## Monday, 10 October 2016

### Masters of some

This is really exciting $-$ well, at least for us... Our new Masters in Health Economics and Decision Sciences is up and running and applications are now open for the next academic year!

We're updating the promotional material (which will also feature a rather embarrassing interview that I and others have filmed to describe the life-changing advantages people will experience if they come and study with us), so I'll point to more (hilarious, but hopefully also helpful) bits as they become available.

In the meantime, we thought we'd include some ideas of what the syllabus might look like, for different students' backgrounds (in brackets the departments/institutes within UCL already providing the module).

Sample module selection for a student with a first degree in Epidemiology or Statistics (or any other quantitative discipline aside from Economics), wishing to take the Decision Science Stream within the degree
1. Health Systems in a Global Context (Institute of Global Health, IGH)
2. Economic Evaluation (IGH)
3. Medical Statistics I (Statistical Science, Stats)
4. Key Principles of Health Economics
5. Introductory Microeconomics
6. Modelling for Decision Science
7. Bayesian Methods in Economic Evaluation
8. Medical Statistics II (Stats)

Sample module selection for a student with a first degree in Economics, wishing to take the Decision Science Stream within the degree
1. Health Policy and Reform  (Centre for Philosophy Justice and Health, CPJH)
2. Economic Evaluation (IGH)
3. Medical Statistics I (Stats)
4. Microeconomics for Health
5. Modelling for Decision Science
6. Bayesian Methods in Economic Evaluation
7. Health Economics (Economics, Econ)
8. Urban Health (IGH)

Sample module selection for a student with a first degree in Epidemiology or Statistics (or any other quantitative discipline aside from Economics), wishing to take the Economic Stream within the degree
1. Health Systems in a Global Context (IGH)
2. Introductory Microeconomics
3. Econometrics (NEW)
4. Economic Evaluation (IGH)
5. Microeconomics for Health
6. Health Economics (Econ)
7. Medical Statistics I (Stats)
8. Bayesian Methods in Economic Evaluation

Sample module selection for a student with a first degree in Economics, wishing to take the Economics Stream within the degree
1. Health Policy and Reform  (CPJH)
2. Econometrics (NEW)
3. Economic Evaluation (IGH)
4. Microeconomics for Health
5. Health Economics (Econ)
6. Modelling for Decision Science (NEW)
7. Bayesian Methods in Economic Evaluation

8. Social Determinants of Health

We've already received some applications, which is super good news $-$ but there's still plenty of room!

## Friday, 7 October 2016

### Shiny happy people in the land of the Czar

During the summer, we've worked silently but relentlessly to set up a departmental server that could run R-Shiny applications.

There's a bunch of us in the department doing work on R and producing packages and so we thought it'd be a good idea to disseminate our research. Which is just as well, as I've been nominated "2020 REF Impact Czar", meaning I'll have to help collate all the evidence that our work does have an impact on the "real world"...

Anyway, after some teething problems (mainly due to my getting familiar with the system and the remote installation of R and Shiny), I think we've now managed to successfully "deploy" (I think that's the correct technical term) two webapps.

These are bmetaweb and BCEAweb. The first one is the web-interface to our bmeta package for Bayesian meta-analysis (which I developed with my PhD student Christina). The main point of bmeta is to allow some sort of standardised framework for a set of models for meta-analysis, depending on the nature of the outcome and some modelling assumption (eg fixed vs random effects). In addition to running the default models (which are based on rather vague priors and pre-defined model structures), bmeta saves data and model code (in JAGS), so that people can actually use these templates and actually modify them to their specific needs.

BCEAweb is the actual mother of the whole project (much as SAVI is then the actual grandmother, as it inspired our work on developing web-interfaces to R packages) and the idea is to use remotely BCEA to post-process the outcome of a (Bayesian) health economic model. BCEAweb works by uploading the simulations from a model and then using remotely R to produce all the relevant output for the reporting of the results in terms of cost-effectiveness analysis.

One thing we've tried very hard to include in both the webapps is the possibility of downloading a full report (in .pdf or .docx format) with a summary of the analyses. I think this is really cool and we'll probably develop more of these $-$ particularly for our work related to statistical methods for health economic evaluations.