Author Archives: Yoryos Lyratzopoulos

Should you blame your patient case-mix for poor performance in patient experience surveys?

There is an unprecedented amount of publicly reported data about what patients think of their care experience in different NHS hospitals. But not uncommonly information on hospital performance in respect of patient experience fails to influence the behaviour of clinicians and managers responsible for improving care delivery.

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Changes over time in socio-economic inequalities in cancer survival. Can “Victora’s law” help us?

We are often pre-occupied with health care inequalities ‘here and now’. But how are such inequalities generated? And more importantly, what happens to them over time? The answer to these questions can help us to narrow inequalities faster. And in principle, it could even help us in preventing inequalities form occurring in the first place.

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Validity of electronic records on ethnicity – and more generally

Increasingly, health research relies on electronic health records and Big Data. On the other side of the argument methodologists like John Ioannidis are questioning the epistemological fitness of administrative data. A more tamed approach would be to acknowledge that electronic records are likely to contain errors, but such errors are unlikely to be systematic. In …read more

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Gender inequalities in the diagnosis of bladder and kidney cancer – the story behind the paper

Together with colleagues at the Universities of Durham and Bangor and the PHE’s National Cancer Intelligence Network, we published a paper in BMJ Open. Here is the story behind the paper.

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‘Cancer Outcomes’ Conference 2013

Read a more detailed BMJ Blog on the same conference here . For several of us who do research on the quality of cancer services, the NCIN Cancer Outcomes annual conference is one of the high points of the year. Keeping up with tradition, there is a large CCHSR ‘footprint’ on this year’s conference which …read more

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How many levels in multi-level modelling? An example from a recent CCHSR paper

A previous blog by Gary Abel here discussed the interpretation of random effects used to account for clustering (i.e. non-independence) of observations within organisations such as general practices or hospitals. We can also use another common term to describe this use of random effect variables, which is ‘multi-level modelling’. For example, patient observations are usually …read more

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Detecting cancer earlier

For cancer patients, on average, more pre-referral consultations mean more “delay”: we unpick the story behind CCHSR’s latest cancer paper

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  • The Cambridge Centre for Health Services Research (CCHSR) is a thriving collaboration between the University of Cambridge and RAND Europe. We aim to inform health policy and practice by conducting research and evaluation studies of organisation and delivery of healthcare, including safety, effectiveness, efficiency and patient experience.