scenarios defined by set mix of, rather than specific individual, interventions
Starting scenario =
the current
intervention mix for
the eligible
population
Uptake of the new
intervention and
market mix effects
May include no intervention as well as
interventions that might be replaced by the
new one
May include interventions used off-label in the
eligible population
Note: he uptake of the new intervention is not
known at the time of analysis and neither is the
impact on the current intervention mix
Substitution
Three possible scenarios
Combination
Expansion
Treatment Mix Estimation Methods
• In most cases, little data on treatment mix are available
• Results of the BIA may be sensitive to alternative assumptions
• Structural uncertainty analysis: 1. allow users to test alternative assumptions
about uptake and 2. include sensitivity and scenario analyses
Literature (e.g.
published data on
similar
interventions)
Internal data (e.g.
from finance)
Claims data
Interviews
Sections of a ‘Simple’ BIM
These sheets are not exhaustive or always included
Welcome with disclaimer*
Overview of model (like a table of contents)*
Population
Treatment mix (market share)
Treatment costs†
Results‡
*May include selection of time horizon and perspective
†May include clinical outcomes and costs, or these factors may be on a separate sheet
‡May include simple, detailed and sensitivity/scenario analysis
Cost of Current and New Intervention Mix
If
appropriate,
adjust for:
Package size
Dosing
Patient cost
sharing
Time on
treatment
Price
concessions
(discounts /
rebates)
Impact on Other Costs
Condition-related costs
• Changes in the diagnosis rates, symptoms, disease duration, disease outcomes, or diseaseprogression rates
• Inclusion of changes in condition-related costs may require substantial assumptions and
may extend beyond the relevant time horizon
• If credible data are available and these changes have an impact on health care budgets,
condition-related co