Methods Manual
1
Introduction
1.1
Purpose of this document
1.2
Author info
2
Glossary of terms
3
Starting a BI project
3.1
Submission of requests and Prioritisation process
3.2
Establishing the scope
3.3
Project planning (timelines)
3.4
Sponsorship and reporting
3.5
Terms of engagement
4
Data Quality Assessment and Audit
4.1
Purpose
4.2
Guidelines
4.3
Outputs
5
Searching for evidence (for inclusion in analyses, models, or business cases)
5.1
Useful sources of evidence
5.2
Search strategies (when & how to use them)
6
Assessing quality of evidence (for inclusion in analyses, models, or business cases)
6.1
Critical appraisal
6.2
Analysis/synthesis
6.3
Quantifying, reporting and incorporating uncertainty
6.4
Subgroups, inequality and diversity considerations
6.5
Summarising evidence
7
Building a data set
7.1
General principles
7.2
Data linkage
7.3
Security and storage
7.4
Version control
7.5
Naming conventions
7.6
Descriptive statistics
7.7
Assumptions testing (parametric etc.)
7.8
Handling Missing Data
7.9
Understanding distributions, their application and consequences
7.10
Data transformation
8
Modelling
8.1
Minimum practice standards
8.2
Regression
8.3
Univariate approaches
8.4
Multivariate approaches
8.4.1
Variable processing
8.4.2
Variable selection
8.5
Advanced approaches
8.5.1
Machine learning
8.5.2
Neural networks
8.6
Simulation approaches
8.6.1
Markov chains
8.6.2
Agent-based simulation
8.7
Accuracy assessment
8.7.1
Model testing and accuracy assessment
8.7.2
Tests of goodness of fit
8.7.3
Sensitivity analyses
8.8
Probabilistic
9
Economic evaluation
9.1
General Approaches
9.2
Assessing benefits and harms (value)
9.3
Economic analysis for interventions funded by the public sector with health and non-health outcomes
9.4
Sources of unit costs
9.5
Sources of Health Related Quality of Life (HRQoL) data
9.6
ICER calculation and Sensitivity analysis
10
Data visualisation
10.1
Presenting tables
10.2
Presenting charts
10.3
Presenting maps
10.4
Model diagrams
11
Library and referencing standards
11.1
Bibliographic
11.2
Packages and code
11.3
Assumptions libraries
11.4
Data dictionaries
11.5
Commenting on code and expressions
11.6
Development diaries
12
Report writing / publishing / Tool deployment
12.1
Structure and formatting
12.2
Version control
12.3
Publishing guidance
12.4
Developer notes and user guide development
12.5
Ongoing support arrangements
12.6
Presentations
12.7
Structure and formatting
12.8
Version control
12.9
Recording audio
12.10
Archiving
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Methods Manual
Chapter 4
Data Quality Assessment and Audit
4.1
Purpose
The purpose of a data quality assessment …
4.2
Guidelines
4.3
Outputs