Aims and objectives
The CVD microsimulation policy model was developed using R. To facilitate model use by patients, physicians, researchers and health policy-makers, we developed a user-friendly web-based interface together with a user guide. The interface allows users to modify model inputs and adapt the model for their needs. Patients can use this model to better understand their risk of CVDs and the projected consequences with or without treatments; physicians can use this model to facilitate their clinical decisions; and researchers and policy-makers can use this model to assess different CVD policies.
Interface development
The web-based user interface was developed using the R ShinyApps interface.72 The interface includes the three sections, ‘introduction’, ‘model parameters’ and ‘run analyses’, which are described in the following sections.
Introduction
The ‘introduction’ section is designed to facilitate the use of the interface. It includes the following panels:
- Model overview – describes the model and cites the references so that users can understand the functionality of the model and where to find further information of the model.
- Glossary – explains the terminology used in the interface.
- User guide and files – includes the user guide and examples of model inputs formatting to facilitate the use of model.
Model parameters
This section is designed to help users input the necessary model inputs. It includes prefilled default values.
To use the CVD microsimulation policy model, profiles are prepared for patients whose outcomes are simulated, treatment scenarios with relevant treatment effects are specified, and the model is run using the integrated model risk equations over a certain time horizon. Therefore, the ‘model parameters’ section includes the following panels:
- patient characteristics – to enter the profiles of a single patient or a group of patients
- treatment profiles – to enter treatment effects and costs
- cost inflation index – to allow users to modify the cost year (default healthcare costs in UK 2021 Great British pounds) by specifying an inflation index using 2021 as the reference year.
Model execution
The section ‘run analyses’ is designed to execute model analyses and report results. After the inputs are filled in the ‘model parameters’ section, the user should use this section and click buttons to run the analyses. This section includes the following panels:
- Base-case analysis – to run the base-case analysis, make predictions for patients under each treatment scenario and summarise the incremental analysis across treatment scenarios.
- Probabilistic analysis – provides an option for the user to specify the uncertainty ranges of some inputs to facilitate the analysis of parameter uncertainty.
Figure 13 presents the first look of the ShinyApps. Details of the models can be accessed by visiting and using the ShinyApps from this website (https://livedataoxford.shinyapps.io/shiny_ctt_ukb_model/).
FIGURE 13 Screenshot of the ShinyApps interface showing the sections and the ‘model overview’ panel. (Figure not reproduced here; see the original article.)
Model application
The CVD microsimulation model interface and user guide are available at https://livedataoxford.shinyapps.io/shiny_ctt_ukb_model/. The model interface enables users to project outcomes for particular patient profiles. To illustrate its use, the model predicted a 39.3% lifetime cumulative incidence of a vascular event (MI, stroke, CRV or VD), 29.3 years’ further lifespan, and 24.5 QALYs over the lifetime of a healthy 60-year-old man [of white ethnicity, in quintile 3 of socioeconomic deprivation, non-smoker, with moderate physical activities, a healthy diet and normal BMI level (18.5–25 kg/m2), a LDL-C of 3.6 mmol/l, a HDL-C of 1 mmol/l, creatinine of 82 μmol/l, BP of 140/80 mmHg, HbA1c of 32 mmol/mol, not on antihypertensive treatment, and without histories of severe mental illness, cancer or diabetes].
Summary
The CVD microsimulation policy model is a CVD decision-analytic cost-effectiveness model built in R. Its ShinyApps interface facilitates the use of the model by a broader set of users interested in assessing the long-term effectiveness and cost-effectiveness of CVD treatments and policies.