Across the world, health and care systems have invested large amounts of money in determining the most effective and efficient treatments for a range of diseases. In the NHS, organisations including health system regulators, other arms-length bodies, specialist royal colleges and professional associations have developed guidelines to ensure that care is provided to a consistently high standard.
Despite these efforts, there exists a high level of variability in the treatments patient receive for given disease conditions. Clinical reviews show that much of this variation is unwarranted i.e. it cannot be explained by the condition or the preference of the patient and is only explainable through differences in health system performance. This means that we cannot be sure that patients are consistently receiving the best quality care.
This issue is not specific to the NHS: studies across United States of America and Europe show that 30–50% of patients are not receiving the care recommended by the ‘best available’ medical evidence. This can have a real and lasting impact on patients. In one study, it was estimated that 5.8 million child deaths could be prevented by better application of best practice.
It is clear from our experience that there are a multitude of reasons why best practice guidelines are not followed consistently. Blockers exist at national, regional, organisational, team and individual levels. From our experience, a key challenge is around changing individual clinical practice. Opposition is frequently a result of the misconception that:
- The risks outweigh the benefits of a new procedure.
- Guidelines undermine clinical autonomy / judgement.
- Certain guidelines are not relevant to their patients / population.
Our team has been using data analytics to challenge these misconceptions in order to:
- Support clinical decision-making.
- Reduce unwarranted clinical variation.
- Increase adherence to best practice guidelines.
To achieve this means using a combination of data analytics and senior clinical insight, to provide an evidence base that supports clinical decision-making, and which is informed by established best practice. As a result, in recent years we have been able to provide an evidence base to improve the delivery of clinical services, which will have a material impact on over 200,000 individual patient contacts over the next 18 months; and support delivery of up to a 50% reduction in Delayed Transfers of Care and 5-10% decrease in referrals to higher levels of care.
For more information on how data analytics can really change lives, please contact PPL Associate Director Dr Folarin Majekodunmi.