By World Healthcare Journal-
To many healthcare professionals, data is a word that can be scary. It can often be unclear how data can help drive improvements, and even how it can be accessed successfully. But for hospitals and systems that are looking to improve their outcomes and manage budgets, data is a valuable tool to analyse performance and reduce expenditure.
The UK has a huge amount of valuable data, much of it within the NHS. With more than 40 years of patient data, there is a wealth of information that can assist newer healthcare systems that are looking to be more efficient from the outset. It has an even greater global application in the treatment of diseases and health trends, so a key aim should be collecting data sets from around the world that can be shared internationally for the good of the patient.
Within this laudable aim are the constraints around governance and ownership of the data. In using such data outside the UK, these needs should be considered carefully and managed but there is potential for widening the usage. And there are several useful immediate applications – the most important of which is in medtech and pharma.
The approach to work now being called real world data or real-world evidence is very valuable in post-licence monitoring of drugs where the evidence is generated from real clinical practice. This is potentially valuable to the life sciences sector and important to citizens who need treatment, because clinical trials are done with tightly defined cohorts of patients under controlled circumstances. These trials are in quite different population segments, so that post-launch evaluation monitoring and the ability to segment patients into population cohorts is potentially very valuable. So equally, it shouldn’t be surprising that, when treatments are used outside of the strict controls and clinical trials, the results are quite different too.
Thus, the more different data sets that we can meaningfully bring together the better. But we need to be assured that the input data is comparable. So where we have a value field in a UK dataset and what appears to be the same value field in a data set from Denmark or the US, it requires further work to ensure that the number in what appears to be the same value field across those different data sets is created and validated in the same way, so they can be used meaningfully, or not.
The importance of developing healthcare systems
Every health system has finite budgets and demand always outstrips supply so the collection of data cannot be the most important thing. However, by using this data all health systems can be better at what they do. It can ensure that people who need treatment can access the best standard of care possible, as systems can be designed to offer the right care to the right people in a timely manner. It can also prevent people from being harmed, not through bad actors or negative intent but through lack of knowledge and comparisons with other patient groups.
How the UK data sets can help
The UK is uniquely positioned to be able to help to make some of those key decisions through the way that we use and manipulate data. We have considerable experience here, and we can use the NHS - an extremely efficient health system - as a baseline. For example, we know in the NHS how many hospitals we need per 100,000 population. We can adjust that figure for all sorts of facts about population and geography and come up with models that we can demonstrate work.
We also have more mature or larger comprehensive data sets than most other countries, and we are accustomed to using that data in order to understand the system and clinical performance. A good example is the UK NHS Getting It Right First Time program which uses a data-driven, clinically-led approach to enable often difficult conversations at a local level, where comparable data is used to inform a clinical conversation around the quality of care, the choices that are made and the outputs delivered. These have a significant impact in the NHS and that methodology is transferable anywhere in the world.
If a healthcare system is interested in doing something with data, my immediate response would be to ask why, what the purpose is and what do they want to achieve. Once you understand their ambition, you can understand if and how you can apply data to support that ambition. For example, if it is equitable access across the population there will be a significant data and maths that can applied to come up with powerful information to drive system design in a direction of equity of access. If the purpose is to improve cost efficiency, then there’s a different approach. If there is a lack of clarity around a problem, we can give many different examples in areas of system design, clinical practice, predictive care and so on to see where the interest lies.
The UK has a publicly funded national health system and probably more experience of using national-level data sets to improve cost quality and efficiency of care than other systems, even where those systems appear to be similar. We have the ability to use these techniques more effectively because of the scale of the UK population, which means we’re more used to using them and ultimately we have more experience.
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