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Personal statement example
My interest in health technology assessment began with a seminar exercise in my second year, when we were asked to decide, as a mock committee, whether a hypothetical drug offering three additional months of progression-free survival should be funded at a given price. What struck me was not the arithmetic but the disagreement about what the arithmetic was for. Some of us argued from opportunity cost, others from the severity of the condition, and nobody could say cleanly where evidence ended and judgement began. I have been reading and arguing my way around that boundary ever since, and I now want to study it properly.
My BSc in Economics gave me the technical grounding. I took health economics, econometrics and microeconomic theory, and taught myself enough R in my own time to stop fighting with spreadsheets. My dissertation examined the distributional effects of prescription charge exemptions in England, using survey data on self-reported cost-related non-adherence. The econometrics was modest, but the project taught me more than the result did: I spent weeks understanding how the exemption categories had accumulated historically rather than by design, and I came to see that an apparently technical question about price elasticity was really a question about which groups had been made visible in policy. My supervisor pushed me hard on selection effects, and I learned to write about uncertainty without either hiding it or hiding behind it.
Alongside my studies I have worked part-time as a data administrator for a small group of community pharmacies, cleaning dispensing records, preparing monthly activity reports and chasing the mismatches that appear when one branch records something differently from another. It is ordinary work, but it has shaped how I read evidence. Routine data that looks clean in a published table has usually been through hands like mine, and I am now sceptical of resource-use estimates that arrive without any account of how the underlying records were generated. I have also seen how quickly a change to a service specification alters what staff record, which has made me careful about comparing costs across time.
Outside work I share care for my grandmother, who has arthritis and reduced mobility, and I help organise a weekly lunch club at our local community centre. Both have given me a practical education in what quality of life actually consists of for older people: not only pain and mobility, but whether someone can get to the club at all, and whether the person who drives the minibus is available that week. When I first read about instruments such as the EQ-5D, my reaction was partly admiration for the attempt to make health states comparable and partly recognition of how much is left outside the descriptive system. I do not think that invalidates the approach, but I would like to study the literature on capability-based and broader outcome measures carefully rather than treating my own impressions as an argument.
I have been reading around the field to test whether my interest survives contact with the detail. Drummond and colleagues' text on economic evaluation has been my main reference, and I have worked through published appraisal documents to see how committees handle immature survival data, indirect comparisons and confidential pricing. I am particularly interested in decision-analytic modelling and in methods for handling structural uncertainty, where the choice of model architecture is itself a judgement that sensitivity analysis cannot fully capture. I would also welcome teaching on evidence synthesis, which I have read about but never done.
In the longer term I would like to work in a technical role supporting appraisal or reimbursement decisions, whether in a national agency, an academic group or a health system. I am realistic that this means becoming genuinely competent at modelling and at explaining models to people who will not read the appendix. A master's in health technology assessment is the route to both, and I am ready for the workload.
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