Guide- Burden of disease review

TABLE OF CONTENTS

Scope of Use for This Data Extraction Form
Overview of the Data Extraction Form
Data extraction process
Tabs description

Scope of Use for This Data Extraction Form

This data extraction form is designed for use in reviews that aim to:

Estimate the cost-effectiveness of a health technology
Assess the burden of disease, including:
Economic burden (e.g. costs and resource use)
Clinical burden (e.g. epidemiological data)
Humanistic burden (e.g. quality of life, health state utility values)
Treatment patterns
Clinical outcomes

Data can be extracted from both primary studies and secondary evidence, such as published economic analyses.

Overview of the Data Extraction Form

There are two categories of tabs in the Data Extraction Form:

General Tab

Tab name: Study Details
This tab is used to extract data regardless of the study type or the types of data included.
It contains data extraction fields that are suitable for various study designs; however, some fields may not be applicable depending on the specific study.

Specific Data Tabs

These tabs are designed to extract specific types of data, tailored to particular aspects of the review (e.g., economic data, clinical outcomes, utility values).

Extraction Summary: You will be able to efficiently export only the specific types of data relevant to your needs—for example, cost and resource usage. The extracted data will be categorized according to data type in tabs.

Data extraction process

Field: Results Group Label

Description: This section defines the population or study group to which the extracted results refer to. It should be completed before extracting the outcome/results data.

This section is highlighted in red.

Instructions: Before extracting any results, determine for what group(s) the data are presented in the study. Use this field to label the groups appropriately. This label should help clarify who the results apply to, and help distinguish between results for different study populations and/or treatments.

Examples of labels you can use:

Main sample – if the results refer to the overall study population (e.g. patient with ulcerative colitis)
Subgroup – [specify] – if the results refer to a subset of the main sample (e.g., “Subgroup – Females”, “Subgroup – UC mild”).
Control sample– if the results refer to a comparator population (e.g. matched cohort-patient from the same hospital without disease).
Target population (applicable for Economic evaluations, it will be label useful to extract input data e.g. utility value for health states)
Treatment arms - Population defined by treatment
Bia scenario: Status quo, projected

Case example: In this cost-effectiveness study, there are two treatment arms. The names of these treatments should be extracted first, as they will be used in the section dedicated to extracting model outputs—such as costs, incremental QALYs, and ICER/ICUR values. To extract input data from this study, such as utility values for different health states, you should create an additional group label specifying the target population.

Look carefully at tables, figures, and captions to determine which population is being analyzed. 
If it's unclear, check the Methods or Results section for clarification.
The goal is to ensure each set of extracted results is clearly labeled by the group they belong to.

Field Study ID: Primary source of data (applicable if value is extracted from secondary evidence such as review, economic analysis, etc.)

The data extraction form is designed to support extraction from both primary studies and secondary evidence. Each section includes dedicated field (i.e. Study ID) to label the original sources of the extracted data, applicable for extraction from secondary evidence—for example, input data from cost-effectiveness analyses. If the data are extracted from a primary study, mark "Not applicable".

Subsections with examples

In each tab you will find different Sections with data extraction fields with or without subsections. Such organised structure enables precise determination of dependencies between elements (extraction fields).

Example 1

In Tab dedicated for Economic analysis you will find section Methods dedicated for extraction of data for methodological approach in Economic analysis like: model type, discount rates etc. Below this section you will find a subsections (Basic) to extract data that may appear more than once in study, for example there is more than one health state in the model, different types of sensitivity analysis etc.

Example 2

In the tab dedicated to Economic Analysis, you will find sections for Model Output: Per Treatment Arm and Incremental, which are designed to extract output data from the economic evaluation. Each of these sections includes subsections for individual treatment arms and comparisons. Study arms are automatically added once they are extracted in the first tab, Study Details.

For the Incremental section, you should first select one of the combinations automatically generated by the tool based on the extracted study arms.

Vocabulary fields

Most of the data extraction fields are text fields, such as those used for extracting numerical values. However, some sections include vocabulary fields, where reviewers select data from a predefined list. During extraction, each reviewer has permission to create new codes if needed.

Database-format extraction

Please note that Laser AI supports a database-driven approach to data extraction. This means, for example, that different outcomes are extracted in separate sections. You won’t find dedicated sections for LYGs or QALYs—instead, there is a single section called Model Output. Within this section, you should select the specific output you are extracting (e.g., LYGs in the first subsection, QALYs in the second), using the controlled vocabulary.

Connections between PDF and values in data extraction forms

The best way to extract data in Laser AI is by using the highlighting mechanism. This method makes the quality assurance process easier, as clicking on a field with an extracted value redirects you to the corresponding section in the PDF where the value was extracted. To use this mechanism, you need to:

Locate the specific data in the document and highlight it.
Click the 'Plus' button (when empty data extraction fields exist) to add the highlighted data to the corresponding data extraction field. In this way the relation between data in PDF and value in data extraction form will be established. When there are no empty fields in data extraction form, click the 'Plus' button located below the data extraction fields. The tool will create additional field and the extracted value will be automatically added to the data extraction form. Please note that this option is available only for sections with a single data extraction field

Tabs description

Study details tab

This tab is dedicated to extracting study characteristics, such as study type, funding source, country, and more.

There are three key sections that require your attention:

Results Group Label
- Read the description in the previous chapter for guidance on how to define and use result groups.
Type and Source of Data

In this section, identify the type(s) of data included in the PDF (e.g. economic, clinical, treatment pattern).
Based on this, extract information only in the relevant data-specific tabs (e.g., Cost and Resource Use, Treatment Pattern).

Patient Characteristics

Use this section to extract baseline characteristics of the study population.
It includes subsections to capture detailed demographic and clinical information for study arms. Study arms in the subsections are automatically added once they are first extracted in the "Results Group Label" section.

Recommended method: Use semi-automated table extraction where applicable.

Economic evaluations tab

This tab is dedicated to extracting data from economic evaluations, such as cost-effectiveness analyses.

It includes five sections:

Two sections for Methods (highlighted in purple)
Three sections for Results (highlighted in blue):
Model Output per Treatment Arm e.g QALY, LYG, cost etc
Model Output: Incremental Analysis: ICER, incremental QALY etc
Threshold Analysis

In the output section, you should:

first decide which scenario, i.e. base case or sensitivity, you want to extract data for
and type of output (this is a vocabulary field): select from the list or create new one

To extract input data (e.g. utility values)  please use relevant tabs: e.g. Humanistic burden: HRQoL/HSUV

Economic burden: Costs and RU tab

This tab is dedicated to extract primary cost and resource use data.

It includes two sections:

First section for Methods (highlighted in purple)
One section for Results (highlighted in blue):

Please extract the cost or resource as reported in the Cost and Resource Description field, and select the relevant code from the list in the 'Type of cost or RU' field.Please extract the cost or resource as reported in the Cost and Resource Description field, and select the relevant code from the list in the 'Type of cost or RU' field. Next, extract data for the study arms in the subsections. The tool will automatically add them once you extract their names in the Results Group label section.

Recommended method: Use semi-automated table extraction where applicable.

Humanistic burden: HRQoL/HSUV tab

This tab is dedicated to extract primary HRQoL/Health state utility data.

It includes two sections:

First section for Methods (highlighted in purple)
One section for Results (highlighted in blue):

Treatment pattern tab

This tab is dedicated to extracting treatment pattern data from primary studies—for example, the percentage of patients on treatment, time to switch therapies, percentage of patients receiving concomitant treatments, etc.

It includes one section:

One section for Results (highlighted in blue)

You can also use this tab to extract market share data from secondary analyses, such as budget impact analyses.

Recommended method: Use semi-automated table extraction where applicable.

Clinical burden: EPI tab

This tab is dedicated to extracting epidemiology data —for example, incidence, prevalence, mortality.

It includes one section:

One section for Results (highlighted in blue)

The first field is a vocabulary field, where you should select the relevant code from the list. You can create a new code if necessary.

Recommended method: Use semi-automated table extraction where applicable.

Clinical outcomes (include transition probabilities) tab

This tab is dedicated to extracting Clinical data—for example transition probabilities used as input data in Economic analysis.

It includes one section:

One section for Results (highlighted in blue)